School of Business and Management Department of Finance 171 Department of Finance Measuring Product Market Competition Supervisor: BISETTI, Emilio / FINA Student: BAI, Tianzong / ECOF CHEN, Yuye / SBM CHENG CHENG, Yi Ting / SBM LI, Ziru / RMBI PHAM, Thanh Hai Binh / T&M WONG, Yee Hang / ECOF XU, Suixin / QFIN YUAN, Wai Man / FINA ZHANG, Jiayi / MAEC ZHANG, Yeyang / SBM Course: UROP1100, Fall UROP1100, Fall UROP1100, Fall UROP1100, Fall UROP1100, Fall UROP1100, Fall UROP4100, Fall UROP3100, Fall UROP2100, Fall UROP1100, Fall The project aims to measure firm-level competition based on the information about product scanner data from the Nielsen database. Inspired by the Text-based Network Industry Classification (TINC) from Hoberg and Phillips (2016), our research constructs the product category vector for each company, builds up the similarity score matrix, and determines the optimal cut-off considering the comparison of the two methods. Besides, we utilize the number of products sold by different firms or the number of firms in a particular industry across all U.S. counties to quantify geographical competition and present the output with heat maps. Measuring Product Market Competition Supervisor: BISETTI, Emilio / FINA Student: BAI, Tianzong / ECOF CHEN, Jinghui / FINA CHENG CHENG, Yi Ting / SBM CHEUNG, Tsz Chun / ECOF JIANG, Yuxuan / MAEC LI, Fei Pang / BIBU LI, Ziru / RMBI TANG, Junhao / RMBI ZHANG, Yeyang / ECOF ZHU, Letian / ECON Course: UROP2100, Spring UROP3100, Spring UROP2100, Spring UROP1100, Spring UROP1100, Spring UROP1100, Spring UROP2100, Spring UROP1100, Spring UROP2100, Spring UROP1100, Spring The project aims to measure firm-level competition based on the information about product scanner data from the Nielsen database. We retrieve information about firms whose manufacturers have yet to be disclosed in the database and employ various methodologies, such as utilizing Google and Refinitiv, to match them with their respective manufacturers. Furthermore, we calculate the local Herfindahl-Hirschman Index (HHI in every county), national HHI (HHI in the US), and market share of each firm in every quarter from 2006 to 2020 and for every product module. To examine the market competitiveness across different regions of the United States, we utilize the above-mentioned data to generate HHI maps and calculate the correlation between HHI and weighted average price or equal weighted price.
RkJQdWJsaXNoZXIy NDk5Njg=