Abstract
In this paper we investigate whether adult children’s internal migration influences expenditure behaviour of households left behind in rural China, and how this impact differs among different types of migrants. Exploiting unique hukou information from the China Health and Retirement Longitudinal Study, we explicitly distinguish between temporary and permanent migration. To deal with the endogeneity of migration, we implement an instrumental variable approach. Our results reveal remarkably distinct effects on household expenditure patterns depending on whether children migrate temporarily or permanently to urban areas. Households with temporary migrant children spend more on one key consumption good—food—and invest less. In contrast, permanent migration of children exerts no impact on household consumption but increases productive investment. Therefore, policymakers should view permanent migration as a potential pathway to foster local economic development.
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Notes
In our paper, we define permanent migrants as those who migrated from rural to urban areas with a local urban hukou registration (hukou migrants), and temporary migrants as those who migrated without hukou changes (non-hukou migrants).
There are other terminologies commonly used to describe these two forms of migration. For example, temporary migration is also called short-term/circular/repeat/informal migration, and permanent migration is also called long-term/planned/formal migration.
Before this reform, the hukou registration had been passed on from mother to child. After the reform, a newborn child was also allowed to inherit their father’s hukou. In addition, a child under the age of 18 could change the hukou status from the mother’s to father’s.
The data are publicly available at the project website: https://opendata.pku.edu.cn/dataverse/CHARLS.
Tibet is beyond the interest of the survey. Hainan and Ningxia are excluded due to very small populations.
In the CHARLS survey, there are two questions that can be used to identify a child’s migration status. The first question asks “How many months in the past year did the child live away from home”, and the second asks “Where does the child normally live now”. The latter question generally produces a more instructive measure since it captures current migrants rather than return migrants, some of whom may be mistakenly included in the analysis if the former question was used. Limiting attention to current migrants here is important because the returnees are sharing the household budget at the time of the survey. Unfortunately, our preferred question on current migration status is only available for all children in the second round (2013–2014), and this question was not asked to co-resident children in the first wave (2011–2012), who instead answered the question about the length of time away from home over last year. Thus including the first wave would produce inconsistent and even incorrect measures on the migration status of the child.
We treat health as a productive item because numerous studies have found that health expenditure can increase the productivity of labour.
Results using province fixed effects rather than region fixed effects are remarkably robust and will be available upon request.
In Fig. 1a, we check the correlation between children’s age cohorts in 1997 and both the observed rates and predicted probabilities of permanent migration. The observed migration rates (blue dot) are unconditional means of permanent migration obtained from child-level data. The point estimates (red dot) and the 95% confidence interval (red bar) of predicted migration probabilities are calculated from running a linear probability model based on the estimations in Table 3 using household-level data. All else equal, children in the 15–18 age group in 1997 have a systematically higher probability of permanently settling in urban areas than other age groups. A similar pattern is seen in actual migration rates. In Fig. 1b, we conduct a non-parametric analysis to examine the smoothed relationship between permanent migration and children’s age (continuous measure) in 1997. The linear smoothing is derived from performing a non-parametric series regression and a kernel-weighted local polynomial regression of a binary variable indicating whether the child is a permanent migrant on child age. The figure shows that the smoothed values of permanent migration peak in the policy year (1997), increasing our confidence in the explanation power of the instrument on migration. We focus on permanent migration here because it seems reasonable to assume that this type of migration would be more affected by the relaxation of the hukou system. Nevertheless, the pattern of results remains similar when looking at temporary migration. This is also confirmed by the first stage estimates (Table 3), where we see that the estimated effect of children’s exposure to the hukou reform on permanent migration is larger than that on temporary migration.
The average migration rate is 13.41%, and the average distance to main railway station is 8.62 km.
These calculations are based on the estimated coefficient for the migration network distance interaction term (0.071) and the average migration rate (13.41%) as well as the average distance to main railway station (8.62 km). It is important to note that the two factors of the interaction influence migration in opposite directions, which makes interpretation of the results difficult. In unreported results, we introduce both migration networks and its interaction with distance in the estimation to see whether the effect of migration networks is reinforced or attenuated by distance. We find that the observed effects of the first IV on temporary migration are mostly driven by migration networks rather than distance. Moreover, the positive impact of migration networks is stronger in the case of a closer distance. We thank the anonymous referee for raising this point.
We also statistically test the effect of the distance on household budget shares and derive similar results. Results on these additional analyses are available from the authors.
To determine the poverty status of a village, we referred to China’s official poverty line, which is 2433 RMB per year in 2011.
The corresponding second-stage estimates will be available upon request. The point estimates of interest are insensitive to these changes.
We thank the anonymous referee for raising this point.
This broad definition of remittances is similar to that used by Clément (2011), in which remittances are defined as “money and goods sent from one place or person to another”.
This data limitation warrants caution in the interpretation of the results. Since our analytical sample effectively excludes all households that have both temporary and permanent migrant children, which account for about 17% of the migrant households, our findings regarding the impact of remittances may not be generalised to the entire migrant households in rural areas.
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Acknowledgements
We are grateful to the editor Eleanor P. Brown and two anonymous referees for their thoughtful comments. We would also like to thank Jackline Wahba, Corrado Giulietti and Richard Upward for helpful discussion and suggestions. Chuhong Wang would like to acknowledge financial support from the UK Economic and Social Research Council (ESRC). Zizhong Yan acknowledges the support from the 111 project of China (project number B18026). Any errors are ours alone.
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All authors contributed to the study conception and design and have been closely involved in writing up of this paper at various stages. Material preparation and data processing were performed by C.W. and Z.Y. Econometric methodology, empirical analysis, writing, reviewing, revision and editing were performed by C.W., X.L. and Z.Y. The first draft of the manuscript was written by C.W. and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Wang, C., Liu, X. & Yan, Z. Temporary versus permanent migration: The impact on expenditure patterns of households left behind. Rev Econ Household 19, 873–911 (2021). https://doi.org/10.1007/s11150-020-09505-y
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DOI: https://doi.org/10.1007/s11150-020-09505-y