Identifying Participation in A Government Program: Empirical Evidence from Thailand

Authors

  • Dr. Nopphawan Photphisutthiphong -

Keywords:

Government measure, inclusiveness, ageing, digital technology, Thailand

Abstract

A government handout given during the outbreak of the coronavirus aimed to alleviate the expenditure burden and stimulate household consumption spending. However, not all households participated in the program. This study seeks to identify the factors explaining the underserved households in the government program, where a cash handout was specifically transferred into a government application on the recipient's smartphone. Using Thailand’s survey of household expenditure and income in 2021, the results of a Probit Model reveal that economically disadvantaged households were less likely to participate in the consumption stimulus program compared to better-off households. Households with paid internet were more likely to participate in the program, as an internet connection was required to make purchases through the smartphone application. The nexus between age and mobile technology adoption was also examined, underscoring the prominent role of age, particularly in the older-age group. Household heads in their old age were less likely to participate in the government program than those in younger age groups. Additionally, even with paid internet available in the household, elderly household heads still had a lower probability of participating in the government measure than the young counterparts. This could be attributed to the unfamiliarity and unpreparedness of mobile technology adoption among older household heads. Our findings suggest that consumption stimulus measures should be inclusive beyond the multiplier effect to avoid widening inequality. Familiarity with and preparedness for mobile technology adoption, along with network accessibility, should be considered in a digital technology-related policy design, particularly for the elderly households.

References

Almeida, V., Barrios, S., Christl, M., De Poli, S., Tumino, A., & Van der Wielen, W. (2021). The impact of COVID-19 on households income in the EU. The Journal of Economic Inequality, 19(3), 413-431.

Anyamele, O. D., McFarland, S. M., & Fiakofi, K. (2022). The disparities on loss of employment income by US households during the COVID-19 pandemic. Journal of economics, race, and policy, 1-19.

Brewer, M., & Tasseva, I. V. (2021). Did the UK policy response to Covid-19 protect household incomes? The Journal of Economic Inequality, 19(3), 433-458.

Bui, D., Dräger, L., Hayo, B., & Nghiem, G. (2022). The effects of fiscal policy on households during the COVID-19 pandemic: Evidence from Thailand and Vietnam. World development, 153, 105828.

Dang, H.-A. H., & Nguyen, C. V. (2021). Gender inequality during the COVID-19 pandemic: Income, expenditure, savings, and job loss. World development, 140, 105296.

Komin, W., Thepparp, R., Subsing, B., & Engstrom, D. (2021). Covid-19 and its impact on informal sector workers: a case study of Thailand. Asia Pacific Journal of Social Work and Development, 31(1-2), 80-88.

Long, W., Zeng, J., & Sun, T. (2021). Who Lost Most Wages and Household Income during the COVID‐19 Pandemic in Poor Rural China? China & World Economy, 29(6), 95-116.

Martin, A., Markhvida, M., Hallegatte, S., & Walsh, B. (2020). Socio-economic impacts of COVID-19 on household consumption and poverty. Economics of disasters and climate change, 4(3), 453-479.

Midões, C., & Seré, M. (2022). Living with reduced income: an analysis of household financial vulnerability under COVID-19. Social Indicators Research, 161(1), 125-149.

Ministry of Finance. (2021). The Ministry of Finance Annual Report 2021.

Paweenawat, S. W., & Liao, L. (2024). Who Suffers the Most During the COVID‐19 Pandemic? Evidence From Thailand. The Developing Economies, 62(3), 238-268.

Qian, Y., & Fan, W. (2020). Who loses income during the COVID-19 outbreak? Evidence from China. Research in Social Stratification and Mobility, 68, 100522.

Satchanawakul, N., Kanchanachitra, M., Liangruenrom, N., & Satchanawakul, N. (2023). The economic impacts of COVID‐19 lockdown on low‐income older people in Thailand. Australasian Journal on Ageing, 42(2), 334-343.

Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data. MIT press.

Downloads

Published

2024-12-27