Two essays on empirical microeconomics

Abstract

This thesis consists of two studies on empirical microeconomics.The first chapter documents the rise and evolution of the high-tech development ofGuangdong. The growth of China’s manufacturing has been striking since the reform andopening up policy takes into effect. Guangdong, the province which has benefited from thepolicy the most, emerged as a cluster of labor-intensive and low-tech manufacturing firms.In the recent years, however, it has experienced a miraculous increase in high-tech firms,particularly in cities like Shenzhen, Dongguan and Huizhou. We find that there exists atremendous variance in the degree of high-tech development among the Guangdong cities.Cities with lower trade costs have a higher percentage of high-tech industrial firms, as wellas a higher percentage of skilled labor. Moreover, soaring housing prices do not thwartthe rise of high-tech firms, but has pooled together the skilled labor in a few cities. Torationalize our findings, we develop a two-industry multi-region spatial equilibrium modelthat captures internal migration, international and domestic trade as critical factors. Theresults of counterfactual exercises based on our model are in line with our predictions.International and domestic trade costs have significant effects on the high-tech developmentof regions.In the second chapter, we develop a model that captures how the search algorithm affectsbuyers’ search process, which further influences the market equilibrium and welfare. Oneprominent feature of online sales is that buyers rely on the search tools offered by platformsto process information when searching for products. The development of online platformscan reduce buyers’ search costs and promote competition among sellers, but a platform maydesign a search algorithm that is too “selective” from the social welfare perspective, whichcauses consumers to consider fewer options and suppresses competition. By using datafrom food delivery platforms, we provide empirical evidence that search algorithms deeplyaffect restaurant revenues and their distributions. Markets with more chain restaurants withestablished brands tend to have more concentrated sales, and this is partly caused by searchalgorithms favoring large restaurant chains.