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Migration Duration and Migration Outcomes

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Rural-Urban Migration in Vietnam

Part of the book series: Population Economics ((POPULATION))

Abstract

This chapter uses the 2013 Vietnam Rural–Urban Migration Survey to study the factors associated with duration of migration and how migration duration may relate to migration outcomes. Our models show that an increase in the migration duration is closely related to migrants’ age, education and parental socioeconomic status. We additionally find that migrants with longer migration duration have better labour market outcomes as measured by a greater probability of working or higher family incomes. Migration duration, however, is not statistically significantly associated with migrants’ life satisfaction.

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Notes

  1. 1.

    This gap in the literature is presumably due to a lack of migration duration information in commonly used datasets in Vietnam. Datasets such as censuses, Vietnam Household Living Standards Surveys (VHLSSs), and the Vietnam Migration Survey 2004 only contain information on either temporary or permanent migrants, but not both.

  2. 2.

    Household members younger than 16 are not asked the relevant questions.

  3. 3.

    We do not have information about the respondent’s place of birth in the data so can’t use it to define migrants.

  4. 4.

    A lack of panel data has precluded us from estimating a hazard model, which is typically used in migration duration studies (Wooldridge 2010). Here our measures of migration ‘duration’ are simply measured at one point in time (Wooldridge 2010).

  5. 5.

    According to Vietnamese culture, sons, especially eldest sons, are expected to take care of their elderly parents and this may affect their migration decisions (Nguyen et al. 2012). To test whether being the oldest son affects the migration decision, we interacted the variable indicating whether the migrant is the oldest child with the gender dummy of the migrant. The estimates for the interaction term are not statistically significant in all regressions. These results will be available upon request.

  6. 6.

    Questions about the economic background of parents are asked regardless of whether the parents are alive. Unfortunately, the data do not allow us to identify fathers and mothers separately. Hence, the variable parental socioeconomic background refers to the socioeconomic background of the parent with the highest status.

  7. 7.

    We do not include the age at first migration as an explanatory variable due to the issue of multi-collinearity. In our sample, about three-quarters of migrants have not migrated for work purposes to cities other than the current one. For them, their years in the current host city (which we control for in the regression) equal their current age (which we also include in the regression) minus the age at migration. Similarly, we do not include the age at migration in the migration outcome equations as we have also controlled for years in the host city.

  8. 8.

    Due to data unavailability, the current chapter cannot further control for other local variables such as economic opportunities, as has been done in some previous work (Démurger 2012; Dang 2015).

  9. 9.

    There is a large literature devoted to examining economic aspects of subjective wellbeing/life satisfaction/happiness. See, for example, Frey and Stutzer (2002), Di Tella and MacCulloch (2006), Kahneman and Krueger (2006), Clark et al. (2008), and Ferrer-i-Carbonell (2013) for reviews. Recently, studies have investigated the impact of home countries’ macroeconomic conditions on the happiness of international immigrants (Nguyen and Duncan 2018; Akay et al. 2017).

  10. 10.

    For the 18 (six) migrants reporting zero monthly (yearly) income, we assign an arbitrary and small number (VND1000) to them in order to take the log.

  11. 11.

    This is based on the fact that migrants in our sample are quite young (i.e. 30 years old). Unfortunately, data do not allow us to identify the ages of the non-co-residing children of the migrants who are not the head of the household.

  12. 12.

    About 69% of migrants in our sample are identified as the household head. Household heads are the household’s breadwinners, so their decisions may not be the same as those of other household members. To investigate this possibility, we estimated Eq. (1) for a sample of household heads only. Estimation results are largely similar to those presented for the whole sample of migrants in terms of the magnitude and direction, indicating that the above prediction does not hold with our data. Unfortunately, the small sample size of our data prevents us from estimating our empirical models for males and females separately.

  13. 13.

    (3.08–2.51)*12≈7 (months).

  14. 14.

    Unfortunately, the data do not provide information about the time and location of university graduation for us to test this prediction.

  15. 15.

    Parents and their children may make decisions about migration (duration) and co-residence together, so our living arrangement variables (such as the number of (non)-co-residing children or the number of co-residing parents) could be endogenous in our migration duration models (Nguyen et al. 2012). We test this possibility by excluding these living arrangement variables from the regressions and find the estimates for other remaining variables are largely unchanged.

  16. 16.

    Only the dummies for Northern Uplands and Central Coast are interacted with the dummy for Hanoi. Other regional variables (i.e. Central Highlands, South-East and Mekong River Delta) are not used because there were no migrants from these regions living in Hanoi in our sample.

  17. 17.

    In this experiment, we introduce the two additional migration duration measures linearly because migration duration variables are highly correlated. Results for other variables are largely similar to those reported in Table 3 so they are not reported for brevity purposes.

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Acknowledgements

Comments and suggestions on a previous version of the paper from Cahit Guven, Amy Liu, Xin Meng, and participants at the Vietnam Rural–Urban Migration Survey (VRUMS) Conference are gratefully acknowledged.

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Authors and Affiliations

  1. Bankwest Curtin Economics Centre, Curtin Business School, Curtin University, Perth, WA, Australia

    Ha Trong Nguyen

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  1. Ha Trong Nguyen
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Correspondence to Ha Trong Nguyen .

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Editors and Affiliations

  1. International and Development Economics, Crawford School of Public Policy, Australian National University, Canberra, ACT, Australia

    Amy Y. C. Liu

  2. College of Business & Economics, Australian National University, Canberra, ACT, Australia

    Xin Meng

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Nguyen, H.T. (2019). Migration Duration and Migration Outcomes. In: Liu, A., Meng, X. (eds) Rural-Urban Migration in Vietnam. Population Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-94574-3_4

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