Estimating Vietnam’s income mobility in 2004 – 2008: a test – retest correlation approach

Khoa Vu,Paul Glewwe

doi:10.32508/stdj.v16i1.1412

Abstract

The economic growth of Vietnam in the 1990s has been a popular topic among the economists because there are many aspects of it are subjected to development studies. This paper attempts to explore one of these aspects, the income mobility of the economy, during the period 2004-2008 by estimating expenditure mobility, using Vietnam Household Living Standard Survey (VHLSS) data. This is done by applying a methodology that Heise (1969) developed in his work on test-retest correlations, to reduce the classical upward bias due to measurement errors. We estimate the mobility to be 0.035 to 0.092 which indicate a low mobility in Vietnam. This estimation allows us to draw out some implications about income inequality in Vietnam.

Highlights

Income mobility is a useful measure for understanding the movements of different income groups in an economy; high mobility implies significant movement of individuals between income groups, i.e. the poor climbing up the income ladder or the rich moves down compared to their original position, while low mobility indicates there is hardly any movement at all
As predicted by other mobility studies, the result shows that the simple mobility estimation overestimates the true mobility due to measurement error; our result in Table 1b indicates that measurement error's effect accounts for 68-85% of the simple mobility estimations by correlation coefficient and regression coefficient
Income mobility is a useful indicator for the movements of different income groups across the distribution

Summary

Introduction

Income mobility is a useful measure for understanding the movements of different income groups in an economy; high mobility implies significant movement of individuals between income groups, i.e. the poor climbing up the income ladder or the rich moves down compared to their original position, while low mobility indicates there is hardly any movement at all. One simple approach to measure the degree of mobility in a country is to estimate the Pearson correlation coefficient of income in two successive periods. Another simple way to estimate income dynamics over time is to estimate the slope coefficient on the log of income obtained by a simple linear regression [1, 2]. These estimations of mobility suffer an upward bias, because observed income often comes with large errors [3, 4].

Methods

Results

Conclusion