Peer Migration in China Yuyu Chen Peking University, Guanghua School of Management Ginger Zhe Jin University of Maryland & NBER Yang Yue Xiamen University October 4, 2018 Abstract With 280 million rural laborers migrating to the city in 2017, China is experiencing the largest internal migration in the human history. Using instrumental variables in the 2006 China Agricultural Census, we find that a 10-percentage-point increase in the migration rate of co- villagers raises one's migration probability by 9.18 percent points. Both information exchange at the origin and cost reduction at the destination could explain migration cluster in age, destination, and occupation. However, migration has little effect on the agricultural productivity of non- migrants, probably because labor redundancy is severe at the origin and migrants are more likely of high productivity. Keywords: internal migration, social network, China. JEL: J6, O12, R23. Contact information: Yuyu Chen, Guanghua School of Management, Peking University. Email: [email protected]. Ginger Zhe Jin, Department of Economics, University of Maryland, College Park, MD 20742. Email: [email protected]. Yang Yue, Wang Yanan Institute for Studies in Economics and School of Economics, Xiamen University. Email: [email protected]. This project is a collaborative effort with a local government of China. We would like to thank Hongbin Cai, Wei Li, Brian Viard, Roger Betancourt, Loren Brandt, Judy Hellerstein, John Ham, Matthew Chesnes, Seth Sanders, V. Joseph Hotz, Duncan Thomas, Francisca Antman and Hillel Rapoport for helpful comments. All errors are our own. 1 1. Introduction The past 30 years has witnessed an explosive growth of labor migration inside China. In 1990, 34.1 million workers had left their rural home for urban jobs (Cai 1996). This number increased to 67 million in 1999 (Huang and Pieke 2003), 131.81 million in 2006, 140.41 million in 2008, and 280 million in 2017.1 In aggregate, labor transfer out of agriculture accounts for nearly one-ninth of the annual GDP growth of China (Young 2003).2 However, due to Hukou3 and other institutional barriers, most migrating workers do not migrate permanently to the city (Zhao 1999a & 1999b). They leave families behind and travel between rural home and urban job every year. We aim to understand factors that drive such migration, with special attention to the role of peers at the origin. In theory, peer effects on job migration can be positive or negative. On the one hand, job information is easier to share within a village. Earlier migrants can also help new migrants to reduce moving cost at the same destination, even if they do not work in the same occupation. If these positive peer effects are clustered by age and gender, it could lead to significant demographic “holes” in the originating village. On the other hand, migration makes more arable land available for non-migrants at the origin. If migration improves the agricultural productivity and social function of remaining villagers, peer effects can be negative. Since different peer effects imply different policies in labor migration and local development, it is important to identify the sign and magnitude of the peer effects. The biggest challenge is identifying peer effects from confounding factors that affect peers at the same time (Manski 1993). Survey evidence often cites informal contacts (such as family, friends and other acquaintances) as the most important channels that lead to employment (Loury, 2006, Pellizzari 2010). In addition, several papers have attempted to identify peer effects from observational data, using either instrumental variable or detailed network information (Munshi 2003, Mckenzie and Rapoport 2007, Woodruff and Zenteno 2007, Chen et al. 2008, Hiwatari 2016). Built upon this literature, we derive novel instruments from China’s unique “one-child” policy. Starting 1984, China has allowed rural households to have a second baby if the first child is a girl. Not only 1 The latter two numbers are based on National Bureau of Statistics reports accessed at http://www.stats.gov.cn/tjgb/nypcgb/qgnypcgb/t20080227_402464718.htm and http://www.stats.gov.cn/tjfx/fxbg/t20090325_402547406.htm on September 1, 2010. In these reports, migrating workers are defined as rural laborers that have migrated for jobs out of the residential township for at least one month during the calendar year. 2 Young (2003) calculates the annual 7.8% GDP growth based on published data from 1978 to 1998. He shows that the deflated annual growth is 6.1%, of which 0.9% can be attributable to the increase of labor participation. 0.9% is approximately one-ninth of 7.8%. 3 Hukou is a residential permit that is often determined by one’s birthplace. Until the late 1990s, it was extremely difficult for an individual with a rural Hukou to live or work in the city, unless he/she attends college, joins the military, and finds an urban unit to accept him/her after graduation. As of today, individuals with rural Hukou can work in the city but they face many restrictions in receiving education, worker protection, disability assistance, social security, health insurance, or other social benefits in the city for themselves or their family members. 2 does this policy minimize sex selection on the firstborns4, it also implies that rural households with a girl firstborn are more likely to have a second child and less likely to have any boy. Because of this effect on the family size and on the children’s gender composition, having a girl firstborn tends to encourage adult males (e.g. fathers and grandfathers) to migrate but hinder adult females (mothers and grandmothers) from migration. In contrast, having multiples in the firstborn is a random shock to a household, which demands more efforts in child care and ends up discouraging labor migration. Based on these variations, we construct IVs for neighbors’ migration decision using the gender and number of neighbors’ firstborn, where neighbors are defined as residents in the same village. The key assumption is that one household’s fertility outcome does not directly affect the migration decision of its neighbors. We validate this assumption through a variety of statistical tests and robustness checks. Our IV results find an overall positive peer effect in migration: a 10 percentage point increase in the percent of 17-35 year old neighbors migrating out of a village will increase one’s own migration probability by 9.18 percentage points. This effect is stronger from people in the same village than from people in other villages in the same township, confirming our choice of village as the unit of potential peers. A closer look finds the peer effect clustered by age, surname, destination and occupation at the destination. In the meantime, the agricultural income of non-migrants does not change significantly as a result of peer migration in the same village, although they have more land to work with. These results suggest that both information exchange at the origin and cost reduction at the destination could explain the positive peer effects, but migration has little effect on the agricultural productivity of non-migrants, probably because labor redundancy is severe at the origin and laborers of high productivity are more likely to migrate. The rest of the paper is organized as follows. Section 2 provides a brief literature review. Section 3 describes the background and data. Section 4 lays out a basic specification and reports the IV results. Section 5 zooms into peer effects in demographic groups, destinations, and types of jobs. Section 6 examines the effects of migration on the land use and agricultural income of non-migrants. Section 7 concludes. 2. Literature Review The existing literature has stressed the importance of peer effects in both labor migration and job search, but empirical evidence lags behind theory. In job search, Calvo-Armengol and Jackson (2004) show that job information sharing within a social network can explain why employment rate varies across networks, why unemployment rate persists in some networks, and why inequality across networks can be long lasting. Their model implies that a public policy that provides incentives to reduce initial labor market 4 Sex selection may take several forms ranging from selective abortion, to abandon of newborns, to infanticide. 3 dropout could have a positive and persistent effect on future employment.5 In a similar spirit, Carrington et al. (1996) establish a dynamic model of labor migration in which earlier migrants help later migrants to reduce moving costs at the same destination. In their model, migration occurs gradually but develops momentum over time. It explains why migration tends to cluster by geography and why migratory flows may increase even as wage differentials narrow. To the extent that information sharing and moving cost reduction are easier among peers of similar age, gender and education, the positive peer effects on migration could generate demographic holes in the origin. In the meantime, other theories suggest that peer effects on labor migration can be negative because the migrating origins are often closely-knit communities. These communities – often small and rural -- count on internal members to help out each other in local economic and social development (Liu 2010). If some work-age males migrate out of a village, they can lease out agricultural land to remaining work-age males, which increases the labor income of stayers and reduces their economic incentives to emigrate. Similarly, peers’ migration decisions may be negatively correlated if they are close relatives and coordinate in non-agricultural activities such as elderly care and child care. Turning to the empirical literature, numerous facts of migration are consistent with the social network theory of peer migration, but causal links are difficult to establish. For example, many surveys find that having friends or relatives at the destination is positively correlated with one’s migration decision (Caces et al.