Short-Term Population Projection for Spain (2008

Short-Term Population
Projection for Spain
(2008-2018)
Methodology
Madrid, December 2008
Index
Introduction
1
General calculation method
2
Baseline population
3
Fertility projection
4
Mortality projection
5
External migration projection
6
Internal migration projection
2
Introduction
The Short-Term Population Projection for Spain provides a forecast of the population,
which will be resident in Spain, in its autonomous communities and provinces over the
next ten years, as well as of the evolution of each of the basic demographic
phenomena in each of those spatial scopes for each year of the projection period.
In this way, its results provide the figure for the population resident at 1 January for
each year from the 2008-2018 period in each spatial scope considered (Spain,
autonomous communities and provinces). Similarly, they provide the demographic
events (births, deaths and migration movements), which have given rise to the
population volume and structure in each geographical scope considered, represented
by those population figures. Both types of magnitude, population stocks and
demographic flows, are broken down in accordance with basic demographic features,
such as sex, age and generation.
It should be borne in mind that the detailed results of this statistical operation are
provided in decimals, in order to thereby guarantee their complete territorial coherence
as well as perfect consistency among demographic flows and population stocks at all
breakdown levels considered.
Lastly, it should be highlighted that this new statistical operation, implemented by the
INE as of 2008, will be carried out with annual periodicity, encompassing the following
ten years, in order to make available a simulation of the population resident in Spain,
updated as appropriate to the most recent demographic development and to the latest
available information and socio-economic forecasts.
3
1
General calculation method
This Short-Term Population Projection for Spain exercise is based on the classic
component method. The application of the aforementioned method is in response to
the following schema: starting with the resident population in a certain geographical
area and data observed for each one of the basic geographical components, mortality,
fertility and migration, the idea is to obtain population figures corresponding to
subsequent dates under certain hypotheses on the future of these three events, which
are those which determine their growth and structure by ages.
Retrospective analysis of each basic demographic phenomenon, utilising the most upto-date demographic information available, has made it possible to establish
hypotheses regarding their future incidence at each territorial level considered, in each
year of the projection period, quantified as specific fertility rates by age, specific
mortality rates by sex and age, specific rates by sex and age of external emigration
and of interprovincial internal migration, as well as a forecast of foreign immigration
flows for each sex and age, in each year of the forecast period. From these the
specific fertility, mortality, foreign emigration and interprovincial internal migration are
derived, as well as the flows of immigrants arriving from abroad by generation, using
the hypothesis of uniform distribution of the incidence of each phenomenon in each
age among generations whose individuals will be of the aforementioned precise age at
some point during the year.
So then, the projection of the population of each sex and age resident in Spain, and in
each autonomous community and province, as of 1 January in each forecast period,
has been carried out in accordance with a multi-regional projection model,1 which
provides as results, not only figures for population by sex and age resident at each
territorial level considered, but also projected figures of births, deaths and migration
movements, which will take place during each year of the projection period, thereby
conserving the necessary coherence among demographic flows and stocks, and the
requisite inter-territorial consistency.
In this way, starting with the population resident at each territorial level considered by
sex and age x at 1 January of year t ( Pst, x ), gives the projection of the resident
population of age x + 1 and sex s in the aforementioned geographical area at 1
January of year t + 1 ( Pst,+x1+1 ), as well as corresponding demographic events occurring
throughout year t starting with the following expressions:
A. For the national total:
- For the remaining ages x = 1,2,...,100 :
Pst,+x1+1 =
[1 − 0,5 ⋅ (m + e )]⋅ P + IM
[1 + 0,5 ⋅ (m + e )]
t
s, x
t
s, x
t
s,x
t
s,x
t
s,x
t
s,x
1
Willekens, F.J. and Drewe, P. (1984) “A multiregional model for regional demographic projection”,
in Heide, H. and Willekens, F.J. (ed) Demographic Research and Spatial Policy, Academic Press,
London.
4
where
mst , x is the annual mortality rate in year t of the generation of individuals
resident in Spain of sex s and age x at 1 January of year t ; est , x is the external
emigration rate in year t of the generation of individuals resident in Spain of sex s and
age x at 1 January of year t ; e IM st , x is the immigration flow arriving from abroad in
year t of individuals of sex s and age x at 1 January of year t .
- For age x = 0 :
Pst,+o1 =
[1 − 0,5 ⋅ ( m + e
[1 + 0,5 ⋅ ( m
t
s , −1
t
s , −1
t
s , −1
]
) ⋅ N st + IM st , −1
+ e st , −1 )
]
where mst ,−1 is the mortality rate of the generation of individuals resident in Spain, of
sex s , born during year t ; est ,−1 the rate of external emigration of individuals resident
in Spain, of sex s , born during year t ; IM st ,−1 is the flow of immigration arriving from
abroad of those born of sex s during year t ; and N st are those born in Spain of sex s
during year t , derived from the following expression:
 PMt ,14 + PMt +,115  t
 PMt ,15 + PMt +,116  f Mt ,15



⋅
N = r ⋅
 ⋅ f M ,14 + r ⋅ 
 2 +
2
2




+
1
+
1
t
t
t
t
t
t
48  
 P + PM , x+1  f x 
P
+P  f
⋅  +
r ⋅ ∑   M , x−1 M , x  ⋅ x−1 +  M , x
 2 

2
2
2
x =16  




t
s
 P t + PMt +,149  f Mt , 48
 PMt , 49 + PMt +,150  t
⋅

 ⋅ f M , 49
r ⋅  M , 48
+
r
⋅
 2


2
2




where r = 0,515679227 for the male sex and r = 0,484320773 for the female sex;
PMt , x the population of women of age x at 1 January of year t ; and f xt is the fertility
rate of the generation of women resident in Spain of age x at 1 January of year t
during the aforementioned year.
-
For the open group aged 101 or over:
+1
Pst,101
+ =
[1 − 0,5 ⋅ (m
t
s ,100+
]
+ est ,100+ ) ⋅ ( Pst,100 + Pst,101+ ) + IM st ,100+
[1 + 0,5 ⋅ (m
t
s ,100+
+ est ,100+ )
]
where Pst,100 is the population resident in Spain of sex s and age 100 at 1 January of
year t ; Pst,101+ is the population resident in Spain or sex
January of year t ; m
t
s ,100 +
s aged 101 or over at 1
is the mortality rate of the generation of individuals of sex s
resident in Spain aged 100 or over at 1 January of year t during the aforementioned
year; est ,100+ is the rate of external emigration of the generation of individuals of sex s
resident in Spain aged 100 or over at 1 January of year t during the aforementioned
5
year; and IM st ,100+ the flow of immigration arriving from abroad of individuals of sex s
aged 100 or over at 1 January of year t during the aforementioned year.
In addition, deaths of individuals resident in Spain of sex s and age x at 1 January of
year t during the aforementioned year, Dst , x , are taken from:
-
For individuals of the generation aged x = 0,1,...,99 at 1 January of year t :
 P t + Pst,+x1+1 

Dst , x = mst , x ⋅  s , x

2


-
For those born during year t :
 N t + Pst,+01 

Dst , −1 = mst , −1 ⋅  s

2


where Dst ,−1 represents deaths occurring in year t of residents in Spain of sex s born
during year and mst ,−1 their annual mortality rate in the aforementioned year.
- For individuals of the generations aged 100 or over at 1 January of year t :
+1
 P t + Pst,101+ + Pst,101
+
Dst ,100+ = mst ,100+ ⋅  s ,100
2

where




Pst,101+ is the population resident in Spain or sex s aged 101 or over at 1
January of year t and Dst ,100+ represents deaths of individuals of sex s aged 100 or
over during year t .
External emigrations of individuals resident in Spain of sex s and age x at 1 January
of year t during the aforementioned year, E st , x , are also taken from:
- For individuals of the generation aged x = 0,1,...,99 at 1 January of year t :
 P t + Pst,+x1+1 

E st , x = est , x ⋅  s , x

2


-
For those born during year t :
 N t + Pst,+01 

Est , −1 = est , −1 ⋅  s

2


where E st ,−1 are emigrations in year t of those born in Spain of sex s and est ,−1 their
rate of external emigration.
- For individuals of generations aged 100 or over at 1 January of year t :
6
+1
 P t + Pst,101+ + Pst,101
+
E st ,100+ = est ,100+ ⋅  s ,100
2

where




Pst,101+ is the population resident in Spain of sex s aged 101 or over at 1
January of year t and est ,100+ is the rate of external emigration of individuals resident in
Spain of sex s and aged 100 or over during year t .
B. For each h province the calculation is carried out by means of an iterative process
according to the following steps in each year of the projection period:
1. Provincial population figures are made available at 1 January of the following year
with interprovincial migration null.
2. Interprovincial migratory flows by sex and generation are calculated with the results
from point 1 and the projected rates of internal migration.
3. The provincial population figures are made available at 1 January of the following
year, taking into account the results from point 2.
4. With the results from point 3 and the projected rates of internal migration,
interprovincial migratory flows by sex and generation are calculated.
All of which is in accordance with the following calculations:
- For the ages x = 1,2,...,100 :
Pht,+s1, x +1 =
[1 − 0,5 ⋅ (m
t
h,s , x
]
+ eht , s , x ) ⋅ Pht,s , x + IM ht , s , x + Iiht , s , x − Eiht , s , x
[1 + 0,5 ⋅ (m
t
h,s , x
+ eht , s , x )
]
where mht ,s , x is the annual mortality rate t of individuals resident in province h of sex s
and age x at 1 January of year t ; est , x is the rate of external emigration in year t of
individuals resident in province h of sex s and age x at 1 January of year t ; IM st , x is
the flow of immigration arriving from abroad arriving in province h in year t of
individuals resident in Spain of sex s and age x at 1 January of year t ; e Iiht ,s , x and
Eiht ,s , x are the interprovincial immigration and emigration flows respectively of
individuals of sex s and age x at 1 January of year t in province h .
- For age x = 0 :
Pht,+s1,o =
[1 − 0,5 ⋅ ( m
t
h ,s , −1
]
+ eht , s , − 1 ) ⋅ N ht , s + IM ht , s , − 1 + Ii ht , s , − 1 − Ei ht , s , − 1
1 + 0 ,5 ⋅ ( m ht , s , − 1 + eht , s , − 1 )
[
]
where mht ,s , −1 is the annual mortality rate t of residents of sex s in province h born
during the aforementioned year; eht ,s , −1 is the rate of external emigration in year t of
those resident in province h of sex s born during year t ; IM ht ,s , −1 is the flow of
immigration arriving from abroad in province h of individuals of sex s born during year
7
t ; Iiht ,s , −1 and Eiht , s , −1 are respectively the interprovincial immigration and emigration
flows during year t , of province h , of individuals of sex s born during the year; and
N ht ,s are those born of the sex s in province h during year t , taken from:
 Pt
 Pt
+ Pht,+M1 ,15  t
+ Pht,+M1 ,16  f ht,M ,15
 ⋅ f h ,M ,14 + r ⋅  h ,M ,15
⋅
N ht , s = r ⋅  h ,M ,14
+



2
2
2




48  
 P t + Pht,+M1 , x+1  f ht, x 
Pt
+ P t +1  f t
+
⋅
r ⋅ ∑   h ,M , x −1 h ,M , x  ⋅ h , x −1 +  h ,M , x



2
2
2
2
x =16  




 Pt
 Pt
+ P t +1  f t
+ P t +1 
r ⋅  h ,M , 48 h ,M , 49  ⋅ h ,M , 48 + r ⋅  h ,M , 49 h ,M ,50  ⋅ f ht,M , 49
2
2
2




in which r = 0,515679227 for the male sex and r = 0,484320773 for the female sex;
Pht, M , x is the population of females resident in province h aged x at 1 January of year
t; and f ht, M , x is the fertility rate in year t of women resident in province h belonging to
the generation aged x at 1 January of the aforementioned year.
-For the open group aged 101 or over:
Pht,+s1,101+ =
[1 − 0,5 ⋅ (m
t
h , s ,100 +
]
+ eht , s ,100 + ) ⋅ ( Pht, s ,100 + Pht, s ,101+ ) + IM ht , s ,100 + + Iiht , s ,100 + − Eiht , s ,100 +
[1 + 0,5 ⋅ (m
t
h , s ,100 +
+ eht , s ,100 + )
]
where Pht,s ,100 is the population resident in province h of sex s aged 100 at 1 January
of year t ; Pht,s ,101+ is the population resident in province h of sex s aged 101 or over at
1 January of year t ; m ht , s ,100 + is the annual mortality rate t of individuals of sex s
resident in province h belonging to the generation aged 100 years or over at 1
January of the aforementioned year; eht ,s ,100+ is the rate of foreign emigration in year t
of individuals resident of sex s resident in province h belonging to the generation
aged 100 years or over at 1 January of year t ; IM st ,100+ is the flow of immigration
arriving from abroad during year t in province h of individuals of sex s aged 100 or
over at 1 January of year t ; and Iiht , s ,100+ and Eiht , s ,100+ are the immigration a flow
arriving from the rest of Spain and the emigration flow destined for the rest of Spain of
individuals of sex s, belonging to the generations aged 100 years or over at 1 January
of year t during the aforementioned year, respectively.
The immigration flows in province h arriving from the rest of Spain are obtained using
the expressions:
- For individuals of generation of age x = 0,1,2,...,99 at 1 January of year t :
8
 P t + Pkt,+s1, x+1 

Iiht ,s , x = ∑ eist , x ,k ,h ⋅  k ,s , x

2
k ≠h


where eist , x , k , h is the specific domestic emigration rate from province k to h in year t
of individuals of sex s belonging to the generation aged x at 1 January of the
aforementioned year.
- For those born during year t :
 N t + Pkt,+s1, 0 

Iiht ,s , −1 = ∑ eist , −1,k ,h ⋅  k ,s

2
k ≠h


where eist ,−1,k ,h is the specific rate of domestic emigration from province k to h year
t of those born of sex s during the aforementioned year.
- For individuals of the generation aged 100 years or over at 1 January of year t :
 Pt
+ Pt
+ Pkt,+s1,101+ 

Iiht ,s ,100+ = ∑ eist ,100 + ,k ,h ⋅  k ,s ,100 k ,s ,101+

2
k ≠h


where eist ,100 + ,k ,h is the specific rate of internalemigration from province k to h in year
t of individuals resident in province k of sex s belonging to the generation aged 100
years or over at 1 January of the aforementioned year.
And the emigration flows arriving from province h destined for the rest of Spain are
obtained using the expressions:
- For all individuals belonging to the generation aged x = 0,1,...,99 at 1 January of
year t :
 P t + Pht,+s1, x+1 

Eiht ,s , x = ∑ eist , x ,h ,k ⋅  h,s , x

2
h


where eist , x , h , k is the specific rate of internal emigration from province h to k in year
t of individuals of sex s belonging to the generation aged x at 1 January of the
aforementioned year.
-For those born during year t :
 N t + Pht,+s1,0 

Eiht ,s , −1 = ∑ eist , −1,h,k ⋅  h,s

2
h


where eist ,−1,h ,k is the specific rate of internal emigration from province h to k in year
t of those born of sex s during the aforementioned year.
9
- For individuals belonging to the generation aged 100 years or over at 1 January of
year t :
 Pt
+ Pt
+ Pht,+s1,101+ 

Eiht ,s ,100+ = ∑ eist ,100+ ,h ,k ⋅  h ,s ,100 h,s ,101+

2
h


where eist ,100,h ,k is the specific rate of internal emigration from province h to k in year
t of individuals resident in province h of sex s belonging the generation aged 100
years or over at 1 January of the aforementioned year.
In addition, deaths of individuals resident in province h of sex s and age
January of year t during the aforementioned year, Dst , x , are taken from:
x at 1
 P t + Pht,+s1, x+1 

Dht , s , x = mht , s , x ⋅  h,s , x

2


where
mht ,s , x is the annual mortality rate t of those resident in province h of sex
s belonging to the generation of individuals aged x at 1 January of year t .
-
For those born during year t :
 N t + Pht,+s1,0 

Dht , s , −1 = mht , s , −1 ⋅  h , s

2


where Dht ,s , −1 are the deaths in year t of those born during the aforementioned year of
sex s in province h and mht ,s , −1 is their annual mortality rate in the aforementioned
year.
- For individuals belonging to the generation aged 100 years or over at 1 January of
year t :
 Pt
+ Pht, s ,101+ + Pht,+s1,101+
Dht ,s ,100+ = mht ,s ,100+ ⋅  h,s ,100
2

where




Pht,s ,101+ is the population resident in province h of sex s belonging to the
generations aged 101 years or over at 1 January of year t ; Dht , s ,100+ are deaths of
individuals resident in province h of sex s belonging to the generations aged 100
years or over at 1 January of year t ; and mht , s ,100+ the mortality rate of individuals
resident in province h of sex s belonging to the generations aged 100 years or over at
1 January of year t .
In the same way, emigrants to abroad of sex s belonging to the generation aged x at
1 January of year t during the aforementioned year, Eht ,s , x are given:
10
- For individuals of the generation x = 0,1,2,...,99 aged at 1 January of year t :
 P t + Pht,+s1, x +1 

Eht ,s , x = eht , s , x ⋅  h, s , x

2


where eht ,s , x is the rate of external emigration in year t of those resident in province h
of sex s belonging to the generation of individuals aged x at 1 January of year t .
- For those born during year t :
 N t + Pht,+s1,0 

Eht ,s , −1 = eht ,s , −1 ⋅  h,s

2


where Eht ,s , −1 are emigrations to abroad in t of those born during the aforementioned
year of sex s in province h and eht ,s , −1 their rate of foreign emigration in the
aforementioned year.
- For individuals belonging to the generation aged 100 years or over at 1 January of
year t :
 Pt
+ Pht,s ,101+ + Pht,+s1,101+
E ht ,s ,100+ = eht ,s ,100+ ⋅  h,s ,100
2





where Eht ,s ,100+ is external emigration of individuals resident in province h of sex s
belonging to the generations aged 100 years or over at 1 January of year t ; and
eht ,s ,100+ the rate of external emigration of individuals resident in province h of sex
s belonging to the generations aged 100 years or over at 1 January of year t .
Lastly, it should be noted that calculating the projection entails an iterative process of
checking for consistency and adjustment of the national results for projected
populations and demographic events obtained from the projected national total and
aggregation of provincial results, introducing successive provincial correction factors
which make very slight changes, to the same degree for all provinces in each age and
sex (and therefore without changing the relative position of each province with regard
to other provinces as far as the incidence of each demographic phenomenon for each
sex and age is concerned), the specific fertility, mortality and external emigration rates,
until such time as total interterritorial consistency of projected population stocks and
demographic events is achieved.
11
2
Baseline population
The baseline population of simple projection by sex and age, to an open age group
aged 100 years and over, at 1 January 2008 is composed of the Population Now Cast
at the aforementioned date, which guarantees the desired coherence with them.
Nevertheless, the population figures for those aged 100 years and over 100 years,
resident in each province at 1 January 2008, have been approximated by applying the
distribution of the population resident in Spain aged 100 years and over in those two
age groups to the population aged 100 years and over resident in each province, since
the aforementioned breakdown of age on a provincial level did not reach the
Population Now-Cast.
12
3
Fertility projection
3.1 Fertility projection in Spain
As far as national fertility is concerned, a short-term projection hypothesis has been
prepared based on the extrapolation of the trends observed in the previous period in
the fertility rates of women resident in Spain.
The general methodology used in projecting fertility in Spain is in accordance with the
following guidelines:
a) Modelling of the evolution in the recent past of observed fertility rates observed for
the generations, by age and iorder of birth:
Fertility rates have been calculated for generations taken from Vital Statistics (VS)
data on births for 1975 to 2006, and Intercensal Estimates of Population data and
Population Now-Cast data for female population stocks. This set of rates has made it
possible to reconstruct the fertility of the generations born between 1925 and 1992, but
none of them completely, since for each generation rates are only available for a
maximum of 31 years of age. These rates have been calculated by order of birth, for
1, 2, 3 and for 4 and higher orders.
Modelling has been performed for each age and order separately, taking the following
linear-log type formulation, in which rates are related to age x order r with the time t
logarithm:
f (t , x, r ) = a ( x, r ) ⋅ ln(t ) + b( x, r )
Values of parameters a and b have been estimated by the minimum ordinary square
method taking the latest nine available observations, for each simple age and each
order. The reason forusing only the latest nine available observations in the
adjustment is that fertility increases progressively from a minimum value in the year
1995, after a long decrease from the year 1980. The adjustment is carried out taking
the values of the 1998-2006 period, in other words after the point at which the trend is
broken.
b) On the basis of this modelling, fertility of the generations has been completed in
order to confirm the coherence of its results:
The projection of the generation rates by age and order is obtained from the value of
parameters a and b estimated in the previous step, in accordance with the following
expression (where t is the year, x is the age, r is the birth bracket):
f (t + 1, x, r ) = f (t , x, r ) + a ( x, r ) ⋅ ln(t + 1 / t )
The aforementioned formula has been applied to all ages and orders, projecting the
rates such that complete information is available for the incidence of the phenomenon
up to the year 2005.
c) Converting the generation rates into period rates in order to obtain the fertility series
up to the year 2018, approximating them taking the semi-sum of the rates of the same
age for two consecutive generations.
13
Fertility curves observed between 1975 and 2005, and projected for the 2008-2018
period according to the described procedure are shown in the following graphs:
Tasas de fecundidad de España proyectadas
Tasas
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2008
2010
2013
2017
2016
Tasa de fecundidad de España observadas y proyectadas
Tasas
0,21
0,18
0,15
0,12
0,09
0,06
0,03
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
1975
1980
1985
1990
1995
2000
2005
2010
2017
2015
The projected evolution of the fertility pattern is thus characterised by a gradual
increase in rates, accompanied by a horizontal movement of the curve to the right from
the age 28 , attributable to the continued delay in fertility of women born in Spain, and
14
an increase in the intensity of fertility around the age 22 , attributable in turn to the
effect of women born abroad.
The period fertility rates observed and projected by five-yearly age groups show a
transition for all ages between a period of decrease and another of increase, although
the period in which the minimum is reached for this trend evolution for each age group
does not coincide, with the earliest recovery corresponding to the 30-34 years age
group, taking place around the year 1987, and the latest corresponding to the 25-29
age group, in the year 2003. It should be noted that the increase in rates as of the age
of 30 years is due to the progressive delay in the age of motherhood in Spanish-born
women, and the increase for groups under the age of 30 years, due to the fertility
effect of foreign women. The following graph shows these rates on a semi-logarithmic
scale, with the objective of making comparable their growth in time and between
groups and being able to better appreciate the values of the aforementioned rates for
the age groups with the lowest values:
The observed and projected values of the total intensity of momentary fertility (Total
Fertility Rate) and of each of the generations (Final Descent) are a reflection of the
gradual increase in the Mean Age at Childbearing in the last few decades, and the
interruption of the aforementioned increasing evolution thereof over recent years and
for the projected period, also as a result of the younger fertility calendar shown by
15
resident women born abroad. Thus, the Total Fertility Rate (ISF) values would
permanently exceed those of Final Descent (DF) as of the year 2006, as a result of the
increase in weight of foreign women in the population structure by nationality, since
Mean Age at Childbearing (EMMp) of the moment will continue to increase at a slow
rate, although the Mean Age at Childbearing of the generations (EMMg) will be
established and will foreseeably begin to decrease:
16
3.2 Fertility projection in the autonomous communities and provinces
The projection hypothesis of fertility for each autonomous community for the 20082017 period is derived from the hypothesis established for the national level, using a
relational method, which would be carried out in two phases:
Firstly, the territorial dispersion of fertility is analysed in relation to the national level for
the historical 1998-2006 period. A hypothesis has been prepared, taking an analysis of
the evolutionary trend of total fertility differences for each autonomous community with
the national total, consisting of a multiplier coefficient time series which describes the
aforementioned differential behaviour with regard to the whole of Spain. This multiplier
coefficient makes it possible to derive the value of the Total Fertility Rate (ISF) for the
autonomous community depending on the Spanish Total Fertility Rate for the
projection period in accordance with the evolution hypothesis established regarding
this.
Secondly, the fertility calendar is analysed for each autonomous community, using
average age as a criterion, as a central position measurement for this, and the interval
or interquartilic range, as an indicator of its dispersion. The value of these two
parameters is projected in time for each autonomous community.
The value of the Total Fertility Rate, the average age and interquartilic interval,
projected in each autonomous community, enables calculation of the fertility rates by
simple age using the value shown for these rates in the community for the latest
17
observation period, using a relational fertility model known as the Relational Gompertz
Method, following the methodology proposed by Zeng and others (2001)2.
The projected Total Fertility Rate value for each autonomous community is derived, as
we have stated, from the Total Fertility Rate of Spain multiplied by a coefficient. The
value of this coefficient is taken from an extrapolation up to the year 2017 of the value
shown during the 1998-2006 period. The aforementioned extrapolation has been
carried out using a time linear-log function, considering the latest nine values shown,
the adjusted parameters of which are shown in the following graphs, as well as the
extrapolated value of the coefficient for the whole of the projection period:
2
Zeng Yi, Wang Zhenglian, Ma Zhongdong and Chen Chunjun. 2000. "A simple method for projecting or
estimating and: An extension of the Brass Relational Gompertz Fertility Model", Population Research and
Policy Review 19:525–549.
18
Aragón
Andalucía
1,6
1,6
1,4
1,4
1,2
1,2
1
1
0,8
0,8
y= -.0201Ln(x) +
0,6
1990
2000
2010
2020
1990
Asturias (Principado de)
1,6
1,4
1,2
1
0,8
0,6
1990
2010
2020
1,6
1,4
y= -.0495Ln(x) +
1,2
y= .0012Ln(x) +
1
0,8
0,6
2000
2010
2020
1990
2000
2010
2020
Cantabria
1,6
1,6
1,4
1,2
y= -.0897Ln(x) +
1,2
1
y= .0365Ln(x) +
1
0,8
0,8
0,6
1990
2000
Baleares
Canarias
1,4
y= .0252Ln(x) +
0,6
2000
2010
2020
0,6
1990
2000
2010
2020
19
Castilla-La Mancha
Castilla y León
1,6
1,4
1,2
1
0,8
0,6
1990
1,6
1,4
y= -.0021Ln(x) +
y= -.0434Ln(x) +
1,2
1
0,8
0,6
2000
2010
2020
1990
Cataluña
2000
2010
2020
Ceuta
1,6
1,6
1,4
1,4
1,2
y= .035Ln(x) +
1,2
1
y= -.0164Ln(x) +
1
0,8
0,8
0,6
1990
2000
2010
2020
0,6
1990
Comunidad Valenciana
2020
1,6
1,4
y= -.0053Ln(x) +
1,2
y= -.0756Ln(x) +
1,2
1
1
0,8
0,8
0,6
1990
2010
Extremadura
1,6
1,4
2000
0,6
2000
2010
2020
1990
2000
2010
2020
20
Galicia
La Rioja
1,6
1,4
1,6
1,4
y= -.027Ln(x) +
1,2
y= .017Ln(x) + .946
1,2
1
1
0,8
0,6
0,8
0,6
1990
2000
2010
2020
1990
2000
2010
2020
Melilla
Madrid (Comunidad de)
1,6
1,6
1,4
1,4
y= .0291Ln(x) +
1,2
1
1,2
0,8
0,6
0,8
y= -.0972Ln(x) +
1
0,6
1990
2000
2010
2020
1990
Murcia (Región de)
1,6
1,4
1,4
1,2
1,2
0,8
0,6
0,6
2000
2010
2020
y= .0227Ln(x) +
1
y= .0045Ln(x) +
0,8
1990
2010
Navarra (Comunidad Foral
de)
1,6
1
2000
2020
1990
2000
2010
2020
País Vasco
1.6
1.4
y= .0279Ln(x) + .8266
1.2
1
0.8
0.6
1995
2000
2005
2010
2015
2020
21
In this way, the Total Fertility Rate values observed and projected in each autonomous
community are shown in the following chart:
Indice Sintético de Fecundidad por comunidades autónomas
Comunidad Autónoma
Total nacional
Andalucía
Aragón
Asturias (Principado de)
Balears (Illes)
Canarias
Cantabria
Castilla y León
Castilla-La Mancha
Cataluña
Comunitat Valenciana
Extremadura
Galicia
Madrid (Comunidad de)
Murcia (Región de)
Navarra (Comunidad Foral de)
País Vasco
Rioja (La)
Ceuta
Melilla
Observado
2002
2003
2004
2005
2006
2007
Proyectado
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
1,26
1,31
1,33
1,35
1,38
1,39
1,40
1,41
1,41
1,42
1,43
1,44
1,44
1,45
1,45
1,46
1,36
1,41
1,44
1,47
1,51
1,50
1,52
1,53
1,54
1,54
1,55
1,55
1,56
1,56
1,57
1,57
1,17
1,22
1,26
1,26
1,33
1,37
1,35
1,36
1,37
1,38
1,39
1,40
1,41
1,42
1,43
1,43
0,86
0,91
0,92
0,96
0,97
1,01
0,98
0,99
1,00
1,00
1,01
1,01
1,02
1,02
1,03
1,03
1,38
1,37
1,35
1,34
1,41
1,38
1,41
1,42
1,42
1,42
1,43
1,43
1,43
1,43
1,43
1,43
1,21
1,18
1,16
1,20
1,22
1,16
1,22
1,21
1,21
1,21
1,20
1,20
1,20
1,20
1,19
1,19
1,10
1,16
1,18
1,21
1,19
1,19
1,22
1,23
1,24
1,25
1,26
1,27
1,28
1,29
1,30
1,31
1,02
1,05
1,07
1,09
1,11
1,13
1,13
1,14
1,14
1,15
1,15
1,16
1,16
1,17
1,17
1,18
1,29
1,33
1,33
1,34
1,41
1,35
1,42
1,42
1,42
1,43
1,43
1,43
1,43
1,44
1,44
1,44
1,33
1,39
1,43
1,46
1,48
1,49
1,52
1,53
1,54
1,55
1,57
1,58
1,59
1,60
1,60
1,61
1,30
1,34
1,35
1,36
1,39
1,41
1,41
1,42
1,43
1,43
1,44
1,45
1,45
1,46
1,46
1,47
1,25
1,27
1,26
1,28
1,29
1,30
1,29
1,29
1,29
1,29
1,29
1,29
1,29
1,29
1,29
1,28
0,95
1,00
1,00
1,02
1,03
1,05
1,04
1,04
1,04
1,05
1,05
1,05
1,06
1,06
1,06
1,06
1,31
1,37
1,39
1,38
1,42
1,45
1,45
1,46
1,47
1,48
1,49
1,50
1,51
1,52
1,53
1,54
1,53
1,58
1,56
1,59
1,64
1,65
1,66
1,67
1,68
1,69
1,70
1,71
1,71
1,72
1,73
1,73
1,31
1,39
1,40
1,35
1,44
1,45
1,46
1,48
1,49
1,50
1,51
1,52
1,53
1,53
1,54
1,55
1,09
1,16
1,18
1,19
1,22
1,27
1,24
1,25
1,27
1,27
1,28
1,29
1,30
1,31
1,32
1,32
1,21
1,32
1,32
1,34
1,33
1,39
1,35
1,36
1,37
1,38
1,39
1,40
1,40
1,41
1,42
1,42
1,76
1,77
1,89
1,93
1,92
2,75
1,94
1,95
1,96
1,97
1,98
1,98
1,99
2,00
2,01
2,01
1,90
2,03
1,86
1,95
2,19
2,57
2,20
2,20
2,20
2,20
2,20
2,20
2,20
2,20
2,20
2,20
Fuente: 2002 - 2007, Indicadores Demográficos Básicos; 2008 - 2017, Proyección de Población a Corto Plazo
The projection of the fertility calendar, in other words of the fertility rates by age
pattern, for each autonomous community, has been projected in accordance with the
following schema:
Firstly, the evolution in time of the value of the Median Age at Childbearing and the
interquartilic interval of the accumulated function of fertility for each autonomous
community has been analysed: the data shown for the last few years appears to point
to the evolution of the average age in time having stabilised in the recent period.
Conversely, the value of the interquartilic interval increases, following a decrease up
until the year 1995:
22
Evolution of the Median Age at Childbearing for the autonomous communities
1975-2006
Evolution of the Interquartilic Range of fertility for the autonomous communities
1975-2006
Secondly, the value has been projected of these two parameters for each autonomous
community, using a time linear-log adjustment extrapolation method for the nine latest
values, as has been done with the fertility by age rates and by order of the national
level, and with the Total Fertility Rate multiplier coefficient.
23
24
And the fertility calendar has been derived for the 2007-2017 period, taking the value
of these two parameters and of the fertility curve by age of each autonomous
community for the year 2006. In order to be able to use the curves for each community
as a projection pattern, these have in addition undergone a prior process of
smoothing, since the profile by age shown for these curves is normally irregular. The
25
4253.Htwice3 robust algorithm has been used for this smoothing. The values shown
and smoothed for the aforementioned curves are shown in the following graph:
3
Velleman, P. F. and D.C. Hoaglin. 1981. Applications, Basics, and Computing of Exploratory Data
Analysis. Boston: Duxbury Press.
26
27
Lastly, the curves have been derived by age for each autonomous community for the
2007-2017 period using the three previous projected series of the Total Fertility Rate,
of the average age at motherhood and of the interquartilic interval, and using the
smoothed curve of fertility rates by age for the year 2006 of the actual community. The
Gompertz relational model is used, taking the re-setting of the Zeng parameter, with t
varying between 2007 and 2018:
γ ( F ( x, t ) / ISF (t )) = α (t ) + β (t ) ⋅ Y ( F ( x,2006) / ISF (2006))
x
with
F ( x, t ) = ∑ f (i, t ) is the value of the accumulated fertility rate at value x and
i =1
γ ( x) = − ln(− ln( x)) is a double-logarithm transformation of this accumulated value. The
value of parameters α (t ) and β (t ) is calculated as follows:
β (t ) = I (2006) / I (t ) , where I (t ) is the interquartilic interval
α (t ) = γ (0,5) − β (t ) ⋅ γ ( F ( M (t ),2006) / ISF (2006)) , where M (t ) is the Median Age at
Childbearing for the autonomous community for year t.
The fertility curves shown in 2006 and projected for the 2007-2018 period in each
autonomous community are shown in the following graphs:
28
Tasas
Tasas de fecundidad observadas y proyectadas. Andalucía.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
Tasas
2009
2012
2015
2017
Tasas de fecundidad observadas y proyectadas. Aragón.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
2009
2012
2015
2017
29
Tasas
Tasas de fecundidad observadas y proyectadas. Principado de Asturias.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
Tasas
2009
2012
2015
2017
Tasas de fecundidad observadas y proyectadas. Illes Balears.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
Edad
2006
2009
2012
2015
2017
30
Tasas
Tasas de fecundidad observadas y proyectadas. Canarias.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
Tasas
2009
2012
2015
2017
Tasas de fecundidad observadas y proyectadas. Cantabria.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
Edad
2006
2009
2012
2015
2017
31
Tasas
Tasas de fecundidad observadas y proyectadas. Castilla y León.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
Tasas
2009
2012
2015
2017
Tasas de fecundidad observadas y proyectadas. Castilla-La Mancha.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
2009
2012
2015
2017
32
Tasas
Tasas de fecundidad observadas y proyectadas. Cataluña.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
Tasas
2009
2012
2015
2017
Tasas de fecundidad observadas y proyectadas. Comunitat Valenciana.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
2009
2012
2015
2017
33
Tasas
Tasas de fecundidad observadas y proyectadas. Extremadura.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
Tasas
2009
2012
2015
2017
Tasas de fecundidad observadas y proyectadas. Galicia.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
2009
2012
2015
2017
34
Tasas
Tasas de fecundidad observadas y proyectadas. Comunidad de Madrid.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
Tasas
2009
2012
2015
2017
Tasas de fecundidad observadas y proyectadas. Región de Murcia.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
2009
2012
2015
2017
35
Tasas
Tasas de fecundidad observadas y proyectadas. Comunidad Foral de Navarra.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
Tasas
2009
2012
2015
2017
Tasas de fecundidad observadas y proyectadas. País Vasco.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
Edad
2006
2009
2012
2015
2017
36
Tasas
Tasas de fecundidad observadas y proyectadas. La Rioja.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
Tasas
2009
2012
2015
2017
Tasas de fecundidad observadas y proyectadas. Ceuta.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
2009
2012
2015
2017
37
Tasas
Tasas de fecundidad observadas y proyectadas. Melilla.
0,14
0,12
0,10
0,08
0,06
0,04
0,02
0,00
15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
Edad
2006
2009
2012
2015
2017
Lastly, the fertility projection methodology on a provincial level follows a relational
model similar to that of autonomous communities with regard to the national total,
taking as a reference the projection made at the level of autonomous community to
which each province belongs.
In this way, the evolution of the coefficient relating the Total Fertility Rate of each with
that of its autonomous community observed in the 1998-2006 period and extrapolated
for that for the years 2007-2018 according to the adjustment for the period shown of a
linear-log model depending on time, is shown in the following graphs:
38
Andalucía
Almería
Cádiz
1.2
1.2
1.1
1.1
1
1
Y = .0126Ln(x) +
0.9
0.8
1995
Y = .0068Ln(x) + 1.005
0.9
2000
2005
2010
2015
2020
0.8
1995
2000
1.2
2015
2020
1.2
1.1
1.1
Y = -.0343Ln(x) + 1.0375
1
1
0.9
0.9
0.8
1995
0.8
2000
2005
2010
2015
2020
1995
Y = -.0231Ln(x) +
2000
Huelva
2005
2010
2015
2020
Jaén
1.2
1.2
1.1
1.1
Y = .0027Ln(x) + .964
1
1
0.9
0.9
2000
2005
2010
2015
2020
0.8
1995
Y = -.0617Ln(x) + 1.0982
2000
Málaga
2005
2010
2015
2020
Sevilla
1.2
1.2
1.1
1.1
Y = .0242Ln(x) + .956
1
1
0.9
0.9
0.8
1995
2010
Granada
Córdoba
0.8
1995
2005
2000
2005
2010
2015
2020
0.8
1995
Y = .0174Ln(x) + .9785
2000
2005
2010
2015
2020
39
Aragón
Huesca
Teruel
1.2
1.2
1.1
1.1
Y = -.0336Ln(x) + 1.0368
1
1
0.9
0.9
0.8
1995
2000
2005
2010
2015
2020
0.8
1995
Y = -.0557Ln(x) + 1.0597
2000
2005
2010
2015
2020
Zaragoza
1.2
1.1
Y = .0164Ln(x) + .987
1
0.9
0.8
1995
2000
2005
2010
2015
2020
Canarias
Santa Cruz de Tenerife
Las Palmas
1.2
1.2
1.1
1.1
1
0.9
0.9
0.8
1995
0.8
2000
2005
2010
2015
Y = -.0109Ln(x) + .9615
1
Y = .0095Ln(x) + 1.0486
2020
1995
2000
2005
2010
2015
2020
40
Castilla y León
Ávila
Burgos
1.2
1.2
1.1
1.1
1
1
Y = -.0038Ln(x) + 1.082
0.9
0.8
1995
Y = .0225Ln(x) + 1.0399
0.9
2000
2005
2010
2015
2020
0.8
1995
2000
León
1.2
1.1
1.1
1
1
Y = -.0267Ln(x) + .9585
0.9
0.9
0.8
1995
0.8
1995
2005
2010
2015
2020
2020
2000
2005
2010
2015
2020
Segovia
1.2
1.2
1.1
1.1
Y = -.0218Ln(x) + 1.0165
1
1
0.9
0.9
2000
2005
2010
2015
2020
0.8
1995
Y = .01Ln(x) + 1.1471
2000
Soria
2005
2010
2015
2020
Valladolid
1.2
1.2
1.1
1.1
1
1
Y = -.0212Ln(x) + 1.143
0.9
0.8
1995
2015
Y = -.005Ln(x) + .9581
Salamanca
0.8
1995
2010
Palencia
1.2
2000
2005
2000
2005
2010
2015
Y = .0437Ln(x) + .9421
0.9
2020
0.8
1995
2000
2005
2010
2015
2020
41
Castilla – La Mancha
Albacete
Cuenca
1.2
1.2
1.1
1.1
Y = -.0425Ln(x) + 1.0528
1
1
0.9
0.8
1995
Y = -.0133Ln(x) + .9327
0.9
2000
2005
2010
2015
2020
0.8
1995
2000
2010
2015
2020
Guadalajara
Ciudad Real
1.2
1.1
2005
1.2
Y = -.0153Ln(x) + 1.0126
1.1
1
1
0.9
0.9
0.8
1995
0.8
2000
2005
2010
2015
2020
1995
Y = .0839Ln(x) + .9293
2000
2005
2010
2015
2020
Toledo
1.2
1.1
1
Y = .0139Ln(x) + 1.0141
0.9
0.8
1995
2000
2005
2010
2015
2020
42
Cataluña
Barcelona
Gerona
1.2
1.2
1.1
1.1
1
1
Y = .0035Ln(x) + .9897
0.9
0.8
1995
2000
2005
2010
2015
Y = .0014Ln(x) + 1.0647
0.9
2020
0.8
1995
2000
Lerida
1.2
1.1
1.1
1
1
0.8
1995
Y = .0008Ln(x) + .9949
2000
2005
2010
2010
2015
2020
Tarragona
1.2
0.9
2005
2015
Y = -.014Ln(x) + 1.0554
0.9
2020
0.8
1995
2000
2005
2010
2015
2020
Comunidad Valenciana
Castellón de la Plana
Alicante
1.2
1,2
1.1
1,1
1
1
Y = -.0332Ln(x) + 1.0624
0.9
0.8
1995
Y = .0189Ln(x) +
0,9
0,8
2000
2005
2010
2015
2020
1995
2000
2005
2010
2015
2020
Valencia
1.2
1.1
1
Y = .0204Ln(x) + .9615
0.9
0.8
1995
2000
2005
2010
2015
2020
43
Extremadura
Badajoz
Cáceres
1.2
1.2
1.1
1.1
1
1
Y = .004Ln(x) + 1.0272
0.9
0.8
1995
2000
2005
2010
2015
Y = -.0117Ln(x) + .9662
0.9
2020
0.8
1995
2000
2005
2010
2015
2020
44
Galicia
La Coruña
Lugo
1.2
1.2
1.1
1.1
1
1
Y = .0104Ln(x) + .9749
0.9
0.8
1995
2000
2005
2010
2015
Y = -.0323Ln(x) + .9243
0.9
2020
0.8
1995
2000
Orense
1.2
1.1
1.1
2005
2010
2020
Y = .0018Ln(x) + 1.0947
0.9
2000
2015
1
Y = -.0063Ln(x) + .8895
0.9
0.8
1995
2010
Pontevedra
1.2
1
2005
2015
2020
0.8
1995
2000
2005
2010
2015
2020
País Vasco
Álava
Guipúzcoa
1.2
1.2
Y = -.0107Ln(x) + 1.0027
1.1
1.1
1
1
0.9
0.9
0.8
1995
2000
2005
2010
2015
2020
0.8
1995
Y = -.0074Ln(x) + 1.1063
2000
2005
2010
2015
2020
Vizcaya
1.2
Y = .0096Ln(x) + .9386
1.1
1
0.9
0.8
1995
2000
2005
2010
2015
2020
45
The intensities shown in 2006 and projected for 2007-2018 in each province are to be
found in the following table:
Índice sintético de fecundidad
Provincias
Álava
Albacete
Alicante/Alacant
Almería
Ávila
Badajoz
Illes Balears
Barcelona
Burgos
Cáceres
Cádiz
Castellón/Castelló
Ciudad Real
Córdoba
A Coruña
Cuenca
Girona
Granada
Guadalajara
Guipúzcoa
Huelva
Huesca
Jaén
León
Lleida
La Rioja
Lugo
Madrid
Málaga
Murcia
Navarra
Ourense
Asturias
Palencia
Las Palmas
Pontevedra
Salamanca
Santa Cruz de Tenerife
Cantabria
Segovia
Sevilla
Soria
Tarragona
Teruel
Toledo
Valencia/València
Valladolid
Vizcaya
Zamora
Zaragoza
Ceuta
Melilla
Años
2002
2003
2004
2005
2006
2007 (p) 2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
1,05
1,13
1,17
1,16
1,22
1,25
1,24
1,25
1,26
1,27
1,28
1,28
1,29
1,30
1,30
1,31
1,29
1,32
1,25
1,28
1,36
1,24
1,35
1,34
1,34
1,34
1,34
1,34
1,34
1,34
1,34
1,33
1,33
1,36
1,34
1,33
1,35
1,33
1,35
1,36
1,36
1,36
1,37
1,37
1,37
1,38
1,38
1,38
1,47
1,53
1,59
1,59
1,65
1,59
1,67
1,68
1,69
1,70
1,71
1,72
1,72
1,73
1,74
1,74
1,05
1,09
1,12
1,22
1,25
1,20
1,26
1,27
1,28
1,28
1,29
1,30
1,30
1,31
1,31
1,31
1,30
1,33
1,29
1,32
1,35
1,36
1,35
1,35
1,35
1,35
1,35
1,35
1,35
1,35
1,35
1,35
1,39
1,38
1,36
1,35
1,42
1,39
1,41
1,42
1,42
1,42
1,43
1,43
1,43
1,43
1,43
1,43
1,33
1,38
1,43
1,45
1,48
1,49
1,51
1,52
1,54
1,55
1,56
1,57
1,58
1,59
1,60
1,61
1,10
1,11
1,16
1,19
1,22
1,24
1,24
1,25
1,26
1,27
1,28
1,29
1,29
1,30
1,31
1,31
1,19
1,18
1,22
1,21
1,20
1,20
1,19
1,19
1,19
1,18
1,18
1,18
1,18
1,18
1,18
1,17
1,38
1,43
1,47
1,51
1,53
1,49
1,54
1,55
1,56
1,57
1,57
1,58
1,59
1,59
1,60
1,60
1,39
1,40
1,37
1,41
1,53
1,47
1,55
1,57
1,58
1,59
1,60
1,60
1,61
1,62
1,63
1,63
1,24
1,27
1,32
1,35
1,41
1,37
1,41
1,41
1,41
1,41
1,42
1,42
1,42
1,42
1,42
1,42
1,34
1,39
1,38
1,41
1,46
1,44
1,46
1,47
1,47
1,47
1,47
1,48
1,48
1,48
1,48
1,48
0,93
0,98
1,00
1,02
1,04
1,05
1,05
1,05
1,06
1,06
1,07
1,07
1,07
1,07
1,08
1,08
1,25
1,24
1,20
1,14
1,22
1,14
1,22
1,23
1,23
1,23
1,23
1,23
1,23
1,23
1,23
1,24
1,40
1,51
1,54
1,52
1,61
1,53
1,65
1,66
1,68
1,69
1,70
1,72
1,73
1,74
1,75
1,76
1,31
1,37
1,41
1,42
1,45
1,51
1,46
1,46
1,47
1,47
1,47
1,48
1,48
1,48
1,49
1,49
1,38
1,47
1,45
1,43
1,59
1,39
1,64
1,65
1,66
1,67
1,69
1,70
1,71
1,72
1,72
1,73
1,18
1,28
1,29
1,29
1,34
1,39
1,37
1,38
1,39
1,40
1,41
1,42
1,43
1,44
1,44
1,45
1,33
1,37
1,37
1,43
1,44
1,46
1,46
1,47
1,48
1,48
1,49
1,49
1,50
1,50
1,51
1,51
1,14
1,15
1,27
1,23
1,28
1,27
1,29
1,30
1,30
1,31
1,32
1,32
1,33
1,33
1,34
1,34
1,36
1,39
1,41
1,39
1,46
1,43
1,44
1,44
1,44
1,44
1,44
1,44
1,44
1,44
1,44
1,44
0,93
0,95
0,98
0,99
0,99
1,06
0,99
0,99
1,00
1,00
1,00
1,01
1,01
1,01
1,01
1,02
1,28
1,39
1,42
1,49
1,48
1,50
1,52
1,53
1,54
1,56
1,57
1,58
1,59
1,60
1,61
1,61
1,22
1,33
1,32
1,35
1,34
1,40
1,35
1,36
1,37
1,38
1,39
1,40
1,41
1,41
1,42
1,43
0,81
0,87
0,85
0,89
0,88
0,95
0,88
0,88
0,88
0,88
0,88
0,88
0,88
0,88
0,88
0,88
1,32
1,37
1,40
1,38
1,43
1,46
1,45
1,46
1,47
1,48
1,49
1,50
1,51
1,52
1,53
1,54
1,36
1,43
1,45
1,46
1,49
1,49
1,52
1,53
1,54
1,55
1,56
1,57
1,57
1,58
1,59
1,59
1,54
1,59
1,57
1,60
1,64
1,65
1,66
1,67
1,68
1,69
1,70
1,71
1,72
1,72
1,73
1,74
1,32
1,39
1,40
1,35
1,45
1,46
1,46
1,48
1,49
1,50
1,51
1,52
1,53
1,54
1,54
1,55
0,83
0,92
0,86
0,87
0,93
0,94
0,93
0,93
0,94
0,94
0,94
0,94
0,94
0,95
0,95
0,95
0,86
0,92
0,93
0,96
0,98
1,01
0,98
0,99
1,00
1,00
1,01
1,01
1,02
1,02
1,03
1,03
0,98
1,00
0,97
1,03
1,07
1,01
1,08
1,09
1,09
1,10
1,10
1,11
1,11
1,11
1,12
1,12
1,29
1,30
1,26
1,25
1,28
1,15
1,27
1,27
1,27
1,26
1,26
1,26
1,26
1,26
1,25
1,25
1,06
1,09
1,10
1,11
1,11
1,13
1,12
1,12
1,13
1,13
1,13
1,14
1,14
1,14
1,14
1,15
1,00
1,04
1,07
1,05
1,05
1,14
1,06
1,06
1,07
1,07
1,08
1,08
1,08
1,08
1,09
1,09
1,15
1,06
1,06
1,16
1,18
1,17
1,17
1,17
1,16
1,16
1,16
1,15
1,15
1,15
1,14
1,14
1,10
1,16
1,19
1,22
1,20
1,20
1,22
1,23
1,24
1,25
1,26
1,27
1,28
1,29
1,30
1,31
1,19
1,24
1,21
1,30
1,29
1,24
1,31
1,32
1,33
1,34
1,35
1,35
1,36
1,37
1,37
1,38
1,36
1,41
1,45
1,50
1,56
1,58
1,58
1,59
1,60
1,61
1,62
1,62
1,63
1,64
1,64
1,65
1,07
1,22
1,19
1,21
1,19
1,15
1,20
1,21
1,21
1,22
1,22
1,23
1,23
1,23
1,24
1,24
1,41
1,42
1,44
1,50
1,51
1,53
1,54
1,55
1,56
1,58
1,59
1,59
1,60
1,61
1,62
1,63
1,04
1,13
1,21
1,25
1,25
1,31
1,26
1,26
1,27
1,27
1,27
1,28
1,28
1,28
1,29
1,29
1,32
1,38
1,42
1,41
1,45
1,46
1,46
1,47
1,47
1,48
1,48
1,49
1,49
1,49
1,50
1,50
1,26
1,33
1,36
1,39
1,41
1,47
1,44
1,45
1,46
1,47
1,48
1,48
1,49
1,50
1,51
1,51
1,04
1,07
1,09
1,12
1,18
1,17
1,21
1,22
1,23
1,24
1,25
1,26
1,27
1,27
1,28
1,29
1,05
1,11
1,13
1,15
1,16
1,22
1,18
1,20
1,21
1,22
1,23
1,24
1,25
1,25
1,26
1,27
0,98
0,97
0,92
0,92
0,95
0,90
0,94
0,94
0,94
0,94
0,93
0,93
0,93
0,93
0,93
0,93
1,20
1,26
1,27
1,28
1,36
1,42
1,39
1,40
1,42
1,43
1,44
1,45
1,46
1,47
1,48
1,49
1,76
1,78
1,89
1,93
1,92
2,75
1,94
1,95
1,96
1,97
1,98
1,98
1,99
2,00
2,01
2,01
1,90
2,04
1,86
1,95
2,20
2,57
2,20
2,20
2,20
2,20
2,20
2,20
2,20
2,20
2,20
2,20
Fuente: 2002 - 2007, Indicadores Demográficos Básicos; 2008 - 2017, Proyección de Población a Corto Plazo
The projection of the fertility calendar in each province is also carried out in a similar
way to the projection thereof in each autonomous community. In this way the values
projected and observed in each province of the Median Age at Childbearing and of the
interquartilic range of the distribution of specific fertility rates by age can be seen in the
following graphs:
46
Andalucía
Alm ería
Cádiz
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
1995
4
2000
2005
2010
2015
2020
22
1995
Edad mediana
4
2000
2005
2010
2015
2020
Int . Int er.
Edad mediana
Int. Inter.
Granada
Córdoba
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
4
22
1995
1995
2000
2005
2010
Edad mediana
2015
2020
2000
2005
2010
Edad mediana
Int . Int er.
2015
4
2020
Int. Inter.
Jaén
Huelva
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
5
24
5
4
2020
22
24
22
1995
2000
2005
2010
Edad mediana
2015
1995
4
2000
Int. Inter.
2005
2010
Edad mediana
Málaga
2015
2020
Int . Int er .
Sevilla
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
1995
2000
2005
Edad mediana
2010
2015
Int. Inter.
4
2020
22
1995
2000
2005
Edad mediana
2010
2015
4
2020
Int. Inter.
47
Aragón
Teruel
Huesca
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
4
2020
22
22
1995
2000
2005
2010
Edad mediana
2015
1995
4
2000
Int. Inter.
2005
2010
Edad mediana
2015
2020
Int . Int er .
Zaragoza
34
10
32
9
30
8
28
7
26
6
24
5
22
1995
2000
2005
2010
Edad mediana
2015
4
2020
Int. Inter.
Canarias
Las Palmas
Santa Cruz de Tenerife
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
1995
2000
2005
Edad mediana
2010
2015
Int. Inter.
4
2020
22
1995
2000
2005
Edad mediana
2010
2015
4
2020
Int. Inter.
48
Castilla y León
Ávila
Burgos
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
4
22
1995
2000
2005
2010
Edad mediana
2015
2020
1995
4
2000
Int . Int er.
2005
2010
Edad mediana
León
2015
2020
Int . Int er .
Palencia
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
4
22
1995
2000
2005
2010
Edad mediana
2015
2020
1995
4
2000
2005
2010
Edad mediana
Int . Int er.
2015
2020
Int. Inter.
Segovia
Salamanca
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
4
2020
22
22
1995
2000
2005
2010
Edad mediana
2015
1995
4
2000
Int. Inter.
2005
2010
Edad mediana
Soria
2015
2020
Int . Int er .
Valladolid
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
1995
2000
2005
Edad mediana
2010
2015
Int. Inter.
4
2020
22
1995
2000
2005
Edad mediana
2010
2015
4
2020
Int. Inter.
49
Castilla – La Mancha
Albacete
Ciudad Real
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
4
22
1995
2000
2005
2010
Edad mediana
2015
2020
1995
4
2000
Int . Int er.
2005
2010
Edad mediana
2015
2020
Int . Int er.
Guadalajara
Cuenca
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
4
22
1995
2000
2005
2010
Edad mediana
2015
2020
1995
4
2000
2005
Edad mediana
Int . Int er.
2010
2015
2020
Int. Inter.
Toledo
34
10
32
9
30
8
28
7
26
6
24
5
22
1995
4
2000
2005
Edad mediana
2010
2015
2020
Int . Int er.
50
Cataluña
Gerona
Barcelona
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
4
2020
22
22
1995
2000
2005
2010
Edad mediana
2015
1995
4
2000
Int. Inter.
2005
2010
Edad mediana
Lerida
2015
2020
Int . Int er .
Tarragona
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
4
22
1995
2000
2005
2010
Edad mediana
2015
2020
1995
4
2000
2005
2010
Edad mediana
Int . Int er.
2015
2020
Int. Inter.
Comunidad Valenciana
Alicante
Castellón de la Plana
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
1995
2000
2005
2010
Edad mediana
2015
4
2020
Int. Inter.
22
1995
2000
2005
Edad mediana
2010
2015
4
2020
Int. Inter.
Valencia
34
10
32
9
30
8
28
7
26
6
24
5
22
1995
2000
2005
Edad mediana
2010
2015
4
2020
Int. Inter.
51
Extremadura
Badajoz
Cáceres
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
4
22
1995
1995
2000
2005
2010
Edad mediana
2015
2020
2000
2005
2010
Edad mediana
Int . Int er.
2015
4
2020
Int. Inter.
Galicia
La Coruña
Lugo
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
1995
2000
2005
2010
Edad mediana
2015
4
2020
22
1995
2000
Int. Inter.
2005
2010
Edad mediana
Orense
2015
4
2020
Int. Inter.
Pontevedra
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
4
2020
22
22
1995
2000
2005
Edad mediana
2010
2015
Int. Inter.
1995
4
2000
2005
Edad mediana
2010
2015
2020
Int . Int er.
52
País Vasco
Álava
Guipúzcoa
34
10
34
10
32
9
32
9
30
8
30
8
28
7
28
7
26
6
26
6
24
5
24
5
22
4
22
1995
2000
2005
2010
Edad mediana
2015
2020
Int . Int er.
1995
4
2000
2005
Edad mediana
2010
2015
2020
Int . Int er.
Vizcaya
34
10
32
9
30
8
28
7
26
6
24
5
22
1995
2000
2005
2010
Edad mediana
4
2015
4
2020
Int. Inter.
Mortality projection
4.1 Mortality projection
The mortality projection of the population resident in Spain is based on the forecast of
the future evolution of two elements characterising the incidence of the phenomenon:
on the one hand, its general level, reflected in life expectancy at birth, as the synthetic
indicator of the mortality conditions at all ages and, on the other hand, its structure or
pattern by age and sex. Thus the methodology presented for mortality projection
combines a hypothesis regarding the general level of mortality, measured in terms of
life expectancy at birth, and a series of factors affecting future behaviour of the risk of
dying in the different stages of the life cycle. Therefore, in order to set the mortality
scene, this is approached in three stages:
a) Projection of the long-term aggregated mortality level (until 2050), measured in
terms of life expectancy at birth:
First, a life expectancy value is established for the year 2050 as a standard.
Determining this value has a direct bearing on the debate on longevity and maximum
life expectancy. Selected authors4 maintain that there is a biological limit imposed by
the actual aging of the organism, which prevents there being significant improvements,
4
Olshansky, S.J.; Carnes.; Cassel, C., L. and Pollard, J.N. (1990), In search of Methuselah:
Estimating the Upper Limits to Human Longevity, in Science, vol 250, pp. 634-639.
53
even removing certain causes of death such as tumours or cardiovascular illnesses,
and that western countries are close to this limit. On the other hand, other researchers
maintain that in decades to come, there will be a series of advances in the field of
genetics and medical technology which will make it possible to have an impact on
processes underlying aging, significantly offsetting age upon death to increasingly
older ages5.
The decision on the aforementioned standard scenario is, in any case, in response to
the following arguments and conditions:
- new illnesses or pathologies not appearing;
- the progressive monitoring in younger adults of risk factors, which enable a
significant reduction in preventable premature mortality;
- the adopting of guidelines and healthier lifestyles which would be beneficial to
reducing mortality at maturity and early old age, together with advances in diagnosis
and treatment of cancers;
- the persistence of the favourable trend in the evolution of mortality by the circulatory
system deseases and the extension of treatments and medical advances.
Life expectancy observed the year 2005 showed stability in mortality, since life
expectancy at birth was similar to that for the year 2004. Nevertheless, that stability
was short-term, as indicated by the 2006 data, which shows a new recovery in life
expectancy for the population resident in Spain.
Conversely, The last few projection exercises for the future resident population in EU
member states (EUROPOP 2008) and of other national statistics offices coincide in
painting a future with significant advances in life expectancy and a more marked
reduction in differentials between sexes than had been forecast in 2007.
Consequently, in light of this upward movement, levels of life expectancy at birth have
been reformulated on the projection horizon (year 2050), as compared with previous
forecasts, particularly in the case of males. For the male population, life expectancy at
birth has been estimated at around 83.5 years, and for the female population, at
around 88.7 years.
Once levels of life expectancy had been established as a standard for the year 2050,
those corresponding to each year in the projection period were obtained, by adjusting
a logistical function to the data shown for the 1960-2006 period. The adjustment of the
aforementioned function was performed by first of all calculating the logits of the
values observed between 1960 and 2006 by means of:
 e max − e 0t
log it(e 0t ) = ln 0t
min
 e0 − e0




Below the parameters have been estimated for the regression line, with the logits
residing therein for every year in the projection period, under the restriction that the
2050 value corresponds the standard established hypothesis. Lastly, these values are
transformed in the corresponding life expectancies by means of the formula:
5
Oeppen, J. and Vaupell, J.W. (2002), Broken limits of life expectancy, in Science, vol 296, pp.
1029-1031.
54
 max
min
 e − e0
e 0t = e min
+ 0
0
 t 
 1 + exp logit  e 0 






The following table and graphs feature the evolution shown and projected of life
expectancy at birth and at the age of 65 years, up to the year 2050:
Esperanza de vida
Años
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2042
2043
2044
2045
2046
2047
2048
2049
2050
Esperanza de vida al nacimiento
Varones
Mujeres
Esperanza de vida a los 65 años
Varones
Mujeres
73,67
80,84
15,73
73,94
81,1
15,85
19,39
19,57
74,21
81,31
15,97
19,71
74,41
81,56
16,09
19,88
74,53
81,70
16,12
19,97
74,88
81,94
16,23
20,11
75,27
82,15
16,26
20,17
75,35
82,22
16,21
20,16
75,64
82,46
16,44
20,35
76,07
82,82
16,74
20,65
76,31
83,02
16,85
20,78
76,36
82,98
16,84
20,74
76,68
83,21
17,04
20,93
76,96
83,48
17,19
21,12
77,59
84,09
17,72
21,66
77,90
84,36
17,62
21,93
78,13
84,54
17,74
22,06
78,35
84,72
17,86
22,19
78,58
84,90
17,99
22,32
78,79
85,07
18,11
22,44
79,00
85,24
18,22
22,56
79,21
85,39
18,34
22,67
79,41
85,54
18,45
22,79
79,61
85,70
18,56
22,90
79,81
85,84
18,67
23,00
80,01
85,99
18,78
23,11
80,19
86,13
18,88
23,22
80,35
86,26
18,97
23,31
80,53
86,39
19,08
23,40
80,69
86,52
19,17
23,50
80,85
86,63
19,26
23,58
81,02
86,74
19,35
23,66
81,16
86,85
19,43
23,75
81,30
86,97
19,51
23,83
81,45
87,07
19,59
23,91
81,57
87,18
19,66
23,99
81,72
87,28
19,74
24,06
81,84
87,36
19,81
24,12
81,94
87,46
19,87
24,20
82,06
87,54
19,94
24,26
82,16
87,64
19,99
24,33
82,29
87,72
20,06
24,39
82,39
87,80
20,12
24,45
82,46
87,86
20,16
24,50
82,56
87,94
20,22
24,56
82,64
88,00
20,26
24,60
82,74
88,07
20,32
24,65
82,82
88,13
20,36
24,70
82,90
88,19
20,41
24,74
82,98
88,25
20,45
24,79
83,03
88,32
20,48
24,84
83,11
88,38
20,52
24,89
83,16
88,42
20,55
24,92
83,24
88,48
20,60
24,97
83,29
88,53
20,63
25,00
83,34
88,57
20,66
25,03
83,40
88,61
20,69
25,06
83,45
88,66
20,72
25,09
83,45
88,70
20,72
25,13
Fuente: 2002-2005, Indicadores Demográficos Básicos; 2006, resultado provisional de Tabla de
Mortalidad de España; 2007-2050, Proyección de Población a Corto Plazo
55
Esperanza de Vida al Nacimiento
Valores observados para 1992-2006 y proyectados para 2007-2050
90
85
80
75
70
1992 1996 2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048
Varones
Mujeres
Fuente: 1992 - 2005, Indicadores Demográficos Básicos; 2006, resultado provisional de Tablas de Mortalidad;
2007 - 2050, Proyección de Población a Corto Plazo
Esperanza de Vida a los 65 años
30
Valores observados para 1992-2006 y proyectados para 2007-2050
25
20
15
19921995199820012004200720102013201620192022202520282031203420372040204320462049
Varones
Mujeres
Fuente: 1992 - 2005, Indicadores Demográficos Básicos; 2006, resultado provisional de Tablas de Mortalidad;
2007 - 2050, Proyección de Población a Corto Plazo
56
b) Construction of a pattern for mortality by age and sex in accordance with levels of
life expectancy at birth set for the year 2050:
The methodology for obtaining the pattern by sex and age of the incidence of mortality
for the year 2050 is based on the parameter proposed by L. Heligman and J. Pollard6.
This law, in its general formulation, segments the quotient curve into three life periods:
childhood, adolescence and early adulthood, maturity and old age:
C
2
q x = A (x +B ) + De −E (ln x −ln F ) +
GH x
k
1 + GH x
k
The parameters A, B and C describe the behaviour of childhood mortality: parameter A
is similar to the likelihood of dying during the second year of life; B measures the
differentials in the risks of dying in the first years of life; and C quantifies the rate of
decrease in childhood mortality. Parameters D, E and F measure the presence of
increased mortality in young adult ages: the value of parameter F indicates the
maximum age of increased mortality; the D parameter indicates its intensity and E its
duration; a D value equal to 0 or a high F value indicate an absence of a significant
increase in mortality at these ages. Parameters G and H express mortality associated
with the aging process: G expresses its level and H its growth rate with age.
The projection of the mortality pattern for the year 2050 has been carried out in two
phases:
The first consisted of adjusting the mortality quotients by simple age calculated with
deaths shown in 2006 and Population Now-Casts at 1 July of the aforementioned year,
obtaining the value for 2006 of the different parameters of the Helligman-Pollard
function. In addition, the presence of a slight mode of increased female mortality
around the age of 50 years requires the introduction of another component in the
adjustment function for the case of women. This component, which encompasses
parameters D’, E’ and F’, is identical in its formulation to that of young adult mortality,
but centred on mature adult ages:
C
2
2
q x = A (x +B ) + De −E (ln x −ln F ) + D' e −E'(ln x −ln F ' ) +
GH x
k
1 + GH x
k
The minimisation criteria used in adjusting the respective functions would be the sum
of the squared of the relative differences since birth up to the age 95 :
85
 q o − qa
Min∑  x a x
qx
x=0 



2
Mortality risks in the population resident in Spain, registered in 2006 and adjusted in
accordance with the aforementioned procedure are shown in the following graph:
6
Heligman, L. and Pollard, J.N. (1980), The age pattern of mortality, in Journal of the Institute of
Actuaries, 107 (1(434)), pp. 49-80
57
Riesgos de muerte por edad observados y
ajustados para 2006
Varones
Riesgos de muerte por edad observados y
ajustados para 2006
Varones
Hasta 60 años
0,0120000
0,0100000
0,0080000
0,0060000
0,0040000
0,0020000
0,0000000
0
5
10 15 20 25 30 35 40 45 50 55 60
0,3500000
0,3000000
0,2500000
0,2000000
0,1500000
0,1000000
0,0500000
0,0000000
Desde 61 años
61
66
71
76
Edad
q(x) obervados
q(x) ajustados
q(x) obervados
Riesgos de muerte por edad observados y
ajustados para 2006
Mujeres
0,0040000
81
86
91
96
Edad
q(x) ajustados
Riesgos de muerte por edad observados y
ajustados para 2006
Mujeres
Hasta 60 años
0,4000000
0,0030000
0,3000000
0,0020000
0,2000000
0,0010000
0,1000000
0,0000000
Desde 61 años
0,0000000
0
5
10
15
20
25
30
35
40
45
50
55
60
61
66
71
Edad
q(x) obervados
q(x) ajustados
76
81
86
91
96
Edad
q(x) obervados
q(x) ajustados
Once the parameters have been obtained from the 2006 function, the mortality curve
for 2050 is generated for each sex, this being based on the following hypotheses:
•
Mortality in the first few years of life: parameter A of the adjustment function, which
indicates the level of mortality in the second year of life, would decrease 60
percent of the 2006 adjusted value in 2050.
•
Mortality in young adult ages: parameter D, which indicates its intensity, would
decrease 80 percent in men and 40 percent in women in relation to the values
adjusted for 2006.
•
Mortality in mature adult women: parameter D’, which indicates the intensity of the
increased mortality mode, centred in the region of 50-55, would decrease by half
in relation to the 2006 value.
In this way, evolution hypotheses are established for the first two components of the
Helligman-Pollard functions, describing childhood and young adult mortality (in women
also above the mortality mode at mature ages), which makes it possible for the
parameters of the last component to be obtained a posteriori, by adjusting the
Heligman-Pollard function with the restriction that life expectancy in 2050 coincide with
that projected and the mortality quotients be no lower at any age than those of the
mortality limit table for J. Duchêne and G. Wunsch7.
c) Obtaining of the mortality tables for each of the years for the period and analysis of
the coherence in the evolution forecast for mortality by age.
7
Duchêne, J. and Wunsch, G. (1988), From the demographer's cauldron: single decrement life
tables and the span of life, in Genus, Vol. 44, No. 3-4, Jul-Dec 1988, pp. 1-17.
58
Once the mortality pattern by age for the year 2050 is available, a broad set of tables
by linear interpolation between the mortality quotients by age and sex, adjusted for
2006 and those projected for the year 2050 is generated. From this broad set of
mortality tables, those offering a level of life expectancy at birth closer to that
previously forecast by means of the logistical function for each year in the 2006-2050
period have been selected.
The graphs below show the projected mortality curves, consistent with a life
expectancy at birth of 83.5 years in men, and 88.7 years in women on the projection
horizon (2050):
q(x) proyectada. Varones
q(x) proyectada. Varones
Hasta 60 años
Desde 61 años
0,01
0,35
0,009
0,3
0,008
0,25
0,007
0,006
0,2
0,005
0,15
0,004
0,003
0,1
0,002
0,05
0,001
0
0
0
3
6
9
12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60
2007
2010
2020
2030
2040
2050
61 63 65 67 69 71 73 75 77
2007
2010
79 81
2020
83 85 87 89 91 93
2030
2040
95 97 99
2050
59
q(x) proyectada. Mujeres
q(x) proyectada. Mujeres
0,004
Hasta 60 años
Desde 61 años
0,35
0,0035
0,3
0,003
0,25
0,0025
0,2
0,002
0,15
0,0015
0,1
0,001
0,05
0,0005
0
0
0
3
6
9
61 63 65 67 69 71 73 75 77 79
12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60
2007
2010
2020
2030
2040
2007
2050
2010
81 83 85 87 89
2020
2030
91 93 95 97 99
2040
2050
q(x) proyectada. Varones
q(x) proyectada. Varones
Desde 61 años
Hasta 60 años
0,35000
0,01000
0,00900
0,30000
0,00800
0,00700
0,25000
0,00600
0,20000
0,00500
0,15000
0,00400
0,00300
0,10000
0,00200
0,05000
0,00100
0,00000
0,00000
0
3
6
9
12 15
2008
2009
2016
2017
18
21
2010
24 27
30
2011
33 36
39
2012
42
2013
45
48
51
2014
54
57
62
60
64
66
2015
68
70
72
2008
2009
2016
2017
74
76
2010
78
80
2011
82
84
86
2012
88
90
92
2013
94
2014
96
98
2015
q(x) proyectada. Mujeres
q(x) proyectada. Mujeres
Desde 61 años
Hasta 60 años
0,35
0,004
0,0035
0,3
0,003
0,25
0,0025
0,2
0,002
0,15
0,0015
0,1
0,001
0,05
0,0005
0
0
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60
2008
2009
2016
2017
2010
2011
2012
2013
2014
2015
61
63
65
67
69
71
2008
2009
2016
2017
73
75
2010
77
79
2011
81
83
2012
85
87
89
2013
91
93
2014
95
97
99
2015
60
The following may be noted as the main results of the projection carried out on the
incidence of mortality regarding the population resident in Spain in the long term:
As far as the incidence of mortality in childhood and in early youth is concerned, the
mortality quotient for the first year of life is estimated at 2.2 per thousand in boys, and
at 1.7 per thousand in girls for the year 2050, representing a drop in the region of 4550% in relation to the most recently-shown levels. Thus, the risk of dying before
reaching their tenth birthday decreases by around 82 percent in both sexes, whereas
the drop in the quotient between the tenth and twentieth birthdays stands at 80 percent
for men and 70 percent for women, as is shown in the following graphs:
61
Evolution and projection of the mortality risks by ten-yearly age group, 19812050
Males
Females
100,00
10,00
10,00
cocientes por mil
cocientes por mil
100,00
1,00
1,00
0,10
1980
1990
2000
2010
Edad 0-9
Edad 30-39
2020
2030
Edad 10-19
Edad 40-49
2040
0,10
1980
2050
Edad 20-29
2000
2010
Edad 0-9
Edad 30-39
1000,00
2020
2030
Edad 10-19
Edad 40-49
2040
2050
Edad 20-29
1000,00
cocientes por mil
cocientes por mil
1990
100,00
10,00
1980
1990
2000
2010
Edad 50-59
Edad 60-69
Edad 80-89
Edad 90-99
2020
2030
2040
Edad 70-79
2050
100,00
10,00
1980
1990
Edad 50-59
Edad 80-89
2000
2010
Edad 60-69
Edad 90-99
2020
2030
2040
Edad 70-79
Source: Short-Term Population Projection
62
2050
As far as mortality in young adults is concerned, a sustained decrease in risks of dying
between the ages of 20 and 40 years is anticipated, generally speaking, of greater
intensity in men, which brings about a decrease in increased mortality in the
aforementioned ages. The most recent data shows that the increased mortality, which
affected young adults in the nineties, was in response to specific factors, the incidence
of which has decreased in recent years, and it is anticipated that a positive trend will
be maintained in the medium to long term. In addition, the margin for improvement,
particularly in men, is still significant, since approximately two thirds of deaths at those
ages are due to causes considered to be avoidable, with a clear preponderance of
those of a preventable type. Therefore, in quantitative terms, and for the period as a
whole, the drop in the male quotient aged between 20 and 30 years is estimated at 80
percent and between 30 and 40 years at 75 percent, whereas in women the decreases
are 68 and 65 percent, respectively. Despite the relative magnitude represented by
these decreases, their impact on life expectancy in terms of time of the population is
very moderate, especially in women, due to the current low levels of mortality at the
aforementioned ages.
As far as this incidence of the phenomenon in adults is concerned, the mortality
quotients between the ages of 40 and 50 years are projected in accordance with a
positive trajectory similar to that of the previous age groups, with a drop of 75 percent
of the quotient in men and 64 percent in women. In turn, the anticipated decrease in
the risk of dying between the ages of 50 and 60 years stands in the region of 70
percent in both sexes.
As far as maturity and old age are concerned, the standard hypothesis regarding life
expectancy at birth and its pattern of mortality by age leads to a rising trend in the
potential years lived in the age groups 60-69, 70-79 and 80-89 years, which links and
accentuates the trends of the last three decades. To exemplify this, in the current
projection it is estimated that between the ages of 80 and 89 years, the potential years
lived will reach 74 percent in men and 85 percent in women by the middle of the
century.
Lastly, in the most advanced ages, the degree of uncertainty regarding the future is
higher due to the newness of the decrease in the risks of dying in the population aged
in their nineties, which poses important questions regarding its intensity, also a
consequence of the actual difficulty in measuring the phenomenon in those ages. The
results obtained suggest the start of a rise in the potential years lived by the Spanish
population aged between 90 and 99 years, more significant in women, reaching a
potential 46 percent in men and 55 percent in women in the year 2050. Lastly, in
relation to life expectancy from the age of 100 years onwards, the hypothesis is
formulated that the remaining life at that age stands at around 2.5 years in men and 3
years in women.
Lastly, and by way of synthesis, the role to be played by the different ages in
anticipated gains in life expectancy has been quantified in the following graph:
63
0,160
0,160
0,140
0,140
0,120
Mujere s
0,100
ganancia de años de vida
ganancia de años de vida
0,120
0, 160
0, 140
0,080
0, 120
0,060
0, 100
0, 080
0,040
0,100
0,080
0,060
0,040
0, 060
0,020
0,020
0, 040
0, 020
0,000
0
10
20
30
40
0,000
0, 000
50
0
60
70
10
80
20
30
90
40
2006-2017
50
60
0
70
10
80
20
90
30
40
50
60
70
80
90
2006-2050
Source: Short-Term Population Projection
4.2 Mortality projection for the autonomous communities
As far as the mortality projection in the Autonomous Communities is concerned, it has
been carried out taking the national total as reference, following the Brass logits
method8. Therefore, complete mortality tables have been prepared (with an upper age
of 90 years) considering deaths for the three-year period 2004-2006 for Spain and
each Autonomous Community. The aforementioned mortality tables have been
prepared taking into account deaths registered in the Vital statistics corresponding to
the aforementioned years and the population figures correspond to the Population
Now-Casts at 1 January each year for the 2004-2007 period, in accordance with the
following expressions for the mortality rates by simple age and the likelihood of death
at each age:
m xCCAA, 2004− 06 =
d xCCAA, 2004 + d xCCAA, 2005 + d xCCAA, 2006
0,5 × PxCCAA, 1−1− 2004 + PxCCAA, 1−1− 2005 + PxCCAA, 1−1− 2006 + 0,5 × PxCCAA, 1−1− 2007
q xCCAA, 2004−06 =
m xCCAA, 2004−06
1 + 1 − a xCCAA, 2004−06 × m xCCAA, 2004− 06
(
)
The values for the estimated time lived at age x by individuals who die at the
aforementioned age for each autonomous community have been calculated as an
average of those shown in the corresponding individual records of the microdata files
of the Vital Statistics as the difference between the date of birth and the date of death
of each of them.
8
William Brass, (1975), Methods for estimating fertility and mortality from limited and defective data.
64
Once those mortality tables have been calculated for each autonomous Community
and for the national total, the survivor series for each sex has been transformed from
the aforementioned tables and from the 2006 national total table by means of a
logistical function:
Logit l xCCAA, 2004−06 =
Logit l xEsp , 2006 =
1  l0CCAA, 2004−06 − l xCCAA, 2004−06
ln 
2 
l xCCAA, 2004−06
1  l 0Esp , 2006 − l xEsp , 2006
ln 
2 
l xEsp , 2006






The survivor series transformed from each community and from the national total have
the property of the relationship between the transformed values of the survivor series
from each autonomous community and from the national total being approximately
linear, such that it is subject to being modelled by means of a line of regression:
Logit l xCCAA, 2004−06 = α + β × Logit l xEspaña, 2005
In adjusting the aforementioned model, only those values from the series
corresponding to the age of 40 years or over. The aforementioned procedure is
justified by a variety of reasons:
1. Firstly, because despite the fact that the mortality tables have been constructed by
aggregating deaths over three years, the risks of dying in childhood, adolescence
and early adulthood continue to be subject to fluctuations and to a significant
randomness in the majority of regions, which causes the survival function to show
fluctuations which impact on the parameter values of the line of regression if all
ages are used for calculating them.
2. On the other hand, the gradual displacement of the mortality force to increasingly
advanced ages has caused a gradual loss in the leading part played by childhood
and adolescence in explaining the territorial differentials of average life between the
autonomous communities and Spain, a process which has been more marked in
women, since they are in a more advanced state of epidemiological transition. As
an exception, the unequal territorial incidence of the recovery of mortality in younger
adults may be highlighted, particularly in men, during the eighties and a large part of
the nineties. Nevertheless, the recent decrease in mortality at those ages has
caused them to lose weight in the explanation of the spatial differences of average
life.
3.
The impact of the mortality hypotheses in the results of the future evolution
projections of populations which enjoy low levels of mortality is centred on mature
ages and, particularly, on advanced ages. Although in terms of the value of life
expectancy at birth, the risks of dying in the first half of life are not insignificant, their
impact on the projected effectives is less than at mature and advanced ages.
Therefore, in constructing the hypotheses, the forecast future behaviour of the risks
of dying in maturity and in old age is most relevant.
4. Lastly, the hypotheses formulated with a view to the future consider that the
decrease in risks of dying in the first years of life will be prolonged, while specific
65
mortality factors in young adulthood will be monitored, which entails the impact of
the risks of dying at those ages in the projection results being increasingly lower.
The values α and β estimated for each sex describe the level and the structure of
mortality for each region in relation to the national total, such that a negative value
of α indicates a more favourable general behaviour of mortality in the
corresponding region than in Spain as a whole, and vice versa, and a value
of β higher than one will indicate that the incidence of mortality in that autonomous
community is more favourable in the first stages of life than in advanced ages in
relation to the country as a whole, and vice versa. The values of the parameters α
and β obtained for each autonomous community and sex in accordance with the
described procedure are shown below.
Males
Intersection
Pending
Females
Intersection
Pending
Andalucía
Aragón
Asturias
Balears
Canarias
Cantabria
Castilla La
Mancha
Cast. y Leon
Cataluña
C. Valenciana
Extremadura
Galicia
C. de Madrid
R. de Murcia
C.F. de Navarra
País Vasco
La Rioja
Ceuta
Melilla
0.097
-0.044
0.069
-0.019
0.056
-0.000
-0.081
1.038
0.972
0.998
1.016
0.997
1.003
0.975
0.133
-0.043
-0.026
0.001
0.108
-0.088
-0.015
1.058
0.971
0.952
1.024
1.022
0.950
1.021
-0.084
-0.018
0.038
0.043
0.004
-0.077
0.022
-0.096
-0.008
-0.085
0.102
0.056
0.953
1.008
1.020
1.021
0.955
0.997
0.998
0.986
1.022
0.971
1.008
0.986
-0.117
-0.023
0.073
0.051
-0.044
-0.089
0.066
-0.127
-0.090
-0.119
0.209
0.236
0.930
1.005
1.031
1.046
0.964
0.974
1.043
0.930
0.959
0.943
1.044
1.062
Spain
0.000
1.000
0.000
1.000
66
Parameters α (a) and β (b) adjusted for each autonomous community (2004-2006)
Males
a>0yb>1
a>0yb<1
Females
a<0yb<1
a<0yb>1
a>0yb>1
a>0yb<1
a<0yb<1
a<0yb>1
As is shown, in the case of males, in the communities of southern mainland Spain, in
addition to Asturias and Galicia, and the autonomous cities of Ceuta and Melilla,
positive values are obtained in the parameter α , due to a greater general intensity of
mortality as compared with the national one. Within this group, Andalucía, Comunitat
Valencia, Extremadura and Ceuta are also characterised by a less favourable relative
position of mortality at advanced ages, since the value of β stands above the unit. In
the group of regions with a more favourable general incidence of mortality than in
Spain as a whole ( α < 0 ), in Illes Balears, Cantabria, Cataluña and País Vasco the
structure of its mortality is less favourable than the national one in more advanced
ages in comparison with adult and mature ages, whereas in those for inland parts of
mainland Spain, the behaviour observed is the opposite.
In women, the spatial dichotomy is clearer, while different positions are not shown in
the level and in the structure. Thus, in the southern and eastern regions, the general
level of mortality exceeds that of Spain and shows a less favourable structure in old
age, whereas in inland and in northern mainland Spain, its general situation is
combined with a more favourable mortality structure in advanced ages, with the
exception of Castilla-La Mancha and Cataluña.
Lastly, the degree of accuracy of the adjusted results compared with those observed
for the 2004-2006 period can be seen by comparing life expectancy shown at birth and
that derived from the survivor series modelled for each autonomous community:
67
Males
Females
86
79
2
2
R = 0,997
Esperanza de vida al nacer observada
Esperanza de vida al nacer observada
R = 0,994
78
77
76
85
84
83
82
Ceuta Melilla
75
81
75
76
77
78
Esperanza de vida al nacer ajustada
79
81
82
83
84
85
86
Esperanza de vida al nacer ajustada
Or also from the representation of risks of death for each age observed and adjusted
in accordance with the described procedure, which is shown below:
68
q(x) Observado y Ajustado. Mujeres. Andalucía
q(x) Observado y Ajustado. Varones. Andalucía
0,015
0,2
0,005
0,175
0,012
0,16
0,004
0,14
0,009
0,12
0,003
0,105
0,006
0,08
0,002
0,07
0,003
0,04
0,001
0,035
0
0
0
0
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87
qx Observado
qx Observado
qx Ajustado
q(x) Observado y Ajustado. Mujeres. Aragón
q(x) Observado y Ajustado. Varones. Aragón
0,01
0,2
0,008
0,16
0,006
0,12
0,004
qx Ajustado
0,004
0,16
0,003
0,12
0,002
0,08
0,001
0,04
0,08
0,002
0,04
0
0
0
0
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87
qx Observado
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87
qx Ajustado
qx Observado
q(x) Observado y Ajustado. Mujeres. Asturias
q(x) Observado y Ajustado. Varones. Asturias
0,014
0,175
0,012
0,15
0,01
0,125
0,008
qx Ajustado
0,004
0,14
0,003
0,105
0,002
0,07
0,001
0,035
0,1
0,006
0,075
0,004
0,05
0,002
0,025
0
0
0
0
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87
qx Observado
qx Observado
qx Ajustado
q(x) Observado y Ajustado. Varones. Baleares
qx Ajustado
q(x) Observado y Ajustado. Mujeres. Baleares
0,012
0,18
0,01
0,15
0,008
0,12
0,006
0,09
0,004
0,06
0,002
0,03
0,0042
0,16
0,12
0,0021
0,08
0,04
0
0
0
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87
qx Observado
qx Ajustado
qx Observado
q(x) Observado y Ajustado. Varones. Canarias
0,175
0,012
0,15
0,125
0,008
0,1
0,006
0,075
0,004
0,05
0,002
0,025
0
0
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87
qx Observado
qx Ajustado
qx Ajustado
q(x) Observado y Ajustado. Mujeres. Canarias
0,014
0,01
0
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87
0,005
0,175
0,004
0,14
0,003
0,105
0,002
0,07
0,001
0,035
0
0
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87
qx Observado
qx Ajustado
69
q(x) Observado y Ajustado. Mujeres. Cantabria
q(x) Observado y Ajustado. Varones. Cantabria
0,012
0,18
0,01
0,15
0,008
0,12
0,006
0,09
0,004
0,06
0,002
0,03
0
0
0,0063
0,12
0,0042
0,09
0,06
0,0021
0,03
0
0
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87
qx Observado
0,15
qx Observado
qx Ajustado
qx Ajustado
q(x) Observado y Ajustado. Mujeres. Castilla y León
q(x) Observado y Ajustado. Varones. Castilla y León
0,0105
0,175
0,0084
0,14
0,0063
0,105
0,0042
0,07
0,0021
0,035
0,0042
0,16
0,12
0,0021
0,08
0,04
0
0
0
0
4
qx Observado
0
0
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
4
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
qx Ajustado
qx Ajustado
q(x) Observado y Ajustado. Mujeres. Castilla-La Mancha
q(x) Observado y Ajustado. Varones. Castilla-La Mancha
0,0105
0,175
0,0084
0,14
0,0063
0,105
0,0042
0,07
0,0021
0,035
0,0042
0,14
0,105
0,0021
0
4
0,035
0
0
0
0
0
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
0,07
4
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
qx Ajustado
q(x) Observado y Ajustado. Varones. Cataluña
qx Ajustado
q(x) Observado y Ajustado. Mujeres. Cataluña
0,0126
0,18
0,0105
0,15
0,0084
0,12
0,0063
0,09
0,0042
0,06
0,0021
0,03
0,0042
0,14
0,105
0,0021
0,07
0,035
0
0
0
4
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
qx Ajustado
0
0
0
4
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
qx Ajustado
70
q(x) Observado y Ajustado. Mujeres. Comunidad Valenciana
q(x) Observado y Ajustado. Varones. Comunidad Valenciana
0,0126
0,18
0,0105
0,15
0,0084
0,12
0,0063
0,09
0,0042
0,06
0,0021
0,03
0
0,0063
0,12
0,0042
4
0,06
0,03
0
0
0
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
0,09
0,0021
0
0
0,15
4
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
qx Ajustado
qx Ajustado
q(x) Observado y Ajustado. Mujeres. Extremadura
q(x) Observado y Ajustado. Varones. Extremadura
0,0126
0,175
0,0105
0,15
0,0042
0,175
0,14
0,125
0,0084
0,105
0,1
0,0063
0,0021
0,075
0,0042
0,07
0,05
0,0021
0,035
0,025
0
0
0
qx Observado
0
0
0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
4
qx Observado
qx Ajustado
0,0126
0,18
0,0105
0,15
0,0084
0,12
0,0063
0,09
0,0042
0,06
0,0021
0,03
0,0042
4
0,0021
0,07
0,035
0
0
0
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
0,14
0,105
0
0
qx Ajustado
q(x) Observado y Ajustado. Mujeres. Galicia
q(x) Observado y Ajustado. Varones. Galicia
0
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
4
qx Observado
qx Ajustado
qx Ajustado
q( x ) Obse r v ado y A j ust ado. M uj er es . M a dr i d
q( x ) Obs er va do y A j us t a do. V ar ones . M a dr i d
0,0105
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
0, 18
0,0042
0,14
0, 15
0,0084
0,105
0, 12
0,0063
0, 09
0,0042
0,0021
0,07
0, 06
0,035
0,0021
0, 03
0
0
0
4
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Obser vado
qx A j us t ado
0
0
0
4
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Obser v ado
qx A j us tado
71
q(x) Observado y Ajustado. Varones. Murcia
q(x) Observado y Ajustado. Mujeres. Murcia
0,0126
0,18
0,0105
0,15
0,0084
0,12
0,0063
0,09
0,0042
0,06
0,0021
0,03
0,0042
0,175
0,14
0,105
0
0,0021
0,07
0,035
0
0
4
0
0
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
0
4
qx Ajustado
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
q(x) Observado y Ajustado. Varones. Navarra
qx Ajustado
q(x) Observado y Ajustado. Mujeres. Navarra
0,0105
0,18
0,0042
0,15
0,15
0,0084
0,12
0,12
0,0063
0,09
0,09
0,0042
0,0021
0,06
0,06
0,0021
0,03
0,03
0
0
0
4
0
0
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
0
4
qx Ajustado
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
q(x) Observado y Ajustado. Varones. País Vasco
qx Ajustado
q(x) Observado y Ajustado. Mujeres. País Vasco
0,0126
0,18
0,0105
0,15
0,0084
0,12
0,0063
0,09
0,0042
0,06
0,0021
0,03
0,0042
0,14
0,105
0,0021
0,07
0,035
0
0
0
4
0
0
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
0
4
qx Ajustado
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
qx Ajustado
q(x) Observado y Ajustado. Mujeres. La Rioja
q(x) Observado y Ajustado. Varones. La Rioja
0,012
0,21
0,005
0,15
0,01
0,175
0,004
0,12
0,008
0,14
0,003
0,09
0,006
0,105
0,002
0,06
0,001
0,03
0,004
0,07
0,002
0,035
0
0
0
4
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
qx Ajustado
0
0
0
4
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
qx Ajustado
72
q(x) Observado y Ajustado. Mujeres. Ceuta
q(x) Observado y Ajustado. Varones. Ceuta
0,014
0,175
0,012
0,15
0,01
0,125
0,008
0,1
0,006
0,075
0,004
0,05
0,002
0,025
0
0
0
4
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
0,01
0,175
0,008
0,14
0,006
0,105
0,004
0,07
0,002
0,035
0
0
0
4
qx Ajustado
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
q(x) Observado y Ajustado. Varones. Melilla
qx Ajustado
q(x) Observado y Ajustado. Mujeres. Melilla
0,014
0,245
0,012
0,21
0,01
0,175
0,008
0,14
0,006
0,18
0,005
0,15
0,004
0,12
0,003
0,09
0,006
0,105
0,004
0,07
0,002
0,06
0,002
0,035
0,001
0,03
0
0
0
4
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
qx Ajustado
0
0
0
4
8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88
qx Observado
qx Ajustado
73
Once the incidence of mortality has been modelled in each autonomous community, in
relation to that observed in Spain as a whole, the future short-term mortality evolution
projection in each autonomous community has consisted of establishing a future
parameter evolution hypothesis α and β in the 2008-2018 period. The analysis of
recent trends has shown that, although gains in life expectancy have been
generalised, there are still no signs of a clear process of territorial convergence, with
significant mortality differentials persisting in mature and advanced ages, therefore it
has been established as an evolution hypothesis in the next 10 years of constant
behaviour of the aforementioned parameters. It is certainly true that, in a more longterm projection, aspects such as the profound implementation of policies of a social
and health-related nature, the territorial convergence of life modes or replacement of
cohorts which have had more differentiated lifestyles with other more homogeneous
ones, would propose the need to formulate hypotheses for moderating the current
territorial differentials.
The mortality tables for the projection period have been obtained thus from the series
of survivors that result from the adjusted model applied to the mortality tables that
would be projected for the national total, according to the expressions:
Logit l xCCAA, t = α CCAA, t + β CCAA, t × Logit l xEspaña, t , for t=2008,2009,...,2017.
l xCCAA, t =
l
1+e
0
2 × Logit l
CCAA , t
x
,t
d xCCAA ,t = l xCCAA,t − l xCCAA
+1
,t
q CCAA
=1−
x
,t
l xCCAA
+1
l xCCAA,t
The function Lx (or seasonal population of the table) has been estimated from a series
of factors regarding the time lived by the deceased persons in each age bracket ( a x ).
For exact age 0, a value of 0.15 has been taken, whereas for the rest of the ages, up
to exact age 99, it has been considered that the deaths are equally distributed in each
age bracket, which yields a value of a x equal to 0.5. It thus gives:
(
,t
,t
LCCAA
= l xCCAA
+ a x × d xCCAA,t
x
+1
)
The seasonal population of the open age group ( L100 ) has been estimated, using as
the reference value that previously projected for the whole of Spain, and considering
the survival differential in the oldest ages among the mortality tables of the
autonomous communities and Spain, according to the formula:
CCAA, t
CCAA, t
CCAA, t
CCAA, t
CCAA, t
 l95
+ l96
+ l97
+ l98
+ l99
CCAA, t
ESP , t

L100
= L100
+
+ ×
l95ESP , t + l96ESP, t + l97ESP, t + l98ESP, t + l99ESP, t




74
The life expectancy series from an exact age has been obtained, accumulating the
function Lx from said age, and dividing the whole of the resulting years lived by the
survivors at said exact age:
100
∑L
CCAA, t
x
e xCCAA, t =
x
l xCCAA, t
Finally, the step perspective probabilities would result from:
•Between birth and full years of age 0 ⇒
•Between two consecutive ages ⇒
•Between
⇒
CCAA, t
z 99
, 100+ =
age 99
,t
LCCAA
99
and
CCAA, t
z nac
=
,o
,t
z xCCAA
, x +1 =
the
,t
LCCAA
0
l 0CCAA,t
,t
LCCAA
x +1
,t
LCCAA
x
open
group
aged
100
and
over
,t
CCAA, t
LCCAA
+ L100
99
+
The following presents the projected life expectancy trajectories at birth, and at age 65
in each autonomous community, comparing it with that projected for the national total:
75
Esperanza de Vida al Nacimiento por comunidades autónomas
Comunidad Autónoma
Observado
2002
2003
2004
2005
2006
Proyectado
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
Varones
Total nacional
Andalucía
Aragón
Asturias (Principado de)
Balears (Illes)
Canarias
Cantabria
Castilla y León
Castilla-La Mancha
Cataluña
Comunitat Valenciana
Extremadura
Galicia
Madrid (Comunidad de)
Murcia (Región de)
Navarra (Comunidad Foral de)
País Vasco
Rioja (La)
Ceuta
Melilla
76,31
76,36
76,68
76,96
77,59
77,90
78,12
78,35
78,57
78,78
78,99
79,21
79,40
79,60
79,80
80,00
75,19
75,09
75,32
75,60
76,55
76,61
76,84
77,08
77,31
77,53
77,75
77,97
78,17
78,38
78,59
78,79
77,16
77,19
77,13
77,36
78,43
78,43
78,65
78,87
79,10
79,30
79,51
79,72
79,92
80,11
80,30
80,50
75,63
75,53
75,66
76,10
76,19
76,80
77,03
77,26
77,50
77,71
77,93
78,15
78,35
78,55
78,76
78,97
76,24
76,69
77,18
77,39
77,94
78,26
78,48
78,71
78,93
79,14
79,35
79,56
79,75
79,95
80,15
80,34
75,33
75,63
75,83
76,09
76,78
77,01
77,23
77,46
77,70
77,91
78,13
78,35
78,55
78,75
78,95
79,16
76,47
76,42
76,77
77,10
77,42
77,91
78,13
78,36
78,59
78,80
79,01
79,22
79,42
79,61
79,81
80,01
77,66
77,50
77,87
78,08
78,78
78,97
79,19
79,41
79,63
79,83
80,03
80,24
80,43
80,62
80,81
81,01
77,36
77,60
77,81
77,99
78,92
79,01
79,23
79,45
79,67
79,87
80,08
80,29
80,47
80,66
80,86
81,05
76,53
76,62
76,97
77,21
78,11
78,21
78,43
78,65
78,88
79,08
79,29
79,51
79,70
79,90
80,09
80,29
75,63
75,67
76,10
76,46
77,33
77,42
77,64
77,87
78,10
78,32
78,53
78,75
78,95
79,15
79,35
79,55
76,00
75,95
76,23
76,34
77,16
77,36
77,58
77,81
78,04
78,26
78,47
78,69
78,89
79,09
79,29
79,49
76,36
76,26
76,58
76,83
77,11
77,58
77,81
78,03
78,26
78,47
78,69
78,90
79,10
79,30
79,50
79,70
77,04
77,19
77,59
78,12
78,92
79,06
79,27
79,49
79,71
79,92
80,12
80,33
80,52
80,71
80,90
81,09
75,75
76,01
76,29
76,50
77,22
77,55
77,77
78,00
78,23
78,44
78,66
78,87
79,07
79,27
79,47
79,67
77,29
77,30
78,18
78,46
78,70
79,30
79,51
79,73
79,95
80,15
80,35
80,56
80,75
80,93
81,13
81,32
76,44
76,61
76,99
77,20
77,99
78,12
78,35
78,57
78,80
79,01
79,22
79,43
79,62
79,82
80,02
80,22
76,83
77,34
77,83
78,02
78,53
79,07
79,29
79,50
79,72
79,93
80,13
80,34
80,53
80,72
80,91
81,10
75,38
74,25
74,96
75,66
75,85
76,34
76,57
76,81
77,04
77,26
77,48
77,71
77,91
78,12
78,32
78,53
74,65
75,05
75,67
76,65
76,00
76,93
77,16
77,39
77,62
77,83
78,05
78,27
78,47
78,67
78,88
79,08
83,02
82,98
83,21
83,48
84,09
84,36
84,54
84,72
84,90
85,07
85,23
85,39
85,54
85,70
85,84
85,98
81,72
81,65
81,89
82,11
82,80
82,98
83,17
83,35
83,54
83,71
83,89
84,05
84,21
84,37
84,52
84,67
83,38
83,29
83,49
83,74
84,55
84,76
84,93
85,11
85,29
85,45
85,62
85,77
85,92
86,08
86,21
86,35
83,37
83,17
83,07
83,39
83,98
84,42
84,60
84,77
84,95
85,12
85,29
85,44
85,59
85,75
85,89
86,03
82,65
82,92
83,30
83,53
84,27
84,47
84,65
84,82
85,00
85,17
85,34
85,49
85,65
85,80
85,94
86,08
81,97
82,23
82,17
82,31
83,26
83,06
83,25
83,43
83,62
83,79
83,97
84,13
84,29
84,45
84,60
84,74
83,98
84,01
84,37
84,64
84,40
85,23
85,40
85,58
85,75
85,92
86,08
86,23
86,38
86,53
86,67
86,81
84,33
84,11
84,43
84,58
85,06
85,50
85,67
85,84
86,02
86,18
86,34
86,49
86,64
86,79
86,92
87,06
83,09
83,19
83,56
83,67
84,47
84,65
84,83
85,01
85,19
85,35
85,52
85,67
85,82
85,98
86,12
86,26
83,22
83,18
83,52
83,76
84,51
84,67
84,85
85,02
85,20
85,37
85,53
85,69
85,84
86,00
86,13
86,28
82,18
82,19
82,47
82,70
83,45
83,59
83,77
83,95
84,13
84,30
84,48
84,63
84,79
84,95
85,10
85,24
82,62
82,52
82,69
83,18
83,87
83,96
84,13
84,31
84,50
84,67
84,84
84,99
85,15
85,31
85,45
85,59
83,30
83,31
83,60
84,00
84,29
84,73
84,91
85,08
85,26
85,43
85,59
85,74
85,90
86,05
86,19
86,33
83,94
83,88
83,97
84,37
85,19
85,35
85,52
85,70
85,87
86,04
86,20
86,35
86,50
86,65
86,79
86,92
82,17
82,00
82,30
82,75
83,43
83,76
83,94
84,12
84,30
84,47
84,64
84,80
84,96
85,12
85,26
85,41
84,57
84,52
84,40
84,55
85,56
85,63
85,80
85,97
86,15
86,31
86,47
86,62
86,77
86,92
87,05
87,19
83,79
83,65
83,95
84,26
85,02
85,29
85,46
85,64
85,81
85,97
86,14
86,29
86,44
86,59
86,73
86,86
84,45
83,85
84,11
84,45
85,34
85,59
85,76
85,93
86,11
86,27
86,43
86,58
86,73
86,88
87,01
87,15
81,06
80,75
81,50
81,61
81,60
81,88
82,06
82,25
82,45
82,63
82,81
82,97
83,14
83,31
83,46
83,61
81,19
81,12
80,76
81,88
81,76
81,65
81,84
82,03
82,23
82,41
82,59
82,76
82,92
83,09
83,25
83,40
Mujeres
Total nacional
Andalucía
Aragón
Asturias (Principado de)
Balears (Illes)
Canarias
Cantabria
Castilla y León
Castilla-La Mancha
Cataluña
Comunitat Valenciana
Extremadura
Galicia
Madrid (Comunidad de)
Murcia (Región de)
Navarra (Comunidad Foral de)
País Vasco
Rioja (La)
Ceuta
Melilla
Fuente: 2002-2005, Indicadores Demográficos Básicos; 2006, resultado provisional de Tablas de Mortalidad de las comunidades autónomas ; 2007-2017, Proyección de
Población a Corto Plazo
76
Evolution and projection of life expectancy at birth, by autonomous community,
1981-2017
82
82
Hombres
80
80
78
78
esperanza de vida a la edad 65
esperanz a de vida a la edad 65
Hombres
76
74
72
70
74
72
70
68
68
1984
1989
1994
1999
2004
2009
2014
Andaluc ía
Aragón
Asturias
Balears
Canarias
Cantabri
Cas-Mancha
Cas t-León
C. Valenciana
España
Mujeres
87 Cataluña
1984
85
83
81
79
1989
Mujeres
87
esperanza de vida a la edad 65
esperanz a de vida a la edad 65
76
1994
1999
2004
2009
Galicia
Madrid
Murcia
Navarra
País Vasc o
Rioja
Ceuta
Melilla
España
2014
85
83
81
79
77
77
1985
1990
1995
2000
2005
2010
2015
1984
1989
1994
1999
2004
2009
Andalucía
Aragón
Asturias
Balears
Galicia
Madrid
Murcia
Canarias
Cantabri
Cas-Mancha
Cast-León
Navarra
País Vasco
Rioja
Cataluña
C. Valenc iana
España
Ceuta
Melilla
Es paña
2014
Source: Short-Term Population Projection
As may be observed, in the projection horizon, year 2017, male life expectancy
reaches 80.0 years for the national total, with an absolute variation range that, with the
exception of Ceuta and Melilla, covers from a minimum of 78.8 years in Andalucía and
79.1 years in Asturias to maximums slightly higher than 81 years in Castilla-La
Mancha, Castilla y León, Madrid, Navarra and La Rioja. In turn, female life expectancy
stands at that time horizon at 86 years, oscillating between values near 84.7 years for
residents of Andalucía and Canarias, to values higher than 87 years for residents of
Castilla y León, Navarra and La Rioja, as is reflected in the following maps:
77
Differences in life expectancy at birth projected for 2017, between Spain and the
autonomous communities
Males
Females
< -1,0
-1.0 a -0.5
-0,5 a 0,0
0,0 a 0,5
0,5 a 1,0
> 1,0
Source; Short-Term Population Projection
4.3 Mortality projection of the provinces
Regarding the mortality projection in each province, this has been carried out in
accordance with an analogous methodology, although the mortality observed and
projected in the autonomous community that each province belongs to will be taken as
a reference. In this case, the methodology of the Brass Logits is applied to abbreviated
mortality tables (by five-year age groups, up to 85 years old and over).
The values of the parameters α and β , which relate the behaviour observed during
the years 2004-2006 in each province, regarding that of the autonomous community
that it belongs to, with the previously described procedure, appears in the following
table:
78
Andalucía
Aragón
Canarias
Cas. La
Mancha
Castilla y
León
Cataluña
C.
Valenciana
Extremadura
Galicia
País Vasco
Almería
Cádiz
Córdoba
Granada
Huelva
Jaén
Málaga
Sevilla
Huesca
Teruel
Zaragoza
Palmas
(Las)
S. C.
Tenerife
Albacete
Ciudad Real
Cuenca
Guadalajara
Toledo
Ávila
Burgos
León
Palencia
Salamanca
Segovia
Soria
Valladolid
Zamora
Barcelona
Girona
Lleida
Tarragona
Alicante
Castellón
Valencia
Badajoz
Cáceres
Coruña (A)
Lugo
Ourense
Pontevedra
Álava
Guipúzcoa
Vizcaya
Males
Females
Intersectio Pending
Intersectio Pending
n
n
-0.006
0.949
-0.016
0.975
0.058
1.035
0.054
1.027
-0.052
0.986
-0.078
0.990
-0.046
0.960
-0.029
0.954
0.021
1.020
0.015
1.016
-0.042
0.988
-0.052
1.003
0.002
1.006
0.041
1.017
0.027
1.025
0.012
1.009
-0.043
0.990
-0.019
1.006
-0.071
0.923
-0.059
0.946
0.027
1.019
0.015
1.008
0.018
1.010
0.026
1.015
-0.017
0.990
-0.025
0.985
-0.021
0.075
-0.045
-0.062
-0.013
1.003
1.013
0.950
1.025
1.000
0.002
0.095
-0.065
-0.142
-0.013
1.012
1.046
0.993
0.880
0.999
0.035
0.004
0.037
0.077
-0.075
-0.030
-0.075
0.015
-0.036
0.005
-0.016
-0.031
0.004
1.035
1.007
0.970
1.019
0.997
1.017
0.942
1.028
0.989
1.014
0.990
0.914
0.967
0.013
-0.025
0.007
0.061
-0.014
0.009
0.017
0.034
-0.065
-0.001
-0.027
-0.007
0.040
0.972
0.996
1.014
1.066
1.010
1.007
0.963
1.007
0.954
1.009
0.968
0.944
1.001
-0.025
-0.026
0.023
0.031
-0.045
0.021
-0.033
-0.036
0.013
-0.052
-0.014
0.021
0.988
0.974
1.014
1.025
0.963
1.012
0.954
0.963
1.026
0.980
1.008
1.000
-0.011
-0.021
0.011
0.046
-0.071
0.020
-0.016
-0.040
0.003
-0.051
0.026
0.000
0.996
1.007
1.000
1.021
0.969
1.011
0.983
1.006
0.996
0.997
1.062
0.969
79
Taking the estimated value for the aforementioned parameters, the respective
functions have been derived from the mortality tables for each province for the three
years comprising 2004-2006, using an identical procedure to that followed for the case
of the autonomous communities.
Lastly, the projection of the evolution of the phenomenon in each province has been
carried out by keeping constant the parameters relating the transformed survival
function for each province with that of its autonomous community, in view of the fact
that recent evolution of provincial mortality does not make it possible to go as far as
hypothesising the short-term convergence of behaviour of the phenomenon among the
provinces of the same autonomous community.
Of note are the multiple situations at the start time, from regions with scarcely any
internal diversity, such as men in Cataluña and women in Comunitat Valenciana, to
others characterised by a greater provincial heterogeneity, such as Castilla-La
Mancha. In numerical terms, and with the exception of Ceuta and Melilla, the absolute
difference between the average for the five worst- and best-situated provinces in the
three years comprising 2004-06, was 3.7 years in men and 3.3 years in women,
whereas in the year 2017, it stands at 3.3 and 3.1 years, respectively.
As can be appreciated in the results obtained, the methodology and the underlying
hypotheses broadly maintain the mortality spaces observed at the beginning of this
century. In men, it has been forecast that life expectancy in 2017 will stand at under 79
years in Cádiz, Almería, Sevilla, Huelva, Málaga, and Las Palmas, whereas it will be in
excess of 81.5 years in Segovia, Soria, Guadalajara and Salamanca. In women, the
bracket estimated on the projection horizon comprises from levels below 84.6 years in
Cádiz, Málaga, Las Palmas, Huelva and Sevilla, to values above 87.3 years in Burgos,
Álava, Guadalajara and Zamora.
80
Esperanza de vida al nacimiento de varones y de mujeres
Provincias
Años
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
Varones
Total Nacional
Álava
Albacete
Alicante/Alacant
Almería
Ávila
Badajoz
Illes Balears
Barcelona
Burgos
Cáceres
Cádiz
Castellón/Castelló
Ciudad Real
Córdoba
A Coruña
Cuenca
Girona
Granada
Guadalajara
Guipúzcoa
Huelva
Huesca
Jaén
León
Lleida
La Rioja
Lugo
Madrid
Málaga
Murcia
Navarra
Ourense
Asturias
Palencia
Las Palmas
Pontevedra
Salamanca
Santa Cruz de Tenerife
Cantabria
Segovia
Sevilla
Soria
Tarragona
Teruel
Toledo
Valencia/València
Valladolid
Vizcaya
Zamora
Zaragoza
Ceuta
Melilla
76,31
76,36
76,68
76,96
77,59
77,90
78,12
78,35
78,57
78,78
78,99
79,21
79,40
79,60
79,80
80,00
77,66
78,28
78,32
77,82
78,77
78,81
79,03
79,25
79,47
79,68
79,88
80,09
80,28
80,47
80,67
80,86
77,50
77,52
77,95
78,33
78,80
79,35
79,56
79,78
80,00
80,20
80,40
80,61
80,80
80,98
81,17
81,37
75,89
76,09
76,48
76,93
77,81
77,75
77,98
78,20
78,43
78,64
78,86
79,07
79,27
79,46
79,66
79,87
74,88
74,55
74,95
75,57
76,23
76,45
76,68
76,91
77,15
77,37
77,59
77,81
78,01
78,22
78,43
78,64
77,42
77,35
78,36
78,47
77,90
78,63
78,85
79,07
79,29
79,50
79,71
79,91
80,10
80,30
80,49
80,69
75,61
75,61
76,02
76,16
76,74
77,01
77,24
77,47
77,70
77,92
78,14
78,36
78,56
78,76
78,96
79,17
76,38
76,80
77,26
77,50
77,95
78,26
78,48
78,71
78,93
79,14
79,35
79,56
79,75
79,95
80,15
80,34
76,58
76,70
77,06
77,31
78,20
78,20
78,42
78,65
78,87
79,08
79,29
79,50
79,70
79,89
80,09
80,29
77,87
77,38
78,04
78,10
78,93
78,94
79,16
79,37
79,60
79,80
80,00
80,21
80,40
80,59
80,78
80,98
76,78
76,59
76,71
76,78
77,78
77,87
78,10
78,32
78,55
78,76
78,97
79,19
79,38
79,58
79,78
79,98
74,67
74,48
74,53
74,59
76,69
75,91
76,14
76,38
76,62
76,84
77,07
77,29
77,50
77,71
77,92
78,13
76,03
76,37
76,64
76,92
77,24
77,70
77,92
78,15
78,38
78,59
78,80
79,02
79,22
79,41
79,61
79,82
76,42
76,33
76,64
76,80
77,96
77,93
78,15
78,37
78,60
78,81
79,02
79,23
79,43
79,62
79,82
80,02
75,97
75,92
76,18
76,45
77,17
77,34
77,57
77,80
78,03
78,24
78,46
78,68
78,88
79,08
79,28
79,48
76,37
76,24
76,31
76,63
77,00
77,32
77,54
77,77
78,00
78,21
78,43
78,64
78,84
79,04
79,24
79,45
78,21
78,73
78,64
78,81
78,97
79,45
79,67
79,88
80,10
80,30
80,50
80,71
80,89
81,08
81,27
81,46
76,81
76,95
77,32
77,57
78,18
78,41
78,63
78,85
79,07
79,28
79,49
79,70
79,89
80,09
80,28
80,48
75,79
75,76
75,91
76,23
76,97
77,14
77,36
77,59
77,83
78,04
78,26
78,48
78,68
78,88
79,08
79,29
78,48
79,71
79,57
79,55
80,67
80,06
80,27
80,48
80,69
80,89
81,09
81,29
81,47
81,66
81,85
82,03
76,43
76,56
77,19
77,59
78,41
78,37
78,59
78,82
79,04
79,25
79,46
79,67
79,86
80,06
80,25
80,45
75,04
74,99
75,40
75,61
76,14
76,39
76,62
76,86
77,10
77,31
77,54
77,76
77,96
78,17
78,38
78,59
77,17
77,63
78,06
78,45
78,56
79,05
79,26
79,48
79,70
79,91
80,11
80,32
80,51
80,70
80,89
81,08
76,11
76,15
76,20
76,36
77,30
77,21
77,44
77,67
77,90
78,11
78,33
78,55
78,75
78,95
79,15
79,36
77,24
77,38
77,16
77,44
77,94
78,19
78,41
78,63
78,86
79,06
79,27
79,48
79,68
79,87
80,07
80,27
76,78
76,55
76,57
77,25
77,96
78,24
78,46
78,68
78,91
79,11
79,32
79,53
79,73
79,92
80,12
80,32
76,88
77,25
77,80
78,03
78,53
79,07
79,29
79,50
79,72
79,93
80,13
80,34
80,53
80,72
80,91
81,10
76,13
76,08
76,53
77,08
77,31
77,87
78,09
78,31
78,54
78,75
78,96
79,17
79,37
79,56
79,76
79,96
77,16
77,32
77,70
78,27
78,95
79,06
79,27
79,49
79,71
79,92
80,12
80,33
80,52
80,71
80,90
81,09
75,22
75,00
75,41
75,84
76,41
76,62
76,85
77,08
77,32
77,53
77,75
77,98
78,18
78,38
78,59
78,80
75,83
76,10
76,40
76,62
77,22
77,55
77,77
78,00
78,23
78,44
78,66
78,87
79,07
79,27
79,47
79,67
77,43
77,36
78,20
78,49
78,72
79,30
79,51
79,73
79,95
80,15
80,35
80,56
80,75
80,93
81,13
81,32
77,63
77,22
77,35
77,48
77,02
77,96
78,18
78,41
78,63
78,84
79,05
79,27
79,46
79,66
79,85
80,05
75,67
75,54
75,69
76,15
76,18
76,80
77,03
77,26
77,50
77,71
77,93
78,15
78,35
78,55
78,76
78,97
76,71
76,12
76,94
76,90
77,74
77,87
78,10
78,32
78,55
78,76
78,97
79,18
79,38
79,57
79,77
79,97
74,68
75,02
75,54
75,89
76,70
76,77
77,00
77,23
77,47
77,69
77,90
78,12
78,33
78,53
78,73
78,94
76,14
76,14
76,72
76,90
76,99
77,52
77,74
77,97
78,20
78,41
78,62
78,84
79,04
79,24
79,44
79,64
78,14
77,85
78,53
79,72
79,57
80,12
80,33
80,54
80,76
80,96
81,15
81,36
81,54
81,72
81,91
82,10
76,25
76,49
76,33
76,53
76,84
77,23
77,45
77,68
77,92
78,13
78,34
78,56
78,76
78,96
79,16
79,37
76,55
76,45
76,83
77,19
77,43
77,91
78,13
78,36
78,59
78,80
79,01
79,22
79,42
79,61
79,81
80,01
78,21
78,31
78,30
78,52
79,60
79,52
79,74
79,95
80,17
80,37
80,57
80,77
80,96
81,15
81,34
81,53
74,91
74,82
75,04
75,44
76,12
76,33
76,56
76,79
77,03
77,25
77,47
77,70
77,90
78,11
78,32
78,53
79,63
79,51
78,99
78,35
79,77
79,86
80,07
80,28
80,49
80,69
80,89
81,10
81,28
81,47
81,65
81,84
76,60
76,61
76,85
77,09
77,67
77,97
78,20
78,42
78,65
78,86
79,07
79,28
79,48
79,67
79,87
80,07
78,50
78,47
78,18
78,48
79,31
79,17
79,39
79,61
79,83
80,03
80,23
80,44
80,63
80,82
81,01
81,20
77,48
77,76
77,90
78,17
79,10
79,21
79,42
79,64
79,86
80,06
80,27
80,47
80,66
80,85
81,04
81,23
75,58
75,39
75,88
76,31
77,06
77,13
77,36
77,59
77,82
78,04
78,25
78,47
78,67
78,87
79,07
79,28
77,17
77,22
77,65
77,68
78,67
78,89
79,11
79,32
79,55
79,75
79,95
80,16
80,35
80,54
80,74
80,93
76,33
76,38
76,73
77,02
77,56
77,81
78,03
78,26
78,49
78,70
78,91
79,12
79,32
79,52
79,72
79,92
78,58
77,80
78,23
79,09
79,18
79,48
79,69
79,91
80,13
80,33
80,53
80,73
80,92
81,11
81,30
81,49
76,92
76,85
76,73
77,01
78,21
78,12
78,34
78,57
78,79
79,00
79,21
79,42
79,62
79,81
80,01
80,21
74,50
73,91
75,03
75,49
79,23
76,34
76,57
76,81
77,04
77,26
77,48
77,71
77,91
78,12
78,32
78,53
74,00
74,25
75,04
76,58
78,06
76,93
77,16
77,39
77,62
77,83
78,05
78,27
78,47
78,67
78,88
79,08
81
Mujeres
Total Nacional
Álava
Albacete
Alicante/Alacant
Almería
Ávila
Badajoz
Illes Balears
Barcelona
Burgos
Cáceres
Cádiz
Castellón/Castelló
Ciudad Real
Córdoba
A Coruña
Cuenca
Girona
Granada
Guadalajara
Guipúzcoa
Huelva
Huesca
Jaén
León
Lleida
La Rioja
Lugo
Madrid
Málaga
Murcia
Navarra
Ourense
Asturias
Palencia
Las Palmas
Pontevedra
Salamanca
Santa Cruz de Tenerife
Cantabria
Segovia
Sevilla
Soria
Tarragona
Teruel
Toledo
Valencia/València
Valladolid
Vizcaya
Zamora
Zaragoza
Ceuta
Melilla
83,02
82,98
83,21
83,48
84,09
84,36
84,54
84,72
84,90
85,07
85,23
85,39
85,54
85,70
85,84
85,98
84,72
84,36
84,85
85,04
85,69
85,94
86,11
86,28
86,45
86,61
86,77
86,92
87,07
87,22
87,35
87,49
83,82
83,53
83,43
83,84
84,39
84,69
84,86
85,04
85,22
85,38
85,55
85,70
85,85
86,01
86,15
86,29
82,47
82,50
82,71
83,10
83,61
83,71
83,89
84,08
84,26
84,43
84,60
84,76
84,92
85,08
85,22
85,37
81,65
81,71
82,30
82,28
82,92
83,07
83,26
83,44
83,63
83,80
83,98
84,14
84,30
84,46
84,61
84,76
84,20
84,14
84,54
84,60
84,81
85,16
85,33
85,51
85,68
85,85
86,01
86,16
86,31
86,46
86,60
86,74
82,50
82,22
82,44
83,02
83,39
83,48
83,66
83,84
84,03
84,20
84,37
84,53
84,69
84,85
84,99
85,14
82,88
83,11
83,54
83,85
84,27
84,47
84,65
84,82
85,00
85,17
85,34
85,49
85,65
85,80
85,94
86,08
83,61
83,53
83,89
84,18
84,63
84,73
84,90
85,08
85,26
85,42
85,59
85,74
85,89
86,05
86,19
86,33
85,44
84,97
85,25
85,26
85,63
85,81
85,98
86,15
86,33
86,49
86,65
86,79
86,94
87,09
87,23
87,36
83,27
83,07
83,26
83,94
84,61
84,71
84,89
85,07
85,25
85,41
85,58
85,74
85,89
86,05
86,19
86,33
81,37
81,11
81,47
81,74
82,39
82,43
82,62
82,81
83,00
83,17
83,35
83,51
83,67
83,84
83,99
84,14
82,28
82,25
82,90
83,10
83,81
83,89
84,07
84,25
84,43
84,60
84,77
84,93
85,08
85,24
85,39
85,53
82,30
82,37
82,97
82,85
83,76
83,71
83,89
84,07
84,26
84,43
84,60
84,75
84,91
85,07
85,21
85,35
82,50
82,49
82,78
83,15
83,74
83,94
84,12
84,30
84,49
84,66
84,83
84,99
85,14
85,30
85,45
85,59
83,63
83,47
83,47
84,11
84,04
84,52
84,70
84,88
85,06
85,22
85,39
85,54
85,69
85,85
85,99
86,13
83,83
83,92
84,70
85,10
85,55
85,43
85,60
85,77
85,95
86,11
86,28
86,43
86,58
86,73
86,87
87,01
83,30
83,02
83,55
83,91
84,65
84,86
85,03
85,21
85,39
85,55
85,72
85,87
86,02
86,18
86,32
86,46
82,08
82,05
82,35
82,27
82,66
83,14
83,32
83,51
83,69
83,87
84,04
84,20
84,36
84,53
84,67
84,82
84,52
84,51
85,16
85,55
85,15
85,99
86,17
86,34
86,52
86,69
86,85
87,00
87,16
87,31
87,45
87,59
84,35
84,25
84,47
84,96
85,29
85,30
85,47
85,64
85,81
85,97
86,14
86,29
86,44
86,59
86,72
86,86
81,71
81,76
81,90
82,23
82,86
82,87
83,06
83,24
83,43
83,61
83,78
83,94
84,10
84,27
84,41
84,56
84,10
83,63
83,93
84,39
85,15
85,04
85,21
85,39
85,57
85,73
85,89
86,05
86,20
86,35
86,49
86,63
82,50
82,37
82,39
82,73
83,47
83,66
83,84
84,02
84,20
84,38
84,55
84,70
84,86
85,02
85,17
85,31
84,52
84,59
85,11
85,01
85,02
85,49
85,66
85,83
86,00
86,17
86,33
86,48
86,62
86,78
86,91
87,05
83,26
83,13
83,54
83,54
84,12
84,45
84,63
84,81
84,99
85,16
85,32
85,48
85,63
85,79
85,93
86,07
84,58
84,00
84,26
84,42
85,35
85,59
85,76
85,93
86,11
86,27
86,43
86,58
86,73
86,88
87,01
87,15
83,46
83,27
83,85
84,57
84,10
84,84
85,02
85,19
85,37
85,54
85,70
85,85
86,01
86,16
86,30
86,44
84,35
84,20
84,28
84,73
85,20
85,35
85,52
85,70
85,87
86,04
86,20
86,35
86,50
86,65
86,79
86,92
81,78
81,66
81,83
82,03
82,59
82,54
82,73
82,92
83,11
83,28
83,46
83,62
83,78
83,95
84,10
84,25
82,30
82,09
82,39
82,93
83,43
83,76
83,94
84,12
84,30
84,47
84,64
84,80
84,96
85,12
85,26
85,41
84,96
84,86
84,69
84,93
85,53
85,63
85,80
85,97
86,15
86,31
86,47
86,62
86,77
86,92
87,05
87,19
84,08
84,18
84,64
85,04
84,99
85,29
85,46
85,63
85,81
85,97
86,14
86,29
86,44
86,59
86,73
86,87
83,52
83,22
83,22
83,59
83,95
84,42
84,60
84,77
84,95
85,12
85,29
85,44
85,59
85,75
85,89
86,03
83,98
84,03
84,66
85,18
84,68
85,09
85,27
85,44
85,61
85,78
85,94
86,09
86,24
86,39
86,53
86,66
81,71
82,02
82,17
82,49
82,93
82,80
82,98
83,17
83,36
83,53
83,71
83,87
84,03
84,19
84,34
84,49
83,47
83,52
84,01
84,26
84,29
84,67
84,85
85,02
85,20
85,37
85,53
85,69
85,84
85,99
86,13
86,27
84,67
84,27
84,63
85,31
85,59
85,74
85,91
86,08
86,25
86,41
86,57
86,72
86,87
87,02
87,15
87,29
82,75
82,98
82,69
82,84
83,58
83,32
83,50
83,69
83,87
84,05
84,22
84,38
84,54
84,70
84,85
84,99
84,39
84,30
84,59
84,90
84,38
85,23
85,40
85,58
85,75
85,92
86,08
86,23
86,38
86,53
86,67
86,81
85,30
84,72
85,10
85,07
85,45
85,42
85,59
85,76
85,94
86,10
86,26
86,41
86,56
86,71
86,85
86,98
81,75
81,52
81,75
82,21
82,58
82,88
83,06
83,25
83,43
83,61
83,78
83,94
84,11
84,27
84,42
84,56
86,54
86,03
85,36
84,40
84,34
85,04
85,21
85,38
85,56
85,72
85,89
86,04
86,19
86,34
86,48
86,62
83,01
82,84
83,14
83,38
83,77
84,16
84,33
84,51
84,69
84,86
85,03
85,18
85,34
85,50
85,64
85,78
83,80
83,81
84,07
84,92
84,80
85,26
85,43
85,60
85,78
85,95
86,11
86,26
86,41
86,57
86,71
86,85
83,18
83,51
83,78
83,90
84,48
84,81
84,99
85,16
85,34
85,51
85,67
85,82
85,98
86,13
86,27
86,41
82,34
82,29
82,54
82,81
83,28
83,44
83,62
83,81
83,99
84,16
84,34
84,49
84,65
84,81
84,96
85,10
84,23
83,89
83,94
83,98
84,49
85,09
85,26
85,43
85,61
85,77
85,94
86,09
86,24
86,39
86,53
86,66
83,87
83,56
83,89
84,23
84,69
85,12
85,29
85,46
85,64
85,80
85,97
86,12
86,27
86,42
86,56
86,70
84,16
83,52
84,50
85,29
85,12
86,13
86,29
86,47
86,64
86,80
86,96
87,10
87,25
87,40
87,54
87,67
83,50
83,30
83,43
83,71
84,38
84,60
84,77
84,95
85,13
85,30
85,46
85,61
85,77
85,92
86,06
86,20
80,66
80,53
80,93
80,93
81,69
81,88
82,06
82,25
82,45
82,63
82,81
82,97
83,14
83,31
83,46
83,61
80,99
80,16
80,01
81,32
83,91
81,65
81,84
82,03
82,23
82,41
82,59
82,76
82,92
83,09
83,25
83,40
Fuente: 2002-2005, Indicadores Demográficos Básicos; 2006, resultado provisional de Tablas de Mortalidad de las comunidades autónomas ; 2007-2017, Proyección de Población a Corto Plazo
82
Observed and projected life expectancy at birth
Males
2004-06
2017
75.36 - 76.14
76.14 - 76.92
76.92 - 77.70
77.70 - 78.47
78.47 - 79.25
79.25 - 80.03
78.13 - 78.79
78.79 - 79.45
79.45 - 80.11
80.11 - 80.78
80.78 - 81.44
81.44 - 82.10
Females
2004-06
2017
82.06 - 82.66
82.66 - 83.25
83.25 - 83.85
83.85 - 84.45
84.45 - 85.04
85.04 - 85.64
84.14 - 84.73
84.73 - 85.32
85.32 - 85.91
85.91 - 86.49
86.49 - 87.08
87.08 - 87.67
Source: Short-Term Population Projection
83
5
External migration projection
External migration undoubtedly constitutes the most determining component in the
population evolution of Spain in recent years. That is, we need to add the extremely
complex future forecast to the intense and persistent flow of immigrants arriving from
abroad observed in Spain in recent times, with all the effects this has had on
population growth and its interaction with the remaining demographic phenomena.
Therefore, the projection procedure of migrations is also more complex than that of the
remaining demographic phenomena, particularly referring to the approximation to the
volume of immigration and emigration flows to and from abroad, always put forward,
which are going to occur in the next few years.
From a strictly demographic perspective, emigration constitutes an internally-occurring
phenomenon, since it is the actual population studied that is at risk, and it may be
processed by taking the projection of perspective rates which determine the incidence
thereof in each sex and age; so then, immigration, on the other hand, constitutes an
externally-occurring phenomenon, which must be processed as a population vector
incorporated annually into the projected population.
Thus, the central and determining aspect of the projection of external migrations,
departing from or arriving in Spain is constituted by the decision of the hypothesis of
the evolution of the flow of external immigration for the next few years, which requires
the use of all available information up until the present, regarding the latest trends
observed and forecast regarding demographic and socio-economic evolution in the
country: the tracking of the latest movements recorded in the Municipal Register of
Inhabitants which, as a basic source of observation of the migration phenomenon in
Spain, will enable us to prepare the best possible approximation of the volume of
those entering Spain in the entry year of the projection, 2008; the most up-to-date
forecasts regarding the macro-economic evolution of Spain for the next few years; the
possible reforms and legislative measures in terms of immigration policy, etc.
As far as foreign emigration is concerned, we should acknowledge that we are faced
with a weaker point in our demographic information system, as a direct consequence
of the well-known sub-register, which the Municipal Register of Inhabitants presents in
this type of migratory movement in the case of the foreign population, which has
favoured designing a projection methodology for the emigration of foreign nationals,
based on an approximation of the pattern of immigrants arriving in Spain returning
abroad.
5.1 External immigration projection
The aim of the projection of the phenomenon of external immigration is to establish the
flow of immigrants arriving from abroad, by sex and age, entering Spain during each
year of the projection period, 2008-2017 . It should be clarified that, although as a type
of input of the projection, external immigration of Spaniards and foreign nationals are
introduced as aggregates, in the analysis and in the formulation of the hypotheses, a
distinction has been drawn between the foreign and Spanish population entering, as is
advised by the fact that it involves migrations of a very different nature and time
dynamic.
84
Thus, the flow of external immigration, broken down by sex and age, which will arrive
in Spain, and its respective autonomous communities and provinces, in the next ten
years, is projected by following the steps below:
1. Decision of the annual volume of the flow on foreign nationals and Spaniards
entering, in accordance with the most up-to-date official forecasts regarding evolution
of the Spanish economy available, and the most recent trends shown therein:
Firstly, the total flow of external immigration for the year 2008 has been established at
701.851 foreign immigrants and 38.024 Spaniards, making use of the latest results
available on monthly foreign immigration until September 2008 of the so-called
Monthly Demographic Now Cast, which are based on the use of the latest available
information on the variations recorded in the Municipal Register of Inhabitants which
have been received at the INE central services and in the expansion of the number of
such variations, replicating the rates of arrival of information of the previous year. A
first preview estimate has also been used of the number of those entering Spain
during the months of October, November and December 2008, carried out in the
scope of the Population Now-Casts for the fourth quarter of the year. These projected
values for the year 2008 involve a clear change in trend and a significant reduction
with regard to the volumes of immigrants observed in recent years.
The projection of foreign nationals entering Spain for the following years has been
established taking into account the most up-to-date official macro-economic forecasts
provided by the Ministry of Economy and Tax. These forecasts anticipate a drastic
reduction in the rate of economic growth this year, and particularly for the year 2009,
to then begin recovering from 2010 onwards, encouraging the recovery of the potential
levels of growth of the economy.
On the basis of this, a projection has been established of the annual flow of foreign
immigration from abroad with a particularly marked decrease until 2010, reaching a
floor of 400,000 foreign immigrants annually. As of 2011, immigration slowly reactivates, increasing again until 2017 and up to 450,000 foreign immigrants. The
projected foreign immigration values for those years have been obtained by means of
a parabolic adjustment in two periods, enabling the linking of the historical series up to
the value estimated for 2008, with the standardised value established in the downturn
in those entering in 2010 (first period), and subsequent growth up until the year 2017
(second period).
85
Inmigrantes extranjeros observados y
proyectados 1998-2017
Inmigrantes
1.000.000
800.000
600.000
Inmigrantes
extranjeros
400.000
200.000
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
0
Año
Source: data shown for the Residential Variation Statistics (1998-2007), completed with entries by omission in the
Municipal Registers of Inhabitants of individuals of foreign nationality in the 1998-2003 period.
This slow recovery of the immigration flow can be justified if we take into account the
following factors:
a) The gradually stricter conditions for entering the country, the most significant proof of
which is the extending of the entry visa to an increasingly greater number of countries,
and the possible limitations of relatives involved in the family regrouping process.
b)
The limitations to hiring in the place of origin recently announced.
c) The possible medium-term reduction in flows of those entering from countries which
have recently joined the European Economic Area, such as Rumania and Bulgaria,
whose flows towards Spain will show a decreasing trend in the extent to which the
economic growth of these countries will follow that already experienced by other new
EU Member States.
d) The reduction in the Latin American immigration, particularly of Ecuadorians,
Colombians and Bolivians, observed over recent months.
e) In the opposite sense, family regrouping and the appearance of flows from other
countries will make up for part of this drop, as well as lead to a growing feminisation of
those entering.
In turn, the future evolution hypothesis of Spaniards entering, implies a change in the
recently observed trend, with a rise in immigration flows by citizens of up 50,000 in
2017, and a parabolic adjustment of the aforementioned value with the series
observed for recent years being established. This increase is to be expected as a
result of future standardisation developments, which would enable the acquisition of
Spanish nationality by descendents of Spaniards, mostly located in Latin America. It
should be highlighted that the years with the maximum number of Latin America
86
citizens entering Spain, 2002 and 2003, also saw a notable increase in the flows of
Spaniards from abroad, as is shown in the following graph:
Inmigrantes españoles observados y
proyectados 1998-2017
60.000
Inmigrantes
50.000
40.000
Inmigrantes
españoles
30.000
20.000
10.000
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
0
Año
Source: data shown for the Residential Variation Statistics (1998-2007), completed with entries by omission of
individuals of foreign nationality in the 1998-2003 period.
2. Distribution by sex of the total projected flow, in accordance with masculinity
coefficients thereof projected for the 2008-2018 period.
Distribution by sex of the projected immigration flows for foreign nationals and
Spaniards, is obtained by means of a parabolic adjustment which links the historical
series with a standardised value established in 2017, which differs slightly for both
groups, and is in response to a different time sequence: immigration of foreign
nationals is feminised, due to the greater presence of flows from other Latin American
countries and to the effect of family regrouping, and the entry of Spaniards is slightly
masculinised, coming to stand at the average values recorded in the 1992-2004
period, an evolution which anticipates the change in trend suggested by the values
observed in the years 2006 and 2007. Thus, the results of the projected series of
Spanish and foreign immigrants for each sex are:
87
Evolución y proyección del número de inmigrantes exteriores según la nacionalidad.
1998-2017. Españoles.
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
Hombres
Mujeres
Total
% Hombres
12.298
14.585
16.404
11.043
21.060
20.833
19.599
18.260
18.828
18.743
11.734
13.658
15.183
9.681
19.115
19.653
19.118
18.313
19.045
18.989
24.032
28.243
31.587
20.724
40.175
40.486
38.717
36.573
37.873
37.732
51,17%
51,64%
51,93%
53,29%
52,42%
51,46%
50,62%
49,93%
49,71%
49,86%
18.893
20.158
21.289
22.288
23.154
23.889
24.492
24.963
25.299
25.500
19.131
20.379
21.466
22.390
23.149
23.745
24.177
24.446
24.553
24.500
38.024
40.537
42.755
44.677
46.304
47.634
48.669
49.409
49.852
50.000
49,69%
49,73%
49,79%
49,89%
50,01%
50,15%
50,32%
50,52%
50,75%
51,00%
Evolución y proyección del número de inmigrantes exteriores según la nacionalidad.
1998-2017. Extranjeros.
Entradas de extranjeros
Hombres
Mujeres
Total
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
52.181
84.415
263.718
352.841
346.473
320.451
354.722
370.562
422.997
502.168
379.470
255.006
213.002
212.215
212.700
214.446
217.446
221.700
227.213
234.000
51.218
80.940
222.665
299.951
307.006
294.773
291.122
312.149
379.974
418.366
322.381
220.457
186.998
188.806
191.381
194.738
198.881
203.811
209.521
216.000
103.399
165.355
486.383
652.792
653.479
615.224
645.844
682.711
802.971
920.534
701.851
475.463
400.000
401.020
404.082
409.184
416.327
425.510
436.735
450.000
% Hombres
51,36%
51,88%
54,52%
54,42%
53,50%
52,65%
54,92%
54,28%
52,68%
54,55%
54,07%
53,63%
53,25%
52,92%
52,64%
52,41%
52,23%
52,10%
52,03%
52,00%
88
Evolution and projection of the proportion of men in flows of Spaniards and foreign
nationals entering Spain from abroad. 1988-2014.
61%
Extranjeros
59%
Españoles
57%
55%
53%
51%
49%
47%
45%
1986
1990
1994
1998
2002
2006
2010
2014
2018
Source: until 2007, Residential Variation Statistics, completed with the entries by omission In the Municipal
Registers of Inhabitants of individuals with foreign nationalities during the 1998-2003 period.
3. Distribution of the total flows of immigrants of each sex, in each of the Spanish
provinces, maintaining the distribution shown in recent years in the projection period:
This has been carried out for the whole projection period, taking the average of
distribution percentages by province of the total flow of foreign immigration of
Spaniards and foreign nationals shown in the years 2004 to 2007 in the Residential
Variation Statistics, in view of the stability of the aforementioned distribution over time.
89
Porcentajes de reparto de la inmigración exterior.
Nacionalidad extranjera.
Provincias
Á LA VA
A LB A CETE
A LICA NTE
A LM ERIA
A STURIA S
A VILA
B A DA JOZ
ILLES B A LEA RS
B A RCELONA
B URGOS
CA CERES
CA DIZ
CA NTA B RIA
CA STELLON
CIUDA D REA L
CORDOB A
CORUÑA (A )
CUENCA
GIRONA
GRA NA DA
GUA DA LA JA RA
GUIP UZCOA
HUELVA
HUESCA
JA EN
LEON
LLEIDA
LUGO
M A DRID
M A LA GA
M URCIA
NA VA RRA
OURENSE
P A LENCIA
P A LM A S (LA S)
P ONTEVEDRA
RIOJA (LA )
SA LA M A NCA
SA NTA CRUZ T.
SEGOVIA
SEVILLA
SORIA
TA RRA GONA
TERUEL
TOLEDO
VA LENCIA
VA LLA DOLID
VIZCA YA
ZA M ORA
ZA RA GOZA
CEUTA
M ELILLA
0
5
10
15
20
Porcentajes
Varones
Mujeres
90
Porcentajes de reparto de la inmigración exterior.
Nacionalidad española.
Provincias
Á LA VA
A LB A CETE
A LICA NTE
A LM ERIA
A STURIA S
A VILA
B A DA JOZ
ILLES B A LEA RS
B A RCELONA
B URGOS
CA CERES
CA DIZ
CA NTA B RIA
CA STELLON
CIUDA D REA L
CORDOB A
CORUÑA (A )
CUENCA
GIRONA
GRA NA DA
GUA DA LA JA RA
GUIP UZCOA
HUELVA
HUESCA
JA EN
LEON
LLEIDA
LUGO
M A DRID
M A LA GA
M URCIA
NA VA RRA
OURENSE
P A LENCIA
P A LM A S (LA S)
P ONTEVEDRA
RIOJA (LA )
SA LA M A NCA
SA NTA CRUZ T.
SEGOVIA
SEVILLA
SORIA
TA RRA GONA
TERUEL
TOLEDO
VA LENCIA
VA LLA DOLID
VIZCA YA
ZA M ORA
ZA RA GOZA
CEUTA
M ELILLA
0
5
10
15
20
Porcentajes
Varones
Mujeres
91
4. Distribution by age of the external immigration flow for each sex projected in every
province, applying a smoothed profile by age to each of them resulting from that
shown in recent years:
As far as the calendar of foreign nationals entering Spain is concerned, the average
structure by age corresponding to the aforementioned province and to each sex
observed in the results of the Residential Variation Statistics in the years 2004 to
2007, subjecting those average structures to a smoothing process, all of which aims to
avoid possible random behaviour or behaviour of a short-term nature therein, and in
turn to gather the differential behaviour of each territory as far as composition by age
of the immigration flow is concerned, has been applied in each province and for the
ten years of the projection period. The smoothing procedure has consisted of a
procedure of mobile averages of five consecutive ages for all ages, except for ages
60-70 years, where a smoothing of mobile averages of three consecutive ages has
been used, in order to respect systematic behaviours of the flows observed in certain
provinces around the age of retirement.
To the same end, distribution of the total of Spanish immigrants of each sex, projected
for each year of the projection period in each province, will be carried out in
accordance with the average distribution structures per province of those shown in the
years 2004-2007 in the Residential Variation Statistics, smoothed in accordance with
the same procedure in the case of foreign immigration.
The resulting profiles by age of those procedures for the total flow of foreign
immigration, as well as for the projected foreign immigration flow in each province, of
both of Spanish and foreign nationalities, are shown in the following graphs:
Estructura por sexo y edad de la inmigración exterior de españoles
Conjunto Nacional
0
5
10
15
20
25
30
35
40
45
50
55
60
Estructura por sexo y edad proyectada de la inmigración exterior de extranjeros
Conjunto Nacional
Porcentajes
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades s im ples
Varones
Mujeres
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades sim ples
Varones
Mujeres
92
Estructura de la inmigración exterior correspondiente a españoles
Álava
0
5
10
15
20
25
30
35
40
45
50
55
60
Estructura de la inmigración exterior correspondiente a españoles
Albacete
Porcentajes
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Edades simples
Varones
Porcentajes
5
Varones
Mujeres
Estructura de la inmigración exterior correspondiente a españoles
Alicante
Mujeres
Estructura de la inmigración exterior correspondiente a españoles
Almería
Porcentajes
Porcentajes
5
5
4
4
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Varones
Varones
Mujeres
Estructura de la inmigración exterior correspondiente a españoles
Asturias
0
5
10
15
20
25
30
35
40
45
50
55
5
10
20
25
30
40
45
50
55
Mujeres
70
75
80
85
90
95
0
100+
60
65
70
75
80
85
90
95
Porcentajes
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
60
Estructura de la inmigración exterior correspondiente a españoles
Illes Balears
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades s imples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Estructura de la inmigración exterior correspondiente a españoles
Ávila
Porcentajes
Estructura de la inmigración exterior correspondiente a españoles
Badajoz
0
50
Mujeres
Edades s imples
Varones
45
Edades simples
Edades s imples
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
93
Estructura de la inmigración exterior correspondiente a españoles
Barcelona
0
5
10
15
20
25
30
35
40
45
50
55
60
Estructura de la inmigración exterior correspondiente a españoles
Burgos
Porcentajes
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Varones
Mujeres
Estructura de la inmigración exterior correspondiente a españoles
Cáceres
0
5
10
15
20
25
30
35
40
45
50
55
5
10
20
25
30
40
45
50
55
70
75
80
85
60
65
70
75
80
85
10
90
95
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
20
25
30
40
45
50
55
Mujeres
0
100+
60
65
70
75
80
85
90
95
Porcentajes
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Mujeres
Estructura de la inmigración exterior correspondiente a españoles
Córdoba
Porcentajes
Porcentajes
60
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades s imples
Varones
95
5
Varones
35
90
Mujeres
Estructura de la inmigración exterior correspondiente a españoles
Castellón
Porcentajes
Mujeres
15
0
100+
Porcentajes
5
5
95
Edades simples
Estructura de la inmigración exterior correspondiente a españoles
Ciudad Real
0
90
4
Edades s imples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Estructura de la inmigración exterior correspondiente a españoles
Cádiz
Porcentajes
Estructura de la inmigración exterior correspondiente a españoles
Cantabria
0
50
Mujeres
Edades s imples
Varones
45
Edades simples
Edades s imples
Varones
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
94
Estructura de la inmigración exterior correspondiente a españoles
Coruña (A)
0
5
10
15
20
25
30
35
40
45
50
55
60
Estructura de la inmigración exterior correspondiente a españoles
Cuenca
Porcentajes
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Edades s imples
Varones
Porcentajes
5
45
50
55
60
65
70
75
80
85
Mujeres
Varones
Estructura de la inmigración exterior correspondiente a españoles
Girona
5
10
15
20
25
30
35
40
45
50
55
Estructura de la inmigración exterior correspondiente a españoles
Granada
Porcentajes
60
65
70
75
80
85
Porcentajes
90
95
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
5
10
Mujeres
15
20
25
30
Varones
35
40
45
50
55
5
10
20
25
30
40
45
50
55
Mujeres
70
75
80
85
90
95
0
100+
60
65
70
75
80
85
90
95
Porcentajes
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
60
Estructura de la inmigración exterior correspondiente a españoles
Huesca
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Edades s imples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Estructura de la inmigración exterior correspondiente a españoles
Guipúzcoa
Porcentajes
Estructura de la inmigración exterior correspondiente a españoles
Huelva
0
50
Mujeres
Edades s imples
Varones
45
Edades simples
Estructura de la inmigración exterior correspondiente a españoles
Guadalajara
0
0
100+
5
Edades s imples
Varones
95
Mujeres
5
0
90
Edades simples
Varones
Mujeres
95
Estructura de la inmigración exterior correspondiente a españoles
Jaén
0
5
10
15
20
25
30
35
40
45
50
55
60
Estructura de la inmigración exterior correspondiente a españoles
León
Porcentajes
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Edades s imples
Varones
Porcentajes
5
45
50
55
60
65
70
75
80
85
Mujeres
Varones
Estructura de la inmigración exterior correspondiente a españoles
Lleida
5
10
15
20
25
30
35
40
45
50
55
Estructura de la inmigración exterior correspondiente a españoles
Lugo
Porcentajes
60
65
70
75
80
85
Porcentajes
90
95
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
5
10
Mujeres
15
20
25
30
Varones
35
40
45
50
55
50
55
60
65
70
75
80
85
60
Estructura de la inmigración exterior correspondiente a españoles
Málaga
Porcentajes
65
70
75
80
85
10
90
95
Porcentajes
5
4
4
3
3
2
2
1
1
0
100+
0
5
Mujeres
15
20
25
30
10
15
20
25
Varones
35
40
45
50
55
30
35
40
45
50
55
60
65
70
75
80
85
Mujeres
90
95
0
100+
Mujeres
Estructura de la inmigración exterior correspondiente a españoles
Navarra
Porcentajes
Porcentajes
60
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades s imples
Varones
0
100+
5
5
5
95
Edades simples
Estructura de la inmigración exterior correspondiente a españoles
Murcia
0
90
Mujeres
Edades s imples
Varones
45
Edades simples
Estructura de la inmigración exterior correspondiente a españoles
Madrid
0
0
100+
5
Edades sim ples
Varones
95
Mujeres
5
0
90
Edades simples
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
96
Estructura de la inmigración exterior correspondiente a españoles
Ourense
0
5
10
15
20
25
30
35
40
45
50
55
60
Estructura de la inmigración exterior correspondiente a españoles
Palencia
Porcentajes
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Edades s imples
Varones
5
10
Mujeres
15
20
25
30
Varones
35
40
45
50
55
50
55
60
65
70
75
80
85
60
Estructura de la inmigración exterior correspondiente a españoles
Pontevedra
Porcentajes
65
70
75
80
85
10
90
95
Porcentajes
5
4
4
3
3
2
2
1
1
0
100+
0
5
Mujeres
15
20
25
30
10
15
20
25
Varones
35
40
45
50
55
30
35
40
45
50
55
60
65
70
75
80
85
Estructura de la inmigración exterior correspondiente a españoles
Salamanca
Porcentajes
60
65
70
75
80
85
5
10
20
25
30
Porcentajes
90
95
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
Varones
35
40
45
50
55
30
35
40
Mujeres
45
50
55
60
65
70
75
80
85
90
95
0
100+
60
Estructura de la inmigración exterior correspondiente a españoles
Segovia
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades s imples
Varones
0
100+
5
Mujeres
15
95
Edades simples
Estructura de la inmigración exterior correspondiente a españoles
Santa Cruz de Tenerife
0
90
Mujeres
Edades s imples
Varones
0
100+
5
5
5
95
Edades simples
Estructura de la inmigración exterior correspondiente a españoles
Rioja (La)
0
90
Mujeres
Edades simples
Varones
45
Edades simples
Estructura de la inmigración exterior correspondiente a españoles
Palmas (Las)
0
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
97
Estructura de la inmigración exterior correspondiente a españoles
Sevilla
0
5
10
15
20
25
30
35
40
45
50
55
60
Estructura de la inmigración exterior correspondiente a españoles
Soria
Porcentajes
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Varones
Mujeres
Estructura de la inmigración exterior correspondiente a españoles
Tarragona
0
5
10
15
20
25
30
35
40
45
50
55
5
10
20
25
30
40
45
50
55
60
65
70
75
80
85
5
10
20
25
30
40
45
50
55
Mujeres
90
95
0
100+
90
95
Porcentajes
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
60
Estructura de la inmigración exterior correspondiente a españoles
Valencia
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
60
Estructura de la inmigración exterior correspondiente a españoles
Vizcaya
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades sim ples
Varones
85
3
Varones
35
80
4
Mujeres
15
75
Edades simples
Estructura de la inmigración exterior correspondiente a españoles
Valladolid
0
70
4
Edades simples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Estructura de la inmigración exterior correspondiente a españoles
Teruel
Porcentajes
Estructura de la inmigración exterior correspondiente a españoles
Toledo
0
50
Mujeres
Edades s imples
Varones
45
Edades simples
Edades simples
Varones
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
98
Estructura de la inmigración exterior correspondiente a españoles
Zamora
0
5
10
15
20
25
30
35
40
45
50
55
60
Estructura de la inmigración exterior correspondiente a españoles
Zaragoza
Porcentajes
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Varones
Mujeres
Estructura de la inmigración exterior correspondiente a españoles
Ceuta
0
5
10
15
20
25
30
35
40
45
50
55
50
55
60
65
70
75
80
85
90
95
0
100+
60
Estructura de la inmigración exterior correspondiente a españoles
Melilla
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Edades sim ples
Varones
45
Edades sim ples
Edades sim ples
Varones
Porcentajes
5
Varones
Mujeres
Mujeres
Estructura de la inmigración exterior correspondiente a extranjeros
Albacete
Estructura de la inmigración exterior correspondiente a extranjeros
Álava
Porcentajes
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
0
5
10
15
20
25
30
35
40
Varones
45
50
55
60
65
70
75
80
85
90
95
Varones
Mujeres
Mujeres
Estructura de la inmigración exterior correspondiente a extranjeros
Almería
Estructura de la inmigración exterior correspondiente a extranjeros
Alicante
Porcentajes
Porcentajes
5
5
4
4
3
3
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
2
2
1
1
0
100+
0
5
10
15
20
25
30
Mujeres
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Edades sim ples
Varones
0
100+
Edades simples
Edades simples
Varones
Mujeres
99
Estructura de la inmigración exterior correspondiente a extranjeros
Asturias
0
5
10
15
20
25
30
35
40
45
50
55
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Ávila
Porcentajes
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Varones
Mujeres
Estructura de la inmigración exterior correspondiente a extranjeros
Badajoz
0
5
10
15
20
25
30
35
40
45
50
55
5
10
20
25
30
40
45
50
55
70
75
80
85
90
95
60
65
70
75
80
85
90
95
Porcentajes
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Burgos
Porcentajes
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
10
Varones
Mujeres
15
20
25
30
35
40
45
50
55
Mujeres
Estructura de la inmigración exterior correspondiente a extranjeros
Cádiz
Porcentajes
Porcentajes
5
5
4
4
3
3
2
2
1
60
65
70
75
80
85
90
95
0
100+
0
5
10
15
20
25
30
Mujeres
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Edades sim ples
Varones
0
100+
Edades simples
1
5
0
100+
Edades simples
Estructura de la inmigración exterior correspondiente a extranjeros
Cáceres
0
0
100+
4
Edades sim ples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Estructura de la inmigración exterior correspondiente a extranjeros
Illes Balears
Porcentajes
Estructura de la inmigración exterior correspondiente a extranjeros
Barcelona
0
50
Mujeres
Edades sim ples
Varones
45
Edades simples
Edades sim ples
Varones
Porcentajes
5
Varones
Mujeres
100
Estructura de la inmigración exterior correspondiente a extranjeros
Cantabria
0
5
10
15
20
25
30
35
40
45
50
55
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Castellón
Porcentajes
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Edades s imples
Varones
Porcentajes
5
45
50
55
60
65
70
75
80
85
Mujeres
Varones
Estructura de la inmigración exterior correspondiente a extranjeros
Ciudad Real
5
10
15
20
25
30
35
40
45
50
55
Estructura de la inmigración exterior correspondiente a extranjeros
Córdoba
Porcentajes
60
65
70
75
80
85
Porcentajes
90
95
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
5
10
Mujeres
15
20
25
30
Varones
35
40
45
50
55
50
55
60
65
70
75
80
85
90
95
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Cuenca
Porcentajes
70
75
80
85
90
95
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
Mujeres
Varones
Mujeres
Estructura de la inmigración exterior correspondiente a extranjeros
Granada
Porcentajes
Porcentajes
5
5
4
4
3
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades simples
Varones
Mujeres
0
100+
Edades simples
Estructura de la inmigración exterior correspondiente a extranjeros
Girona
0
0
100+
Mujeres
Edades s imples
Varones
45
Edades simples
Estructura de la inmigración exterior correspondiente a extranjeros
Coruña (A)
0
0
100+
5
Edades simples
Varones
95
Mujeres
5
0
90
Edades simples
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
101
Estructura de la inmigración exterior correspondiente a extranjeros
Guadalajara
Estructura de la inmigración exterior correspondiente a extranjeros
Guipúzcoa
Porcentajes
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100+
0
5
10
15
20
25
30
35
40
Edades s imples
Varones
Mujeres
Varones
Estructura de la inmigración exterior correspondiente a extranjeros
Huelva
0
5
10
15
20
25
30
35
40
45
50
55
5
10
20
25
30
40
45
50
55
60
65
70
75
80
85
5
10
20
25
30
40
45
50
55
Mujeres
90
95
0
100+
90
95
Porcentajes
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
León
Porcentajes
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Lugo
Porcentajes
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Edades sim ples
Varones
85
3
Varones
35
80
4
Mujeres
15
75
Edades simples
Estructura de la inmigración exterior correspondiente a extranjeros
Lleida
0
70
4
Edades sim ples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Estructura de la inmigración exterior correspondiente a extranjeros
Huesca
Porcentajes
Estructura de la inmigración exterior correspondiente a extranjeros
Jaén
0
50
Mujeres
Edades simples
Varones
45
Edades simples
Varones
Mujeres
102
Estructura de la inmigración exterior correspondiente a extranjeros
Madrid
0
5
10
15
20
25
30
35
40
45
50
55
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Málaga
Porcentajes
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Edades simples
Varones
5
10
Mujeres
15
20
25
30
Varones
35
40
45
50
55
5
10
20
25
30
40
45
50
55
60
65
70
75
80
85
5
10
20
25
30
40
45
50
55
Mujeres
90
95
0
100+
90
95
Porcentajes
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Palencia
Porcentajes
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Pontevedra
Porcentajes
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades simples
Varones
85
3
Varones
35
80
4
Mujeres
15
75
Edades simples
Estructura de la inmigración exterior correspondiente a extranjeros
Palmas (Las)
0
70
4
Edades simples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Estructura de la inmigración exterior correspondiente a extranjeros
Navarra
Porcentajes
Estructura de la inmigración exterior correspondiente a extranjeros
Ourense
0
50
Mujeres
Edades simples
Varones
45
Edades simples
Estructura de la inmigración exterior correspondiente a extranjeros
Murcia
0
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades sim ples
Varones
Mujeres
103
Estructura de la inmigración exterior correspondiente a extranjeros
Rioja (La)
0
5
10
15
20
25
30
35
40
45
50
55
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Salamanca
Porcentajes
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Varones
Mujeres
Estructura de la inmigración exterior correspondiente a extranjeros
Santa Cruz de Tenerife
0
5
10
15
20
25
30
35
40
45
50
55
50
55
60
65
70
75
80
85
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Segovia
Porcentajes
70
75
80
85
90
95
Porcentajes
5
4
4
3
3
2
2
1
1
0
100+
0
5
Mujeres
10
15
20
25
10
15
20
25
Varones
30
35
40
45
50
55
30
35
40
45
50
55
60
65
70
75
80
85
Estructura de la inmigración exterior correspondiente a extranjeros
Soria
Porcentajes
60
65
70
75
80
85
5
10
15
25
30
35
Porcentajes
90
95
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
Varones
40
45
50
55
30
35
40
Mujeres
45
50
55
60
65
70
75
80
85
90
95
0
100+
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Teruel
Porcentajes
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades simples
Varones
0
100+
5
Mujeres
20
95
Edades sim ples
Estructura de la inmigración exterior correspondiente a extranjeros
Tarragona
0
90
Mujeres
Edades sim ples
Varones
0
100+
5
5
5
95
Edades sim ples
Estructura de la inmigración exterior correspondiente a extranjeros
Sevilla
0
90
Mujeres
Edades simples
Varones
45
Edades sim ples
Edades sim ples
Varones
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades sim ples
Varones
Mujeres
104
Estructura de la inmigración exterior correspondiente a extranjeros
Toledo
0
5
10
15
20
25
30
35
40
45
50
55
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Valencia
Porcentajes
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Varones
Mujeres
Estructura de la inmigración exterior correspondiente a extranjeros
Valladolid
0
5
10
15
20
25
30
35
40
45
50
55
5
10
20
25
30
40
45
50
55
60
65
70
75
80
85
5
10
20
25
30
40
45
50
55
Mujeres
90
95
0
100+
90
95
Porcentajes
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Zaragoza
Porcentajes
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
60
65
Estructura de la inmigración exterior correspondiente a extranjeros
Melilla
Porcentajes
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Edades sim ples
Varones
85
3
Varones
35
80
4
Mujeres
15
75
Edades simples
Estructura de la inmigración exterior correspondiente a extranjeros
Ceuta
0
70
4
Edades sim ples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Estructura de la inmigración exterior correspondiente a extranjeros
Vizcaya
Porcentajes
Estructura de la inmigración exterior correspondiente a extranjeros
Zamora
0
50
Mujeres
Edades sim ples
Varones
45
Edades simples
Edades sim ples
Varones
Porcentajes
5
Varones
Mujeres
105
5.2 Projection of external emigration
5.2.1 PROJECTION OF EXTERNAL EMIGRATION FROM SPAIN
The flow of external emigration, broken down by sex and age, which will leave Spain,
and each of its autonomous communities and provinces, to foreign destinations in the
next ten years, is projected following the steps below:
1. Projection of the annual volume of the emigration to abroad flow:
Estimating external emigration flows, until the present, constitutes the greatest
weakness in Spanish demographic statistics, largely due to the fact that Municipal
Registers present a clear subregister as far as external emigration of individuals of
foreign nationality is concerned, making the ongoing monitoring of the phenomenon
unfeasible, and greatly hindering current estimates and their future projection.
In order to partially solve this problem, development of the Organic Law Regulation
14/2003, “On the rights and freedoms of foreign nationals in Spain and their social
integration”, compels non-community foreign nationals without permanent residence,
as of 31 December 2005, to renew their record in the municipal register every two
years. This administrative procedure is a good starting point, albeit an incomplete one,
for estimating flows of those heading abroad, since it has two essential limitations: on
the one hand, the process of removals due to expiry only affects part of foreign
nationals as a whole, since it excludes community foreign nationals and those noncommunity foreign nationals with permanent residence; on the other hand, it limits the
observation chronological scope for the two years following the last registration in the
municipal register, introducing a certain degree of uncertainty regarding the
chronological distribution of those leaving thus recorded.
Nevertheless, although slanted and incomplete, information which provides removals
due to expiry in the Municipal Register, enables an approximation of the proportion of
departures by immigrants who arrived in the preceding years, and confers a certain
degree of statistical robustness to the hypothesis that we can build on time intensity
and dynamics of departures abroad.
Thus, as has already been mentioned, the projection model for external emigration of
foreign nationality designed is based on the setting of departures abroad of foreign
nationals who had arrived during the preceding years, based on a statistical
approximation of the municipal register of those foreign immigrants arriving in Spain
returning abroad in the years following their arrival. The way in which foreign
emigration is handled therefore depends on two closely linked aspects:
A. Estimating the propensity of an arriving cohort to return abroad in subsequent
years.
B. The calendar or chronological distribution of those departures.
Indeed, an analysis carried out by taking removals of foreign nationals from the
municipal register, and of the actual expiry process makes it possible to estimate that
approximately 30% of foreign immigration finally leaves Spain during the years
subsequent to its arrival. In fact, counting removals recorded in the Municipal Register,
as well as those resulting from the expiry process, either through confirmed removal,
106
or through expiries awaiting a response to the requirement by the respective municipal
council to renew the record in the municipal register, in relation to foreign nationals
arriving in the country in recent years, provides us with results which enable the
establishment of a basis for that claim, as is shown in the following graphs (it should
be borne in mind that in the aforementioned analysis, the possible departures of
community national individuals, or those with permanent residence in Spain, are not
considered):
Análisis de la relación de las salidas en el periodo 1996 - 2007 con las
entradas registradas en el periodo 1996 - 2005.
Total de extranjeros
0,3
0,25
22,38%
20,28%
0,2
14,66%
0,15
0,1
0,05
0
BBCs
BBCs + caducados pendientes de respuesta
BBCs + caducados pendientes de respuesta + BCRs con entrada anterior a 01-01-06
In addition, it has been assumed that those returning abroad do so in accordance with
a certain time profile, characterised by an accumulation thereof in the years
immediately following the year of arrival. The aforementioned assumptions regarding
the time profile of those foreign nationals departing, are based on the analyses carried
out in order to estimate the length of stay of immigrants, obtained by taking a carrying
out of removals due to change of residence (BCR) from the Municipal Register ,and
the date of their first recording therein (date of arrival in Spain). The following three
graphs show these results:
107
Distribución porce ntual de las BCR de nacionalidad extranjera con destino a l extranjero según
los me ses de permanencia en España. Años 2001 a 2008.
Porce ntaje s
7,7
6,6
5,5
4,4
3,3
2,2
1,1
0,0
0
3
6
9
12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93 96
M e s e s de pe rm ane ncia e n Es paña
BCRs año 2001
BCRs año 2002
BCRs año 2003
BCRs año 2004
BCRs año 2005
BCRs año 2006
BCRs año 2007
BCRs año 2008 (hasta 15 sept.)
Distribución porcentual de las BCR de nacionalidad extranjera (comunitarios y no
comunitarios) 2001-2008 con destino al extranjero según los meses de
permanencia en España
Porcentajes
6,0
5,0
4,0
3,0
2,0
1,0
0,0
0 3 6
9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93 96
Meses de perm anencia en España
BCRs 2001-2008
BCRs comunitarios 2001-2008
BCRs no comunitarios 2001-2008
108
Distribución porcentual de las BCR de nacionalidad extranjera (comunitarios y no
comunitarios) con destino al extranjero durante 2001-2008, según años de
permanencia en España.
Porce ntaje s
50,0
45,0
40,0
35,0
30,0
25,0
20,0
15,0
10,0
5,0
0,0
Menos de 1
1
2
BCRs total
3
4
5
Años de pe r m ane ncia e n Es paña
BCRs comunitarios
6
7
8 y más
BCRs no comunitarios
Whereupon, the calendar of returning abroad of emigrants of foreign nationality has
been approximated, taking the following five-parameter negative exponential function:
Ete = I e ⋅ p ⋅ a1 ⋅ e −α ⋅DR
where E te are the foreign emigrants departing from Spain in year t and who arrived in
Spain in year e ; I e is the flow of foreign immigrants arriving in Spain in year e ; p is
the propensity to leave Spain by foreign immigrants in the years following their arrival,
estimated at 0.3; DR is the duration of residence in Spain (difference between the
current year and year e of arrival in Spain); the parameters a1 and α have been set
at 0.4221 and 0.5474, respectively.
So then, the application of the values of this negative exponential function to the flows
of immigrants arriving each year in Spain gives rise to the total foreign emigrants
classified by years of residence in Spain:
109
Año de
Calendario
Salidas
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
estim adas
1998
13.094
1999
7.575
20.940
2000
4.382
12.113
61.595
2001
2.535
7.007
35.630
82.669
2002
1.466
4.053
20.611
47.821
82.756
2003
848
2.345
11.923
27.663
47.871
77.911
2004
491
1.356
6.897
16.002
27.692
45.069
81.789
2005
284
785
3.990
9.256
16.019
26.071
47.312
86.458
2006
164
454
2.308
5.354
9.266
15.081
27.368
50.013
101.688
2007
95
263
1.335
3.097
5.360
8.724
15.831
28.930
58.822
116.576
2008
55
152
772
1.792
3.101
5.046
9.158
16.735
34.027
67.435
88.882
2009
32
88
447
1.036
1.794
2.919
5.297
9.681
19.683
39.008
51.415
60.212
51
258
600
1.038
1.689
3.064
5.600
11.386
22.565
29.741
34.830
50.656
149
347
600
977
1.773
3.239
6.586
13.053
17.204
20.148
29.302
50.785
201
347
565
1.025
1.874
3.810
7.551
9.952
11.655
16.950
29.377
51.173
201
327
593
1.084
2.204
4.368
5.757
6.742
9.805
16.994
29.601
51.819
189
343
627
1.275
2.527
3.330
3.900
5.672
9.830
17.123
29.975
52.723
198
363
737
1.462
1.926
2.256
3.281
5.686
9.905
17.339
30.498
53.886
210
427
845
1.114
1.305
1.898
3.289
5.730
10.030
17.642
31.171
55.308
247
489
645
755
1.098
1.903
3.314
5.802
10.205
18.031
31.993
56.988
283
373
437
635
1.101
1.917
3.356
5.903
10.430
18.507
32.965
216
253
367
637
1.109
1.941
3.415
6.034
10.706
19.069
146
213
368
642
1.123
1.975
3.490
6.193
11.031
123
213
371
650
1.143
2.019
3.582
6.381
123
215
376
661
1.168
2.072
3.691
124
217
382
676
1.199
2.135
126
221
391
693
1.235
128
226
401
714
131
232
413
2010
13.094
2011
28.515
2012
78.090
2013
127.841
2014
156.707
2015
168.561
2016
179.295
2017
190.173
2018
211.696
2019
239.034
2020
227.154
2021
191.612
2022
161.478
2023
144.164
2024
134.480
2025
129.494
2026
127.514
2027
2028
Entradas
Salidas
cohorte
127.539
128.969
134
239
436.735
131.020
450.000
135.000
131.470
138
103.399
31.020
165.355
49.607
486.383
145.915
652.792
195.838
653.479
196.044
615.224
184.567
645.844
193.753
682.711
204.813
802.971
240.891
920.534
276.160
701.851
210.555
475.463
142.639
400.000
120.000
401.020
120.306
404.082
121.224
409.184
122.755
416.327
124.898
425.510
127.653
As far as emigration by Spaniards is concerned, this has been projected for the year
2008 with a procedure similar to that described for the case of external immigration,
taking the latest information available regarding the evolution of the aforementioned
flow in the first few months of 2008. Subsequently, a value of the aforementioned flow
in 2017 of 55,000 annual departures has been projected, in accordance with recent
evolution of those flows, particularly the increase shown therein in the first months of
2008, bearing in mind, primarily, that part of the former immigrants who have acquired
citizenship go on to form part both of transnational flows occurring between former
naturalised immigrants within the European Union, and with their countries of origin.
In view of this, the evolution observed (estimated in the case of foreign nationals) and
projected for foreign emigration flows from Spain by nationality is shown in the
following graphs:
110
2016
2017
2016
2017
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
300.000
250.000
200.000
150.000
100.000
50.000
0
2002
Emigrantes
Emigrantes extranjeros estimados y proyectados
2002-2017
Año
Emigrantes extranjeros
60.000
50.000
40.000
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
30.000
20.000
10.000
0
2002
Emigrantes
Emigrantes españoles observados y proyectados
2002-2017
Año
Emigrantes españoles
2. Distribution by sex of the total emigration flow of Spaniards and foreign nationals in
accordance with masculinity coefficients thereof projected for the 2008-2018 period:
The distribution by sex of departures by foreign nationals and Spaniards is obtained by
means of a parabolic adjustment of the male proportions in the total flow of departures
which links the 2002-2007 series with a projected value on the different projection
horizon for each of the two groups: it increases slightly for foreign nationals, from
60.14 percent of the start value to 62 percent in 2017, whereas among Spaniards, it
ranges from 50’06 percent in 2007 to 52 percent in 2017, in tune with the slight and
constant increase deriving from this parameter since 2004.
111
Proportion of males observed and projected in the flows of external departures of
Spaniards and foreign nationals in 2002-2017
64%
62%
60%
Extranjeros
Españoles
58%
56%
54%
52%
50%
48%
46%
2002
2004
2006
2008
2010
2012
2014
2016
2018
Source: Residential variation Statistics
112
Evolución y proyección del número de emigrantes exteriores según la nacionalidad.
2002-2017. Extranjeros
Hombres
Mujeres
Total
2002
156.707
2003
168.561
2004
179.295
2005
190.173
2006
211.696
2007
% Hombres
239.034
2008
136.603
90.551
227.154
60,14%
2009
115.979
75.633
191.612
60,53%
2010
98.296
63.182
161.478
60,87%
2011
88.188
55.976
144.164
61,17%
2012
82.604
51.876
134.480
61,42%
2013
79.810
49.684
129.494
61,63%
2014
78.795
48.719
127.514
61,79%
2015
78.957
48.582
127.539
61,91%
2016
79.931
49.038
128.969
61,98%
2017
81.512
49.959
131.470
62,00%
113
Evolución y proyección del número de emigrantes exteriores según la
nacionalidad. 2002-2017. Españoles.
Hombres
Mujeres
Total
% Hombres
2002
14.168
15.506
29.674
47,75%
2003
7.775
8.215
15.990
48,62%
2004
6.275
6.881
13.156
47,70%
2005
9.345
9.945
19.290
48,44%
2006
10.812
11.230
22.042
49,05%
2007
14.061
14.030
28.091
50,06%
2008
26.454
26.008
52.462
50,42%
2009
26.898
26.097
52.995
50,76%
2010
27.292
26.173
53.465
51,05%
2011
27.636
26.236
53.872
51,30%
2012
27.929
26.288
54.217
51,51%
2013
28.170
26.329
54.499
51,69%
2014
28.358
26.360
54.718
51,82%
2015
28.492
26.383
54.875
51,92%
2016
28.573
26.396
54.969
51,98%
2017
28.600
26.400
55.000
52,00%
3. Projection of a calendar of age of emigration in each sex, which remains constant
for the entire projection period, bearing in mind the observed stability thereof in recent
years:
The constant calendar of emigration by age in each sex of foreign nationals and
Spaniards has been derived from specific rates of foreign emigration by age calculated
by the following steps:
1) Calculation of the average flows of emigration for Spain by sex and age of the
years 2004-2007, observed in the Residential Variation Statistics (excluding
removals due to expiry in the aforementioned statistics, counted from the year
2006, which, given that, among other reasons, they only affect certain
nationalities, may have the unwanted effect of distorting the distributions
observed).
2) Smoothing of the flows obtained in point 1) in accordance with a procedure of
mobile averages of five ages, except in the ages 60-70, where a smoothing of
mobile averages of three consecutive ages, endeavouring to avoid random
fluctuations thereof and respecting certain systematic behaviours observed
around the age of retirement.
3) With the flows resulting from 2), we calculated rates of foreign emigration, using
as a denominator therein, the Population Now-Casts at 1 January 2006.
114
4) Smoothing rates obtained in point 3) in accordance with a procedure of mobile
averages of five ages, except in the ages 60-70, where a smoothing of mobile
averages of three consecutive ages has been used, trying to avoid random
fluctuations thereof and respecting certain systematic behaviours of the flows
observed around the age of retirement.
5) These rates have been subjected to a new transformation, consistent with
maintaining constant the emigration rate of 85 years, from said age, given the
extreme variability presented by the same for the oldest ages.
6) Obtaining of the standardised calendar derived from the rates resulting from
point 5).
4. External migration flows and the external emigration calendar projected are
subjected to an iterative process of execution of the projection exercise at a national
level, making it possible to derive, taking a starting solution, a Total External
Emigration Rate for each year of the projection period, consistent with the projected
flows and calendars.
5.2.2 PROJECTION OF EXTERNAL EMIGRATION FROM EACH PROVINCE
The specific rate by age of external emigration in a year t from each province i and
for each sex s may be expressed as the product of the intensity of the foreign
emigration in the aforementioned province and sex quantified in the Total External
Emigration Rate ( ISM st ,i ) thereof and the percentage distribution of these or calendar
of that migration ( cit,s , x ):
mi , s , x = ISM s ,i ⋅ ci , s , x
where ISM i ,s =
100
mit,s , x
x =0
ISM it,s , x
∑ mi ,s,x and cit,s, x =
in which x is the age s the sex, i the
province of origin and t the year.
So then, the projection of those specific rates of external emigration in each province
has been carried out in accordance with the following steps:
1. The Total External Emigration Rate projected for each province is obtained by
taking that projected for the national total in each year, multiplying this by the ratio
projected between both indices, provincial and national, in each year of the projection
period.
The aforementioned ratio has been projected for the years 2008-2017, setting for the
year 2008 that derived from the recent trend observed therein from the average
emigration flows observed in the 2004-2007 period (excluding removals due to expiry
in the aforementioned statistics, counted as of the year 2006, since there may be
unwanted distortions, as has already been commented, in the distributions by age
observed), and forecasting a reduction by half of the differential which in that index is
kept by every province in Spain for the year 2017, based on a territorial convergence
in the emigration trend in the next few years, given the expected consolidation of
redistribution processes of the residence of the foreign population in the different
115
regions and provinces, which constitutes the main component in foreign emigration
flows.
Total External Emigration Rate , projected for 2008, and ratio projected on the relationship
between the province and the whole of Spain. Males
Ratio for Spain
Province
Álava
Albacete
Alicante
Almería
Ávila
Badajoz
Balears
Barcelona
Burgos
Cáceres
Cádiz
Castellón
Ciudad Real
Córdoba
Coruña (A)
Cuenca
Girona
Granada
Guadalajara
Guipúzcoa
Huelva
Huesca
Jaén
León
Lleida
Rioja (La)
Lugo
Madrid
Málaga
Murcia
Navarra
Ourense
Asturias
Palencia
Palmas (Las)
Pontevedra
Salamanca
Tenerife
Cantabria
Segovia
Sevilla
Soria
Tarragona
Teruel
Toledo
Valencia
Valladolid
Vizcaya
Zamora
Zaragoza
Ceuta
Melilla
SMIforeign 2008
0.223
0.074
0.207
0.093
0.054
0.079
0.181
0.393
0.119
0.031
0.046
0.128
0.032
0.021
0.102
0.046
0.300
0.084
0.089
0.232
0.052
0.094
0.027
0.045
0.113
0.249
0.054
0.136
0.126
0.103
0.102
0.160
0.053
0.049
0.070
0.101
0.054
0.099
0.058
0.083
0.035
0.074
0.150
0.087
0.056
0.152
0.041
0.175
0.084
0.089
0.063
0.938
1.544
0.509
1.432
0.642
0.375
0.547
1.250
2.717
0.821
0.213
0.319
0.883
0.224
0.144
0.706
0.316
2.071
0.584
0.614
1.602
0.358
0.651
0.190
0.311
0.784
1.719
0.374
0.942
0.871
0.711
0.707
1.109
0.364
0.342
0.485
0.700
0.372
0.685
0.401
0.572
0.242
0.511
1.038
0.601
0.384
1.053
0.284
1.213
0.580
0.616
0.433
6.481
2009
1.541
0.512
1.429
0.644
0.379
0.550
1.249
2.706
0.822
0.218
0.323
0.884
0.229
0.149
0.707
0.321
2.064
0.586
0.617
1.598
0.362
0.653
0.195
0.316
0.786
1.714
0.378
0.943
0.871
0.713
0.709
1.108
0.368
0.346
0.488
0.702
0.376
0.687
0.405
0.574
0.246
0.514
1.037
0.603
0.388
1.052
0.288
1.211
0.583
0.618
0.436
6.447
2010
1.531
0.521
1.421
0.651
0.390
0.558
1.244
2.674
0.825
0.232
0.335
0.886
0.243
0.165
0.713
0.333
2.044
0.594
0.624
1.587
0.374
0.660
0.210
0.328
0.790
1.701
0.389
0.944
0.874
0.718
0.714
1.106
0.379
0.358
0.498
0.707
0.387
0.693
0.416
0.582
0.260
0.523
1.037
0.610
0.400
1.051
0.302
1.207
0.591
0.625
0.447
6.346
2011
1.514
0.536
1.408
0.662
0.409
0.572
1.236
2.621
0.831
0.257
0.357
0.890
0.267
0.191
0.722
0.354
2.011
0.607
0.636
1.569
0.394
0.670
0.235
0.350
0.796
1.679
0.408
0.946
0.878
0.727
0.723
1.103
0.399
0.378
0.514
0.716
0.407
0.703
0.434
0.596
0.284
0.538
1.036
0.623
0.419
1.050
0.324
1.201
0.604
0.637
0.464
6.177
2012
1.491
0.557
1.389
0.678
0.436
0.592
1.226
2.547
0.838
0.291
0.386
0.895
0.301
0.228
0.735
0.384
1.965
0.625
0.653
1.543
0.422
0.685
0.270
0.379
0.806
1.648
0.436
0.948
0.883
0.740
0.736
1.098
0.427
0.407
0.536
0.729
0.434
0.716
0.460
0.614
0.317
0.559
1.034
0.640
0.445
1.048
0.355
1.192
0.622
0.654
0.489
5.940
2013
1.460
0.585
1.365
0.697
0.471
0.617
1.212
2.452
0.848
0.334
0.424
0.901
0.344
0.276
0.751
0.422
1.906
0.648
0.674
1.509
0.457
0.705
0.315
0.418
0.818
1.608
0.470
0.951
0.891
0.756
0.752
1.092
0.462
0.443
0.565
0.746
0.469
0.734
0.493
0.638
0.359
0.586
1.032
0.662
0.479
1.045
0.394
1.180
0.645
0.675
0.520
5.635
2014
1.423
0.618
1.336
0.722
0.514
0.648
1.195
2.335
0.860
0.388
0.470
0.909
0.397
0.334
0.771
0.468
1.833
0.676
0.700
1.468
0.501
0.728
0.370
0.464
0.832
1.559
0.513
0.955
0.899
0.775
0.772
1.084
0.505
0.488
0.600
0.767
0.511
0.755
0.534
0.667
0.410
0.620
1.029
0.689
0.521
1.041
0.443
1.165
0.674
0.701
0.559
5.263
2015
1.380
0.657
1.301
0.750
0.564
0.684
1.175
2.197
0.875
0.451
0.525
0.918
0.459
0.403
0.795
0.523
1.747
0.710
0.731
1.420
0.553
0.756
0.435
0.520
0.850
1.501
0.563
0.960
0.910
0.798
0.796
1.076
0.556
0.541
0.641
0.791
0.562
0.781
0.582
0.701
0.471
0.659
1.026
0.721
0.571
1.037
0.501
1.148
0.707
0.732
0.604
4.823
2016
1.329
0.703
1.261
0.784
0.622
0.726
1.151
2.038
0.891
0.524
0.588
0.929
0.531
0.482
0.822
0.586
1.648
0.748
0.767
1.364
0.612
0.789
0.510
0.583
0.870
1.435
0.621
0.965
0.922
0.825
0.823
1.066
0.615
0.602
0.689
0.818
0.620
0.810
0.638
0.741
0.541
0.704
1.023
0.758
0.628
1.032
0.567
1.129
0.746
0.768
0.657
4.316
2017
1.272
0.754
1.216
0.821
0.687
0.774
1.125
1.858
0.910
0.607
0.659
0.942
0.612
0.572
0.853
0.658
1.535
0.792
0.807
1.301
0.679
0.825
0.595
0.656
0.892
1.359
0.687
0.971
0.935
0.856
0.853
1.054
0.682
0.671
0.743
0.850
0.686
0.843
0.700
0.786
0.621
0.755
1.019
0.800
0.692
1.026
0.642
1.106
0.790
0.808
0.716
3.741
Spain
0.145
1
1
1
1
1
1
1
1
1
Source: external emigration flows 2004-2007 from the Residential Variation Statistics (without including removals due to
expiry) and Population Now-Casts at 1 January 2006.
1
116
Total External Emigration Rate, projected for 2008, and ratio projected on the relationship
between the province and the whole of Spain. Females
Ratio for Spain
Province
Álava
Albacete
Alicante
Almería
Ávila
Badajoz
Balears
Barcelona
Burgos
Cáceres
Cádiz
Castellón
Ciudad Real
Córdoba
Coruña (A)
Cuenca
Girona
Granada
Guadalajara
Guipúzcoa
Huelva
Huesca
Jaén
León
Lleida
Rioja (La)
Lugo
Madrid
Málaga
Murcia
Navarra
Ourense
Asturias
Palencia
Palmas (Las)
Pontevedra
Salamanca
Tenerife
Cantabria
Segovia
Sevilla
Soria
Tarragona
Teruel
Toledo
Valencia
Valladolid
Vizcaya
Zamora
Zaragoza
Ceuta
Melilla
Spain
SMIforeign
0.124
0.057
0.159
0.059
0.049
0.053
0.157
0.285
0.099
0.031
0.045
0.101
0.026
0.020
0.093
0.038
0.221
0.068
0.082
0.189
0.039
0.079
0.019
0.039
0.102
0.115
0.051
0.135
0.097
0.071
0.085
0.133
0.054
0.039
0.058
0.083
0.062
0.092
0.058
0.063
0.033
0.060
0.126
0.066
0.041
0.107
0.047
0.150
0.045
0.078
0.091
0.958
2008
1.072
0.489
1.371
0.506
0.426
0.457
1.356
2.462
0.851
0.266
0.387
0.871
0.220
0.176
0.799
0.331
1.910
0.586
0.707
1.632
0.336
0.684
0.162
0.334
0.879
0.994
0.438
1.162
0.836
0.608
0.730
1.150
0.462
0.338
0.499
0.715
0.537
0.794
0.503
0.547
0.287
0.515
1.084
0.568
0.353
0.921
0.405
1.296
0.386
0.676
0.786
8.262
2009
1.072
0.493
1.369
0.509
0.429
0.460
1.354
2.453
0.852
0.271
0.390
0.871
0.225
0.181
0.800
0.335
1.905
0.588
0.708
1.628
0.341
0.685
0.167
0.338
0.879
0.994
0.441
1.161
0.837
0.611
0.732
1.149
0.465
0.342
0.502
0.716
0.540
0.795
0.506
0.549
0.292
0.518
1.083
0.571
0.357
0.921
0.409
1.294
0.389
0.678
0.788
8.217
2010
1.071
0.502
1.362
0.518
0.440
0.470
1.347
2.426
0.855
0.285
0.402
0.874
0.240
0.196
0.804
0.348
1.888
0.596
0.714
1.616
0.353
0.691
0.183
0.351
0.882
0.995
0.452
1.158
0.840
0.618
0.737
1.147
0.475
0.354
0.511
0.722
0.548
0.799
0.515
0.558
0.305
0.527
1.082
0.579
0.369
0.923
0.420
1.289
0.401
0.684
0.792
8.083
2011
1.068
0.518
1.351
0.533
0.458
0.487
1.336
2.381
0.859
0.307
0.421
0.878
0.264
0.222
0.810
0.368
1.860
0.609
0.723
1.597
0.373
0.701
0.209
0.371
0.885
0.995
0.469
1.153
0.845
0.630
0.745
1.142
0.492
0.375
0.526
0.731
0.563
0.806
0.530
0.572
0.327
0.542
1.079
0.592
0.389
0.925
0.438
1.280
0.420
0.694
0.798
7.859
2012
1.065
0.540
1.334
0.555
0.483
0.511
1.321
2.317
0.866
0.339
0.447
0.883
0.297
0.257
0.819
0.397
1.820
0.627
0.736
1.569
0.402
0.715
0.245
0.400
0.891
0.995
0.493
1.146
0.852
0.647
0.757
1.136
0.515
0.403
0.548
0.743
0.583
0.814
0.552
0.591
0.358
0.563
1.075
0.611
0.417
0.928
0.464
1.267
0.446
0.708
0.807
7.545
2013
1.061
0.568
1.314
0.582
0.515
0.541
1.301
2.236
0.874
0.380
0.481
0.891
0.341
0.303
0.830
0.435
1.770
0.650
0.752
1.534
0.439
0.732
0.291
0.437
0.897
0.995
0.524
1.137
0.861
0.669
0.772
1.127
0.545
0.440
0.576
0.759
0.608
0.826
0.580
0.617
0.397
0.589
1.071
0.635
0.453
0.933
0.497
1.250
0.480
0.726
0.819
7.142
2014
1.056
0.603
1.289
0.616
0.553
0.578
1.277
2.137
0.884
0.429
0.523
0.899
0.394
0.359
0.843
0.480
1.708
0.678
0.772
1.491
0.484
0.754
0.348
0.482
0.906
0.996
0.563
1.126
0.873
0.695
0.790
1.117
0.581
0.485
0.610
0.778
0.640
0.840
0.613
0.647
0.446
0.622
1.065
0.664
0.497
0.938
0.538
1.230
0.522
0.748
0.834
6.648
2015
1.050
0.644
1.259
0.655
0.600
0.621
1.248
2.020
0.896
0.488
0.572
0.910
0.456
0.425
0.860
0.534
1.635
0.711
0.795
1.441
0.537
0.779
0.415
0.536
0.915
0.996
0.608
1.113
0.886
0.727
0.812
1.105
0.625
0.538
0.650
0.801
0.677
0.856
0.653
0.684
0.503
0.661
1.058
0.699
0.549
0.945
0.585
1.207
0.571
0.774
0.851
6.066
2016
1.044
0.691
1.225
0.701
0.653
0.672
1.215
1.884
0.910
0.556
0.629
0.922
0.528
0.502
0.878
0.595
1.551
0.749
0.822
1.382
0.599
0.809
0.493
0.597
0.927
0.997
0.660
1.098
0.901
0.763
0.837
1.091
0.674
0.600
0.697
0.827
0.720
0.875
0.699
0.726
0.569
0.706
1.051
0.739
0.608
0.952
0.640
1.179
0.628
0.804
0.871
5.393
2017
1.036
0.745
1.186
0.753
0.713
0.729
1.178
1.731
0.926
0.633
0.693
0.935
0.610
0.588
0.899
0.666
1.455
0.793
0.853
1.316
0.668
0.842
0.581
0.667
0.939
0.997
0.719
1.081
0.918
0.804
0.865
1.075
0.731
0.669
0.749
0.857
0.769
0.897
0.751
0.773
0.644
0.757
1.042
0.784
0.676
0.960
0.703
1.148
0.693
0.838
0.893
4.631
0.116
1
1
1
1
1
1
1
1
1
1
Source: external emigration flows 2004-2007 from the Residential Variation Statistics (without including removals due to
expiry) and Population Now-Casts at 1 January 2006.
In this way, the Total External Emigration Rate of the sex s in province i projected for
each year t of the projection period comes from:
ISM it,s = ISM ( España ) ts ⋅
ISM it, s
ISM ( España ) ts
117
where ISM ( España ) ts is the Total External Emigration Rate from Spain projected for
ISM it,s
year t ;
ISM ( España ) ti ,s
is the relationship projected between the Total External
Emigration Rate in the province and Spain in year t .
2. The calendar for each sex of those for external emigration rates of each province
has been kept constant for the entire projection period, being derived from these
external emigration rates observed for the 2004-2007 period in each one of them,
obtained from the similar smoothing procedure of flows and rates applied for the case
of the national total.
The external emigration calendars projected for each sex and age in each province,
are represented in the following graphs:
Calendario de la emigración exterior (españoles y extranjeros)
Álava
0
5
10
15
20
25
30
35
40
45
50
55
Calendario de la emigración exterior (españoles y extranjeros)
Albacete
Porcentajes
60
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Mujeres
Varones
Calendario de la emigración exterior (españoles y extranjeros)
Alicante
0
5
10
15
20
25
30
35
40
45
50
55
Mujeres
50
55
60
65
70
75
80
85
90
95
0
100+
60
Calendario de la emigración exterior (españoles y extranjeros)
Almería
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades simples
Varones
45
Edades s imples
Edades simples
Varones
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
118
Calendario de la emigración exterior (españoles y extranjeros)
Asturias
0
5
10
15
20
25
30
35
40
45
50
55
60
Calendario de la emigración exterior (españoles y extranjeros)
Ávila
Porcentajes
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Mujeres
Varones
Calendario de la emigración exterior (españoles y extranjeros)
Badajoz
0
5
10
15
20
25
30
35
40
45
50
55
5
10
20
25
30
40
45
50
55
60
65
70
75
80
85
5
10
20
25
30
40
45
50
55
Mujeres
90
95
0
100+
90
95
Porcentajes
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
60
Calendario de la emigración exterior (españoles y extranjeros)
Burgos
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
60
Calendario de la emigración exterior (españoles y extranjeros)
Cádiz
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades simples
Varones
85
3
Varones
35
80
4
Mujeres
15
75
Edades simples
Calendario de la emigración exterior (españoles y extranjeros)
Cáceres
0
70
4
Edades simples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Calendario de la emigración exterior (españoles y extranjeros)
Illes Balears
Porcentajes
Calendario de la emigración exterior (españoles y extranjeros)
Barcelona
0
50
Mujeres
Edades simples
Varones
45
Edades sim ples
Edades simples
Varones
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
119
Calendario de la emigración exterior (españoles y extranjeros)
Cantabria
0
5
10
15
20
25
30
35
40
45
50
55
60
Calendario de la emigración exterior (españoles y extranjeros)
Castellón
Porcentajes
65
70
75
80
85
90
5
4
4
3
3
2
2
1
1
0
100+
95
0
5
10
15
20
25
30
35
40
Edades sim ples
Varones
5
10
Varones
Mujeres
15
20
25
30
35
40
45
50
55
50
55
60
65
70
75
80
85
90
95
Calendario de la emigración exterior (españoles y extranjeros)
Córdoba
Porcentajes
60
65
70
75
80
85
90
95
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
Mujeres
Varones
Mujeres
Calendario de la emigración exterior (españoles y extranjeros)
Cuenca
Porcentajes
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100+
0
5
10
15
20
25
30
35
40
Edades sim ples
Varones
5
10
Varones
Mujeres
15
20
25
30
35
40
45
50
55
Mujeres
50
55
60
65
70
75
80
85
90
95
0
100+
60
Calendario de la emigración exterior (españoles y extranjeros)
Granada
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades sim ples
Edades simples
Varones
45
Edades simples
Calendario de la emigración exterior (españoles y extranjeros)
Girona
0
0
100+
Edades sim ples
Calendario de la emigración exterior (españoles y extranjeros)
Coruña (A)
0
0
100+
Mujeres
Edades simples
Varones
45
Edades simples
Calendario de la emigración exterior (españoles y extranjeros)
Ciudad Real
0
Porcentajes
5
Varones
Mujeres
120
Calendario de la emigración exterior (españoles y extranjeros)
Guadalajara
0
5
10
15
20
25
30
35
40
45
50
55
60
Calendario de la emigración exterior (españoles y extranjeros)
Guipúzcoa
Porcentajes
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Edades sim ples
Varones
5
10
Mujeres
15
20
25
30
Varones
35
40
45
50
55
5
10
20
25
30
40
45
50
55
60
65
70
75
80
85
5
10
20
25
30
40
45
50
55
Mujeres
90
95
0
100+
90
95
Porcentajes
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
60
Calendario de la emigración exterior (españoles y extranjeros)
León
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
60
Calendario de la emigración exterior (españoles y extranjeros)
Lugo
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades sim ples
Edades simples
Varones
85
3
Varones
35
80
4
Mujeres
15
75
Edades sim ples
Calendario de la emigración exterior (españoles y extranjeros)
Lleida
0
70
4
Edades simples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Calendario de la emigración exterior (españoles y extranjeros)
Huesca
Porcentajes
Calendario de la emigración exterior (españoles y extranjeros)
Jaén
0
50
Mujeres
Edades simples
Varones
45
Edades sim ples
Calendario de la emigración exterior (españoles y extranjeros)
Huelva
0
Porcentajes
5
Varones
Mujeres
121
Calendario de la emigración exterior (españoles y extranjeros)
Madrid
0
5
10
15
20
25
30
35
40
45
50
55
Calendario de la emigración exterior (españoles y extranjeros)
Málaga
Porcentajes
60
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Edades simples
Varones
5
10
Mujeres
15
20
25
30
Varones
35
40
45
50
55
5
10
20
25
30
40
45
50
55
60
65
70
75
80
85
5
10
20
25
30
40
45
50
55
Mujeres
90
95
0
100+
90
95
Porcentajes
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Calendario de la emigración exterior (españoles y extranjeros)
Palencia
Porcentajes
60
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
60
Calendario de la emigración exterior (españoles y extranjeros)
Pontevedra
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades sim ples
Varones
85
3
Varones
35
80
4
Mujeres
15
75
Edades simples
Calendario de la emigración exterior (españoles y extranjeros)
Palmas (Las)
0
70
4
Edades simples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Calendario de la emigración exterior (españoles y extranjeros)
Navarra
Porcentajes
Calendario de la emigración exterior (españoles y extranjeros)
Ourense
0
50
Mujeres
Edades simples
Varones
45
Edades simples
Calendario de la emigración exterior (españoles y extranjeros)
Murcia
0
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
122
Calendario de la emigración exterior (españoles y extranjeros)
Rioja (La)
0
5
10
15
20
25
30
35
40
45
50
55
Calendario de la emigración exterior (españoles y extranjeros)
Salamanca
Porcentajes
60
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Mujeres
Varones
Calendario de la emigración exterior (españoles y extranjeros)
Santa Cruz de Tenerife
0
5
10
15
20
25
30
35
40
45
50
5
10
20
25
30
40
45
50
55
55
60
65
70
75
80
85
5
10
20
25
30
40
45
50
55
Mujeres
90
95
0
100+
90
95
Porcentajes
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Calendario de la emigración exterior (españoles y extranjeros)
Soria
Porcentajes
60
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades sim ples
60
Calendario de la emigración exterior (españoles y extranjeros)
Teruel
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades sim ples
Varones
85
3
Varones
35
80
4
Mujeres
15
75
Edades simples
Calendario de la emigración exterior (españoles y extranjeros)
Tarragona
0
70
4
Edades simples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Calendario de la emigración exterior (españoles y extranjeros)
Segovia
Porcentajes
Calendario de la emigración exterior (españoles y extranjeros)
Sevilla
0
50
Mujeres
Edades sim ples
Varones
45
Edades sim ples
Edades simples
Varones
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades sim ples
Varones
Mujeres
123
Calendario de la emigración exterior (españoles y extranjeros)
Toledo
0
5
10
15
20
25
30
35
40
45
50
55
Calendario de la emigración exterior (españoles y extranjeros)
Valencia
Porcentajes
60
65
70
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Mujeres
Varones
Calendario de la emigración exterior (españoles y extranjeros)
Valladolid
0
5
10
15
20
25
30
35
40
45
50
55
5
10
20
25
30
40
45
50
55
60
65
70
75
80
85
5
10
20
25
30
40
45
50
55
Mujeres
90
95
0
100+
90
95
Porcentajes
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
60
Calendario de la emigración exterior (españoles y extranjeros)
Zaragoza
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100+
Edades sim ples
60
Calendario de la emigración exterior (españoles y extranjeros)
Melilla
Porcentajes
65
70
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Edades simples
Varones
85
3
Varones
35
80
4
Mujeres
15
75
Edades simples
Calendario de la emigración exterior (españoles y extranjeros)
Ceuta
0
70
4
Edades simples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Calendario de la emigración exterior (españoles y extranjeros)
Vizcaya
Porcentajes
Calendario de la emigración exterior (españoles y extranjeros)
Zamora
0
50
Mujeres
Edades simples
Varones
45
Edades sim ples
Edades simples
Varones
Porcentajes
5
Varones
Mujeres
124
6
Internal migration projection
The hypothesis of the evolution of the phenomenon of internal migration in Spain has
been carried out from the projection for each year of projection period t of the specific
interprovincial migration rates by sex and age, m st , x ,i , j . Said rates can be broken down
in the product of three factors: the intensity of emigration to the rest of Spain for each
sex s from a province i , quantified in the Total Internal Emigration Rate of said
province for each year ( ISM it,s ); the calendar by age x of said emigration to the rest
of Spain from province i ( cit,s , x ); and a distribution coefficient according to province of
destination j of domestic migration for each sex and age from province i ( a st , x ,i , j ). In
this way, we obtain:
m st , x ,i , j = ISM it, s ⋅ cit,s , x ⋅ a st , x ,i , j
Now, the projection of those internal mobility rates has been carried out in the
following steps:
1. Projection of the Total Internal Migration Rate from each province to the rest of
Spain from an autoregressive regression model with delays in the endogenous
variable, which makes said emigratory intensity to the rest of Spain in a given year
depend on the immigration flow from abroad of foreign nationals from the same year
and the previous year, as well as on the emigratory intensity to other provinces in
Spain from the previous year.
This thus establishes the following regression model to explain the evolution of the
migratory intensity of each province to the rest of Spain:
ISM it, s = β 0 + β1 ISM it,−s1 + β 2 IM it, s + β 3 IM it,−s1 + ε t
where ISM it,s is the Total Internal Migration Rate to the rest of Spain for sex s and
province i in year t ; IM it,s is the immigration flow from abroad, of foreign individuals of
sex s in province
i during year
t ; and ε t is the margin of random error of the model.
Said adjustment model of the historical series of the Total Internal Migration Rate to
the rest of Spain for each province is based on the effect observed of the foreign
population on the internal mobility in Spain, more intense when the time of residence
of said population in Spain is shorter, as well as on the autoregressive trend behaviour
of the series.
The adjustment of the model has considered, for each province, the historical series
observed from 1988 to 2008 for foreign immigrants arriving from abroad in each
9
province, observed in the Residential Variation Statistics and of interprovincial
migrations by sex and five-year age group (up to open age group 85 years old and
9
complete with the entries by omission In the Municipal Registers of Inhabitants of individuals with
foreign nationalities during the years 1998-2003
125
10
over), also obtained from the Residential Variation Statistics until the year 2007 , and
of the population figures of the Intercensal Population Estimates and of the Population
Now-Casts. In addition, the values of the Total Internal Migration Rates to the Rest of
Spain for each province in the years 1991, 1996 and 2001 have been replaced by the
semi-sum of those corresponding to the adjacent years, to solve the sub-register
problem that the Residential Variation Statistics themselves present for said years.
On the other hand, the specific behaviour observed in some provinces has made it
necessary to remove some of the model regressors therein, in order to achieve a
greater explicative veracity of the response variable. Specifically, in the case of men
and women from Cádiz and Baleares, and men from Asturias, we have removed from
the regression model the foreign immigration flow from the previous year, and in the
case of men from León and Cantabria, the foreign immigration flow from the same
year.
The adjustment and consistent estimation of those autoregressive regression models
with delays in the endogenous variable, have been carried out taking the iterative
procedure of Cochrane and Orcutt, obtaining the following values of the regression
coefficient, adjusted as a measure of the veracity of the adjustment of each one of the
them in each province:
10
For the year 2008, an estimate has been made of the total interprovincial migrations from the
monthly series of Monthly Demographic Now Castfrom October 2008 to the month of September,
and from an advanced estimation of the same for the fourth quarter of the year, carried out with a
methodology of the Population Now-Casts, and using the distribution structures of said flows by
province, sex and age observed in the 2007 RVS
126
Provincia
Hombres
R2 ajustado
Mujeres
R2 ajustado
Álava
0,883
0,88
Albacete
0,957
0,941
Alicante
0,991
0,98
Almería
0,932
0,894
Ávila
0,93
0,933
Badajoz
0,845
0,788
Balears
0,823
0,85
Barcelona
0,99
0,992
Burgos
0,916
0,911
Cáceres
0,866
0,83
Cádiz
0,658
0,792
Castellón
0,984
0,953
Ciudad Real
0,869
0,838
Córdoba
0,678
0,721
Coruña (A)
0,679
0,85
Cuenca
0,988
0,947
Girona
0,989
0,99
Granada
0,739
0,693
Guadalajara
0,944
0,935
Guipúzcoa
0,904
0,886
Huelva
0,957
0,877
Huesca
0,984
0,974
Jaén
0,904
0,855
León
0,947
0,937
Lleida
0,95
0,928
Rioja (La)
0,972
0,986
Lugo
0,934
0,939
Madrid
0,97
0,967
Málaga
0,973
0,974
Murcia
0,931
0,897
Navarra
0,984
0,984
Ourense
0,884
0,899
Asturias
0,96
0,824
Palencia
0,825
0,837
Palmas (Las)
0,839
0,875
Pontevedra
0,727
0,835
Salamanca
0,884
0,868
Tenerife
0,975
0,974
Cantabria
0,933
0,848
Segovia
0,979
0,973
Sevilla
0,617
0,711
Soria
0,935
0,947
Tarragona
0,933
0,853
Teruel
0,968
0,944
Toledo
0,947
0,915
Valencia
0,97
0,952
Valladolid
0,893
0,908
Vizcaya
0,846
0,82
Zamora
0,856
0,841
Zaragoza
0,935
0,924
Ceuta
0,831
0,881
Melilla
0,939
0,941
127
From the model adjusted for each province, we derive the Total Internal Migration
Rates to the rest of Spain projected for each one of them in each year of the
projection period:
Índice sintético de emigración a otras provincias. Hombres (2007-2017)
Provincia
Álava
Albacete
Alicante
Almería
Ávila
Badajoz
Balears
Barcelona
Burgos
Cáceres
Cádiz
Castellón
Ciudad Real
Córdoba
Coruña (A)
Cuenca
Girona
Granada
Guadalajara
Guipúzcoa
Huelva
Huesca
Jaén
León
Lleida
Rioja (La)
Lugo
Madrid
Málaga
Murcia
Navarra
Ourense
Asturias
Palencia
Palmas (Las)
Pontevedra
Salamanca
Tenerife
Cantabria
Segovia
Sevilla
Soria
Tarragona
Teruel
Toledo
Valencia
Valladolid
Vizcaya
Zamora
Zaragoza
Ceuta
Melilla
2007
1,47
1,73
1,37
1,90
2,70
1,19
1,60
1,29
1,67
1,63
0,95
1,46
1,49
1,07
0,88
2,71
1,75
1,27
2,99
0,90
1,18
1,94
1,48
1,52
1,99
1,64
1,26
1,53
1,09
1,32
1,05
1,56
0,90
1,66
1,36
0,96
1,56
1,11
1,13
2,65
0,74
2,29
1,82
3,01
2,23
1,03
1,33
1,07
1,87
1,17
2,91
3,40
2008
1,65
1,82
1,41
1,99
2,55
1,22
1,61
1,45
1,73
1,80
0,97
1,40
1,51
1,07
0,95
2,70
1,85
1,28
2,70
0,95
1,24
2,16
1,45
1,68
2,43
1,91
1,32
1,60
1,06
1,33
1,22
1,60
0,94
1,68
1,38
1,00
1,52
1,16
1,19
2,57
0,78
2,25
1,92
2,75
1,98
1,07
1,31
1,14
1,94
1,28
3,23
3,86
2009
1,59
1,70
1,39
1,93
2,22
1,12
1,61
1,45
1,71
1,76
0,94
1,29
1,36
1,00
0,94
2,33
1,78
1,22
2,40
0,86
1,21
2,11
1,27
1,77
1,96
1,89
1,32
1,61
1,06
1,30
1,20
1,42
0,96
1,65
1,27
0,98
1,40
1,12
1,19
2,40
0,78
2,07
1,79
2,35
1,73
1,03
1,20
1,10
1,95
1,23
3,22
3,87
2010
1,45
1,53
1,36
1,86
1,98
1,03
1,50
1,36
1,68
1,70
0,93
1,15
1,23
0,94
0,90
2,03
1,61
1,15
2,17
0,79
1,12
1,98
1,14
1,73
1,58
1,75
1,31
1,53
1,03
1,24
1,13
1,23
0,85
1,59
1,15
0,92
1,30
1,03
1,14
2,22
0,76
1,90
1,57
2,05
1,54
0,95
1,11
1,04
1,92
1,13
3,18
3,81
2011
1,34
1,40
1,33
1,81
1,87
0,97
1,40
1,28
1,65
1,64
0,89
1,06
1,16
0,91
0,86
1,89
1,48
1,10
2,05
0,77
1,05
1,86
1,09
1,60
1,48
1,62
1,30
1,45
0,99
1,18
1,06
1,15
0,75
1,54
1,06
0,87
1,24
0,95
1,05
2,09
0,74
1,79
1,42
1,93
1,44
0,88
1,05
0,99
1,88
1,04
3,15
3,75
2012
1,28
1,33
1,30
1,78
1,83
0,96
1,33
1,21
1,62
1,59
0,86
1,01
1,13
0,89
0,83
1,83
1,41
1,07
1,99
0,77
1,01
1,77
1,07
1,50
1,48
1,53
1,29
1,39
0,97
1,13
1,01
1,13
0,70
1,51
1,02
0,83
1,21
0,90
0,98
2,00
0,73
1,73
1,36
1,90
1,40
0,83
1,02
0,97
1,84
0,99
3,12
3,70
2013
1,26
1,29
1,28
1,74
1,81
0,95
1,29
1,17
1,60
1,55
0,85
0,99
1,12
0,88
0,81
1,81
1,37
1,05
1,97
0,76
0,98
1,72
1,07
1,44
1,49
1,48
1,29
1,35
0,95
1,09
0,97
1,13
0,68
1,49
0,99
0,81
1,19
0,86
0,95
1,94
0,72
1,70
1,33
1,90
1,38
0,80
1,01
0,96
1,82
0,96
3,10
3,66
2014
1,25
1,27
1,26
1,72
1,81
0,95
1,26
1,14
1,59
1,51
0,84
0,98
1,12
0,88
0,80
1,81
1,36
1,04
1,96
0,77
0,96
1,68
1,07
1,40
1,49
1,44
1,28
1,31
0,93
1,07
0,95
1,13
0,68
1,47
0,99
0,80
1,18
0,84
0,93
1,90
0,71
1,68
1,32
1,90
1,38
0,78
1,01
0,95
1,79
0,95
3,08
3,62
2015
1,24
1,27
1,24
1,70
1,82
0,95
1,25
1,12
1,57
1,48
0,84
0,98
1,12
0,87
0,79
1,82
1,35
1,04
1,96
0,77
0,95
1,65
1,07
1,39
1,51
1,42
1,28
1,29
0,92
1,05
0,93
1,14
0,68
1,47
0,98
0,79
1,18
0,83
0,92
1,88
0,70
1,68
1,32
1,92
1,39
0,77
1,01
0,95
1,78
0,94
3,07
3,59
2016
1,25
1,27
1,23
1,69
1,83
0,95
1,24
1,10
1,57
1,46
0,84
0,98
1,13
0,88
0,78
1,84
1,36
1,04
1,97
0,77
0,95
1,64
1,08
1,38
1,52
1,40
1,28
1,28
0,91
1,03
0,92
1,15
0,68
1,46
0,99
0,79
1,19
0,82
0,92
1,87
0,70
1,69
1,33
1,93
1,40
0,76
1,01
0,95
1,76
0,94
3,06
3,57
2017
1,25
1,28
1,23
1,69
1,85
0,96
1,25
1,10
1,56
1,44
0,84
0,99
1,14
0,88
0,78
1,86
1,37
1,05
1,99
0,77
0,95
1,64
1,09
1,38
1,54
1,40
1,28
1,27
0,91
1,03
0,91
1,16
0,68
1,46
0,99
0,79
1,20
0,82
0,93
1,87
0,70
1,70
1,34
1,95
1,41
0,76
1,02
0,95
1,76
0,94
3,06
3,56
128
Índice sintético de emigración a otras prov
Provincia
Álava
Albacete
Alicante
Almería
Ávila
Badajoz
Balears
Barcelona
Burgos
Cáceres
Cádiz
Castellón
Ciudad Real
Córdoba
Coruña (A)
Cuenca
Girona
Granada
Guadalajara
Guipúzcoa
Huelva
Huesca
Jaén
León
Lleida
Rioja (La)
Lugo
Madrid
Málaga
Murcia
Navarra
Ourense
Asturias
Palencia
Palmas (Las)
Pontevedra
Salamanca
Tenerife
Cantabria
Segovia
Sevilla
Soria
Tarragona
Teruel
Toledo
Valencia
Valladolid
Vizcaya
Zamora
Zaragoza
Ceuta
Melilla
2007
1,47
1,73
1,37
1,90
2,70
1,19
1,60
1,29
1,67
1,63
0,95
1,46
1,49
1,07
0,88
2,71
1,75
1,27
2,99
0,90
1,18
1,94
1,48
1,52
1,99
1,64
1,26
1,53
1,09
1,32
1,05
1,56
0,90
1,66
1,36
0,96
1,56
1,11
1,13
2,65
0,74
2,29
1,82
3,01
2,23
1,03
1,33
1,07
1,87
1,17
2,91
3,40
2008
1,65
1,82
1,41
1,99
2,55
1,22
1,61
1,45
1,73
1,80
0,97
1,40
1,51
1,07
0,95
2,70
1,85
1,28
2,70
0,95
1,24
2,16
1,45
1,68
2,43
1,91
1,32
1,60
1,06
1,33
1,22
1,60
0,94
1,68
1,38
1,00
1,52
1,16
1,19
2,57
0,78
2,25
1,92
2,75
1,98
1,07
1,31
1,14
1,94
1,28
3,23
3,86
2009
1,59
1,70
1,39
1,93
2,22
1,12
1,61
1,45
1,71
1,76
0,94
1,29
1,36
1,00
0,94
2,33
1,78
1,22
2,40
0,86
1,21
2,11
1,27
1,77
1,96
1,89
1,32
1,61
1,06
1,30
1,20
1,42
0,96
1,65
1,27
0,98
1,40
1,12
1,1 9
2,40
0,78
2,07
1,7 9
2,35
1,73
1,03
1 ,20
1,10
1,95
1,23
3,2 2
3,87
2010
1,45
1,53
1,36
1,86
1,98
1,03
1,50
1,36
1,68
1,70
0,93
1,15
1,23
0,94
0,90
2,03
1,61
1,15
2,1 7
0,79
1,12
1,98
1,14
1,73
1,58
1,75
1,31
1,53
1,03
1,24
1,13
1,23
0,85
1,59
1,15
0,92
1,30
1,03
1,14
2,22
0,76
1,90
1,57
2,05
1,54
0,95
1,11
1,04
1,92
1,13
3,18
3,81
incias. Mujeres (2007
2011
1,34
1,40
1,33
1,81
1,87
0,97
1,40
1,28
1,65
1,64
0,89
1,06
1,16
0,91
0,86
1,89
1,48
1,10
2,05
0,77
1,05
1,86
1 ,09
1,60
1,48
1,62
1,30
1,45
0,99
1,18
1,06
1,15
0,75
1,54
1 ,06
0,87
1,24
0,95
1,05
2,09
0,74
1,79
1,42
1,93
1,44
0,88
1,05
0,99
1,88
1,04
3,15
3,75
2012
1,28
1,33
1 ,30
1,78
1,83
0,96
1,3 3
1,21
1,62
1,59
0,86
1,01
1,13
0,89
0,83
1,83
1,41
1,07
1,99
0,77
1,01
1,77
1,07
1,50
1,48
1,53
1,29
1,39
0,97
1,13
1,0 1
1,13
0,70
1,51
1,02
0,83
1,21
0,90
0,98
2,00
0,73
1,73
1,36
1,90
1,40
0,83
1,02
0,97
1,84
0,99
3,12
3,70
2013
1,26
1,29
1,28
1,74
1,81
0,95
1,29
1,17
1,60
1,55
0,85
0,99
1,12
0,88
0,81
1,81
1,37
1,05
1,97
0,76
0,98
1,72
1,07
1,44
1,49
1,48
1,29
1,35
0,95
1,09
0,97
1,13
0,68
1,49
0,99
0,81
1,19
0,86
0,95
1,94
0,72
1,70
1,33
1,90
1,38
0,80
1,01
0,96
1,82
0,96
3,10
3,66
2014
1,25
1,27
1,26
1,72
1,81
0,95
1,26
1,14
1,59
1,51
0,84
0,98
1,12
0,88
0,80
1,81
1,36
1,04
1,96
0,77
0,96
1,68
1,07
1,40
1,49
1,44
1,28
1,31
0,93
1,07
0,95
1,13
0,68
1,47
0,99
0,80
1,18
0,84
0,93
1,90
0,71
1,68
1,32
1,90
1,38
0,78
1,01
0,95
1,79
0,95
3,08
3,62
- 2017)
2015
1,24
1,27
1,24
1,70
1,82
0,95
1,25
1,12
1,57
1,48
0,84
0,98
1,12
0,87
0,79
1,82
1,35
1,04
1,96
0,77
0,95
1,65
1,07
1,39
1,51
1,42
1,28
1,29
0,92
1,05
0,93
1,14
0,68
1,47
0,98
0,79
1,18
0,83
0,92
1,88
0,70
1,68
1,32
1,92
1,39
0,77
1,01
0,95
1,78
0,94
3,07
3,59
2016
1,25
1,27
1,23
1,69
1,83
0,95
1,24
1,10
1,57
1,46
0,84
0,98
1,13
0,88
0,78
1,84
1,36
1,04
1,97
0,77
0,95
1,64
1,08
1,38
1,52
1,40
1,28
1,28
0,91
1,03
0,92
1,15
0,68
1,46
0,99
0,79
1,19
0,82
0,92
1,87
0,70
1,69
1,33
1,93
1,40
0,76
1,01
0,95
1,76
0,94
3,06
3,57
2017
1,25
1,28
1,23
1,69
1,85
0,96
1,25
1,10
1,56
1,44
0,84
0,99
1,14
0,88
0,78
1,86
1,37
1,05
1,99
0,77
0,95
1,64
1,09
1,38
1,54
1,40
1,28
1,27
0,91
1,03
0,91
1,16
0,68
1,46
0,99
0,79
1,20
0,82
0,93
1,87
0,70
1,70
1,34
1,95
1,41
0,76
1,02
0,95
1,76
0,94
3,06
3,56
The 1998-2017 series, observed, adjusted and projected of said indices in each one
of the provinces, is observed in the following graphs:
129
1.Alava
2. Albacete
1,800
2,000
1,600
1,800
1,600
1,400
1,400
1,200
1,200
1,000
1,000
0,800
0,800
0,600
0,600
0,400
0,400
0,200
0,200
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
3.Alicante/Alacant
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
4.Almería
1,600
2,500
1,400
2,000
1,200
1,000
1,500
0,800
1,000
0,600
0,400
0,500
0,200
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
5.Ávila
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
6.Badajoz
3,500
1,400
3,000
1,200
2,500
1,000
2,000
0,800
1,500
0,600
1,000
0,400
0,500
0,200
0,000
1986
1990
Hombres Real
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
130
7.Illes Balears
8.Barcelona
2,000
1,600
1,800
1,400
1,600
1,200
1,400
1,000
1,200
1,000
0,800
0,800
0,600
0,600
0,400
0,400
0,200
0,200
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
9. Burgos
2,000
1,800
1,800
1,600
1,600
1,400
1,400
1,200
1,200
1,000
1,000
0,800
0,800
0,600
0,600
0,400
0,400
0,200
0,200
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
10. Cáceres
2,000
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
11.Cádiz
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
12.Castellón/Castelló
1,200
1,600
1,400
1,000
1,200
0,800
1,000
0,600
0,800
0,600
0,400
0,400
0,200
0,200
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
131
13.Ciudad Real
14. Córdoba
1,600
1,200
1,400
1,000
1,200
0,800
1,000
0,800
0,600
0,600
0,400
0,400
0,200
0,200
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
15. A Coruña
1990
1994
Hombres Real
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
16. Cuenca
1,000
3,000
0,900
2,500
0,800
0,700
2,000
0,600
0,500
1,500
0,400
1,000
0,300
0,200
0,500
0,100
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
17. Girona
1990
1994
Hombres Real
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
18.Granada
2,000
1,400
1,800
1,200
1,600
1,000
1,400
1,200
0,800
1,000
0,600
0,800
0,600
0,400
0,400
0,200
0,200
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
132
19.Guadalajara
20.Guipúzcoa
3,500
1,000
0,900
3,000
0,800
2,500
0,700
0,600
2,000
0,500
1,500
0,400
0,300
1,000
0,200
0,500
0,100
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
21. Huelva
1990
1994
Hombres Real
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
22. Huesca
1,400
2,500
1,200
2,000
1,000
1,500
0,800
0,600
1,000
0,400
0,500
0,200
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
23. Jaén
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
24. León
1,600
2,000
1,800
1,400
1,600
1,200
1,400
1,000
1,200
0,800
1,000
0,800
0,600
0,600
0,400
0,400
0,200
0,200
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
133
25. Lleida
26. La Rioja
3,000
2,500
2,500
2,000
2,000
1,500
1,500
1,000
1,000
0,500
0,500
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
27. Lugo
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
28. Madrid
1,600
1,800
1,400
1,600
1,400
1,200
1,200
1,000
1,000
0,800
0,800
0,600
0,600
0,400
0,400
0,200
0,200
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
30. Murcia
29. Málaga
1,200
1,400
1,200
1,000
1,000
0,800
0,800
0,600
0,600
0,400
0,400
0,200
0,200
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
134
31. Navarra
32. Ourense
1,400
1,800
1,600
1,200
1,400
1,000
1,200
0,800
1,000
0,600
0,800
0,600
0,400
0,400
0,200
0,200
0,000
1986
1990
1994
Hombres Real
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
33. Asturias
1990
1994
Hombres Real
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
34. Palencia
1,200
2,000
1,800
1,000
1,600
1,400
0,800
1,200
0,600
1,000
0,800
0,400
0,600
0,400
0,200
0,200
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
35. Las Palmas
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
36. Pontevedra
1,600
1,200
1,400
1,000
1,200
0,800
1,000
0,800
0,600
0,600
0,400
0,400
0,200
0,200
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
135
37. Salamanca
38. Santa Cruz de Tenerife
1,800
1,400
1,600
1,200
1,400
1,000
1,200
1,000
0,800
0,800
0,600
0,600
0,400
0,400
0,200
0,200
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
39. Cantabria
1990
1994
Hombres Real
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
40. Segovia
1,400
3,000
1,200
2,500
1,000
2,000
0,800
1,500
0,600
1,000
0,400
0,500
0,200
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
41. Sevilla
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
42. Soria
0,900
3,000
0,800
2,500
0,700
0,600
2,000
0,500
1,500
0,400
0,300
1,000
0,200
0,500
0,100
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
136
43. Tarragona
44. Teruel
2,500
3,500
3,000
2,000
2,500
1,500
2,000
1,500
1,000
1,000
0,500
0,500
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
45. Toledo
1990
1994
Hombres Real
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
46. Valencia/València
2,500
1,200
1,000
2,000
0,800
1,500
0,600
1,000
0,400
0,500
0,200
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
47. Valladolid
1990
1994
Hombres Real
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
48. Vizcaya
1,600
1,200
1,400
1,000
1,200
0,800
1,000
0,800
0,600
0,600
0,400
0,400
0,200
0,200
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
137
49. Zamora
50. Zaragoza
2,500
1,400
1,200
2,000
1,000
1,500
0,800
0,600
1,000
0,400
0,500
0,200
0,000
1986
1990
Hombres Real
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
0,000
1986
Mujeres Modelo
1990
Hombres Real
51. Ceuta
1994
1998
2002
Hombres Modelo
2006
2010
Mujeres Real
2014
2018
Mujeres Modelo
52. Melilla
3,500
4,500
4,000
3,000
3,500
2,500
3,000
2,000
2,500
1,500
2,000
1,500
1,000
1,000
0,500
0,500
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
0,000
1986
1990
Hombres Real
1994
1998
Hombres Modelo
2002
2006
Mujeres Real
2010
2014
2018
Mujeres Modelo
138
2. The calendar of emigration of the rest of Spain for each sex from each province is
reached from the average observed in the years 2004-2007, and has remained
constant throughout the projection period, in view of the stability observed therein
during recent years.
Said calendar by age has been obtained through the following steps:
1) Calculation of the average flows of emigration to the rest of Spain from each
province, by sex and simple age of the years 2004-2007, observed in the
Residential Variation Statistics.
2) Smoothing of the flows obtained in point 1), according to a procedure of mobile
averages of five ages, except for ages 60-70 years old, where a smoothing of
mobile averages of three consecutive ages has been used, trying to avoid
random fluctuations thereof, and respecting certain systematic behaviours
observed around the age of retirement.
3) With the flows resulting from 2), we calculated rates of emigrations to the rest of
Spain for each province, using as a denominator therein, the Population NowCasts at 1 January 2006.
4) Smoothing of the rates obtained in point 3), according to a procedure of mobile
averages of five ages, except for ages 60-70 years old, where a smoothing of
mobile averages of three consecutive ages has been used, endeavouring to
avoid random fluctuations thereof, and respecting certain systematic behaviours
of the flows observed around the age of retirement.
5) These rates have been subjected to a new transformation, consistent with
maintaining constant the emigration rate of 85 years, from said age, given the
extreme variability presented by the same for the oldest ages.
6) Obtaining of the standardised calendar derived from the rates resulting from
point 5).
The following graphs show the projected provincial calendar of emigration to other
provinces, constant for each year of the projection period:
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Álava
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Albacete
Porcentajes
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Mujeres
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades sim ples
Edades simples
Varones
Porcentajes
5
Varones
Mujeres
139
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Alicante
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Almería
Porcentajes
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Edades simples
Varones
5
10
Mujeres
15
20
25
30
Varones
35
40
45
50
55
5
10
20
25
30
40
45
50
55
60
65
70
75
80
85
5
10
20
25
30
40
45
50
55
Mujeres
90
95
0
100+
90
95
Porcentajes
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Illes Balears
Porcentajes
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Burgos
Porcentajes
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades simples
Varones
85
3
Varones
35
80
4
Mujeres
15
75
Edades sim ples
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Barcelona
0
70
4
Edades simples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Ávila
Porcentajes
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Badajoz
0
50
Mujeres
Edades simples
Varones
45
Edades simples
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Asturias
0
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
140
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Cáceres
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Cádiz
Porcentajes
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Edades simples
Varones
5
10
Mujeres
15
20
25
30
Varones
35
40
45
50
55
45
5
10
20
25
30
40
45
50
55
75
80
85
90
95
60
65
70
75
80
85
90
95
Porcentajes
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Córdoba
Porcentajes
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
10
Varones
Mujeres
15
20
25
30
35
40
45
50
55
Mujeres
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Cuenca
Porcentajes
Porcentajes
5
5
4
4
3
3
2
2
1
1
60
65
70
75
80
85
90
95
100+
0
5
10
15
20
25
30
Edades sim ples
Varones
Mujeres
0
100+
Edades simples
0
5
0
100+
Edades simples
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Coruña (A)
0
0
100+
4
Edades simples
Varones
70
5
Varones
35
65
5
Mujeres
15
60
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Castellón
Porcentajes
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Ciudad Real
0
55
Mujeres
Edades sim ples
Varones
50
Edades simples
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Cantabria
0
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
141
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Girona
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Granada
Porcentajes
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Mujeres
Varones
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Guadalajara
0
5
10
15
20
25
30
35
40
45
50
55
5
10
20
25
30
40
45
50
55
60
65
70
75
80
85
5
10
20
25
30
40
45
50
55
Mujeres
90
95
0
100+
90
95
Porcentajes
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Huesca
Porcentajes
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100+
Edades sim ples
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
León
Porcentajes
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades simples
Varones
85
3
Varones
35
80
4
Mujeres
15
75
Edades simples
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Jaén
0
70
4
Edades simples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Guipúzcoa
Porcentajes
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Huelva
0
50
Mujeres
Edades sim ples
Varones
45
Edades sim ples
Edades simples
Varones
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
142
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Lleida
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Lugo
Porcentajes
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Mujeres
Varones
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Madrid
0
5
10
15
20
25
30
35
40
45
50
55
5
10
20
25
30
40
45
50
55
60
65
70
75
80
85
5
10
20
25
30
40
45
50
55
Mujeres
90
95
0
100+
90
95
Porcentajes
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Navarra
Porcentajes
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Palencia
Porcentajes
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades simples
Varones
85
3
Varones
35
80
4
Mujeres
15
75
Edades simples
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Ourense
0
70
4
Edades simples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Málaga
Porcentajes
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Murcia
0
50
Mujeres
Edades simples
Varones
45
Edades sim ples
Edades simples
Varones
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
143
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Palmas (Las)
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Pontevedra
Porcentajes
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Edades sim ples
Varones
5
10
Varones
Mujeres
15
20
25
30
35
40
45
50
55
50
55
60
65
70
75
80
85
90
95
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Salamanca
Porcentajes
75
80
85
90
95
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
Mujeres
Varones
Mujeres
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Segovia
Porcentajes
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100+
0
5
10
15
20
25
30
35
40
Edades sim ples
Varones
5
10
Varones
Mujeres
15
20
25
30
35
40
45
50
55
Mujeres
50
55
60
65
70
75
80
85
90
95
0
100+
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Soria
Porcentajes
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Edades simples
Varones
45
Edades simples
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Sevilla
0
0
100+
Edades simples
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Santa Cruz de Tenerife
0
0
100+
Mujeres
Edades simples
Varones
45
Edades simples
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Rioja (La)
0
Porcentajes
5
Varones
Mujeres
144
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Tarragona
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Teruel
Porcentajes
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
Edades sim ples
Varones
5
10
Mujeres
15
20
25
30
Varones
35
40
45
50
55
5
10
20
25
30
40
45
50
55
60
65
70
75
80
85
5
10
20
25
30
40
45
50
55
Mujeres
90
95
0
100+
90
95
Porcentajes
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Vizcaya
Porcentajes
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Zaragoza
Porcentajes
75
80
85
90
95
Mujeres
Porcentajes
5
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades sim ples
Edades simples
Varones
85
3
Varones
35
80
4
Mujeres
15
75
Edades sim ples
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Zamora
0
70
4
Edades simples
Varones
65
5
Varones
35
60
5
Mujeres
15
55
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Valencia
Porcentajes
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Valladolid
0
50
Mujeres
Edades simples
Varones
45
Edades sim ples
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Toledo
0
Porcentajes
5
Varones
Mujeres
145
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Ceuta
0
5
10
15
20
25
30
35
40
45
50
55
60
65
70
Calendario de la emigración al resto de provincias (españoles y extranjeros)
Melilla
Porcentajes
75
80
85
90
95
5
4
4
3
3
2
2
1
1
0
100+
0
5
10
15
20
25
30
Edades simples
Varones
Mujeres
Porcentajes
5
35
40
45
50
55
60
65
70
75
80
85
90
95
0
100+
Edades simples
Varones
Mujeres
3. The distribution coefficient of the specific rates, by sex and age of emigration to the
rest of Spain, by province of destination, has also been derived from the average
observed during the 2004-2007 period, and has remained constant for the entire
projection period.
Said coefficient has been obtained from a smoothing process of flows and specific
rates, by sex and age of interprovincial migration, analogous to that obtained from the
emigration calendar, from the results of the Residential Variation Statistics 2004-2007,
and of the Population Now-Casts, halfway through said period, at 1 January 2006.
146