Using Online Prices for Inflation Estimation and Pricing Behaviour Research

By Ngo Quynh Hoa (VNP 26)

Supervisor: Dr. Matthias Rieger / Dr. Nguyen Trong Hoai

Abstract:

This thesis examines the potential of using online pricing data from multi-channel retailers for economic research during the pandemic time. It describes the method of collecting data through webscraping techniques in two of the largest retailers in Vietnam during its first “true” wave of COVID-19 in 2021 and discusses the benefits and challenges of this approach. Data were collected daily across 167 days and from 2,398 product items, for a total of 396,335 observations. Despite limitations such as the short time frame of the research and the fluctuations in the number of data points gathered during the lock-down, the thesis shows that the online price index is capable of tracking the inflation dynamics during the pandemic. The approach can be helpful when price data cannot be collected in person due to lockdowns. Regressions of price dynamics on pandemic variables indicate that the pandemic tr ajectory, including the total number of vaccinations and the lockdown measures, correlates strongly with the discounting benefits consumers can enjoy, particularly on essential products like foods. Still, no evidence for the correlation between pandemic variables and inflation has been found within the scope of this research.