An Assessment of Relationship Between Growth and Inequality Using Micro Data from Thailand

This paper shows that growth and income distribution dynamics are closely linked through occupation, financial intermediation, and education, using the micro data from Thailand. The compositional change of these characteristics accounts for half of the Thai inequality increase and forty percent of the Thai growth and poverty reduction during 1976-1996. Financial deepening and educational expansion contributed to increase in inequality while occupational transformation contributed to poverty alleviation. The change in income gaps due to differential growth rates, divergence and then convergence, across the income-status groups by these three characteristics shapes the inequality dynamics as inverted-U. These two growth-related inequality dynamics, composition and income-gap dynamics, explain virtually all the change in overall inequality except the initial rise. Thus, the long swing in income inequality can be viewed as part of wider process of growth as Kuznets speculated. (JEL D31, O41, I32) This paper examines the relationship between growth and inequality using the micro data from Thailand. Due to the scarcity of appropriate data, most empirical studies that attempted to establish the relationship between growth and inequality focused on cross-country regressions though the relationship is dynamic. The results of these studies are, unfortunately, robust neither to the specification of estimation nor to the selection of data. Thus, though they have provided suggestive clues, they can hardly reveal the underlying nature of the relationship between growth and inequality. A natural alternative for studying this dynamic relationship would be an analysis of evolution of income distribution for a given economy using a series of micro data, which was originally called for by Kuznets (1954), according as more micro data have become available. To study the factors determining the trends of income inequality in the course of a country’s economic growth, the data are classified by average income levels for a two-decade span so that one can form long-term income-status groups. Then, long-term changes in the income distribution consist of (1) population shifts across income-status groups, (2) changes in income levels across these groups, and (3) distributional changes within these groups. The first component may be called “composition dynamics,” the second component “income-gap dynamics,” and the third one “intra-group inequality dynamics.” Kuznets (1955) viewed the long term change in income inequality as part of wider process of growth. The first two component dynamics of inequality are indeed related to growth features. As more people join the higher-