Hoang Linh Vu - Academia.edu (original) (raw)

Papers by Hoang Linh Vu

Rural-Urban Migration in Vietnam, 2019

We investigate determinants of individual migration decisions in Vietnam, a country with increasi... more We investigate determinants of individual migration decisions in Vietnam, a country with increasingly high levels of geographical labour mobility. Using data from the Vietnam Household Living Standards Survey 2012 (VHLSS2012), we find that the probability of migration is strongly associated with individual, household and community-level characteristics. The probability of migration is higher for young people and those with post-secondary education. Migrants are more likely to be from households with better-educated household heads, female-headed households, and households with higher youth dependency ratios. Members of ethnic minority groups are much less likely to migrate, other things being equal. Using multinomial logit methods, we distinguish migration by broad destination, and find that those moving to Ho Chi Minh City or Hanoi have broadly similar characteristics and drivers of migration as those moving to other destinations. We also use the VHLSS2012 together with the VHLSS2010, which allows us to focus on a narrow cohort of recent migrants—those present in the household in 2010, but who had moved away by 2012. This yields much tighter results. For education below upper secondary school, the evidence on positive selection by education is much stronger. However, the ethnic minority “penalty” on spatial labor mobility remains strong and significant, even after controlling for specific characteristics of households and communes. This lack of mobility is a leading candidate to explain the distinctive persistence of poverty among Vietnam’s ethnic minority populations, even as national poverty has sharply diminished.

2009 Annual Meeting, July 26-28, 2009, Milwaukee …, 2009

Changes and trends in farm productivity have been of intense interest to many involved with agric... more Changes and trends in farm productivity have been of intense interest to many involved with agriculture. This study used data envelopment analysis (DEA) to estimate the output-oriented Malmquist total factor productivity (TFP) index from panel data for 1993-2006 for ...

Agricultural Economics, 2009

Factors explaining differences in economic efficiency between farms are of major interest to owne... more Factors explaining differences in economic efficiency between farms are of major interest to owners, managers, and other stakeholders as they strive to improve earnings and improve the chances of firm survival. This study is undertaken to improve our understanding of interfarm differences in, and opportunities to improve, farm household efficiency in utilizing their land, labor, and capital resources to achieve household objectives. The technical, allocative, and scale efficiencies of farm households are estimated using a nonparametric, output-based data envelopment analysis (DEA) of a panel data set from 1993 to 2006. Single and double bootstrapping procedures are used to estimate technical efficiency. Initial technical efficiency assuming variable returns to scale (TEV) is estimated to be 0.83. Using single bootstrapping, the average bias-corrected TEV estimate is 0.70; using double bootstrapping, the TEV estimate is 0.72. Allocative efficiency is estimated to be 0.81. Scale efficiency is estimated to be 0.93. The only factor that is consistently associated with higher technical efficiency across analysis methods and years is larger farm size (as measured by the log of farm income). The significance of other factors changes with analysis methods.

Rural-Urban Migration in Vietnam, 2019

We investigate determinants of individual migration decisions in Vietnam, a country with increasi... more We investigate determinants of individual migration decisions in Vietnam, a country with increasingly high levels of geographical labour mobility. Using data from the Vietnam Household Living Standards Survey 2012 (VHLSS2012), we find that the probability of migration is strongly associated with individual, household and community-level characteristics. The probability of migration is higher for young people and those with post-secondary education. Migrants are more likely to be from households with better-educated household heads, female-headed households, and households with higher youth dependency ratios. Members of ethnic minority groups are much less likely to migrate, other things being equal. Using multinomial logit methods, we distinguish migration by broad destination, and find that those moving to Ho Chi Minh City or Hanoi have broadly similar characteristics and drivers of migration as those moving to other destinations. We also use the VHLSS2012 together with the VHLSS2010, which allows us to focus on a narrow cohort of recent migrants—those present in the household in 2010, but who had moved away by 2012. This yields much tighter results. For education below upper secondary school, the evidence on positive selection by education is much stronger. However, the ethnic minority “penalty” on spatial labor mobility remains strong and significant, even after controlling for specific characteristics of households and communes. This lack of mobility is a leading candidate to explain the distinctive persistence of poverty among Vietnam’s ethnic minority populations, even as national poverty has sharply diminished.

2009 Annual Meeting, July 26-28, 2009, Milwaukee …, 2009

Changes and trends in farm productivity have been of intense interest to many involved with agric... more Changes and trends in farm productivity have been of intense interest to many involved with agriculture. This study used data envelopment analysis (DEA) to estimate the output-oriented Malmquist total factor productivity (TFP) index from panel data for 1993-2006 for ...

Agricultural Economics, 2009

Factors explaining differences in economic efficiency between farms are of major interest to owne... more Factors explaining differences in economic efficiency between farms are of major interest to owners, managers, and other stakeholders as they strive to improve earnings and improve the chances of firm survival. This study is undertaken to improve our understanding of interfarm differences in, and opportunities to improve, farm household efficiency in utilizing their land, labor, and capital resources to achieve household objectives. The technical, allocative, and scale efficiencies of farm households are estimated using a nonparametric, output-based data envelopment analysis (DEA) of a panel data set from 1993 to 2006. Single and double bootstrapping procedures are used to estimate technical efficiency. Initial technical efficiency assuming variable returns to scale (TEV) is estimated to be 0.83. Using single bootstrapping, the average bias-corrected TEV estimate is 0.70; using double bootstrapping, the TEV estimate is 0.72. Allocative efficiency is estimated to be 0.81. Scale efficiency is estimated to be 0.93. The only factor that is consistently associated with higher technical efficiency across analysis methods and years is larger farm size (as measured by the log of farm income). The significance of other factors changes with analysis methods.