Seasonal migration and improving living standards in Vietnam.

To this point, the results imply that increasing participation in migration leads to an increase in monetary well-being. However, Baulch and Masset (2003) found that in the VLSS, measures of monetary well-being are not strongly correlated with other non-monetary measures of well-being. We test our main result using height-for-age z-scores among children as the dependent variable, calculated using charts published by the Center for Disease Control. Since heights among children in the VLSS increased faster than weights (Glewwe, Koch, and Nguyen 2004), height-for-age z-scores are more likely to respond to migration than other measures of improved child nutrition. We found 3,770 children aged one to ten in 1993 with height measures in both surveys, and use the change in their z-scores between surveys as a dependent variable. To control for inherent differences between children in our regressions, we include the child's gender and age dummies (in years). We then tested whether migration affects height-for-age z-scores among children aged one to five, one to eight, and one to ten in 1993.

We find that increasing migration associated with improvements in child height-for-age z-scores among children aged one to eight and one to ten, but not aged one to five in 1993 (table 6). Among children one to five, we estimate a positive coefficient, but it is not statistically different than zero (columns 1 and 2). When we include children aged six to eight or six to ten in the regressions, we estimate coefficients between 0.375 and 0.45 on migration, depending upon the sample and specification (columns 3 to 6). These results are somewhat surprising given that height-for-age z-scores are usually associated with the aggregate stock of health in children, and one would expect effects among younger rather than older children. However, z-scores among children aged six to ten in 1993 were particularly low; they were -2.28 on average, whereas the average was -2.11 among younger children. As Glewwe, Koch, and Nguyen (2004) show a remarkable amount of catch-up in heights among children in Vietnam in general between the two surveys, our results suggest that in households with good access to migrant networks, catch-up among those children is associated with the increase in migration.

In summary, we find that when we control for the endogeneity of migration using two variables that measure the availability of networks to the household, we find that migration has a positive effect on both monetary and nonmonetary measures of well-being in the household. Had these households not increased their participation in migration, on average their per capita expenditures would have grown 5.2% slower between the surveys than they actually did. Since the average per capita expenditure growth rate in the sample was 5.7%, migration accounts for about 90% of expenditure growth for participating households.

Poverty, Inequality, and Migration

To further understand benefits and possible drawbacks of increasing migration in rural Vietnam, we calculate selected poverty and inequality measures for 1993 and for 1998, the latter both with and without migration. In calculating the counterfactual measure, we subtract the most conservative estimate of the effect of migration (5.2%) from actual expenditure growth, and calculate per capita expenditures in 1998 with the resulting lower growth rate for migrant households. We then compare the difference between the actual change in poverty and inequality measures with the change after removing the effect of migration.

Even though only 10% of households sent out migrants in 1998, the overall poverty rate would have been significantly higher had migration not occurred (table 7). Whereas 44.1% of rural individuals were below the poverty line in 1998, 47.4% of individuals would have been below the poverty line had migration not increased. Since 60.3% of individuals had expenditures below the poverty line in 1993, increased migration accounts for approximately one-fifth of the decline in the poverty headcount in rural Vietnam. Among households actually participating in migration, the poverty rate would have been much higher in 1998 (68.9 %), although these households were slightly more likely to be classified as poor in 1993 than other households (66%).

Although one might be tempted to conclude from these calculations that migration contributed to a significant decline in poverty, we want to note a few caveats. First, household expenditures are measured with error, which almost certainly affects whether or not households and individuals are labeled as poor. Positive or negative shocks may have affected expenditures in some households in either 1993 or 1998, also affecting whether or not households are labeled as poor. Finally, we base this calculation on per capita expenditures, and so individuals in large households may appear poor due to the presence of large numbers of children, whereas children consume less than adults. (9)

Inequality measures for 1998 with and without migration are quite similar (table 7, rows 3 and 4). Although the Gini coefficient increases slightly from 0.28 to 0.281 when we remove expenditure growth associated with migration, the Theil ratio drops slightly from 0.14 to 0.139 when expenditure growth associated with migration is removed. Neither difference is statistically significant. This finding is not surprising, as relatively few households participated in migration, so the expenditure distribution does not change much when expenditures associated with migration are removed. Moreover, the decrease in poverty suggests that migrant households do not come from the tail of the 1993 expenditure distribution, but rather from the middle. So, we can conclude that migration has helped decrease poverty in rural Vietnam without increasing inequality.

Conclusion

In this article, we study one way that rural households have taken advantage of Vietnam's rapid economic growth since the beginning of Doi Moi. Using two instruments that measure different types of migration networks, we find that we can attribute 5.2 percentage points of per capita expenditure growth to participation in migration for those households increasing participation in migration. Since the mean per capita expenditure growth rate was 5.7% among all rural households in the VLSS, most of the expenditure growth for those households can be attributed to migration.

We also find that without seasonal migration, the estimated poverty rate would have been three percentage points higher than it was in 1998. The reduction in poverty took place without an increase in inequality, in part because households that increased participation in migration tended to be in the middle of the expenditure distribution. As a result, during the period of study, increased migration reduced poverty without affecting inequality within rural areas, though it is unclear how inequality would have changed had there been more migration. These results imply that migration, in its infancy, has been positive for rural Vietnam. Migration could, however, negatively affect some types of urban workers, as wages might stagnate or fall in industries that attract migrants.

There are several ways that migration may have further affected Vietnam's rural economy during the 1990s that can serve as a basis for further research. First, we miss links between migrant households and other households within their communities (e.g., Taylor and Wyatt 1996). By expanding the money available within the community either to purchase goods and services or for investment (Francis and Hoddinott 1993), migration may lead to multiplier effects that further increase local development. Second, we know little about how migration may affect poverty persistence; further research is necessary to study how much, if at all, households that can be considered persistently poor are participating in or benefitting from migration in rural Vietnam. Appendix Table A1. Descriptive Statistics for Selected Variables, VLSS, 1992-1993 and 1997-1998 Variable 1992-3 1997-8 Per capita expenditures 1,732 2,360

(995) (1452) Number of migrants 0.025 0.140

(0.214) (0.461) Household demographics Women, aged over fifty-five 0.299 0.343

(0.473) (0.490) Men, aged over sixty 0.169 0.184

(0.375) (0.389) Women, aged eighteen to fifty-five 1.156 1.140

0.689 0.719 Men, aged eighteen to sixty 1.103 1.130

(0.771) (0.724) Children aged six to seventeen 1.59 1.56

(1.48) (1.37) Other household variables Years of schooling, 5.59

household head (3.90) Age of household head 45.10 --

(14.7) Total land holdings (hectares) 0.35 --

(0.48) Log value of productive assets 9.45 --

(0.90) Commune level variables Distance to road (km) 1.09 --

(3.33) Log, commune population 8.90 --

(0.58) Total land, commune (hectares) 3.49 --