(Undergraduate Thesis) Understanding Real Economic Activity During COVID-19 Using a Dynamic Factor Model Decomposition

I comparatively study the performance of three public macroeconomic monitoring indexes (ADS, CFNAI and WEI) during the Pandemic Recession and find that they all indicate a very deep but also very short recession (trough at May 2020). Using the algorithm of Kalman filter, I construct my own macroeconomic monitoring index with four monthly indicators. As many economic indexes exhibited wild movements during COVID-19, to understand why this happened, I further illustrate two methods for decomposing my economics index into movements of underlying economic indicators.

Investing Strategy in Pharmaceutical Companies Based on Corporate Donations

Given the growing trend in ESG investing, we study whether a single measurable ESG criteria, charitable donations, can predict stock return controlling for other investing characteristics. Using a two-stage least squares (2SLS) specification, we identify a positive relationship between a firm’s cash donations and annual stock return. Moreover, we find that the relationship is more pronounced for pharmaceutical companies, which often are the biggest corporate donors to charities.

Evaluating Early Economic Impacts of COVID-19 in India from Nightlights

Using a difference-in-differences design, I study the differential economic impacts in India at the district level under varying lockdown measures with nightlights data. My results show that districts with strict lockdown rules experienced a 14% greater reduction of nightlights radiance in April and a 24% greater reduction in May relative to districts with loose lockdown rules. Moreover, I document India's sharp transition into the lockdown period using NASA's latest daily nightlights data for a two-week window around the lockdown announcement.