The main objective of this paper is to propose a systematic approach to empirically analyse the relationship between sending remittances and the utility of migrants, as proxied by their subjective well-being (SWB). Using data from a new survey on China, we estimate models in which a SWB measure is regressed on the level of remittances, finding a sizeable positive correlation. The estimates vary with the socio-economic characteristics of migrants, migration experience and the diversity of family arrangements. As a complementary objective, we use SWB measures to elicit the motivations behind remittances, finding evidence that both altruistic and contractual motivations are at work among rural-to-urban migrants in China.
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Among the major findings documented are the relatively large disutility from being unemployed (Clark and Oswald 1994; Winkelmann and Winkelmann 1998; Clark 2003); that age and SWB exhibit a U-shaped relationship (Blanchflower and Oswald 2004); that married people have higher SWB than those unmarried (Clark and Oswald 2002); and that both absolute and relative income affect SWB (Easterlin 1995; Clark et al. 2008).
The relationship between remittances and well-being has been explored by Borraz et al. (2010), who focus on the welfare consequences of household members left behind in Ecuador. The authors document that while remittances have a positive effect on well-being, they do not compensate for the costs associated with the absence of migrants from the household. Another strand of the literature somewhat related to our approach focuses on monetary donations and SWB (Dunn et al. 2008; Konow 2010; Tsai and Dzorgbo 2012).
From a policy perspective, understanding what drives the remittance behaviour is important in order to assess, for instance, whether public redistributive policies crowd-out private transfers (Cox and Fafchamps 2007).
According to hukou regulations, migrants are generally allowed to reside in a city as long as they are employed or up to six months after unemployment. During the 1990s, the hukou regulations were partially reformed. Since then, migrants who attain certain levels of education or income, have been granted urban hukou. More recently, migrants have been allowed partial access to public medical insurance in urban areas. However, the persistence of hukou regulations still implies that welfare is accessible mostly at the place of residence. Hence migrants are not eligible to access benefits such as public housing and pensions schemes, and furthermore they are often employed in low-wage occupations.
Although more recent waves of RUMiC are available, our analysis focuses on the first wave, as this collects information of the period preceding the financial crisis that started at the end of the 2000s. The ability of the survey to track migrants over time was hindered by the financial crisis. As of the end of 2008, around 23 million migrants had returned to their home village, the majority jobless and in need of new employment (National Bureau of Statistics of China 2010). Furthermore, the crisis might have temporarily distorted the remittance behaviour after 2008. Accordingly, our analysis focuses on a less recent, yet more representative period.
In our analysis we focus on household heads assuming that they are the “breadwinners”, and those who ultimately decide the amount to remit to the family back home. We prefer to restrict our sample to household heads principally because we do not have information on how the income is pooled between household members, nor do we have further information concerning intra-household bargaining power. For completeness, we have extended our analysis to other members of the household, obtaining very similar results to our benchmark. We also exclude unemployed individuals because most internal migrants in China are migrant workers. Our sample shows that virtually all migrants (99.5 %) are employed, owing to few migrants having access to social assistance or unemployment benefits in urban areas and hence if they become unemployed and cannot find another job, they are likely to return back to their villages.
Migrants in our sample originate from both rural areas where the one-child policy, implemented in China since the end of the 1970s, is binding, and from areas where the policy is not binding. The fact that migrants report having fewer than one child mainly reflects that they are relatively young and that half of them are unmarried.
Full estimation results of our benchmark specification are reported in Akay et al. (2012).
For completeness, we also estimate regression models using the level of remittances as dependent variable. Once again, the scope is to investigate how our estimates compare to those of previous studies. We consider two specifications: one for the whole sample of migrants, using tobit regression (i.e., accounting for the censoring of remittances for those migrants who do not send money back home) and one for the sub-sample of remitters. Our results are very similar to previous studies (see, e.g., Lucas and Stark 1985; Hoddinott 1994; Vanwey 2004; Piracha and Saraogi 2011). These estimates are reported in Table A3 of Akay et al. (2012).
The Ordered Probit models are estimated using a variable that is an aggregation of the GHQ-12 index into a 7-class ordered variable.
Full estimates of all models are available upon request.
All models include additional income-related variables, such as an indicator for self-employment status.
We have also conducted robustness tests to check the sensitivity of the estimates to the presence of unobservable regional attributes. In practice, we compare estimates of models without and with (our preferred estimates) fixed effects for provinces of origin and destinations of migrants. While the estimates become smaller in size when controlling for province fixed effects, our main results still hold even after controlling for these important confounding factors. These results are reported in Table 4 of Akay et al. (2012). Furthermore, in unreported results we have estimated models with 15 city of residence dummies instead of 9 indicators for provinces of residence. The results are essentially similar; for example, the benchmark regression yields a coefficient of 0.356 with a standard error of 0.124.
We have also estimated a model in which we use the happiness measure as dependent variable. Consistently, we found a positive correlation between sending remittances and happiness, albeit with estimates only significant at 10 % (0.086 with a standard error of 0.048). The weak statistical significance is mainly attributable to the happiness variable being defined in a four point scale, hence exhibiting scarce variation.
We have also explored the interaction between remittances and income, using quartiles of the income distribution. Even in this case, we found that the marginal utility of remittances decreases monotonically with income, reflecting the diminishing marginal utility associated with the concavity of the SWB function.
It is important to emphasize that since we analyse internal migration, the migration experience could be interrupted, i.e., migrants might have returned back home in between the period that they were interviewed and when they left home for the first time. Inspection of the RUMiC data suggest that only 16 % of migrants have been back to their hometown for longer than 3 months since their first migration, and therefore circular migration is unlikely to affect our results.
Our data indicates that 57 % of migrants moved within the home province.
The exact wording of the question is: “If policy allowed, how long would you like to stay in the city?” Hence, this question relates to a hypothetical scenario of a policy allowing unconditional residence of migrants in the city. The hypothetical nature of the question owes to policy generally not encouraging migrants to reside permanently in cities.
Table 7 in Akay et al. (2012) reports the average level of remittances for these groups. As one would expect, the level of remittances increases with the degree of “responsibilities” towards the family left behind in the hometown. For example, a migrant whose spouse is left behind yet has no children remits more than a migrant who is single, but less than a migrant whose spouse and children live in the hometown.
More than 75 % of the migrants report having parents still alive in the hometown, which reflects the quite young age of migrants in our sample.
Becker (1974) model of altruistic remittances assumes “pure” altruism. However, there are other forms of altruism identified within the literature. One such example is the “warm glow” altruism suggested by Andreoni (1989). Such “impure altruism” would imply that migrants derive utility simply from sending money, but not from the improvement of the conditions of the family back home. Our data does not allow us to distinguish between “pure” and “impure” altruism, and hence our results necessarily pertain to both forms of giving.
An additional key variable that would have been useful for the analysis is the actual level of SWB of the family members left behind; however this is not available in our data.
In principle, the size of the land per capita is a good proxy for capturing economic conditions of the family left behind. Although land in China is not owned by individuals, it is still a productive asset. However, most of the variation in land per-capita is attributed to differences across rather than within villages. The value of the property back home is also a potentially useful proxy. Aside from measurement issues, the main problem of this variable is yet again its intrinsic scarce variation in our sample. Our fourth proxy makes use of a variable that classifies the family background of migrants’ parents as: (1) Extremely poor, (2) Poor, (3) Intermediate rich, and (4) Rich. We aggregate categories (1) and (2) to capture a “poor” background of the family left behind, and (3) and (4) into a relatively “rich” category.
The estimates of these models are reported in Akay et al. (2012).
We have replicated this analysis by using per capita remittances and found that the pattern of the two curves is even more similar than that in Fig. 1.
A very similar pattern emerges when we use indicators for health status.
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The authors would like to thank two anonymous referees for constructive comments. We are grateful also to Catalina Amuedo-Dorantes, Albert Park and participants in: the 4th CIER/IZA Workshop in Bonn, seminars at the National Centre for Social and Economic Modelling of the University of Canberra, at Temple University, at Princeton University, the 24th EALE Conference in Bonn, the 7th IZA/World Bank Conference in New Delhi and the Chinese Economists Society Session “Challenges for the Chinese Labor Market” at the 2013 ASSA Meeting in San Diego. The paper is based on the IZA Discussion Paper 6631 “Remittances and Well-Being among Rural-to-Urban Migrants in China”. The Longitudinal Survey on Rural Urban Migration in China (RUMiC) consists of three parts: the Urban Household Survey, the Rural Household Survey and the Migrant Household Survey. It was initiated by a group of researchers at the Australian National University, the University of Queensland and the Beijing Normal University and was supported by the Institute for the Study of Labor (IZA), which provides the Scientific Use Files. Financial support for RUMiC was obtained from the Australian Research Council, the Australian Agency for International Development (AusAID), the Ford Foundation, IZA and the Chinese Foundation of Social Sciences.
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Akay, A., Giulietti, C., Robalino, J.D. et al. Remittances and well-being among rural-to-urban migrants in China. Rev Econ Household 12, 517–546 (2014). https://doi.org/10.1007/s11150-013-9208-7
- Subjective well-being