Comparative Population Projections for France,Hungary and Slovakia Methods and resultats

Size: px
Start display at page:

Download "Comparative Population Projections for France,Hungary and Slovakia Methods and resultats"

Transcription

1 Direction des Statistiques Démographiques et Sociales F0504 Comparative Population Projections for France,Hungary and Slovakia Methods and resultats Isabelle ROBERT-BOBEE (Insee) et Jean-Paul SARDON (ODE), Laszlo HABLICZEK (NKI), Maria H. RICHTER (NKI), Ferenc KAMARAS (NKI), Danusa JURCOVA (VDC), Jan MESZAROS (VDC), Boris VANO (VDC) Document de travail

2 INSTITUT NATIONAL DE LA STATISTIQUE ET DES ÉTUDES ÉCONOMIQUES Série des Documents de Travail de la DIRECTION DES STATISTIQUES DÉMOGRAPHIQUES ET SOCIALES Département de la Démographie N F0504 Comparative Population Projections for France, Hungary and Slovakia Methods ands resultats Final report of the working group Isabelle ROBERT-BOBEE (Insee) et Jean-Paul SARDON (ODE), Laszlo HABLICZEK (NKI), Maria H. RICHTER (NKI), Ferenc KAMARAS (NKI), Danusa JURCOVA (VDC), Jan MESZAROS (VDC), Boris VANO (VDC) May 2005 Ces documents de travail ne reflètent pas la position de l'insee et n'engagent que leurs auteurs. Working papers do not reflect the position of INSEE but only their authors' views. 1

3 Comparative population projections for France, Hungary and Slovakia Methods and results Final report of the Working Group I. Robert-Bobée (Insee 1 ), J.P. Sardon (ODE 2 ), L. Habliczek (NKI 3 ), Maria H. Richter (NKI 3 ), F. Kamaras (NKI 3 ), D. Jurcova (VDC 4 ), J. Meszaros (VDC 4 ), B. Vano (VDC 4 ) Summary Hungary and Slovakia entered the EU-25 in May This important change was an opportunity to work together with "old" EU member states, including on population projections. A working group operated from August 2002 to July The aim was to analyse potential changes in the demographic situation in two "new" EU member states in comparison to an existing member state. The present document analyses past trends in fertility, mortality and migrations in the three countries; it presents the way population projections are modelled and the assumptions investigated. The report ends with a comparative analysis of future trends in the three countries, including extensive comments on population ageing, which is a common issue for France, Hungary and Slovakia. Key words: population projections, fertility, mortality, migrations, past trends, future trends, new EU member states Résumé La France, la Hongrie et la Slovaquie ont entrepris un travail commun sur les projections de population, à l'occasion de l'entrée dans l'union Européenne de la Hongrie et la Slovaquie (mai 2004). Un groupe de travail a été mis en place et cinq rencontres ont été organisées. Le présent document présente les tendances passées dans les trois pays en termes de fécondité, mortalité et migrations, la méthode retenue pour élaborer les projections de population et les hypothèses retenues, ainsi que les tendances futures ainsi projetées. Les trois pays sont confrontés à un vieillissement inéluctable, du fait de l'avancée en âge de générations nombreuses, et ce phénomène est plus ou moins marqué cependant selon les pays. Mots-clés: projections de population, fécondité, mortalité, migrations, tendances passées, tendances projetées, nouveaux pays membres de l'union européenne 1 Insee, timbre 170, 18 bld Adolphe Pinard Paris cedex 14, dg75-f170@insee.fr, isabelle.robertbobee@insee.fr 2 European Demographic Observatory (Observatoire Démographique Européen), 2 bis rue du Prieuré Saint-Germain-en-Laye cedex, odeurope@wanadoo.fr 3 Demographic Research Center, Hungary, KSH Népességtudományi Kutató Intézet 1149 Budapest, Angol utca 77., kshnki@mailop.ksh.hu, lhabli@mailop.ksh.hu, maria.richter@office.ksh.hu 4 Demographic Research Center, INFOSTAT, Dubravska cesta 3, Bratislava, Slovakia, vdc@infostat.sk; vano@infostat.sk, jurcova@infostat.sk, meszaros@infostat.sk

4 Contents Introduction... 4 Section 1: Past trends in fertility, mortality and migration in France, Hungary and the Slovak Republic Past fertility trends in France, Hungary and the Slovak Republic Total Period Fertility Rates and Total Cohort Fertility Rates Mean age at childbearing Age-specific fertility rates Fertility patterns Past mortality trends in France, Hungary and Slovakia Methods and data sources Decreasing mortality at young ages The opposite trends in working age groups The growing gap at old ages Life expectancies Conclusion Past migration trends in France, Hungary and the Slovak Republic Net migration in France Net migration in Hungary and Slovakia Section 2: Population projections: methods, assumptions and scenarios The standard component method The method Computation Assumptions Baseline assumptions for France Assumptions for Hungary and Slovakia The 8 scenarios for Hungary and Slovakia Indexes used Period analysis, for year Y Cohort analysis, for birth cohort C Ageing index and index of economic burden Section 3: Results Comparative results: population, births, and deaths Population Births Deaths Ageing issues Age structure in 2003: comparative analysis Changes in the age structure of population List of abbreviations Appendix 1: List of participants in the meetings on population projections Appendix 2: SAS code for the computation of population projections

5 Introduction Hungary and Slovakia entered the European Union in May Various projects of cooperation on demographic topics between France, Hungary and Slovakia were planned in this perspective, including comparisons of population projections in the three countries. The preliminary meeting took place in February 2002 in Paris. The French-Hungarian-Slovak Working Group on Population Projections first met in 2002 in Bratislava. Five meetings were organised from 2002 to (See appendix 1 for the list of participants and a brief summary of contents. 5 ) The aim of the Working Group on Population Projections is to compare the situation in France (an "old" member of the European Union) with the situation in Hungary and Slovakia (countries in transition, and "new" EU member states). It was decided to use only one scenario for France (the baseline scenario) and a set of scenarios for Hungary and Slovakia. The group investigated future demographic trends using 8 scenarios combining 2 assumptions for fertility, 2 assumptions for mortality and 2 assumptions for migration trends. Two of the 8 scenarios may be further analysed: the so-called "convergent" scenario and the "semi-convergent" scenario. In the "convergent scenario" (assuming fertility patterns similar to France, mortality a little lower than in France, and higher future migration in Hungary and Slovakia), the differences between France and the new member states narrow faster. By contrast, in the "semi-convergent" scenario (levels for fertility and life expectancy at birth increase but remain below the French level), the differences decrease more slowly. The main goal of the working group was to analyse the relationship between old and new EU member states as a function of the pace of demographic convergence of the new EU member states. The working group then examined assumptions for trends in Hungary and the Slovak Republic regarding mortality ("optimistic" / "pessimistic"), fertility ("convergent" / "non convergent"), and migration (two assumptions). This reports sets out the conclusions of the Working Group on Population Projections. It is divided into three main sections. Section 1 presents a comparative analysis of past trends in fertility, mortality and migrations. Section 2 details the way the projections were done. It presents the method and the baseline scenario adopted for France; details on the assumptions on fertility, mortality and migrations for Hungary and Slovakia; and the resulting scenarios investigated to analyse future demographic trends. Section 3 analyses future demographic trends for the three countries, using the eight scenarios for Hungary and Slovakia, and the baseline scenario for France. This includes analyses of the number of inhabitants, the number of births and deaths, and focus on ageing issues. 5 See the following Insee notes for details (F=in French only, F/E=French and English): 2002: No. 100/F170/FC (F) 2003: No. 009/F170 (F), No. 049/F170 (F/E) 2004: No. 011/F170 (F/E), No. 042/F170 (F/E), No. 042b/F170 (F/E) 4

6 Section 1: Past trends in fertility, mortality and migration in France, Hungary and the Slovak Republic 1.1. Past fertility trends in France, Hungary and the Slovak Republic Total Period Fertility Rates and Total Cohort Fertility Rates France France experienced a strong sustained post-war baby boom from 1946 through the mid-1960s, when Total Period Fertility Rates (TPFRs) were between 2.5 and 3.0 births per woman (Figure 1). This was followed by a pronounced fertility decline into the mid-1970s. Nevertheless, during the second half of the 20th century, France ranked among the Western countries with relatively high fertility. France's period fertility fell below replacement only in 1974, but never became very low. In 1976, the TPFR was 1.8, and throughout the last quarter of the century fluctuated between 1.7 and 1.9. From 1994 through, the TPFR exhibited a positive slope, increasing from 1.7 to 1.9 births per woman. Completed fertility rose to a peak of 2.6 births per woman with the cohorts born around 1930 (Figure 2). The total cohort fertility rate (TCFR) declined between the 1929 birth cohort and the 1948 birth cohort from 2.6 to 2.1, and has remained at that level through the 1960 birth cohort. Hungary Unlike other European countries, Hungary did not experience a baby boom or increase in fertility. The fertility peak of was caused by strict enforcement of an 1878 law that criminalised abortion (Figure 1). Enforcement was relaxed in 1955 and fertility reverted to the previous trend in 1956, when induced abortion legislation was liberalised. This shift between two opposite situations caused a rapid fertility decline. Between 1953 and 1962, the TPFR declined by 40 percent, from 3.0 to 1.8 births per woman. Subsequently, from 1962 to 1992, period fertility was stable within a range of moderately below-replacement fertility, with a TPFR between 1.8 to 2.1 births per woman. There was a four-year exception in the mid-1970s when as a consequence of implementing an array of pronatalist population policy measures with simultaneous restriction on legal induced abortions total fertility rose above replacement, with a peak value of 2.4 in 1975 (Figure 1). The 1990s, with the transition to the market economy, witnessed a rapid fertility decline. The TPFR declined from 1.9 in 1991 to 1.3 in 1998, a drop of almost 30 percent within seven years. Since then, the level has stabilised around 1.3. In contrast to the fluctuating trend of the TPFR, the trend of the total cohort fertility rate (TCFR) was significantly smooth and almost horizontal (Figure 3). Cohorts born before 1930 exhibited a gradual fertility decline and the birth cohorts of the 1930s, 1940s and 1950s were within a narrow range, as all had TCFRs between 1.9 and 2.1 births per woman. Our estimates indicate that completed fertility of the cohorts born after 1960 displays a moderately declining trend. The 1967 and 1968 birth cohorts were estimated to have TCFRs around 1.9 births per woman. The Slovak Republic Slovak fertility was among the highest in Europe throughout the 20th century. Indeed, the demographic transition occurred later in Slovakia than in neighbouring countries and ended in the mid- 1930s. 5

7 In the middle of the century the total period fertility rate (TPFR) was around 3.5 births per woman. It then declined quite steadily, though with some irregularities, and reached replacement level only around 1990 (Figure 1). The fertility decline accelerated in the 1990s and by the TPFR came to 1.29 with a net reproduction rate of The irregularities in the fertility trend from the 1950s through the 1980s were in part influenced by Czechoslovakian government policy measures (preferential development of primary industries, promotion of female employment, pronatalist social policies, and liberalization of abortion legislation interspersed with occasional restrictions). Slovakia's total cohort fertility rates (TCFRs) for the generations born around 1930 were higher than in practically all other European countries, including the former Eastern bloc, at almost 2.9 births per woman (Figure 4). Thereafter cohort fertility declined from one generation to the next and our estimates indicate that the generations born in the late-1960s will have TCFRs around 1.9 births per woman. Comparative perspective Since the last world war, and especially since mid-1970, differences in fertility levels in the three countries had diminished rapidly. At the beginning of the 1990s TPFRs were very close. Then, in the 1990s, the trends diverged: in both Hungary and Slovakia, the transition towards a market economy was associated with a deep decrease in TPFR, while TPFR was increasing in France. The gap between France on the one hand, and Hungary and the Slovak Republic on the other, then increased rapidly. This situation is doubtless a transitional one. It is therefore reasonable to analyse a projection scenario under which Hungary and the Slovak Republic could return to fertility levels close to the level observed in France. Nevertheless, one of the main difficulties is foreseeing when the convergence will occur Mean age at childbearing Past trends in the mean age at childbearing show that the three countries have moved in the same direction but on different paths (Figure 5). The mean age had been declining continuously since before 1950 in all three countries; the trend has reversed and the mean age is now increasing rapidly. The lowest mean age, before the trend reversed, occurred in the mid-1970s in France, at the turn of the 1970s in Hungary, and at the very beginning of the 1990s in Slovak Republic. After the trend reversed, developments were similar in all three countries, until the most recent years. The mean age seemed to stabilize around in France, whereas it continued to increase rapidly in the Slovak Republic and Hungary. Today, the gap between France and the other two countries is around two years (Figure 5). Another way of summarizing and comparing fertility trends in the three countries is to analyse the relationship between TPFRs and mean age at childbearing. This makes it possible to determine and date different phases in fertility trends and see that there is no linear relationship between the two indexes (Figures 6-8). In France, three general phases can be identified (Figure 6). Until the mid-1960s, mean age decreased without important changes in TPFR. Then, for a decade, TPFR registered a deep decline while mean age decreased only slightly. With the end of the 1970s, a new stage occurs, with a rapid increase in the mean age at childbearing and a degree of stabilisation of the TPFR. For Hungary (Figure 7), the picture is different but relatively close to the Slovak Republic (Figure 8), if we do not take into account the specific situation of the 1970s and 1980s in Hungary. To simplify, since the beginning of the 1980s, fertility development showed three phases, with a continuous increase in the mean age at childbearing. During the first stage, until 1991, the increase in mean age occurred without any change in TPFR. Then, between 1991 and 1999, the mean age at childbearing increased and the TPFR decreased. Since 1999, a new stage has begun with a another stabilisation in the TPFR. In the Slovak Republic, fertility development is still in what we called the second stage for Hungary, i.e., a decrease in TPFR associated with an increase in mean age at childbearing. Nevertheless, considering the past two years, TPFR seems on the way to stabilisation. 6

8 Age-specific fertility rates Analysis of age-specific fertility rates reveals that the end of 1970s was a turning point in France (Figure 9). At that time, fertility rates at older ages (above 28) stopped decreasing and began a continuous rebound, which is interpreted as the sign of the recovery of births postponed when women were at younger ages. In an initial stage, fertility at younger ages continued to decline until the end of the 1990s. The subsequent trend is not very clear, but fertility rates at all ages appear to be stabilizing. Developments in both Hungary and Slovakia were quite different from France. The difference was more pronounced in the Slovak Republic, where fertility at younger ages was quite stable (after factoring-out the impact of changes in population policy), while above-25 age-specific fertility rates were declining since the end of the second world war (Figure 11). In the Slovak Republic at that time, there was a rejuvenation of fertility, with a decline at older ages, as a consequence of the disappearance of high parity births. But in the 1990s, with the transition to the market economy, fertility at younger ages declined sharply, while at older ages fertility rates continued to decline at the previous pace. A few years later, in the second half of the 1990s, fertility after age 28 increased slightly. In Hungary (Figure 10), the situation is somewhat between the other two countries, as the trend in age-specific fertility rates resembled the trend in France, but the transition to a market economy was associated with a strong decline in fertility at ages which were traditionally those of maximum fertility (21-27). This temporary deficit was compensated somewhat by an increase in fertility at older ages (29 and over) at the very end of the 1990s Fertility patterns All these changes in age-specific fertility rates have affected fertility patterns over time. In France, two stages can be distinguished (Figure 12). The first is characterised by a decline of fertility at older ages without any changes before 22, and a decrease of the highest rates. In the 1970s, fertility at younger ages also declined and, since 1980, fertility has shifted to older ages, with the curves crossing over after Then, in the early to mid-1990s, the shift towards older ages changes somewhat (Figure 15). At younger ages fertility seems stabilized but age-specific rates continue to increase at older ages, with a shift of maximum fertility towards ever older ages. In Hungary, the changes are relatively close to those observed in France. Nevertheless, the starting point of the evolution came later and the shift of the fertility pattern toward older ages was preceded by a temporary rejuvenation (Figure 13). The decrease of fertility at younger ages starts around the late 1980s. During the 1990s, there is a very pronounced change in fertility patterns. The fertility of younger women declined very rapidly, but there was no major increase of fertility over 30 (Figure 16). In the Slovak Republic, the fertility pattern was very stable until the early 1990s (Figure 14). Declines of age-specific fertility rates are quite homothetic over ages. The shape stays the same; only the level decreases. It is only during the 1990s that teenage fertility begins to decrease, but at the time the age of maximum fertility shifts from age 22 to 26 (Figure 17). At 22, age-specific rates were divided by nearly 4 between 1990 and Fertility after age 30 begins to increase in 2002, and after age 30 the fertility curves cross those of preceding years. Nevertheless, the 2002 curve remains inside the limits of the 1990s curve. Comparison of fertility developments in the three countries accordingly shows a time lag between countries. France can be seen as a precursor and Hungary and the Slovak Republic are only at the very beginning of the second stage of the post-transitional fertility evolution, that is, the "catching up" of postponed fertility after age 30, even if the process began slightly earlier in Hungary than in the Slovak Republic. While fertility trends are moving in the same direction in all three countries, there is a gap between France and the two others. In France, childbearing occurs at much older ages and is more concentrated, whereas the other countries have seen more drastic changes, especially during the economic transition in the early 1990s. 7

9 The challenge for the future is predicting whether the current differences will disappear, as the accession countries converge with the European Union overall, or if demographic differences reflect cultural differences and a not temporary gap in the timing of a common trend. In the latter case, differences between countries could continue, at least for age at childbearing, even if fertility levels converge. 8

10 Figure 1. France, Hungary and Slovak Republic. Total period fertility rate, Average no. of children per woman SLOVAK REPUBLIC ODE HUNGARY 200 FRANCE Year of observation for TFR Figure 2. Total period fertility rate, France, , and total cohort fertility rate in French birth cohorts lagged by the average age at childbearing ODE Average no. of children per woman Year 1950 Total period fertility rate Cohort 1930 Year 1970 Total cohort fertility rate 250 Cohort 1940 Cohort Year Year of observation for TFR NOTE: Dotted lines indicate that a minor proportion of the respective TCFRs is based on estimates 9

11 Figure 3. Total period fertility rate, Hungary, , and total cohort fertility rate in Hungarian birth cohorts lagged by the average age at childbearing ODE Average no. of children per woman Year Total period fertility rate Total cohort fertility rate 250 Cohort 1940 Year 1970 Cohort Cohort Year Year of observation for TFR NOTE: Dotted lines indicate that a minor proportion of the respective TCFRs is based on estimates Figure 4. Total period fertility rate, Slovak Republic, , and total cohort fertility rate in Slovak birth cohorts lagged by the average age at childbearing ODE Average no. of children per woman Year 1950 Cohort 1930 Total period fertility rate Year Cohort Total cohort fertility rate Cohort 1960 Year Year of observation for TFR NOTE: Dotted lines indicate that a minor proportion of the respective TCFRs is based on estimates 10

12 Figure 5. France, Hungary and Slovak Republic. Mean age of women at childbearing, ODE Mean age (years) FRANCE SLOVAK REPUBLIC HUNGARY Year of observation Figure 6. France, , correlation between entre : - total period fertility rate - period mean age at childbirth 30 ODE Mean age at childbirth (years) Average number of children per woman 11

13 Figure 7. Hungary, , correlation between entre : - total period fertility rate - period mean age at childbirth 30 ODE Mean age at childbirth (years) Average number of children per woman Figure 8. Slovak Republic, , correlation between entre : - total period fertility rate - period mean age at childbirth 30 ODE Mean age at childbirth (years) Average number of children per woman 12

14 Figure 9. France, Age-specific fertility rate at the same age (Rate by age reached during the calendar year of the birth) Left-hand side : Ages 17-26, right-hand side : Ages ODE 22 ODE 22 Fertility rate (number of live births per 100 females at the same age) de 17 à 26 ans de 27 à 42 ans Observation years Observation years Figure 10. Hungary, Age-specific fertility rate at the same age (Rate by age reached during the calendar year of the birth) Left-hand side : Ages 16-24, right-hand side : Ages ODE 21 ODE 21 Fertility rate (number of live births per 100 females at the same age) de 16 à 24 ans de 25 à 42 ans Observation years Observation years 13

15 Figure 11. Slovak Republic, Age-specific fertility rate at the same age (Rate by age reached during the calendar year of the birth) Left-hand side : Ages 17-24, right-hand side : Ages ODE ODE Fertility rate (number of live births per 100 females at the same age) de 17 à 24 ans de 25 à 42 ans Observation years Observation years Figure 12. France. Age-specific fertility rates, years of observation 1950, 1960, 1970, 1980 and 1990 ODE Age-specific fertility rate Age 14

16 Figure 13. Hungary. Age-specific fertility rates, years of observation 1950, 1960, 1970, 1980 and 1990 Age-specific fertility rate ODE Age Figure 14. Slovak Republic. Age-specific fertility rates, years of observation 1950, 1960, 1970, 1980 and 1990 ODE Age-specific fertility rate Age 15

17 Figure 15. France. Age-specific fertility rates, years of observation 1990, 1994, 1998 and 2002 Age-specific fertility rate ODE Age Figure 16. Hungary. Age-specific fertility rates, years of observation 1990, 1994, 1998 and 2002 Age-specific fertility rate ODE Age 16

18 Figure 17. Slovak Republic. Age-specific fertility rates, years of observation 1990, 1994, 1998 and 2002 ODE Age-specific fertility rate Age Data source: ODE 17

19 1.2. Past mortality trends in France, Hungary and Slovakia Mortality is a component of population change, along with fertility, migration and ageing. All individuals die, but populations show very different death rates. Longer or shorter life expectancies, and older or younger age structures, influence the number and rate of deaths. In order to apply the cohort component method (see section 2.1), forecasts of mortality by age and sex are necessary. Therefore, the analysis of past trends here focuses on sex and age specific mortality Methods and data sources The cohort component method requires detailed information on mortality. Yearly deaths from each cohort can be estimated using age-specific and sex-specific probabilities or mortality rates. The use of mortality in population projections requires the life table approach; mortality assumptions are usually based on life table characteristics. The probability of dying at age x denoted by q x is estimated from the observed death frequencies using specific adjustments to the data and procedures for smoothing. The probability of survival at age x, denoted by p x, is the complementary value of q x : px = 1 q x. The survival function l x shows how many infants born would survive until exact age x, if a birth cohort were to die in keeping with those probabilities of dying at each age. The survival function l x is computed using the recursive function: (1) l x+ = l x ( 1 q x ) = l x px 1. The stationary population Lx shows the average number of survivors between exact ages x and x+1. The life expectancy function then shows the average life duration the cohort has after survival to age x. Life expectancy at birth is determined by the equation 0 ω x= 0 x x= 1 (2) e0 = , l l 0 L x ω 0 l while the formula for life expectancy at age x is the following: 0 ω y = x y y = x+ 1 (3) ex = , l l x L y where ω is the upper limit of human life. ω x l The usual probabilities of dying show the probabilities of dying between exact ages (from birthday to birthday). However, population projections need probabilities from beginning of year to end of year for each cohort. Therefore the "perspective probabilities" are determined: (4) Q B L = 1 0 for deaths of infants under one year and Q l 0 x Lx+ 1 = 1 for other cohorts. L There are some easy transformation methods between "simple" probabilities and "perspective" probabilities. In this chapter we use the classical birthday-to-birthday approach. The data were provided by the European Demographic Observatory (ODE) in the form of the probabilities of dying. The ODE database was used instead of national sources because of its consistent methodology, systematically corrected figures, and complete time series. For each country we have the set of probabilities of dying: { : x = 0,...,99; t = 1950,...,2001} is the age and t is the time. The survival function was estimated using Equation (1). q t x x, where x 18

20 On the basis of the survival function, the probability of dying in age intervals can be computed. The general formula for the probability of dying between exact ages x and y denoted by q is: (5) x+ ( y x) y x q x = 1 = 1 l x l l l y x. According to (5), probabilities of dying for ages 0, 1-9, 10-19, 20-29,, 70-79, were computed. Applying the approximation in (2) and (3) we estimated life expectancy at birth and at age 60. Finally, using (5), the probability of survival to age 60 was estimated: (6) l p = q = l 0 Figures present the time series of death probabilities separately for males and females. Figure 28 shows life expectancy at birth, and Figure 29 shows life expectancy at age 60. Figure 30 presents the survival probabilities until age 60. Using the same scale for male and female series, one can easily compare the differences by sex. y x x Decreasing mortality at young ages Figure presents the probabilities of dying in the young age groups: for infants under one and for the 1-9, 10-19, and age groups. The general trend in the last 50 years has been a decline, as fewer people in these age groups die. The probability of dying for infants under one year of age is relatively high compared to the probability of dying at subsequent ages because of the dangers to which infants are exposed after birth. However, fundamental developments in health and services for mother and child have reduced those probabilities substantially, reducing the death probabilities to a very low level in all three countries. The recent q0 is only 5-6 percent of its 1950 value in Slovakia, 8-9 percent in France and 9-10 percent in Hungary. Differences among the countries have decreased very much in absolute terms, but remain more or less stable in relative terms. The French probabilities were almost half the Hungarian and Slovakian values between 1950 and The trend has been broadly parallel in France and Hungary. In Slovakia, there was a rapid decrease until the 1960s, followed by stagnation until the 1980s. The current levels for infants under one year are very close to the probabilities in age interval 1-9 (whereas they were far higher before), which is also a sign of radical improvement (Figure 18). Figure 18 Probability of dying, under 1 year of age, Males Females 0,14 0,14 0,12 0,10 0,08 0,06 0,04 0,02 0, France Hungary Slovakia 0,12 0,10 0,08 0,06 0,04 0,02 0, France Hungary Slovakia 19

21 Deaths of children over one and under 10 years of age have also decreased very significantly in all three countries. The decline was slower, however, than in the case of infants under one. Unlike France and Slovakia, in Hungary the decrease in the probability of dying between ages 1 and 10 is greater than for children under age one. The French probabilities for the 1-9 age group have decreased to about 13 percent of their 1950 values. Slovakian probabilities have fallen to 9 percent of the 1950 level for females and 17 percent for males. In general, the development of child care, and implementation of child-friendly institutions, such as maternity leave and kindergartens, may have contributed to the trend (Figure 19). Figure 19 Probability of dying, 1-9 age group, Males 0,030 0,025 0,020 0,015 0,010 0,005 0,000 France Hungary Slovakia ,030 0,025 0,020 0,015 0,010 0,005 0,000 Females France Hungary Slovakia Probabilities of dying in the age group (Figure 20) also show a declining trend, but there are different stages of development. In the first period, until the 1960s, the probabilities fell sharply, to almost half the previous level, in Hungary and Slovakia. An exception came in Hungary, where the one-year peak in 1956 is obviously related to Hungary's October Revolution. The next two decades saw a slight decrease in Hungary and Slovakia, but a remarkable increase in France. Greater use of motor vehicles, and "lifestyle" factors such as smoking, alcohol use and drug consumption might explain this stagnation period. The increasing appearance of social differences regarding living conditions for children under age 10 might play a role. Over the past two decades, a step-by-step improvement and convergence among the three countries can be observed. Figure 20: Probability of dying, age group, Males Females 0,018 0,018 0,016 0,014 0,012 France Hungary Slovakia 0,016 0,014 0,012 France Hungary Slovakia 0,010 0,008 0,006 0,004 0,002 0, ,010 0,008 0,006 0,004 0,002 0,

22 The same trends, and possibly the same underlying causes, appear in the age group (Figure 21), though with some exceptions and peculiarities. The stagnation period between 1960 and 1990 is much more pronounced and appears to be longer with the age group than with the age group. The decrease in the probability of dying is remarkable for all three countries in the last decade, leading to nearly the same probabilities as nowadays. However, Slovakia shows a declining trend since the 1970s, while death probabilities in Hungary had a slightly increasing trend between 1970 and 1990, especially for males. This latter observation may be connected to the regressive trend in mortality that developed in Hungary at that time. Figure 21: Probability of dying, age group, Males 0,035 0,030 0,025 0,020 0,015 0,010 0,005 0,000 France Hungary Slovakia ,035 0,030 0,025 0,020 0,015 0,010 0,005 0, The opposite trends in working age groups Females France Hungary Slovakia In the working-age groups, or more specifically between ages 30 and 70, the trends in the three countries can be divided into three different periods. Until the second half of the 1960s, mortality developed in parallel and the probabilities were close to each other in these age groups. In the second period, in the 1970s and 1980s, the countries showed differing trends. Probabilities of dying decreased very significantly in France, but rose in Slovakia and especially in Hungary, primarily among males. It can be said that a regressive trend in mortality developed in Hungary and, to a certain extent, in Slovakia. The third period can be defined since the early 1990s. The previous decline continued in France, and the death probabilities in Hungary and Slovakia also started to decrease from their peak values. However, there are too few observations for this latest period to determine whether differences will disappear step-by-step or whether there will be parallel development in the countries, as they keep the recent distances for a longer time. Figures show the time series for the three countries by sex. What is behind these large differences between France on the one hand, and Hungary and Slovakia, on the other? Various approaches can be used in an attempt to answer the question. In general, one can attribute the upturn in mortality to the unsuccessful development of Hungary and Slovakia in the communist era. Another approach would be to differentiate the causes of the increase in the probability of dying in the two countries from the causes that led to a decrease in the probabilities of dying in France. The most developed countries have entered a new stage of the epidemiological transition. Four transitions can be identified in human history up to now. The first transition saw success in the struggle against infectious diseases; and in the second transition infectious diseases have been forced back. Dealing with "degenerative" diseases characterizes the third transition. A new transition period started in the 1970s. With improvements in health care, prevention and life-style changes, the probability of survival improved further. Without radical changes in the medical causes of death, people started to live longer and healthier lives, postponing the ageing of their organism to very old ages. The results of this new transition period can be summarized in the case of France as follows. The probability of dying among males aged 30-39, 40-49, and decreased by 34, 29, 36, and 21

23 40 percent, respectively, since the 1970s. The decrease among females is more pronounced: 39, 36, 43, and 48 percent in the same age groups. From this point of view, the increased differences between France on the one hand, and Hungary and Slovakia on the other, is due to the fact that the latter countries remained in the third epidemiological transition period. The structure of medical causes of death is nearly the same; the leading cause of death is cardiovascular disease, followed by neoplasms and accidents, but the evolution and progress of diseases are different. These occur much later and progress more slowly in France than in Hungary and Slovakia. General development issues, namely the basic problems in Hungary and Slovakia under the former regime, may have aggravated the differences. The ever wider gap between aspirations and possibilities were thought to have contributed to overwork and poor life-style habits including smoking and alcoholism, poor nutrition, lack of exercise, and stress. These may have contributed to the specific regressive trend in mortality, especially in Hungary. Compared to the values in 1970, the probabilities of dying increased in the Hungarian male population by 64, 73, 59 and 13 percent in the 30-39, 40-49, and age groups, respectively. An increase is the main tendency for Slovakian males, though to a lesser extent than in Hungary: 36 percent in the age group, 42 percent in the age group, and 14 percent in the age group. Concerning females, there is a clear tendency towards an increased probability of dying in Hungary in the age group, and stagnation among women aged However, the extent of the increase is much lower than for males. In Slovakia, death probabilities among women aged were practically unchanged between 1970 and 1990, while there was a slight decrease in the and age groups. Because of their different development paths, the gap between France on the one hand, and Hungary and Slovakia on the other, increased to a very significant extent. For extreme values, consider the relative difference in the probabilities of dying between Hungarian and French males in The Hungarian values were higher than the French values by 84, 114, 98 and 72 percent in the 30-39, 40-49, and age groups, respectively (Figures 22-25). Figure 22 Probability of dying, age group, Males Females 0,050 0,050 0,045 0,040 0,035 0,030 0,025 0,020 0,015 0,010 0,005 0,000 France Hungary Slovakia ,045 0,040 0,035 0,030 0,025 0,020 0,015 0,010 0,005 0, France Hungary Slovakia 22

24 Figure 23 Probability of dying, age group, Males 0,12 0,10 0,08 0,06 0,04 0,02 0,00 France Hungary Slovakia ,12 0,10 0,08 0,06 0,04 0,02 0,00 Figure 24 Probability of dying, age group, Males 0,25 0,20 0,15 0,10 0,05 0,00 France Hungary Slovakia ,25 0,20 0,15 0,10 0,05 0,00 Females Females France Hungary Slovakia France Hungary Slovakia 23

25 Figure 25: Probability of dying, age group, Males 0,40 0,40 0,35 0,35 0,30 0,30 0,25 0,25 0,20 0,20 0,15 France 0,15 0,10 Hungary Slovakia 0,10 0,05 0,05 0,00 0, Females France Hungary Slovakia An interesting point requiring further study is that the differences seem to be even higher for females than for males. The corresponding percentages in Hungary are 89, 107, 106, 116, though the absolute level is much lower than for males. The situation is similar in Slovakia. In the early 1990s, the regressive trends began to turn around in both Hungary and Slovakia. The increase in mortality in the relevant age groups ended and a definite decrease can be observed. Between 1990 and 2001, the death probabilities among Hungarian males decreased to 61, 93, 89 and 89 percent in the 30-39, 40-49, and age groups, respectively. The decrease is nearly the same in the female population. In Slovakia, the corresponding percentages are 72, 72, 79, 88 for males, and somewhat higher for females. The curves indicate parallel development rather than convergence. However, the period is too short to draw any firm conclusion The growing gap at old ages Old age mortality (defined as mortality in the and age groups) has nearly the same tendency in all three countries. The trends show essentially a decline in mortality in these age groups, especially for women. But there is a growing gap between France on the one hand, and Hungary and Slovakia on the other. As an exception, we must note a period of an increase in the probabilities of dying in Hungary and a period of stagnation in Slovakia between 1970 and 1990 in the male population aged (Figure 26). 24

26 Figure 26 Probability of dying, age group, Males 0,7 0,7 Females 0,6 0,5 0,4 0,6 0,5 0,4 0,3 0,2 0,1 0, France Hungary Slovakia Figure 27 Probability of dying, age group, Males 1,0 0,3 0,2 0,1 0,0 1, France Hungary Slovakia Females ,9 0,8 0,9 0,8 0,7 0,6 0,5 0, France Hungary Slovakia ,7 0,6 0,5 0, France Hungary Slovakia The increase in differences between countries is very significant. In 1970, the relative difference between the probabilities of dying in France and Hungary was 18 percent among males aged 70-79, and 33 percent among females aged The corresponding values in 2001 were 51 and 98 percent. In the age group, the differences were 6 and 16 percent in 1970, and 16 and 35 percent in 2001, for males and females, respectively. In Slovakia, the tendencies and the size of the differences are nearly the same as in Hungary, because the probabilities of dying are nearly the same, especially in the most recent years. In seeking possible causes behind these tendencies, one may point to the same problems of development as those mentioned in the case of the working ages. Stagnation in health care and in general development resulted in a far more limited reduction in mortality in Hungary and Slovakia than in France. An additional element should also be mentioned. The declared full employment and early retirement ages in Hungary and Slovakia led to a worsening situation among pensioners, especially after the regime change. The number and share of pensioners started to be too high. Further, the collapse of the economy in the early 1990s pushed millions of people in working ages into finding low but secure income under the social security system, first of all with early pensions or disability pensions. As a result, a very large portion of the population are currently receiving pension-type benefit; in Hungary, this is the case of almost one third of the population. It is obvious that for such a huge portion of the population, only a relatively low level of benefit can be guaranteed, taking into consideration the low level of employment as well. These factors all led to a situation where elderly 25

27 people are less able to cope with the challenges of old age in Hungary and Slovakia than their counterparts in France. Even assuming favourable development of the new EU member states in the future, a longer period may be necessary before one observes clear convergence between the countries in old age mortality Life expectancies Figure 28 Life expectancy at birth, Males 90,0 85,0 France 80,0 Hungary Slovakia 75,0 70,0 65,0 60,0 55,0 50, ,0 85,0 80,0 75,0 70,0 65,0 60,0 55,0 50,0 Females France Hungary Slovakia 1995 The evolution of life expectancy at birth clearly summarizes the age-specific mortality trends described above. Starting with a significant advantage in France, we can observe a clear reduction of the gap in average life duration up to the middle of the 1960s. Then, significant progress in France and stagnation in Hungary and Slovakia are shown up to the 1990s in Figure 28. The Hungarian figures for males even worsened up to More recently, since the 1990s, life expectancy at birth has increased faster in both Hungary and Slovakia, while in France the development was straight. The recent differences are 7.3 and 5.7 years for males, and 6.4 and 5.0 years for females, comparing Hungary and Slovakia to France, respectively. Looking at Figure 28, one possible hypothesis is a parallel change among the countries in the future. However, taking into consideration the divergent trends in the old ages, a further increase in the gap cannot be ruled out, at least in the short run. Figure 29 clearly points out the latter possibility. Starting from the 1970s, the difference in life expectancy at age 60 between France on the one hand, and Hungary and Slovakia on the other, has widened. In 2001, French people at age 60 had a life expectancy nearly five years longer than their counterparts in the other two countries. Only in the last two or three years have signs emerged of an initial phase of parallel development. 26

28 Figure 29 Life expectancy at age 60, Males 30,0 28,0 France 26,0 Hungary 24,0 Slovakia 22,0 20,0 18,0 16,0 14,0 12,0 10, ,0 28,0 26,0 24,0 22,0 20,0 18,0 16,0 14,0 12,0 10, France Hungary Slovakia Females Looking at the probabilities of survival to age 60, one can point out the different situation by sex. The main difference in male mortality between France on the one hand, and Hungary and Slovakia on the other, seems to be the large proportion of early death in recent decades in the latter countries. The problems for females are more in the old ages; the survival rate until age 60 seems much closer between the countries than it is for males (Figure 30). Figure 30 Probability of survival to age 60, Males Females 1,00 0,95 0,90 0,85 0,80 0,75 0,70 0,65 0,60 0,55 0, France Hungary Slovakia ,00 0,95 0,90 0,85 0,80 0,75 0,70 0,65 0,60 0,55 0, France Hungary Slovakia Conclusion This brief analysis of mortality trends of two new EU member states, Hungary and Slovakia, and France points out the different tendencies among different age groups and by sex. The probabilities of dying in the young age groups are low and quite similar in the countries, showing developed maternity and child health care systems and a child-friendly society in the background. The situation at older ages is the opposite, as very significant differences in probabilities of survival have developed over the past several decades. As a result, life expectancies in France are far higher than the Hungarian and Slovakian values. 27

No. 1. THE ROLE OF INTERNATIONAL MIGRATION IN MAINTAINING HUNGARY S POPULATION SIZE BETWEEN WORKING PAPERS ON POPULATION, FAMILY AND WELFARE

No. 1. THE ROLE OF INTERNATIONAL MIGRATION IN MAINTAINING HUNGARY S POPULATION SIZE BETWEEN WORKING PAPERS ON POPULATION, FAMILY AND WELFARE NKI Central Statistical Office Demographic Research Institute H 1119 Budapest Andor utca 47 49. Telefon: (36 1) 229 8413 Fax: (36 1) 229 8552 www.demografia.hu WORKING PAPERS ON POPULATION, FAMILY AND

More information

STATISTICAL REFLECTIONS

STATISTICAL REFLECTIONS World Population Day, 11 July 217 STATISTICAL REFLECTIONS 18 July 217 Contents Introduction...1 World population trends...1 Rearrangement among continents...2 Change in the age structure, ageing world

More information

INFOSTAT INSTITUTE OF INFORMATICS AND STATISTICS Demographic Research Centre. Population in Slovakia 2004

INFOSTAT INSTITUTE OF INFORMATICS AND STATISTICS Demographic Research Centre. Population in Slovakia 2004 INFOSTAT INSTITUTE OF INFORMATICS AND STATISTICS Demographic Research Centre Population in Slovakia 24 Bratislava, December 25 2 Population of Slovakia 24 Analytical publication, which assesses the population

More information

THE ROLE OF INTERNATIONAL MIGRATION IN MAINTAINING THE POPULATION SIZE OF HUNGARY BETWEEN LÁSZLÓ HABLICSEK and PÁL PÉTER TÓTH

THE ROLE OF INTERNATIONAL MIGRATION IN MAINTAINING THE POPULATION SIZE OF HUNGARY BETWEEN LÁSZLÓ HABLICSEK and PÁL PÉTER TÓTH THE ROLE OF INTERNATIONAL MIGRATION IN MAINTAINING THE POPULATION SIZE OF HUNGARY BETWEEN 2000 2050 LÁSZLÓ HABLICSEK and PÁL PÉTER TÓTH INTRODUCTION 1 Fertility plays an outstanding role among the phenomena

More information

POPULATION DEVELOPMENT IN THE SLOVAK REPUBLIC

POPULATION DEVELOPMENT IN THE SLOVAK REPUBLIC INFOSTAT - INSTITUTE OF INFORMATICS AND STATISTICS Demographic Research Centre POPULATION DEVELOPMENT IN THE SLOVAK REPUBLIC 1999 Published by: Akty Bratislava, September 2000 2 Population Development

More information

Changing Times, Changing Enrollments: How Recent Demographic Trends are Affecting Enrollments in Portland Public Schools

Changing Times, Changing Enrollments: How Recent Demographic Trends are Affecting Enrollments in Portland Public Schools Portland State University PDXScholar School District Enrollment Forecast Reports Population Research Center 7-1-2000 Changing Times, Changing Enrollments: How Recent Demographic Trends are Affecting Enrollments

More information

Eurostat Working Papers

Eurostat Working Papers Eurostat Working Papers Population and social conditions 3/1999/E/n 15 Report on the demographic situation in 12 Central European Countries*, Cyprus and Malta eurostat Population and social conditions

More information

Human Population Growth Through Time

Human Population Growth Through Time Human Population Growth Through Time Current world population: 7.35 Billion (Nov. 2016) http://www.worldometers.info/world-population/ 2012 7 billion 1999 13 years 12 years 1974 1927 1804 13 years 14 years

More information

8. United States of America

8. United States of America (a) Past trends 8. United States of America The total fertility rate in the United States dropped from 3. births per woman in 19-19 to 2.2 in 197-197. Except for a temporary period during the late 197s

More information

Introduction: The State of Europe s Population, 2003

Introduction: The State of Europe s Population, 2003 Introduction: The State of Europe s Population, 2003 Changes in the size, growth and composition of the population are of key importance to policy-makers in practically all domains of life. To provide

More information

The Human Population and Its Impact. Chapter 6

The Human Population and Its Impact. Chapter 6 The Human Population and Its Impact Chapter 6 Core Case Study: Are There Too Many of Us? (1) Estimated 2.4 billion more people by 2050 Are there too many people already? Will technological advances overcome

More information

Evaluating the Role of Immigration in U.S. Population Projections

Evaluating the Role of Immigration in U.S. Population Projections Evaluating the Role of Immigration in U.S. Population Projections Stephen Tordella, Decision Demographics Steven Camarota, Center for Immigration Studies Tom Godfrey, Decision Demographics Nancy Wemmerus

More information

Some important terms and Concepts in population dynamics

Some important terms and Concepts in population dynamics By Dr. Sengupta, CJD International School, Braunschweig Some important terms and Concepts in population dynamics DEMOGRAPHY- is the study of population Population Density Population per unit of land area;

More information

Britain s Population Exceptionalism within the European Union

Britain s Population Exceptionalism within the European Union Britain s Population Exceptionalism within the European Union Introduction The United Kingdom s rate of population growth far exceeds that of most other European countries. This is particularly problematic

More information

Labor markets in the Tenth District are

Labor markets in the Tenth District are Will Tightness in Tenth District Labor Markets Result in Economic Slowdown? By Ricardo C. Gazel and Chad R. Wilkerson Labor markets in the Tenth District are tighter now than at any time in recent memory.

More information

The Impact of Canadian Immigrant Selection Policy on Future Imbalances in Labour Force Supply by Broad Skill Levels

The Impact of Canadian Immigrant Selection Policy on Future Imbalances in Labour Force Supply by Broad Skill Levels The Impact of Canadian Immigrant Selection Policy on Future Imbalances in Labour Force Supply by Broad Skill Levels Alain Bélanger Population Change and Life Course Cluster Conference on Income, health,

More information

People. Population size and growth

People. Population size and growth The social report monitors outcomes for the New Zealand population. This section provides background information on who those people are, and provides a context for the indicators that follow. People Population

More information

People. Population size and growth. Components of population change

People. Population size and growth. Components of population change The social report monitors outcomes for the New Zealand population. This section contains background information on the size and characteristics of the population to provide a context for the indicators

More information

The Effects of Immigration on Age Structure and Fertility in the United States

The Effects of Immigration on Age Structure and Fertility in the United States The Effects of Immigration on Age Structure and Fertility in the United States David Pieper Department of Geography University of California, Berkeley davidpieper@berkeley.edu 31 January 2010 I. Introduction

More information

HEALTH STATUS OVERVIEW FOR COUNTRIES OF CENTRAL AND EASTERN EUROPE THAT ARE CANDIDATES FOR ACCESSION TO THE EUROPEAN UNION

HEALTH STATUS OVERVIEW FOR COUNTRIES OF CENTRAL AND EASTERN EUROPE THAT ARE CANDIDATES FOR ACCESSION TO THE EUROPEAN UNION OVERVIEW FOR COUNTRIES OF CENTRAL AND EASTERN EUROPE THAT ARE CANDIDATES FOR ACCESSION WHO Regional Office for Europe European Commission JULY 22 E76888 This project, to develop Highlights on health and

More information

The labor market in Japan,

The labor market in Japan, DAIJI KAWAGUCHI University of Tokyo, Japan, and IZA, Germany HIROAKI MORI Hitotsubashi University, Japan The labor market in Japan, Despite a plummeting working-age population, Japan has sustained its

More information

Case study: China s one-child policy

Case study: China s one-child policy Human Population Case study: China s one-child policy In 1970, China s 790 million people faced starvation The government instituted a onechild policy China s growth rate plummeted In 1984, the policy

More information

Supplementary Notes: (PJ Shlachtman, Miller book) Human Population: Growth, Demography, and Carrying Capacity

Supplementary Notes: (PJ Shlachtman, Miller book) Human Population: Growth, Demography, and Carrying Capacity Supplementary Notes: (PJ Shlachtman, Miller book) Human Population:, Demography, and Carrying Capacity Factors Affecting Human Population Size Pop. size is affected by birth s, death s, emigration and

More information

Recent demographic trends

Recent demographic trends Recent demographic trends Jitka Rychtaříková Charles University in Prague, Faculty of Science Department of Demography and Geodemography Albertov 6, 128 43 Praha 2, Czech Republic tel.: 420 221 951 420

More information

Population Aging, Immigration and Future Labor Shortage : Myths and Virtual Reality

Population Aging, Immigration and Future Labor Shortage : Myths and Virtual Reality Population Aging, Immigration and Future Labor Shortage : Myths and Virtual Reality Alain Bélanger Speakers Series of the Social Statistics Program McGill University, Montreal, January 23, 2013 Montréal,

More information

RECENT POPULATION CHANGE IN EUROPE

RECENT POPULATION CHANGE IN EUROPE RECENT POPULATION CHANGE IN EUROPE Silvia Megyesiová Vanda Lieskovská Abstract Population ageing is going to be a key demographic challenge in many Member States of the European Union. The ageing process

More information

The Human Population 8

The Human Population 8 8 The Human Population Overview of Chapter 8 The Science of Demography Demographics of Countries Demographic Stages Age Structure Population and Quality of Life Reducing the Total Fertility Rate Government

More information

DEMOGRAPHIC SHOCKS: THE VIEW FROM HISTORY. DISCUSSION

DEMOGRAPHIC SHOCKS: THE VIEW FROM HISTORY. DISCUSSION DEMOGRAPHIC SHOCKS: THE VIEW FROM HISTORY. DISCUSSION David N. Weil* Massimo Livi-Bacci has taken us on a fascinating tour of demographic history. What lessons for developments in the world today can we

More information

The new demographic and social challenges in Spain: the aging process and the immigration

The new demographic and social challenges in Spain: the aging process and the immigration International Geographical Union Commission GLOBAL CHANGE AND HUMAN MOBILITY The 4th International Conference on Population Geographies The Chinese University of Hong Kong (10-13 July 2007) The new demographic

More information

2. In what stage of the demographic transition model are most LDC? a. First b. Second c. Third d. Fourth e. Fifth

2. In what stage of the demographic transition model are most LDC? a. First b. Second c. Third d. Fourth e. Fifth 1. The three largest population clusters in the world are in a. East Asia, South Asia, Southeast Asia b. East Asia, South Asia, South America c. Africa, South Asia, East Asia d. Australia, South Asia,

More information

Population & Migration

Population & Migration Population & Migration Population Distribution Humans are not distributed evenly across the earth. Geographers identify regions of Earth s surface where population is clustered and regions where it is

More information

PROJECTING THE LABOUR SUPPLY TO 2024

PROJECTING THE LABOUR SUPPLY TO 2024 PROJECTING THE LABOUR SUPPLY TO 2024 Charles Simkins Helen Suzman Professor of Political Economy School of Economic and Business Sciences University of the Witwatersrand May 2008 centre for poverty employment

More information

ISSN Methodologies and Working papers. Demographic Outlook. National reports on the demographic developments in 2007.

ISSN Methodologies and Working papers. Demographic Outlook. National reports on the demographic developments in 2007. ISSN 1977-0375 Methodologies and Working papers Demographic Outlook National reports on the demographic developments in 2007 2008 edition How to obtain EU publications Our priced publications are available

More information

Population & Migration

Population & Migration Population & Migration Population Distribution Humans are not distributed evenly across the earth. Geographers identify regions of Earth s surface where population is clustered and regions where it is

More information

Assuming the Future: Evaluating World Population Projections

Assuming the Future: Evaluating World Population Projections Assuming the Future: Evaluating World Population Projections By Joseph Chamie Extended Abstract World population, now at 7 billion, is expected to be nearing stabilization at 10 billion by the end of the

More information

TRANSLATION. Laurent Roy Jean Bernier. Family Policy, Social Trends and Fertility in Québec: Experimenting with the Nordic Model?

TRANSLATION. Laurent Roy Jean Bernier. Family Policy, Social Trends and Fertility in Québec: Experimenting with the Nordic Model? TRANSLATION Laurent Roy Jean Bernier Family Policy, Social Trends and Fertility in Québec: Experimenting with the Nordic Model? RESEARCH AND WRITING Laurent Roy Jean Bernier Ministère de la Famille, des

More information

Migration and Demography

Migration and Demography Migration and Demography Section 2.2 Topics: Demographic Trends and Realities Progressively Ageing Populations Four Case Studies Demography and Migration Policy Challenges Essentials of Migration Management

More information

Assessment of the demographic effect on future rural development in Bulgaria

Assessment of the demographic effect on future rural development in Bulgaria Minka Anastasova-Chopeva, Dimitre Nikolov 233 Institute of Agricultural Economics 125, Zarigradsko shoes, Bl. 1, 1113 Sofi a, Bulgaria anastasova_m@yahoo.com dnik_sp@yahoo.com Assessment of the demographic

More information

Chapter One: people & demographics

Chapter One: people & demographics Chapter One: people & demographics The composition of Alberta s population is the foundation for its post-secondary enrolment growth. The population s demographic profile determines the pressure points

More information

Population Projection Alberta

Population Projection Alberta Population Projection Alberta 215 241 Solid long term growth expected Alberta s population is expected to expand by about 2.1 million people by the end of the projection period, reaching just over 6.2

More information

Population Projection Methodology and Assumptions

Population Projection Methodology and Assumptions Population Projection Methodology and Assumptions Introduction Population projections for Alberta and each of its 19 census divisions are available for the period 217 to 241 by sex and single year of age.

More information

Alberta Population Projection

Alberta Population Projection Alberta Population Projection 213 241 August 16, 213 1. Highlights Population growth to continue, but at a moderating pace Alberta s population is expected to expand by 2 million people through 241, from

More information

Meanwhile, the foreign-born population accounted for the remaining 39 percent of the decline in household growth in

Meanwhile, the foreign-born population accounted for the remaining 39 percent of the decline in household growth in 3 Demographic Drivers Since the Great Recession, fewer young adults are forming new households and fewer immigrants are coming to the United States. As a result, the pace of household growth is unusually

More information

NAME DATE CLASS. Directions: Answer each of the following questions. Include in your answers the vocabulary words in parentheses.

NAME DATE CLASS. Directions: Answer each of the following questions. Include in your answers the vocabulary words in parentheses. Vocabulary Activity Content Vocabulary Directions: Answer each of the following questions. Include in your answers the vocabulary words in parentheses. 1. What does the term crude birthrate have to do

More information

In class, we have framed poverty in four different ways: poverty in terms of

In class, we have framed poverty in four different ways: poverty in terms of Sandra Yu In class, we have framed poverty in four different ways: poverty in terms of deviance, dependence, economic growth and capability, and political disenfranchisement. In this paper, I will focus

More information

SOCI CIETIES. The enlarged European Union: fifteen + ten = 455. Alain Monnier*

SOCI CIETIES. The enlarged European Union: fifteen + ten = 455. Alain Monnier* ONTNTS U L L T I N M N S U L I N F O R M T I O N L I N S T I T U T N T I O N L É T U S É M O G R P H I Q U S POPU When its ten new members join in May, the uropean Union will have a population of million

More information

Population density is a measure of how crowded a population is. It looks at land area as well as population.

Population density is a measure of how crowded a population is. It looks at land area as well as population. Population Population density is a measure of how crowded a population is. It looks at land area as well as population. Population Density = population per unit area (unit area is usually measured in Km

More information

What's Driving the Decline in U.S. Population Growth?

What's Driving the Decline in U.S. Population Growth? Population Reference Bureau Inform. Empower. Advance. What's Driving the Decline in U.S. Population Growth? Mark Mather (May 2012) Between 2010 and 2011, the U.S. population increased by 0.7 percent, after

More information

Number of marriages increases and number of divorces decreases; infant mortality rate is the lowest ever

Number of marriages increases and number of divorces decreases; infant mortality rate is the lowest ever Demographic Statistics 2017 15 November 2018 Number of marriages increases and number of divorces decreases; infant mortality rate is the lowest ever The demographic situation in Portugal in 2017 continues

More information

Dov Raphael MWG meeting St Petersburg, May 2016

Dov Raphael MWG meeting St Petersburg, May 2016 Does immigration affect mortality? A study of the effects of immigration from the former Soviet Union to Israel Dov Raphael MWG meeting St Petersburg, May 2016 May 2016 Immigration and mortality - Dov

More information

EUROBAROMETER 71 PUBLIC OPINION IN THE EUROPEAN UNION SPRING

EUROBAROMETER 71 PUBLIC OPINION IN THE EUROPEAN UNION SPRING Standard Eurobarometer European Commission EUROBAROMETER 71 PUBLIC OPINION IN THE EUROPEAN UNION SPRING 2009 Standard Eurobarometer 71 / SPRING 2009 TNS Opinion & Social Standard Eurobarometer NATIONAL

More information

The proportion of the UK population aged under 16 dropped below the proportion over state pension age for the first time in (Table 1.

The proportion of the UK population aged under 16 dropped below the proportion over state pension age for the first time in (Table 1. Population In 2007, there were 6.0 million people resident in the UK, an increase of almost 400,000 (0.6 per cent) on 2006, equivalent to an average increase of around,000 people a day. (Table.) Chapter

More information

Demographic change and work in Europe

Demographic change and work in Europe Demographic change and work in Europe Relevant features of demographic change in Europe What does the demographic change mean for work? Commentary Bibliography Annex: Methodology and data sources This

More information

The impact of immigration on population growth

The impact of immigration on population growth Briefing Paper 15.3 www.migrationwatchuk.com Summary 1. The impact of immigration on the size of the UK population is substantially greater than is generally realised. Between 2001 and 2012 inclusive,

More information

http://www.youtube.com/watch?v=ymwwrgv_aie Demographics Demography is the scientific study of population. Demographers look statistically as to how people are distributed spatially by age, gender, occupation,

More information

The Demography of the Labor Force in Emerging Markets

The Demography of the Labor Force in Emerging Markets The Demography of the Labor Force in Emerging Markets David Lam I. Introduction This paper discusses how demographic changes are affecting the labor force in emerging markets. As will be shown below, the

More information

Labour market crisis: changes and responses

Labour market crisis: changes and responses Labour market crisis: changes and responses Ágnes Hárs Kopint-Tárki Budapest, 22-23 November 2012 Outline The main economic and labour market trends Causes, reasons, escape routes Increasing difficulties

More information

SS 11: COUNTERPOINTS CH. 13: POPULATION: CANADA AND THE WORLD NOTES the UN declared the world s population had reached 6 billion.

SS 11: COUNTERPOINTS CH. 13: POPULATION: CANADA AND THE WORLD NOTES the UN declared the world s population had reached 6 billion. SS 11: COUNTERPOINTS CH. 13: POPULATION: CANADA AND THE WORLD NOTES 1 INTRODUCTION 1. 1999 the UN declared the world s population had reached 6 billion. 2. Forecasters are sure that at least another billion

More information

Labor market migration nexus in Slovakia: time to act in a comprehensive way. Boris Divinský

Labor market migration nexus in Slovakia: time to act in a comprehensive way. Boris Divinský Labor market migration nexus in Slovakia: time to act in a comprehensive way Boris Divinský IOM International Organization for Migration Labor market migration nexus in Slovakia: time to act in a comprehensive

More information

MAGNET Migration and Governance Network An initiative of the Swiss Development Cooperation

MAGNET Migration and Governance Network An initiative of the Swiss Development Cooperation International Labour Organization ILO Regional Office for the Arab States MAGNET Migration and Governance Network An initiative of the Swiss Development Cooperation The Kuwaiti Labour Market and Foreign

More information

Survey sample: 1,013 respondents Survey period: Commissioned by: Eesti Pank Estonia pst. 13, Tallinn Conducted by: Saar Poll

Survey sample: 1,013 respondents Survey period: Commissioned by: Eesti Pank Estonia pst. 13, Tallinn Conducted by: Saar Poll Survey sample:,0 respondents Survey period:. - 8.. 00 Commissioned by: Eesti Pank Estonia pst., Tallinn 9 Conducted by: Saar Poll OÜ Veetorni, Tallinn 9 CHANGEOVER TO THE EURO / December 00 CONTENTS. Main

More information

POPULATION STUDIES RESEARCH BRIEF ISSUE Number

POPULATION STUDIES RESEARCH BRIEF ISSUE Number POPULATION STUDIES RESEARCH BRIEF ISSUE Number 2008021 School for Social and Policy Research 2008 Population Studies Group School for Social and Policy Research Charles Darwin University Northern Territory

More information

Labour market of the new Central and Eastern European member states of the EU in the first decade of membership 125

Labour market of the new Central and Eastern European member states of the EU in the first decade of membership 125 Labour market of the new Central and Eastern European member states of the EU in the first decade of membership 125 Annamária Artner Introduction The Central and Eastern European countries that accessed

More information

David Istance TRENDS SHAPING EDUCATION VIENNA, 11 TH DECEMBER Schooling for Tomorrow & Innovative Learning Environments, OECD/CERI

David Istance TRENDS SHAPING EDUCATION VIENNA, 11 TH DECEMBER Schooling for Tomorrow & Innovative Learning Environments, OECD/CERI TRENDS SHAPING EDUCATION DEVELOPMENTS, EXAMPLES, QUESTIONS VIENNA, 11 TH DECEMBER 2008 David Istance Schooling for Tomorrow & Innovative Learning Environments, OECD/CERI CERI celebrates its 40 th anniversary

More information

AMID Working Paper Series 45/2005

AMID Working Paper Series 45/2005 AMID Working Paper Series 45/2005 The Demography of the Middle East and North Africa in a Global Context Poul Chr. Matthiessen Collstrops Fond Introduction The present paper aims to provide a description

More information

Dynamic Diversity: Projected Changes in U.S. Race and Ethnic Composition 1995 to December 1999

Dynamic Diversity: Projected Changes in U.S. Race and Ethnic Composition 1995 to December 1999 Dynamic Diversity: Projected Changes in U.S. Race and Ethnic Composition 1995 to 2050 December 1999 DYNAMIC DIVERSITY: PROJECTED CHANGES IN U.S. RACE AND ETHNIC COMPOSITION 1995 TO 2050 The Minority Business

More information

APES Chapter 10 Study Guide. 1. How can the population change in a particular year be calculated?

APES Chapter 10 Study Guide. 1. How can the population change in a particular year be calculated? APES Chapter 10 Study Guide 1. How can the population change in a particular year be calculated? 2. Define the term crude birth rate. 3. Name the continent that has the highest crude birth rate and crude

More information

THE DEMOGRAPHIC PROFILE OF THE ARAB COUNTRIES

THE DEMOGRAPHIC PROFILE OF THE ARAB COUNTRIES Distr. LIMITED E/ESCWA/SDD/2013/Technical paper.14 24 December 2013 ORIGINAL: ENGLISH ECONOMIC AND SOCIAL COMMISSION FOR WESTERN ASIA (ESCWA) THE DEMOGRAPHIC PROFILE OF THE ARAB COUNTRIES New York, 2013

More information

econstor Make Your Publications Visible.

econstor Make Your Publications Visible. econstor Make Your Publications Visible. A Service of Wirtschaft Centre zbwleibniz-informationszentrum Economics Sukneva, Svetlana Conference Paper Arctic Zone of the North-Eastern region of Russia: problems

More information

The Future of South Asia: Population Dynamics, Economic Prospects, and Regional Coherence

The Future of South Asia: Population Dynamics, Economic Prospects, and Regional Coherence PROGRAM ON THE GLOBAL DEMOGRAPHY OF AGING Working Paper Series The Future of South Asia: Population Dynamics, Economic Prospects, and Regional Coherence David E. Bloom and Larry Rosenberg February 2011

More information

FORECASTING NORTHERN ONTARIO'S ABORIGINAL POPULATION

FORECASTING NORTHERN ONTARIO'S ABORIGINAL POPULATION FORECASTING NORTHERN ONTARIO'S ABORIGINAL POPULATION B. Moazzami Professor of Economics Department of Economics Lakehead University Thunder Bay, Ontario Canada, P7B 5E1 AbstractI Resume Changes in population

More information

Shrinking populations in Eastern Europe

Shrinking populations in Eastern Europe Shrinking populations in Eastern Europe s for policy-makers and advocates What is at stake? In several countries in Eastern Europe, populations are shrinking. The world s ten fastest shrinking populations

More information

Using data provided by the U.S. Census Bureau, this study first recreates the Bureau s most recent population

Using data provided by the U.S. Census Bureau, this study first recreates the Bureau s most recent population Backgrounder Center for Immigration Studies December 2012 Projecting Immigration s Impact on the Size and Age Structure of the 21st Century American Population By Steven A. Camarota Using data provided

More information

1 Dr. Center of Sociology, Ho Chi Minh National Political Academy, Vietnam.

1 Dr. Center of Sociology, Ho Chi Minh National Political Academy, Vietnam. Conference "Southeast Asia s Population in a Changing Asian Context June 10-13, 2002 Siam City Hotel, Bangkok, Thailand The Patterns of fertility decline and family changes in Vietnam s emerging market

More information

Demographics. Chapter 2 - Table of contents. Environmental Scan 2008

Demographics. Chapter 2 - Table of contents. Environmental Scan 2008 Environmental Scan 2008 2 Ontario s population, and consequently its labour force, is aging rapidly. The province faces many challenges related to a falling birth rate, an aging population and a large

More information

Economic Growth & Population Decline What To Do About Latvia?

Economic Growth & Population Decline What To Do About Latvia? Economic Growth & Population Decline What To Do About Latvia? Edward Hugh Riga: March 2012 Warning It Is Never Too Late To do Something, But This Is Not An Excuse For Doing Nothing. As We All Know, Latvia

More information

SECTION 1. Demographic and Economic Profiles of California s Population

SECTION 1. Demographic and Economic Profiles of California s Population SECTION 1 Demographic and Economic Profiles of s Population s population has special characteristics compared to the United States as a whole. Section 1 presents data on the size of the populations of

More information

11. Demographic Transition in Rural China:

11. Demographic Transition in Rural China: 11. Demographic Transition in Rural China: A field survey of five provinces Funing Zhong and Jing Xiang Introduction Rural urban migration and labour mobility are major drivers of China s recent economic

More information

Population Dynamics in Poland, : Internal Migration and Marital Status Changes

Population Dynamics in Poland, : Internal Migration and Marital Status Changes Population Dynamics in Poland, 1950-2050: Internal Migration and Marital Status Changes Kotowska, I.E. IIASA Working Paper WP-94-074 August 1994 Kotowska, I.E. (1994) Population Dynamics in Poland, 1950-2050:

More information

Does It Pay to Migrate? The Canadian Evidence

Does It Pay to Migrate? The Canadian Evidence Canadian Studies in Population, Vol. 35.1, 2008, pp. 103-117 Does It Pay to Migrate? The Canadian Evidence Y. Edward Shin Bali Ram Demography Division Statistics Canada Ottawa, Canada edward.shin@statcan.ca

More information

Iowa Voting Series, Paper 4: An Examination of Iowa Turnout Statistics Since 2000 by Party and Age Group

Iowa Voting Series, Paper 4: An Examination of Iowa Turnout Statistics Since 2000 by Party and Age Group Department of Political Science Publications 3-1-2014 Iowa Voting Series, Paper 4: An Examination of Iowa Turnout Statistics Since 2000 by Party and Age Group Timothy M. Hagle University of Iowa 2014 Timothy

More information

By the year 2100 the U.S. current 275 million

By the year 2100 the U.S. current 275 million A Faulty Demographic Road Map to the Future by B. Meredith Burke By the year 2100 the U.S. current 275 million population will most likely be a) 275 million; b) 571 million; c) 1.2 billion; d) somewhere

More information

The Crime Drop in Florida: An Examination of the Trends and Possible Causes

The Crime Drop in Florida: An Examination of the Trends and Possible Causes The Crime Drop in Florida: An Examination of the Trends and Possible Causes by: William D. Bales Ph.D. Florida State University College of Criminology and Criminal Justice and Alex R. Piquero, Ph.D. University

More information

EXPERT GROUP MEETING ON POLICY RESPONSES TO POPULATION AGEING AND POPULATION DECLINE

EXPERT GROUP MEETING ON POLICY RESPONSES TO POPULATION AGEING AND POPULATION DECLINE UN/POP/PRA/2000/9 11 September 2000 ENGLISH ONLY EXPERT GROUP MEETING ON POLICY RESPONSES TO POPULATION AGEING AND POPULATION DECLINE Population Division Department of Economic and Social Affairs United

More information

FOREIGNER S INTERNAL MIGRATION IN SPAIN: RECENT SPATIAL CHANGES DURING THE ECONOMIC CRISIS

FOREIGNER S INTERNAL MIGRATION IN SPAIN: RECENT SPATIAL CHANGES DURING THE ECONOMIC CRISIS Boletín de la Asociación Foreigner s de internal Geógrafos migration Españoles in Spain: N.º 69 recent - 2015, spatial págs. changes 547-551 during the economic crisis I.S.S.N.: 0212-9426 FOREIGNER S INTERNAL

More information

Margarita Mooney Assistant Professor University of North Carolina at Chapel Hill Chapel Hill, NC

Margarita Mooney Assistant Professor University of North Carolina at Chapel Hill Chapel Hill, NC Margarita Mooney Assistant Professor University of North Carolina at Chapel Hill Chapel Hill, NC 27517 Email: margarita7@unc.edu Title: Religion, Aging and International Migration: Evidence from the Mexican

More information

CEPAL. Review. Director. Technical Editor ADOLFO GURRIERI UNITED NATIONS ECONOMIC COMMISSION FOR LATIN AMERICA SANTIAGO, CHILE / FIRST HALF OF 1977

CEPAL. Review. Director. Technical Editor ADOLFO GURRIERI UNITED NATIONS ECONOMIC COMMISSION FOR LATIN AMERICA SANTIAGO, CHILE / FIRST HALF OF 1977 CEPAL Review Director RAUL PREBISCH Technical Editor ADOLFO GURRIERI UNITED NATIONS ECONOMIC COMMISSION FOR LATIN AMERICA SANTIAGO, CHILE / FIRST HALF OF 1977 CONTENTS The 'Futures* debate in the United

More information

ANNUAL SURVEY REPORT: BELARUS

ANNUAL SURVEY REPORT: BELARUS ANNUAL SURVEY REPORT: BELARUS 2 nd Wave (Spring 2017) OPEN Neighbourhood Communicating for a stronger partnership: connecting with citizens across the Eastern Neighbourhood June 2017 1/44 TABLE OF CONTENTS

More information

Effects of migration on fertility patterns of non-native women in Spain

Effects of migration on fertility patterns of non-native women in Spain Effects of migration on fertility patterns of non-native women in Spain (Draft Version 08/04/2012) Daniel Devolder (ddevolder@ced.uab.es) Xiana Bueno (xbueno@ced.uab.es) Centre d Estudis Demogràfics, Barcelona

More information

VOLUME 19, ARTICLE 2, PAGES 5-14 PUBLISHED 01 JULY DOI: /DemRes

VOLUME 19, ARTICLE 2, PAGES 5-14 PUBLISHED 01 JULY DOI: /DemRes Demographic Research a free, expedited, online journal of peer-reviewed research and commentary in the population sciences published by the Max Planck Institute for Demographic Research Konrad-Zuse Str.

More information

The population of Spain will decrease 1.2% in the next 10 years if the current demographic trends remain unchanged

The population of Spain will decrease 1.2% in the next 10 years if the current demographic trends remain unchanged 28 September 2011 Short-Term Population Projection for Spain, 2011-2021 The population of Spain will decrease 1.2% in the next 10 years if the current demographic trends remain unchanged From 2019 the

More information

Small Effects of Selective Migration and Selective Survival in Retrospective Studies of Fertility

Small Effects of Selective Migration and Selective Survival in Retrospective Studies of Fertility Eur J Population (2013) 29:345 354 DOI 10.1007/s10680-013-9293-6 Small Effects of Selective Migration and Selective Survival in Retrospective Studies of Fertility Faibles effets de sélection de la migration

More information

Population, Health, and Human Well-Being-- Portugal

Population, Health, and Human Well-Being-- Portugal Population, Health, and Human Well-Being-- Portugal EarthTrends Country Profiles Demographic and Health Indicators Portugal Europe World Total Population (in thousands of people) 1950 8,405 548,206 2,519,495

More information

Chapter 6: Human Population & Its Impact How many is too many? 7 billion currently; 1.6 mill. more each week ~2.4 bill. more by 2050 Developing 82%

Chapter 6: Human Population & Its Impact How many is too many? 7 billion currently; 1.6 mill. more each week ~2.4 bill. more by 2050 Developing 82% Chapter 6: Human Population & Its Impact How many is too many? 7 billion currently; 1.6 mill. more each week ~2.4 bill. more by 2050 Developing 82% of population Developed high resource use; (more coming

More information

RECENT DEMOGRAPHIC TRENDS IN THE DEVELOPED COUNTRIES

RECENT DEMOGRAPHIC TRENDS IN THE DEVELOPED COUNTRIES RECENT DEMOGRAPHIC TRENDS IN THE DEVELOPED COUNTRIES Jean-Paul Sardon I.N.E.D Population 2006/3 - Vol. 61 pages 197-266 ISSN 0032-4663 Available online at: --------------------------------------------------------------------------------------------------------------------

More information

The Graying of the Empire State: Parts of NY Grow Older Faster

The Graying of the Empire State: Parts of NY Grow Older Faster Research Bulletin No. 7.2 August 2012 EMPIRE The Graying of the Empire State: Parts of NY Grow Older Faster By E.J. McMahon and Robert Scardamalia CENTER FOR NEW YORK STATE POLICY A project of the Manhattan

More information

Fiscal Impacts of Immigration in 2013

Fiscal Impacts of Immigration in 2013 www.berl.co.nz Authors: Dr Ganesh Nana and Hugh Dixon All work is done, and services rendered at the request of, and for the purposes of the client only. Neither BERL nor any of its employees accepts any

More information

Demographic Challenges

Demographic Challenges Demographic Challenges Tomas Sobotka Vienna Institute of Demography (Austrian Academy of Sciences), Wittgenstein Centre for Demography and Global Human Capital Background Demographic Changes in Portugal

More information

POPULATION AND DEMOGRAPHIC PROCESSES IN 2016

POPULATION AND DEMOGRAPHIC PROCESSES IN 2016 POPULATION AND DEMOGRAPHIC PROCESSES IN 2016 Demographic situation in Bulgaria in 2016: Population number decrease and population ageing continue; Unbalanced territorial distribution of population go deeper;

More information

TOPICS INCLUDE: Population Growth Demographic Data Rule of 70 Age-Structure Pyramids Impact of Growth UNIT 3: POPULATION

TOPICS INCLUDE: Population Growth Demographic Data Rule of 70 Age-Structure Pyramids Impact of Growth UNIT 3: POPULATION TOPICS INCLUDE: Population Growth Demographic Data Rule of 70 Age-Structure Pyramids Impact of Growth UNIT 3: POPULATION # of individuals in a given area Uniform equally spaced Clumped/Clustered individuals

More information