Author

Zheliang Zhu

Date of Award

Spring 5-15-2023

Author's School

Graduate School of Arts and Sciences

Author's Department

Economics

Degree Name

Doctor of Philosophy (PhD)

Degree Type

Dissertation

Abstract

This dissertation has three chapters. The first chapter examines the information transmissionfrom the central bank to the private sector regarding the public signal interest rate. The second chapter presents a proposed belief-driven Taylor rule and analyzes the rule’s impact on private expectation anchoring and social welfare loss. The third chapter studies the relationship between corporate Environmental, Social, and Governance (ESG) practices and their associated financing costs. Omitted proofs in each chapter are presented in the last section of each chapter.

In the first chapter, we study the information transmission from the central bank to theprivate sector regarding the public signal interest rate based on a benchmark New Keynesian dynamic stochastic general equilibrium (DSGE) model, and we provide a closed-form solution. We exclude the central bank’s information set and introduce asymmetric information sets between households and firms, then examine the scenario in which the central bank uses either the households’ or firms’ information set in the monetary policy. The objective is to analyze the impact of different information choices in the Taylor rule on the transmission of information from the public signal, interest rate, to households or firms.

In the second chapter, we introduce central bank communication error into the benchmarkmodel and explore the role of the private sector’s information in the Taylor-rule-based monetary policy, which is referred to as the belief-driven Taylor rule. The model includes non-nested information among all sectors, and we investigate the effects of incorporating the information sets of households, firms, and the central bank into the belief-driven Taylor rule. The results suggest that incorporating the private sector’s information into monetary policy can effectively anchor the private sector’s inflation forecasts. Moreover, when the household has an asymmetric information set compared to firms’, incorporating the household’s information in the belief-driven Taylor rule leads to better anchoring results and results in the lowest welfare loss. This finding is further reinforced by our examination of a weighted strategy in the belief-driven Taylor rule. This is a pioneering study as it introduces a new approach in which a DSGE model with a belief-driven Taylor rule is employed to investigate the impact of private sector information on monetary policy.

In the third chapter, we study the relationship between corporate Environmental, Social, andGovernance (ESG) practices and their associated financing costs in China, given the country’s focus on achieving Carbon Neutrality and Emission Peak targets. Accordingly, the present study investigates the relationship between corporate ESG practices and financing costs, focusing on the Chinese Shanghai and Shenzhen A-share listed companies from 2011 to 2020. Our findings indicate that: Firstly, better ESG performances and their components help to reduce companies’ financing costs. Secondly, ESG disclosure can also reduce financing costs, and a substitution effect exists between ESG performance and disclosure. Companies with low ESG performance can decrease their financing costs by strengthening their ESG disclosure. Thirdly, heterogeneity analysis reveals that the impact of ESG performances on financing costs is mainly manifested in state-owned enterprises, companies operating in the eastern region, and those in the green sector. Although gender diversity among senior executives can enhance corporate ESG performance, it reduces its effect on financing costs. Lastly, we propose and examine two channels through which ESG performance impacts financing costs: (i) better ESG performances reduce corporate credit risk and, thus, mitigate risk premium, and (ii) better ESG performances increase firms’ visibility, resulting in a decrease of information asymmetry between lenders and borrowers.

Language

English (en)

Chair and Committee

Gaetano Antinolfi Fei Tan

Committee Members

Ping Wang, Costas Azariadis, Yongseok Shin,

Available for download on Thursday, April 24, 2025

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