After finishing my undergraduate studies, I worked as a junior researcher at IDE, mainly on international finance. Observing the repetitive cycle of financial crises in developing countries and given that most research looks backward, starting only after a crisis has damaged the economy, I decided to enroll in a graduate program in economics in the US to study the interactions of agents’ incentives and regulations. After the first year, a theory professor showed me a negative theorem in mechanism design and suggested that the field is not promising. In the meantime, I worked as a research assistant to a professor of development economics who ingeniously combined theory and data to test interesting hypotheses. Since then, I have also followed the same method. My research topics include intrahousehold resource allocation, human capital, microfinance, minimum wages and firms, health, and COVID-19.

My current research focuses on minimum wages, microfinance, and COVID-19.

The effects of minimum wages are discussed mostly in terms of employment. However, firms can adjust to changes in minimum wages with profit reduction and/or output prices[[Should this be something like “by reducing profits and/or increasing prices”?]]. Using data from the South African Revenue Services, we study the impacts of higher agricultural minimum wages on firm profits and employment. Our preliminary results show a squeeze on profits and movement away from labour and toward capital.

Microfinance has long been out of reach for the poorest people. It has been pointed out that they are considered high risk and the loaned amount is too small to start any income-generating activities. We took these ideas to the ultra-poor of northern Bangladesh and, in a randomized controlled trial, offered traditional microfinance loans, large cash loans three times greater than traditional loans, and in-kind loans (a heifer) also worth three times the value of traditional loans. We found that traditional microfinance loans lead to smaller asset accumulation and have lower repayment rates compared with other loans, affirming the hypothesis.

As COVID-19 started to spread around the world, I started a research project that required only a domestic public dataset. In August 2020, the government of Japan launched a travel subsidy program called Go To Travel (GTT). Due to its large number of daily new cases, Tokyo was excluded from the GTT program for the first two months and was only added in October. Using the synthetic control method, I estimated the impacts of adding Tokyo to the GTT program on the daily new cases in nearby Shizuoka Prefecture and found that the addition of Tokyo to the GTT program increased the number of new cases in Shizuoka in mid-November.