Essays in Financial Economics

Thesis (Ph.D.)--University of Washington, 2017-06This dissertation aims to investigate the interaction between financial markets and the real economy both in the short-run and the long-run. The first two chapters study the distinct interactions between different states of stock markets and the real economy at monthly frequencies. The third chapter studies the causality between financial development and the economic growth at business cycle frequencies (i.e., three or five-year spells). The first chapter focuses on forecasting the states of the stock market. While previous literature classifies the stock market into binary states (i.e., bull and bear markets), I further classify U.S. stock bear markets into good bear and bad bear markets. The latter are the bear markets associated with contraction phases of future cash flows, while the former are not. Most bad bear markets are accompanied with NBER declared recessions, whereas good bear markets are not accompanied with serious depressions in the real economy. Commonly used macroeconomic predictors also signal differently in forecasting these two types of bear markets. The value premium has distinct magnitude across the two types of bear markets. By applying a multinomial logit model with three alternatives (bull, good bear, and bad bear markets) to predict stock market states, I provide richer information about stock market states which is beneficial for policy makers and investors. In the second chapter, I examine the reliability and timeliness of using stock bad bear markets as early warning signals of economic recessions. I find that bad bear markets are much more reliable to predict recessions than conventional stock bear markets or the forecasting model that targets recessions directly. The forecasting model that predicts bad bear markets also provide timely information about the starts and the ends of economic recessions over NBER announcements. In the third chapter, I revisit the debate of “too much finance” on economic growth. I use different econometric methods in the dynamic panel data framework to address potential biases induced by the dynamic nature of economic growth and financial development but control the heterogeneity across countries. Particularly, I conduct a battery of robustness tests to examine weak instrument problems in the system GMM estimator, developed by Blundell and Bond (1998), and use Half-Panel Jackknife Fixed-Effect estimator, developed by Chudik, Pesaran, and Yang (2016), as an alternative method. I also take care of the outlier issue, which is particularly sensitive when there is nearly multicollinearity among explanatory variables. My empirical results find no sufficient evidence to support a positive causal effect, nor do I find a quadratic effect of financial development on economic growth