The Income and Consumption Effects of Covid-19 and the Role of Public Policy
This paper provides empirical evidence on how the labour market impacts of the covid-19 pandemic vary across workers’ incomes, assets, characteristics and household structures in the UK. Using data from the UK Household Longitudinal Study, we find that less educated and young workers are most likely to be laid-off. This is particularly the case for females. Moreover, less educated workers tend to have low income and low assets, limiting their ability to maintain consumption in the face of reduced income. This is compounded at the household level by assortative partnering between workers with similar education levels. We analyse the source of these inequalities by relating employment outcomes to factors related occupational and industrial characteristics. We then conduct a quantitative assessment of the likely impact of covid-19 on households’ consumption and find that, because the adverse labour market impacts are concentrated on workers with low income and low assets, 70 percent of households in the bottom fifth of the income distribution cannot maintain their usual expenditure for even one week. Finally, we consider the effectiveness and distributional implications of two different policy interventions: the Coronavirus Job Retention Scheme in the UK and Economic Impact Payments in the US. Our findings suggest that both policies can alleviate the increase in consumption inequality that would have otherwise arisen during the pandemic. In the short term, the US-style one-off payment is most effective at providing affected households with the means to smooth consumption. However, the CJRS provides better insurance against prolonged disruption as the program provides continuous income support.
Effect of Minimum Wage on Changes in the Thai Labor Market
This study evaluates the effect of the minimum wage on changes in the Thai labor market from 2002 to 2010, when the real minimum wage gradually decreased, and 2011 to 2013 when the real minimum wage substantially increased. These changes include labor force participation, employment, dis-employment, weekly working hours, real hourly wages, real hourly total labor income, and various other types of income. This study uses the individual-level panel data generated from the Matched-Outgoing Rotation Group (Matched-ORG) of the Thai Labor Force Survey. We observed the negative effect of minimum wage on employment, where the elasticity was in the range of – 0.0029 to -0.0474. We also observed the dis-employment for the foreign workers. We found that firms adjust working hours and various types of income to mitigate minimum wage shock. We conclude that the competitive equilibrium theory can reasonably explain the effect of minimum wage on employment as well as the overall changes in the Thai labor market from 2002 to 2013.
Bunching for Free Electricity
This paper documents the impacts of Thailand’s Free Basic Electricity program on electricity consumption behavior. Under the program, households who use less than 50 units are exempt from paying their electricity bill in that month, while households who use more than 50 units have to pay for the full amount. The program thus creates a large notch in the household’s budget set. In contrast to existing literature that finds little or no bunching, we observe a distinct bunching of electricity consumption around the threshold. Nonetheless, the excess bunching is still small compared to the overall distribution. We provide possible explanations on the role of various optimization frictions.
On Covid-19: New Implications of Job Task Requirements and Spouse’s Occupational Sorting
The Covid-19 pandemic has disrupted working life in many ways, the negative consequences of which may be distributed unevenly under lockdown regulations. In this paper, we construct a new set of pandemic-related indices from the Occupational Information Network (O*NET) using factor analysis. The indices capture two key dimensions of job task requirements: (i) the extent to which jobs can be adaptable to work from home; and (ii) the degree of infection risk at workplace. The interaction of these two dimensions help identify which groups of workers are more vulnerable to income losses, and which groups of occupations pose more risk to public health. This information is crucial for both designing appropriate supporting programs and finding a strategy to reopen the economy while controlling the spread of the virus. In our application, we map the indices to the labor force survey of a developing country, Thailand, to analyze these new labor market risks. We document differences in job characteristics across income groups, at both individual and household levels. First, low income individuals tend to work in occupations that require less physical interaction (lower risk of infection) but are less adaptable to work from home (higher risk of income/job loss) than high income people. Second, the positive occupational sorting among low-income couples amplifies these differences at the household level. Consequently, low-income families tend to face a disproportionately larger risk of income/job loss from lockdown measures. In addition, the different exposure to infection and income risks between income groups can play an important role in shaping up the timing and optimal strategies to unlock the economy.
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.