Abstract
The first two chapters of my dissertation focus on sustainable investing and asset pricing, while the third chapter explores macroeconomics, particularly in the areas of incomplete information and monetary policy. In Chapter 1, “A Theory of Green Investing: Driven by Values and Value”, I investigate the real impacts of green investing driven by both ethical values and financial value. Green investing encourages firms to reduce social costs, even in scenarios where green investors lack bargaining power and profit-driven capital is perfectly elastic in supply. The key driver of this impact is the willingness of some investors to sacrifice financial returns, motivated by values. These investors have a warm glow effect from investing in divisions that adopt clean technology, but only when such investments are made with the intention to reduce pollution. In addition, from a value perspective, such impact expands due to its potential to be exempt from regulations and lower return variance. While green investing has the potential to enhance social welfare, it also contributes to structural inequality by transferring financial gains from green investors to firms. Direct regulations outlawing dirty technology are not optimal if it is nontrivial for green investors to find other causes to get a warm glow effect. The results suggest that lobbying could be an alternative for achieving impact investing without incurring structural inequality. In Chapter 2, “Climate Risk Preparedness and the Cross Section”, we develop a theoretical framework to examine the relationship between a firm’s climate risk preparedness and its investment returns within a two-date stochastic general equilibrium production-based asset pricing model. Our analysis shows that, in equilibrium with an interior solution, a firm’s initial climate preparedness is positively correlated with the expected return on equity. We empirically test this theoretical model using a comprehensive set of assets, including stocks, ETFs, anomalies, and portfolios sorted by characteristics. The empirical findings support our theoretical predictions, highlighting the significant role that the constructed preparedness factor plays in explaining the cross-sectional variation in asset returns. In Chapter 3, ``Policy Rule Regressions with Survey Data", we introduce a simple procedure that leverages survey data to rectify endogeneity bias when estimating policy rule coefficients using the ordinary least squares (OLS) method under flexible information assumptions. We decompose policy rule regressors (e.g., inflation and output gap) into their forecasts made before policy decisions and the associated forecast errors. The forecasts are readily available in survey data and, by construction, orthogonal to the forecast errors and policy shocks under complete information. We further orthogonalize the forecast errors to remove the bias in the presence of information rigidities. Using Monte Carlo simulations, we showcase the efficacy of this procedure in a prototypical new Keynesian model under distinct information settings. As an empirical application, we employ Bayesian methods to compare the performance of the standard OLS approach using real-time data and our approach based on survey data in estimating monetary and fiscal policy rules. Marginal likelihood estimates reveal that our approach consistently outperforms across nearly all model specifications considered.
Committee Chair
Siddhartha Chib
Committee Members
Fei Tan; Gaetano Antinolf; Guofu Zhou; Philip Dybvig
Degree
Doctor of Philosophy (PhD)
Author's Department
Economics
Document Type
Dissertation
Date of Award
5-2-2025
Language
English (en)
DOI
https://doi.org/10.7936/qkrt-qm45
Recommended Citation
Lyu, Leifei, "Essays on Financial Economics and Macroeconomics" (2025). Arts & Sciences Theses and Dissertations. 3501.
The definitive version is available at https://doi.org/10.7936/qkrt-qm45