关键词:
Economics
Finance
摘要:
This dissertation consists of three essays in macroeconomics and finance. The first and second chapters analyze the impact of the financial shocks and anti-corruption campaign on Chinese firms through the bank lending channel. The third chapter provides a new method to predict the cash flow from operations (CFO) via semi-parametric estimation and machine learning. The first chapter explores the impact of the financial crisis and sovereign debt crisis on Chinese firms through the bank lending channel and firm borrowing channel. Using new data linking Chinese firms to their bank(s) and four different measurements of exposure to the international markets (international borrowing, importance of lending to foreign listed companies, share of trade settlement, and exchange/income), I find that banks with higher exposure to the international markets cut lending more during the recent financial crisis. In addition, state-owned bank loans are more pro-cyclical compared with private bank loans. Moreover, banks with higher exposure to the international markets cut lending more when there is a negative shock in OECD GDP growth. With regard to firm borrowing channel, I find that firms with higher weighted aggregate exposure to the international markets through banks have lower net debt, cash, employment, and capital investment during the financial crisis. Firms with higher weighted aggregate exposure to the global markets have higher net debt and lower cash, employment, and capital investment when there is a negative shock in OECD GDP growth. This paper also provides a theoretical model to explain the mechanism in a partially opened economy like China. The second chapter discusses the impact of the anti-corruption campaign on Chinese firms through the bank lending channel. Using confidential data linking Chinese firms to their bank(s) and prefecture-level corruption index, I find that banks located in more corrupted prefectures offer significantly less credits before the anti-cor