Tianhao Zhao

PhD Candidate ยท tianhao.zhao@emory.edu

Hello! I am a PhD candidate in Economics at Emory University, currently on the job market. My research focuses on empirically and theoretically examining the impact of economic frictions on macroeconomic dynamics.

Curriculum Vitae


Job Market Paper

Frictions, Net Worth Shocks, and Heterogeneous Impacts

(Job Market Paper)

The wealth effect is a critical channel through which economic shocks propagate. This paper examines the persistent and heterogeneous effects of net worth shocks across U.S. counties, focusing on the local collateral constraints and downward nominal wage rigidity and their interactions. We develop a two-agent general equilibrium model that demonstrates how the interaction between collateral constraints and DNWR shapes local wealth effects on consumption, unemployment and house prices. Using a new county-level dataset spanning 2003-2019 and a semi-varying coefficient approach, we identify large heterogeneities and non-linearities in shock transmission: the marginal propensity to consume out of wealth varies from 11 to 3 cents per dollar between low- and high-friction counties, with shock responses amplified 2-5 times when both frictions bind. These findings highlight how local financial and labor market conditions determine heterogeneous responses to aggregate shocks, informing the design of regionally targeted economic policies.

Slides


Research

Data and Code

CountyPlus

CountyPlus is an open-source panel dataset that covers 3000+ U.S. counties from 2003 to 2019. It consists of 100+ variables, including demographic, geographic, household balance sheet, local economy indicators. Specially, this dataset estimates household consumption, measure of local financial friction, and measure of local nominal friction (Downward Nominal Wage Rigidity).

(Version 0.0.2 is available now! Newly added 04-19 identified net worth shock and spatial weight matrices)

AdaptiveSG.jl

This package provides object-oriented API to define, train, evaluate and adapt multi-linear Adaptive Sparse Grid (ASG) interpolations. It can be used to solve high-dimensional discrete/continuous time models; perform high-dimensional non-parametric estimations; and help with other high-dimensional numerical exercises.

Blogs

In Progress

Financial Dollarization, Exchange Rate, and Macroprudential Policy

with Cheng Ding, Vivian Yue, and Aliaksandr Zaretski

Journal Article

Population aging and its effects on the gap of urban public health insurance in China

China Economic Review

with Yunyun Jiang and Haitao Zheng

2021

Socioeconomic Status and Morbidity Rate Inequality in China: Based on NHSS and CHARLS Data

International Journal of Environmental Research and Public Health

with YunYun Jiang and Haitao Zheng

2019

Conference

30th anniversary of the Midwest Macroeconomics Meetings (MMM)

Purdue University

Presenter

2024

International Conference on Empirical Economics

Pennsylvania State University at Altoona (virtual)

Presenter & Session chair

2024

Referee

BMC Public Health

Seminar

Federal Reserve Bank of Atlanta

Brownbag seminar (scheduled)
Nov 20, 2024

Teaching

ECON 112: Principle of Macroeconomics

Instructor, Emory University
Fall 2022

Teaching Assistantship

Emory University
  • ECON 421: Microeconometric Data Analytics, Spring 2024
  • ECON 610: Macroeconomic Theory, Fall 2023
  • ECON 212: Intermediate Macroeconomics, Fall 2023
  • ECON 363: Political Economy of China, Spring 2023
  • ECON 112: Principle of Macroeconomics, Spring 2022
  • ECON 363: Political Economy of China, Fall 2021
  • ECON 363: Political Economy of China, Fall 2020

Blogs

A 15 min tutorial for Adaptive Sparse Grid (ASG)

High-dimensional models, either numerical or empirical, are known to suffer from the curse of dimensionality. Starting from the basic idea of interpolation, this blog post provides an intuitive explanation of how ASG works and how it can further reduce the curse of dimensionality.

2024

Analyzing the monotonicity of numerical schemes with examples

The important paper by Barles and Souganidis (1991) provides a powerful framework to analyze a class of 2nd-order non-linear PDEs which are commonly used in economics. Among all the required conditions, the monotonicity of the numerical scheme is critical and often violated in practice. This blog post explains how to analyze the monotonicity of a wide class of numerical schemes with multiple examples that share similar structures with some commonly used economics models. One can follow the examples to design their own numerical schemes.

2024