Labor Income Inequality in Thailand: the Roles of Education, Occupation and Employment History
Thailand’s income inequality has reportedly declined since the mid-1990s. This paper examines possible mechanisms underlying the dynamic patterns of the country’s labor income inequality. Using the Thai labor force survey between 1988 and 2017, we document that the country’s reduction in income inequality is likely driven by the fact the earnings at the bottom part of the distribution have become more similar. The median wage gap between college and non-college workers, however, still gets larger over time. Our key explanation is the changes in education-occupation composition. Recently college graduates are no longer concentrated in high skill jobs. A larger share of secondary educated workers works in low-skill jobs instead of the middle-skill ones. Using panel administrative data from the Thai Social Security Office, we find that wage disparity can also be explained by employment history. The high wage earners earn more since they enter the market, and the gap gets wider as the workers age. Additionally, the top of the group can command higher wages by working at a large firm or switching to a new job. These findings highlight the fact that to tackle the income inequality issue, the country needs to understand the underlying mechanisms behinds its dynamics.
Educational Assortative Mating and Income Inequality in Thailand
This study measures educational assortative mating in Thailand and its relationship with income inequality using national labor force survey data from 1985-2016. Since the 1990s, Thailand shows a trend of decreasing educational homogamy, but there is evidence of continuing educational hypergamy in Thai households. Using the semiparametric decomposition method of DiNardo, Fortin and Lemieux (1996), the study finds that educational assortative mating has affected changes in household income inequality over time. Furthermore, there exists a negative relationship between income inequality and marital sorting with same education, which contradicts evidence found in developed countries.
Evaluating Thailand’s Free Basic Electricity Program
This study evaluates the performance of Thailand’s Free Basic Electricity (FBE) program along three dimensions: targeting effectiveness, benefit adequacy, and subsidy burden distribution. While the FBE benefits reaches the targeted population (low-income families) quite well, the benefit leakage to the non-targeted population could result in a significant increase in the overall subsidy cost. Furthermore, the current 50-unit free quota given by the FBE program is insufficient for the basic need of many low-income families. Lastly, the FBE subsidy burden falls exclusively on the industrial/commercial customers, but the cost increase has been rather small. Therefore, Thailand’s FBE program can be markedly improved by introducing a more effective targeting approach to reduce leakage, which will allow the government to raise the free electricity quota while maintaining the same overall subsidy cost.
Night Lights, Economic Growth, and Spatial Inequality of Thailand
This paper explains the method using a set of night light imaginary to estimate GPP of Thailand. This method is quite new but widely acceptable in the area of economics because luminosity of night lights is normally based on the amount of economic activities in each area. The results showed a high and significant correlation between the night lights and the GPP growth. Even if the estimation was controlled by some specific factors, such as population density, timing size of agricultural or manufacturing sector, the relationship is still robust. After this relationship is confirmed in the provincial level of Thailand, this research applied the results to show the relationship between economic values and spatial inequality, which indicates new understanding about spatial development patterns.
Intertwining Inequality and Labor Market under the New Normal
This paper builds on a life cycle model of occupational choices and financial frictions to understand the main channel through which demography and inequality influence the economy. Based on household data from Thailand, younger cohorts are likely to be workers and older cohorts are likely to be entrepreneurs due to age-dependent skills and asset accumulation. Under the new normal faced by the Thai economy as well as others, aging population can lower overall total factor productivity and increase inequality. An increase in equilibrium wage due to shortage of labor supply drives mediocre entrepreneurs to become self-employed – a low-income and low-productivity occupation – and worsens total factor productivity and hence inequality. Moreover, a decline in world interest rates associated with global aging population will exacerbate this negative effect. Reducing financial frictions or alleviating a borrowing constraint of talented entrepreneurs can mitigate this effect while extending retirement age will only improve output per capita while total factor productivity and inequality worsen.