Alone but better off? Adult child migration and health of elderly parents in Moldova

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may AbstractIncreasing labor migration and simultaneous aging of societies are two important demographic developments many poor countries face. Elderly people who are left behind may experience a decrease in welfare when their children migrate. This paper investigates the effect of migration on various dimensions of elderly health using unique data from Moldova, which has one of the highest emigration rates in the world. We find positive migration effects on the body mass index (BMI), mobility and self-reported health. No effects are found on depression and cognitive capacity. We trace these positive outcomes to an income effect which leads to improvements in diet and a reallocation of time use from subsistence farming to leisure and sleep. These positive effects seem to compensate the elderly for decreasing social contact with their migrant family members.

Emigration, remittances, and the subjective well-being of those staying behind

“…Correcting reverse causality and selection bias is usually achieved using instrumental variables (Böhme et al 2015;Waidler et al 2016), natural experiments (Gibson et al 2011), or selection-correction procedures and matching (Borraz et al 2010). Nonetheless, finding convincing instruments that are only correlated with the migration decision but not subjective well-being is challenging.…”

“…The literature shows that migration and remittances can affect various socio-economic outcomes among those left behind, such as poverty and income (Adams 2011;Gibson et al 2011), education (Antman 2012;Cortes 2015;Kroeger and Anderson 2014;Yang 2008), and health (Antman 2010;Böhme et al 2015;Gibson et al 2011;Kroeger and Anderson, 2014). Migrants can also change norms, attitudes, and behaviors back home.…”

“…The evidence for Thailand is more mixed, with Adhikari et al (2011) reporting a negative association and Abas et al (2009) finding the opposite. Providing causal estimates is a common challenge (Démurger 2015), and the few studies explicitly addressing causality (Böhme et al 2015;Gibson et al 2011;Waidler et al 2016) find that emigration has no effect on the mental health (captured by various indicators, including an index of feeling happy, peaceful, tense, blue and downhearted, and feeling depressed) of the elderly staying behind in Moldova and Tonga. 1 An emerging literature has considered the well-being consequences of receiving migrant remittances from abroad (which we define as transfers of money and goods made by migrants to the family members back home; henceforth, remittances).…”

Can Parental Migration Reduce Petty Corruption in Education?

“…21 The data for the migrant-destination share at the community level are derived from the 2004 Moldovan Census. 22 The variable has already been employed as an instrument for migration in other studies of the Moldovan context (Böhme, Persian, and Stöhr 2015;Lücke, Omar Mahmoud, and Peuker 2012). The rationale behind the use of Network-Growth is twofold.…”

“…23 For the migration network, we assume that past migration rates are predictors of current migration rates only via network effects and, otherwise, have no influence on the household's education spending. Accordingly, we include the 2004 share of the population who is a migrant to Italy, Romania, Russia and Ukraine as additional controls in the 2SLS setup to account for proximity to the border and any systematic differences in development that may have arisen because of migration to any of these important destinations between the take-off of migration, in 1999, and 2004, as in Böhme, Persian, and Stöhr (2015) 24 . Moreover, later in the paper we will match administrative data on public school expenditures to underscore the robustness of our identification strategy and to look for mediating factors in the private allocation of inputs.…”