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Siblings’ interaction in migration decisions: who provides for the elderly left behind?

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Abstract

In most poor countries, with high emigration rates, elderly people are dependent on their children for the provision of care and income. This paper is the first to explicitly model and estimate social interaction between siblings’ migration decisions in such settings. The interaction consists of two effects with opposite signs; a chain migration effect that can cause traditional caregiving structures to break down and an opposing specialization effect that increases family members’ incentives to remain at home and provide care when their siblings migrate. The estimates for Moldova, one of the countries with the highest emigration rates in the world, indicate that siblings’ interaction strongly decreases their equilibrium emigration rates. Siblings’ interaction is found to increase in line with the incentives that are assumed in the model. Hence, the paper provides evidence of the robustness of families’ informal security arrangements to large-scale emigration and has important implications for policies that aim at the population left behind.

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Notes

  1. Other work on the left behind often focuses on factors such as the human capital development of children (e.g., Antman 2012b, Biavaschi 2015) or the labor market decisions of working age adults (e.g., Giuletti et al. 2013) and is not primarily concerned with elderly family members.

  2. For the given context, family-level decisions are far more relevant than household-level decisions. Whereas household-level decision-making has become standard in the economics of migration, evidence at the family level is still lacking. This is often a pragmatic consequence of data availability and is not ideal because endogenous household formation is typically ignored. I use a core definition of the family here whereby each family consists of an elderly person, their spouse (if alive), and their descendants. Focusing on the family is particularly crucial for understanding the effects and determinants of migration in countries where households are small.

  3. I leave out index f until the empirical part of the paper for notational ease. For the time being, there is only one parent-children relationship per family, although this will be relaxed in the empirical part of the paper by allowing elderly spouses to co-reside.

  4. This assumption can be relaxed easily by assuming that a fraction ς of elderly parents’ budgets can be invested into formal care, leaving C e =(1−c−ς)(I+R). In the empirical case that will be analyzed in this paper, the market is severely underdeveloped (European Commission 2010). For instance, out of a population in Moldova of more than 3 million, only 430 elderly people were in residential care in 2008 (European Commission 2009). Thus, the model simplifies to ς ∗≈0, allowing us to assume away a market for care. Including formal care in the model does not change the general mechanisms used to model the processes that cause elderly parents to be left behind alone. Furthermore, if the market for general health care does not exist the model simplifies as c≈1. The quality of general health care infrastructure and its possible free provision are deliberately left unspecified as they can most easily be represented through the relative importance of inputs in H e .

  5. Or preferences with similar consequences within the model; e.g., reciprocity for long-past investment by their parents or impure altruism.

  6. The limits on δ are optional and rule out two extreme cases: First, δ<0 reflects a situation in which children receive disutility from parental well being and second, δ>1, when a unit of individual consumption provides less utility than a unit of consumption for the elderly individual (\(\frac {\partial U_{i}}{\partial C_{i}}<\frac {\partial U_{i}}{\partial C_{e}} \ \text {with} \ C_{e}=C_{i}\)).

  7. The simplifying assumption that the link in altruism runs only one-way from children to the elderly rather than both ways decouples siblings’ utility. Including a two-way link would mean that adult children care indirectly (through their parents’ utility) about their siblings. This would decrease the public good character of contributions to parents and thereby decrease the size of some effects. However, the main mechanisms of the model would not be affected.

  8. This thought is also noted by Antman (2012a) in a footnote. She assumes that the migration cost decreases with the number of siblings who migrate.

  9. I assume these decisions to be only infinitesimally spaced in time and repeated until an equilibrium is reached. As multiple equilibria are possible under certain conditions, the empirical estimation will allow for them. It is possible to assume fully simultaneous decision-making without observing other siblings’ choices. This would require the introduction of beliefs about siblings’ likely decisions. However, this would not yield any added advantage for the empirical analysis. In order to evaluate this assumption in the empirical Section 1 will also estimate sequential frameworks in which one child decides before the next and thereby has a first mover advantage.

  10. Assuming \(\frac {\partial H_{e}}{\partial T_{i}}>\frac {\partial H_{e}}{\partial R_{i}}\) for high levels of frailty seems realistic as care can benefit frail (but not necessarily sick) elderly people more than spending on, for example, medication. This assumption would make the decrease in migration unambiguous.

  11. However, there is general coverage regarding health. The country introduced a universal health care system with mandatory health insurance in the mid-2000s so that, apart from the sometimes necessary bribes to health care workers, the treatment of acute disease at the district hospital or by a family doctor is free. This has probably decreased the share of income spent on health but it is not relevant for the main conclusions of this paper.

  12. Using the latest Penn tables’ PPP conversion factor.

  13. In the literature on peer effects, the most common reason is selection into groups. Although the birth of an individual child into family f is exogenous to her siblings, observed and unobserved characteristics correlate at the family level. Hence, although group formation is not endogenous, growing up together has similar implications. This is in contrast to a random assignment to groups (e.g., in Sacerdote, 2001).

  14. This would require that they decrease available information or increase cost of travel increases, et cetera.

  15. In some studies on peer effects randomization assures, it is approximately zero. In such cases, the assumption is often not made explicitly.

  16. For a detailed discussion of this assumption, please refer to Krauth (2006), Krauth (2005b), and Altonji et al. (2005).

  17. In his paper, Krauth provides Monte Carlo evidence of the bias associated with breaking these assumptions. Additional tests using no observables that could have been affected by observing other siblings’ unobservables (e.g., education) suggest that the stylized findings presented below are robust to this assumption.

  18. If multiple equilbria exist a random one is chosen with equal probability. As Brian Krauth pointed out via email, this ”random” rule should be preferred if the endogenous effect could be positive or negative because ”low activity” and ”high activity” rules provided with his software are only well defined for positive peer effects. Multiple choices are tested empirically and yield similar results below. The same outcome is suggested by the Monte Carlo study in Krauth (2006).

  19. If there were neither small biological departures from 0.5 likelihoods of female births, no fertility choices after observing the gender of the last-born, and equal chances of survival.

  20. 0.487⋅1/1+0.513⋅1/2=0.75 and 0.424⋅1/3+0.327⋅1/4+0.133⋅1/5+0.084⋅1/6+0.025⋅1/7+0.06⋅1/8=0.28, where the denominators are the number of siblings and the numbers with decimal points are the subsample shares of the respective family size.

  21. These results are based on 100 simulations of each specification for exactly one set of random numbers per column. At the bottom of the table I report means over 50 different sets of random numbers.

  22. See Antman (2013) for a short test based on a simulation for the case of Mexico.

  23. Thus, I abstract from the budget allocation literature, which deals with the ways budgets are shared and distributed within a decision-making unit. Additional sources of income that are endogenous and lie outside of the scope of the model, such as income from the sale of assets, are ignored. Monetary transfers from children within the country are not considered because they were hardly reported.

  24. Age is highly correlated with and almost linearly related to an IADL mobility indicator (ρ: 0.46). The self-reported need for help increases almost linearly from a base of 36 % at age 60 to 100 % at age 88 and over. However, the proxy is not optimal. In the model, a shock that increases the frailty of the elderly would make adult children reconsider their choices. As there are no shocks to age no equivalent exists when using age as a proxy for frailty.

  25. The formula is as follows: \(\mathrm {Network Growth Interaction}_{i}\,=\,{\sum }_{j=1}^{J} \!\!\left [\!\frac {{\mathrm {migrants 2004}}_{i, j}}{{\mathrm {population 2004}}_{i}} \frac {1}{T}\! {\sum }_{t=1}^{T}\! \left (\frac {{\text {\!GDP}_{j,t+1}- \text {GDP}_{j,t}}}{ \text {GDP}_{j,t}} \!\right )\! \right ]\), where t=2004,...,2010 are years, j=1,...,J are all destination countries, and i=1,...,I all sampled localities in Moldova. For more detailed discussion of the specific instrument see Böhme et al. (2015).

  26. Additional destination country shares can be included but they do not affect the results.

  27. The variable ranges from 2.3 to 691.7.

  28. This implicitly assumes that the error is independent of the included individual characteristics after controlling for the family fixed effect, i.e., \(cov\left [{\epsilon _{jf}, \gamma _{j} \zeta _{j} X_{jf}}|\eta _{f}\right ]=0\).

  29. In urban areas, which include semi-urban suburbs, 26 % (0.9 hectares on average) owned some land.

  30. Of those who ever had primary responsibility 56 % receive care themselves. Among those who never had such responsibility, 54 % receive care. Elderly individuals without grandchildren and those who report not to need help are excluded.

References

  • Altonji JG, Elder TE, Taber CR, Journal S, February N (2005) Selection on observed and unobserved variables: Assessing the effectiveness of Catholic Schools. J Polit Econ 113(1):151–184

    Article  Google Scholar 

  • Altonji JG, Hayashi F, Kotlikoff LJ (1992) Is the extended family altruistically linked? Direct tests using micro data. Am Econ Rev 82(5):1177–1198

    Google Scholar 

  • Antman FM (2012a) Elderly care and intrafamily resource allocation when children migrate. J Hum Resour 47(2):331–363

    Article  Google Scholar 

  • Antman FM (2012b) Gender, educational attainment, and the impact of parental migration on children left behind. J Popul Econ 25(4):1187–1214

    Article  Google Scholar 

  • Antman FM (2013) The impact of migration on family left behind. In: International Handbook on the Economics of Migration. Edward Elgar, Cheltenham, Ch. 16. Constant A., Zimmermann K. F. (eds)

  • Arrondel L, Masson A (2006) Altruism, exchange or indirect reciprocity: what do the data on family transfer show? In: Kolm S.-C., Ythier J. M. (eds) Handbook of the economics of giving, altruism and reciprocity. Elsevier, Ch.14, pp 971–1053

  • Bernheim BD, Shleifer A, Summers LH (1985) The Strategic Bequest Motive. J Polit Econ 93(6):1045–1076

    Article  Google Scholar 

  • Böhme M, Persian R, Stöhr T (2015) Alone but Better Off? Adult child migration and health of elderly parents in Moldova. J Health Econ 39:211–227

    Article  Google Scholar 

  • Biavaschi C, Giulietti C, Zimmermann KF (2015) Forthcoming. Sibling influence on the human capital of the left behind. J Human Cap.

  • Black SE, Devereux PJ, Salvanes KG (2005) The more the merrier? the effect of family size and birth order on children’s education. Q J Econ 120(2):669–700

    Google Scholar 

  • Bramoullé Y, Djebbari H, Fortin B (2009) Identification of peer effects through social networks. J Econ 150(1):41–55

    Article  Google Scholar 

  • Byrne D, Goeree MS, Hiedemann B, Stern S (2009) Formal home health care, informal care, and family decision making. Int Econ Rev 50(4):1205–1242

    Article  Google Scholar 

  • Cameron L, Cobb-Clark D (2008) Do coresidency and financial transfers from the children reduce the need for elderly parents to works in developing countries? J Popul Econ 21(4):1007–1033

    Article  Google Scholar 

  • Clemens M (2011) Economics and emigration : Trillion-dollar bills on the sidewalk J Econ Persp 25(3):83–106

    Article  Google Scholar 

  • Conley D, Glauber R (2006) Parental educational investment and children’s academic risk: estimates of the impact of sibship size and birth order from exogenous variation in fertility. J Hum Resour 41(4):722–737

    Google Scholar 

  • Cox D (1987) Motives for private income transfers. J Polit Econ 95(3):508–546

    Article  Google Scholar 

  • Cox D, Rank MR (1992) Inter-vivos transfers and intergenerational exchange. Rev Econ Stat 74(2):305–314

    Article  Google Scholar 

  • Davezies L, D’Haultfoeuille X, Fougere D (2009) Identification of peer effects using group size variation. Econ J 12(3):397–413

    Google Scholar 

  • European Commission (2009) Study on social protection and social inclusion in moldova. Tech. rep. http://ec.europa.eu/social/BlobServlet?docId=4348&langId=en

  • European Commission (2010) Social protection and social inclusion in Belarus, Moldova and Ukraine - Synthesis Report. Tech. Rep. June. http://ec.europa.eu/social/BlobServlet?docId=5759&langId=en

  • Giles J, Mu R (2007) Elderly parent health and the migration decisions of adult children: evidence from rural China. Demogr 44(2):265–88

    Article  Google Scholar 

  • Giulietti C, Wahba J, Zimmermann KF (2013) Entrepreneurship of the left-behind. In: Giulietti C, Tatsiramos K, Zimmermann KF (eds) Labor market issues in China (Research in Labor Economics, Volume 37). Emerald Group Publishing Limited, pp 65–92

  • Glaeser EL, Sacerdote BI, Scheinkman JA (2003) The social multiplier. J Eur Econ Assoc 1(2):345–353

    Article  Google Scholar 

  • Hanushek EA (1992) The trade-off between child quantity and quality. J Polit Econ 100(1):84–117

    Article  Google Scholar 

  • Heston A, Summers R, Aten B (2012). Penn world table version 7:1. https://pwt.sas.upenn.edu/php_site/pwt_index.php

    Google Scholar 

  • IOM (2013) Extended migration profile of the republic of moldova. Tech. rep.,International Organisation for Migration, Chisinau. http://publications.iom.int/bookstore/index.php?main_page=product_info&cPath=42&productsid=929

  • Krauth BV (2005a) Fortran code for ”Simulation-based estimation of peer effects”. Version 1:1. http://www.sfu.ca/bkrauth/code.htm

    Google Scholar 

  • Krauth BV (2005b) Peer effects and selection effects on smoking among Canadian youth. Can J Econ 38(3):735–757

    Article  Google Scholar 

  • Krauth BV (2006) Simulation-based estimation of peer effects. J Econ 133(1):243–271

    Article  Google Scholar 

  • Lawton MP, Brody EM (1969) Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist 9(3):179–186

    Article  Google Scholar 

  • Lee L-f (2007) Identification and estimation of econometric models with group interactions, contextual factors and fixed effects. J Econ 140(2):333–374

    Article  Google Scholar 

  • Lloyd-Sherlock P (2000) Old age and poverty in developing countries: New policy challenges. World Dev 28(12):2157–2168

    Article  Google Scholar 

  • Luecke M, Omar Mahmoud T, Steinmayr A. (2009) Labour migration and remittances in Moldova:Is the Boom Over? Tech rep. http://hdl.handle.net/10419/32525

  • MacDonald M, Koh S-K (2003) Consistent motives for inter-family transfers: simple altruism. J Fam Econ Issues 24(1):73–97

    Article  Google Scholar 

  • Manski CF (1993) Identification of social endogenous effects: the reflection problem. Rev Econ Stud 60(3):531–542

    Article  Google Scholar 

  • McKenzie D, Rapoport H (2007) Network effects and the dynamics of migration and inequality: Theory and evidence from Mexico. J Dev Econ 84(1):1–24

    Article  Google Scholar 

  • MLSPF (2011) Annual Social Report 2010. Tech. rep.,Ministry of Labour, Social Protection and Family of the Republic of Moldova, Chisinau. http://mpsfc.gov.md/file/rapoarte/RSA2010en.pdf

  • MLSPF (2012) Implementation of the un convention on the rights of persons with disabilities. Tech. rep., Ministry of Labour, Social Protection and Family of the Republic of Moldova. www.ohchr.org/Documents/HRBodies/CRPD/Future/CRPD.C.MDA.1_en.doc

  • Munshi K (2003) Networks in the modern economy: mexican migrants in the U.S. labor market. Q J Econ 118(2):549–599

    Article  Google Scholar 

  • Perozek MG (1998) A reexamination of the strategic bequest motive. J Polit Econ 106(2):423–445

    Article  Google Scholar 

  • Pezzin LE, Schone BS (1999) Intergenerational household formation, female labor supply and informal caregiving a bargaining approach. J Hum Resour 34(3):475–503

    Article  Google Scholar 

  • Rapoport H, Docquier F (2006) The economics of migrant’s remittances. In: Kolm S., Ythier J M (eds) Handbook of the economics of giving, altruism and reciprocity. No 1531. Elsevier, Amsterdam, Ch. 17

  • Sacerdote B (2001) Peer effects with random assignment: Results for dartmouth roommates. Q J Econ 116(2):681–704

    Article  Google Scholar 

  • Sloan F. a., Picone G, Hoerger TJ (1997) The supply of children’s time to disabled elderly parents. Econ Inq 35(2):295–308

    Article  Google Scholar 

  • Stark O, Bloom DE (1985) The new economics of labor migration. Am Econ Rev P&P 75(2):173–178

    Google Scholar 

  • Winters P, de Janvry A, Sadoulet E (2001) Family and community networks in Mexico-U.S. Migration J Hum Resour 36(1):159–184

    Article  Google Scholar 

  • Wolf DA, Freedman V, Soldo BJ (1997) The division of family labor: Care for elderly parents. J Gerontol Ser B 52B:102–109

    Article  Google Scholar 

  • Woodruff C, Zenteno R (2007) Migration networks and microenterprises in Mexico. J Dev Econ 82(2):509–528

    Article  Google Scholar 

  • Worldbank (2007) From red to gray: the third transition of aging populations in eastern europe and the former soviet union. http://web.worldbank.org/WBSITE/EXTERNAL/COUNTRIES/ECAEXT/0,,contentMDK:21378474pagePK:146736piPK:146830theSitePK:258599,00.html

  • Worldbank (2011) Migration and Remittance Factbook. http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTDECPROSPECTS/0,,contentMDK:21352016pagePK:64165401piPK:64165026theSitePK:476883,00.html

  • Yang D (2008) International migration, remittances and household investment: Evidence from philippine migrants’ exchange rate shocks. Econ J 118(528):591–630

    Article  Google Scholar 

Download references

Acknowledgments

I would like to thank Marcus Böhme, Brian Krauth, Judith Heidland, Toman Omar Mahmoud, Kacana Sipangule, Andreas Steinmayr, Rainer Thiele, Michaella Vanore, the editor, four anonymous referees, and seminar participants at the Kiel Institute for the World Economy, the University of Kiel, Maastricht School of Governance, SMYE 2013 and the 2013 AEL conference. All remaining errors are my own. Financial support from EuropeAid project DCI-MIGR/210/229-604 is acknowledged.

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    Tobias Stöhr

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Stöhr, T. Siblings’ interaction in migration decisions: who provides for the elderly left behind?. J Popul Econ 28, 593–629 (2015). https://doi.org/10.1007/s00148-015-0546-z

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