Does Aging Influence Migration in Romania? A Comprehensive Analysis

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ScienceDirect Procedia Economics and Finance 10 (2014) 87 – 96

7th International Conference on Applied Statistics

Does Aging Influence Migration in Romania? A Comprehensive Analysis Emilia Titana, Adrian Otoiua * a

Bucharest Academy of Economic Studies, Department of Statistics and Econometrics, Piata Romana 6

Abstract An integrated analysis of the impact of population ageing on migration is done for Romania. The effects of aging are examined with respect to emigration and immigration. Results show that there is a significant relationship between emigration flows and the dependency ratio for Romania and the EU, but that a decrease in birth rates in the EU does not act as a pull factor in the case of Romania. There is no significant link between aging and immigration to Romania. Knowing these relationships will help to better model the impact of migration on mitigating the effects of ageing, determine how migration will evolve given the age structure of the population, and how these influences can be incorporated into standard migration analyses. © B.V. This is an open access article © 2014 2014 Elsevier The Authors. Published by Elsevier B.V. under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Selection and peer-review under responsibility of the Department of Statistics and Econometrics, Bucharest University of Selection peer-review under responsibility of the Department of Statistics and Econometrics, Bucharest University of Economicand Studies. Economic Studies. Keywords: international migration; aging; dependency ratio

1. Introduction Aging is a demographic phenomenon with multiple ramifications. It determines the age structure of the population, the size of the active population and of specific age cohorts, and the size and demand for major government-funded social services such as health care, pensions, education, etc. The massive retirement of the baby boomers currently underway, coupled with historically low fertility rates and decreasing marriage rates has triggered serious concerns about the economic and social sustainability of many countries.

*

Corresponding author. E-mail address: [email protected]

2212-5671 © 2014 Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Selection and peer-review under responsibility of the Department of Statistics and Econometrics, Bucharest University of Economic Studies. doi:10.1016/S2212-5671(14)00281-0

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Here, migration has been seen as a solution to aging. Immigration to developing countries was deemed to offset massive retirements and make the demographic profile more balanced towards the youths. Studies by Eurostat (2013a) have concluded that, although immigration cannot entirely offset the effects of aging, it can alleviate its effects and prevent the demographic decline. This evolution has also been experienced by Romania. A strong emigration wave starting since the 90’s which abated only recently, has made the demographic situation worse. A decline in dependency ratio due to demographic ageing, mainly due to a negative natural increase, with the elderly being more numerous than the youth since 2000, as shown by Vasile (2004), is worsened by emigration, as shown in the work of Petrescu et al, (2013). However, research on migration related to aging has failed so far to examine the conditions at the origin countries. Migrants have a specific age profile, and their decision to move to another country is linked not only to push and pull factors, but also to the pool of available migrants. Aging increases the proportion of the population that is less likely to move, and lower fertility decreases the pool of prospective migrants that migrate mostly during their 20s and 30s. Moreover, there exists evidence that an ageing population can act as a pull factor in attracting migrants from developing countries. Research by Margarita (2010) points out to the fact that a shortage of health care and social assistance has created opportunities for migrants, especially for women. This paper attempts to do an integrated analysis on the effects of aging on migration which takes into account the complex influences of the former on the latter. Starting with an examinations on the main socio-economic trends induced by aging, that can act as significant push and pull factors, it looks at whether aging impacts both emigration and immigration for Romania, and attempts to make a detailed account of the influences of aging on migration. 2. Literature review Most literature is focusing on the effects of immigration on the age structure of the population in the receiving country. International organizations such as OECD, governments around the world and multinational bodies such as the European Commission (2013) have produced policy papers in which the impact of migration on aging has been thoroughly explored. Almost all demographic forecasters incorporate migration into their forecasts, as shown in the work of Samir et al, (2010), O’Neill et al, (2001), and Lutz and Samir (2010). Migration seems to be playing a major role in population growth of developed countries, and is included in the models employed by major international population forecasters: UN, US Census Bureau, and International Institute for Applied Systems Analysis (O’Neill et al, 2001). Demographic research has examined the impact of demographics on migration. In his paper, Plane (1993) explores the multiple connections between migration and demographics. It advocates that a cohort analysis may be appropriate given the complex interrelations between migration and aging, and due to different groups of people that can influence migratory flows at different points in time. The impacts of ageing on the labour force and on health care services have been explored in several publications and studies. ILO (2011) and US Census Bureau (Toosi, 2012) produce labour force projections based on demographic forecasts, pointing to a slower growth in the labour force for developed nations. Margarita (2010) showed that demand for care work triggered by aging has opened significant opportunities for migrant workers in Spain. There is ample anecdotal evidence related to medical personnel being recruited abroad, as pointed out by Driouchi et al. (2009), and Rutten (2009). Romania is among the countries with strong emigration and relatively insignificant immigration. Emigration has had significant impacts on Romania’s society, starting with its very numbers: 1,2 million permanent emigrants between 1990 and 2008, out of a total population decrease of 1.7 million, as shown by Ghetau (2009). However, Sandu (2009) showed that the annual levels are not very high, approaching 11 thousands a year. Another characteristic of migratory phenomena in Romania is that, while immigration has increased, it is still below emigration, as pointed out by Sandu (2009) and Roman and Voicu (2010). Roman and Voicu (2010) also showed that it is the youths and the most educated that are the most mobile.

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As most European countries, Romania experiences a strong demographic decline since early 90’. In his paper, Ghetau (2009) has pointed out that the second cause behind Romania’s strong demographic decline is the decrease in birth rates. While this decrease represents a little less than one third of total population decline, its implications are more far-reaching and harder to tackle, as it will lead to smaller cohorts and a strong decrease in old-age dependency ratio, with major impact on sustainability of the health care and the pension system. 3. Key Trends in Population Aging Aging itself, as a major demographic phenomenon, is complex and consists of two major events: one is the large number of retirements following the post WWII baby boom, and the second one is the sharp decrease in total fertility rates below the natural replacement levels. These two events translate in the following four major impacts of aging, which can act as major pull and push factors for the migration flows. Aging is an important pull factor as the workforce shrinks and there are not enough youths to replace them. Statistics for Romania show that the number of the 18 years olds is on a declining trend, whereas the number of 60 and 65 year olds is rather stable and on an increasing trend during the past few years. Thus, the difference between the number of people reaching legal age and those at or close to retirement age is on a strong declining trend since 2008. The difference between the number of 18 year olds and 60 year olds has become negative for the past three years and is likely to become so for the difference between the 18 and the 65 year olds.

Evolution of Key Age Groups- Romania 1990-2012

'000

121

99 96

130

153 147 147

120 119 126 108

12 127

146 146

170 125 122

89 87

56

18 yo

60 yo

65 yo

Gap 18-65

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

-26 -29 -32 1990

450 400 350 300 250 200 150 100 50 0 -50 -100

Gap 18-60

Source: Insse, Demographic Statistics Fig. 1. Demographic Change Analysis on Key Age Groups The elderly require health care and social assistance. As people age, they make an increased use of health care services. The proportion of the population consulted by doctors and physicians in the past 4 months jumps from 8.4% for those aged 35-44 to 18.7% for those age 45 to 54 and 31.7% for those aged 55-64. As the number of youths is on a declining trend and the elderly are more numerous, this will induce a strong increase in demand of physician services. A similar trend is observed in table 3: while less than 1.2% of the population younger than 45 years takes medication for all of the five major disease categories, the proportion jumps to over 5% for diabetes, 13.2% for hypertension, and over 2.5% for asthma and other respiratory diseases, for those aged 55 and over.

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There is ample anecdotal evidence related to medical personnel being recruited abroad as shown by the work of Driouchi et al. (2009) and Rutten (2009). Scholarly research by Margarita (2010).showed existence of opportunities in care provision in Spain.

Consultation of Physicians or Doctors During the Last 4 Weeks- Romania- 2008 100

31 3.1

6.0

8.4

18.7

80

31.7

37.2

41.2

43.5

68.4

62.7

58.7

56.5

55-64

65-74

75 -84

85+

60 97

94.1

40

91.8

81.2

20 0 15-24

25-34

35-44

45-54

No contacts Source: Insse, Health Statistics

1 or more

Fig. 2. Use of Physician and Doctor Services in Romania

Use of Medicines During the Past 2 Weeks, Romania 2008

% 85+

7.2

75 -84

7.4

65-74

7.5

43.5

2

34.7

3.9

25.5

55-64

5.9

45-54

2.8 2.9

13.2

5.6

5.8

3.1 3

2.5 2.8

Diabetes mellitus

1

1.6

Depressive disorders

35-44

Hypertensive diseases

25-34

Chronic bronchitis, emphysema, other pulmonaryy disease p

15-24 0.0

10.0

20.0

30.0

40.0

50.0

60.0

Source: Insse, Health Statistics Fig. 3. Use of Drugs in Romania by Age Groups Aging shrinks the pool of available migrants. Migration happens at younger ages. An age profile of the Romanian migrants reveals the fact that most migratory movements involve young people. The share of emigrants and immigrants belonging to the core working age group 25-41 is 10 percentage points higher than the share of this age group in total population, while migrants over 50 are much less numerous than

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their share in the total population. We also observe different patterns from emigration and immigration. While emigrants under 25 tend to be younger, immigrants’ age structure is closer to the one in total population. Moreover, the share of immigrants age 41 to 50 is slightly higher than the share of this age group in total population.

Age Structure of Migrant and Total Population, Romania 2011

2001 100.0% 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0%

6.7% 8.0%

6.7% 4 3% 4.3% 10.2%

17.8%

10.4% 14.2%

17.4%

40.5%

33.1%

9.5%

4 9% 4.9% 8.6% 14.9%

13.5% 13.6%

40.7% 23.6%

18.7%

13.5%

11.8%

21.9%

25.9%

22.3%

17.6%

19.2%

33.6%

21.7%

17.1%

28.8%

4 4% 4.4% 6.5% 6 5% 10.9%

18.3%

9.0%

Emigration Immigration Population Emigration Immigration Population < 18

18-25

26-40

41-50

51-60

61+

Source: INSSE, Demographic Statistics Fig. 4. Comparative Age Structure: Population vs Migrants in Romania Declining fertility decreases the pool of the population groups more likely to migrate. This has been the situation for Romania from 1990 to 2002, with the number of live births dropping dramatically from 315 to 211 thousands. Total fertility rate also dropped from a high of 1.83 to 1.25. The following period has seen a mild rebound in the number of births and fertility rates, reaching 222 thousands and, respectively 1.38 in 2009. Since then, births and fertility have started to decline again to new lows of 196 thousands and, respectively, 1.25. This will shrink the pool of available migrants, and will require a stronger influence of the economic factors in order to keep migration flows at current levels.

Fertility and Live Births- Romania 1990-2011 2.0 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0

Total fertility rates

'000 350

Live Births

300 250 200 150 100 50

Source: INSSE, Demographic Series

Fig. 5. Births and Fertility in Romania

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

0

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Thus, we have a comprehensive picture of how demographic influences affect migratory flows. With respect to Romania, the complex influences of aging on migratory flows are shown in fig 6.

Fig. 6. Demographic Push and Pull factors for Romanian Migration Flows We observe that there are two main types of effects of migration, which correspond to the two main characteristics of the aging process. On one side, we have the consequences of just having more old people around, which will likely increase the demand for health care and social assistance services both home and abroad, and decrease the size of the labour force as the labour force attachment of older people is rather low. This affects both immigration and emigration in a positive way, unless improved economic conditions at places of origin can entice people to stay home. The other effect concerns the baby bust, with smaller cohorts entering labour force. In Romania’s case, this will shrink the pool of available migrants and provide opportunities for immigrants to find employment. This also applies for the recipient countries. 4. Analysis of the Impact of Aging and Migration: Data, Methods and Results The analysis attempts to quantify the impacts of aging on migration by exploring the following main hypotheses: 1) Is an older age structure of Romania’s population affecting emigration from Romania? 2) In an older age structure of Romania’s population affecting immigration to Romania? 3) Is an older age structure in the Eurozone affecting emigration from Romania? While there is significant emigration to the US, more than half of all Romanian emigration has the Eurozone as its destination. 4) Is Romania’s birth rate affecting emigration from Romania? 5) In Romania’s birth rate affecting immigration to Romania? 6) Is Eurozone’s birth rate affecting emigration from Romania? While there is significant emigration to the US, more than half of all Romanian emigration has the Eurozone as its destination. Data comes from the Eurostat and INSEE for the period 1991-2011. We used the following variables for analysis: - emigration (REMIG) and immigration (RIMIG) flows for Romania, expressed in rates per 1000 inhabitants.,

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- old age dependency ratio for Romania (ROMDR) and Eurozone (EUDR) as the ratio of population aged 65 and over in the population aged 15 to 64, and - crude birth rates per 1000 inhabitants as an average over a 10-year period starting 20 years ago for the Eurozone (ABRATEEU) and Romania (ABRATERO). Emigration and immigration numbers are counts of persons who ceased to have their usual in Romania for a period of at least 12 months. This definition is consistent with the Eurostat definition of migratory flows (Eurostat, 2013b) and is applied for almost all official immigration statistics of EU. However, international migration is a rather complex process, and official flows data, based on administrative records, may capture only a part of the migratory processes. As pointed out by several authors, migration paths are often complex, and permanent vs. temporary migration decisions can be made at any time during the process, as pointed out by Mendola and Carletto (2012). Thus, apart from official records that indicate a firm intention to migrate, there is a high degree of uncertainty as to the precise moment when temporary migrants leave their destination country, and even less so when they decide to permanently settle in the host country. Statistical data collection on migrants also faces the issues of undercoverage (Eurostat, 2011), as there is time lag between a newcomer enters the sampling frame. Also, the fact that labour markets are not completely open to the emigrants, and fear that their responses impact their ability to remain in the host country, can result in fear to provide administrative information about themselves (Eurostat, 2011). These issues are well-known and, according to Nowok and Willekens (2010), the EU policymakers have recognized these difficulties and the need and possibility to address them via modelling techniques. In conclusion, the difficulty in estimating the total migration movements, coupled with significant time lags, makes impossible to construct a reliable time series for estimating the annual evolution of migration. The Eurozone was chosen as being considered as the main emigration destination of Romanians, as shown by Ciocanescu (2011). The choice of modeling the birth rates was given by considering the availability of data since 1960, and the fact that peak migration years are between 20 to 40 years of age. Thus, we have built averages of the birth rates occurring 21 to 30 years before the migration years considered for analysis. The aforementioned hypotheses have been tested using the following regression analysis models on emigration and immigration: REMIGt= α+ β*ROMDRt+ γ*EUDRt + ε RIMIGt= α+ β*ROMDRt+ γ*EUDRt + ε REMIGt= α+ β*ABRATEEUt+ γ*ABRATEROt + ε RIMIGt= α+ β*ABRATEEUt+ γ*ABRATEROt + ε

(1) (2) (3) (4)

Before running the regression models, correlation analysis and cointegration analysis have been carried out as preliminary steps of determining the relationships between variables and decide whether the use of regression models 1-4 is appropriate. The correlation matrix reveals the fact that there is a high correlation between most of the variables chosen for analysis. Correlations have the expected sign with a few notable exceptions. Thus, ageing in the EU is not positively correlated with emigration. While a high negative correlation was expected, the fact that birth rates are almost perfectly correlated with the dependency ratios is rather surprising.

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Table 1. Correlation matrix ABRATEEU

ABRATERO

EUDR

REMIG

RIMIG

ROMDR

ABRATEEU

100%

94%

-100%

67%

-55%

-98%

ABRATERO

94%

100%

-94%

66%

-45%

-92%

-100%

-94%

100%

-67%

55%

98% -75%

EUDR REMIG

67%

66%

-67%

100%

-32%

RIMIG

-55%

-45%

55%

-32%

100%

52%

ROMDR

-98%

-92%

98%

-75%

52%

100%

The high correlation posed particular problems with respect to estimation of the models. Thus we chose to test separately the relationships between migration and dependency ratios, and the relationships between migration and birth rates. Before doing regression work, we have examined the data for unit roots and cointegration in order to see whether a time series model is appropriate to use. However, only three variables had unit roots: emigration, dependency rate for Romania and birth rates for the EU. Among them, there was only weak cointegration between emigration and dependency rate for Romania, and emigration and birth rate for the Eurozone. This validates to a small extend the fact that emigration was the main factor of population decline, as shown by Ghetau (2009). Both cointegrating relationships were significantly above the 5% level of significance. Regression analysis revealed the fact that only emigration was impacted by the dependency ratio of Romania and Eurozone. An increase of Romania’s dependency ratio by one percentage point caused a decrease in emigration rate of 0.28, while a similar increase in the Eurozone dependency ratio caused an increase of the emigration rate by 0.14. The decrease in the birth rate in the Eurozone had a rather counterintuitive effect on the Romanian emigration, which requires further investigation, given the negative correlation between the two. Table 2. Regression results on emigration Estimate

Std. Error

t value

Pr(>|t|)

(Intercept)

2.8138656

0.54541213

5.159155

2.48E-07

ROMDR

-0.2838057

0.09799156

-2.896226

3.78E-03

EUDR

0.1378247

0.0799281

1.724359

8.46E-02

Multiple R-squared: 0.6444 Estimate

Std. Error

t value

Pr(>|t|)

(Intercept)

-0.59632

0.42907

-1.39

0.18252

ABRATEEU

0.15765

0.04981

3.165

0.00566

ABRATERO

-0.05105

0.04859

-1.051

0.30817

Multiple R-squared: 0.5869

Results reported for dependency ratio are adjusted for heteroskedasticity using a HAC covariance matrix, as there was a mild heteroskedasticity, as indicated by the Breusch-Pagan test (BP value= 5.5431, p-value = 0.06256). There was no significant autocorrelation present for both regressions. Regressions on immigrations did not yield any statistically significant results, showing that there is no significant relationship between it and the demographic factors.

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5. Conclusion Apart from the well-known impact of migration in mitigating the effects of ageing in the destination countries, and accelerating them in origin countries, there is a direct link between ageing and migration. Aging induced by relatively large cohorts reaching retirement age is decreasing the pool of Romanian migrants as the propensity to migrate decreases with age, while making room for the migrants to settle in and get a job in the EU, especially in the areas where massive retirements and stronger demand for health care and assistance services are particularly heavy. There is little evidence that aging induced by a decrease in birth rates leads to lower emigration from Romania. This finding has important implications in forecasting the national labour force and working age population, which will bear the full impact of a decrease in cohort sizes, especially for the young age groups. The fact that lower birth rates in the EU countries also lower Romanian emigration to the EU shows that the strong decline in birth rates does not lead to a replacement “pull” effect. It may be the case that the generalized decrease in the size of all cohorts induces a lower demand of economic migration. This relationship deserves further analysis and attention, as a smaller population may impact future immigration in the Eurozone through lower demand for goods and services, which can induce lower job creation, lower opportunities for social integration Also, there is no evidence that aging influences immigration to Romania. This may be mainly due that immigration is a fairly recent phenomena in Romania, and that other drivers such as economic opportunities and family reunification may explain it. This insight is very important in assessment and policy design on immigrationrelated matters. All of the findings point out that Romanian migration can be explained up to a certain extent by the impact that aging has on the age structure of the population, the labour force and the demand for specific services such as health care and social assistance. However, some influences of aging may not be an essential factor in explaining migration. The relationship between migration and birth rates suggests that other factors may play an important role in explaining the magnitude of migration flows. Also, the lack of relationship between aging and immigration may point out to the specifics of Romanian immigration, which may be primarily motivated by large differentials between living and working conditions in Romania and their origin countries. While the analysis and the conclusions of this paper are based on data which records officially documented migratory moves, likely the result of a firm decision to migrate, they should be considered against the fact that many migratory moves are rather complex, and that current international statistics on migration flows only capture a part of them. Future research may be needed to improve the methodology of producing estimates of international migration flows, which gauge temporary and complex migratory moves, and produce reliable time series. The comprehensive approach that attempts to model the multiple demographic impacts on ageing is useful for policy making in assessing the influences of aging, and modelling a policy response that takes them into account.\ Acknowledgements The authors wish to thank the anonymous referees, as well as comments received given during the conference. This work was co-financed from the European Social Fund through Sectoral Operational Programme Human Resources Development 2007-2013, project number POSDRU/159/1.5/S/134197 „Performance and excellence in doctoral and postdoctoral research in Romanian economics science domain”.

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References Ciocanescu, E., 2011. The External Migration With Romania As Country Of Origin And Destination Countries In The European Union – Brief Analysis For 1998-2009 Period, Revista Română de Statistică nr. 7 Driouchi, A., Achehboune, A., Akhawayn, A., Boboc, C., Titan, E., Andrès Antonio, R., Fakhar A., 2012. What Can Be Learnt from the New Economics of Immigration of Medical Doctors to the European Union: The Cases of East and Central European, Middle Eastern and North African Economies? FEMISE 34-07 European Commission, 2012.The 2012 Ageing Report: Economic and budgetary projections for the EU27 Member States (2010-. 2060), available at http://ec.europa.eu/economy_finance/publications/european_economy/2012/pdf/ee-2012-2_en.pdf, accessed August 26, 2013 Eurostat, 2013a. Migration and migrant population statistics, available at http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Migration_and_migrant_population_statistics , accessed August 3, 2013 Eurostat 2013b. International migration flows, Reference Metadata in Euro SDMX Metadata Structure (ESMS), available at http://epp.eurostat.ec.europa.eu/cache/ITY_SDDS/EN/migr_flow_esms.htm, accessed August 3, 2013 Eurostat 2011. Migrants in Europe. A statistical portrait of the first and second generation 2011 edition Gheţău, V., 2009. România: 1990-2009 – 20 de ani de natalitate scăzută. Efecte şi implicaţiipe termen lung. Procesele socio-demografice în societatea contemporană: de la meditaţii la acţiuni”, conf.şt.intern. Chisinau ILO, 2011. Ilo Estimates And Projections Of The Economically Active Population: 1990Ǧ2020 (Sixth Edition), Methodological description, available at http://laborsta.ilo.org/applv8/data/EAPEP/v6/ILO_EAPEP_methodology_2011.pdf, accessed August 12, 2013 King, R., Skeldon, R. (2010). ‘Mind the Gap!’ Integrating Approaches to Internal and International Migration, Journal of Ethnic and Migration Studies, 36:10, 1619-1646 Lutz, W., Samir, K.C., 2010. Dimensions of global population projections: what do we know about future population trends and structures? Phil. Trans. R. Soc. B 27 vol. 365 no. 1554 2779-2791 Margarita, L., 2010. Migration and Care Work in Spain: The Domestic Sector Revisited, Social Policy and Society, vol. 9 issue 3, pp 409-418 Mendola, M, Carletto, C. (2012). Migration and gender differences in the home labourmarket: Evidence from Albania. Labour Economics vol. 9 issue 6, pp 870–880 Cover Image Nowok, B., Willekens, F. 2011. A Probabilistic Framework for Harmonisation of Migration Statistics. Population Space And Place, Volume 17, Issue 5, pp. 521 - 533 O'Neill, B. C., Balk, D., Brickman, M., Ezra, M., 2001. A guide to global population projections. Demogr. Res. 4, 203–288 Petrescu R. M., Bac D, Zgură I.D., 2013. Descriptive Analysis of the International Migration Phenomenon in Romania Between 1991 and 2008, The Annals of the University of Oradea. Economic Sciences, Tom XXII Plane, D. A., 1993. Demographic influences on migration, Reg. Studies 27, 375–383 Raftery, A. E., Chunn, J. E., Gerland, P., & Ševčíková, H., 2013. "Bayesian Probabilistic Projections of Life Expectancy for All Countries". Demography, 50(3), 777-801. doi:10.1007/s13524-012-0193-x Roman, M., Voicu, C., 2010. Some Socio-Economic Effects of Labor Migration on Sending Countries. Evidence from Romania. Theoretical and Applied Economics, Vol 01 7(548) (7(548)):61-76. Rutten, M., 2009. The Economic Impact of Medical Migration: An Overview of the Literature. World Economy, 32: 291–325. doi: 10.1111/j.1467-9701.2008.01147.x Samir, K. C., Barakat, B., Goujon, A., Skirbekk, V., Sanderson, W., Lutz, W., 2010. Projection of populations by level of educational attainment, age, and sex for 120 countries for 2005-2050 Demographic Research, Vol. 22, No. 55. pp. 383-472 Toosi, M., 2012. Labor force projections to 2020: a more slowly growing workforce. Monthly Labour Review, January 2012. Sandu, D., 2009. Migraţia şi consecinţele sale. Riscuri şi inechităţi sociale în România, Administraţia Prezidenţială, Comisia Prezidenţială Pentru Analiza Riscurilor Sociale şi Demografice, pg. 266-285. Vasile, V., 2004. Demographic Changes And Labour Market In Romania, The PIE International Workshop on Demographic Changes and Labor Markets in Transition Economies, Tokyo, Japan February 20-21, 2004)