Migration to competing destinations and off-farm employment in Rural Vietnam: a conditional logit analysis

Type Report
Title Migration to competing destinations and off-farm employment in Rural Vietnam: a conditional logit analysis
Publication (Day/Month/Year) 2008
URL http://econpapers.repec.org/RePEc:dpc:wpaper:2208
In this paper, we explore employment decision of Vietnamese farmers as having five choices: staying on the farm exclusively, staying in the village but partially engaging in local off-farm activities, and working outside the home region for a certain period, in which destination options are Hanoi, Ho Chi Minh City and Other which combines the remaining places. This choice model departs from the existing literature in several aspects. Firstly, previous papers focused mainly on the population that takes off-farm jobs or migrate, that are dichotomous employment choice. More importantly, most existing papers using the random utility model ignore factors in the destination areas. They assume implicitly that either migrants choose their destination randomly or that all migrants face exactly the same migration choices. In our paper, we allow multi-destination possibility, and examine impacts of distance, wages and social network on migrants' decisions. The indirect utility of a given migration option is modeled as a function of choice attributes and individual specifics. Choice attributes for each migration option include wage in destination area, transport between origin and destination area which is proxied by the corresponding distances, and social network of the migrants, while those for farm and non-farm option mainly include agricultural prices and local job creation opportunities. Individual specific include age, education, gender, marital status, share of children and elderly in the household. The data used in this research are the Vietnam Living Standard Survey (1998) which is until now the only available data set that provides information on the migrant destinations. We start by estimating determinants of wage in destination areas using full information maximum likelihood to overcome selection bias. Then, we predict wages of those who do not currently work for wage. Finally, we run a conditional logit estimation with predicted wage being one of the explanatory variables to examine probability of migration to each location choice and of taking off-farm employment. Our results show that wage and network have significantly positive effects on all migration choices, while distance negatively affects them. Impact magnitude however differs across destination locations.

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