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.
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 (DNWR) 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. Using a new county-level dataset spanning 2003-2019 and a semi-varying coefficient approach, we identify non-linearities in shock transmission that linear models do not capture. Our empirical analysis shows that counties with more binding collateral constraints and higher degrees of DNWR experience larger and more persistent effects on consumption, unemployment, and house prices following net worth shocks. These findings highlight how local financial and labor market conditions determine heterogeneous responses to aggregate shocks, informing the design of regionally targeted economic policies.
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.
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).
with Cheng Ding, Vivian Yue, and Aliaksandr Zaretski
with Yunyun Jiang and Haitao Zheng
with YunYun Jiang and Haitao Zheng
with Shanshan Wang, Jie Hu and Haitao Zheng
Presenter
Presenter & Session chair
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.
The important paper by Barles and Souganidis (1991) provides a powerful framework to analyze a class of 2nd order PDEs (elliptic, parabolic, and hyperbolic) 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 arbitrary 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.
The analysis of shadow values is a common practice in economics, especially in the context of discrete time models. However, the continuous time models are less discussed. The Pontryagin's maximum principle (PMP) provides a powerful tool to do this. This blog post gives and explains the PMP and its application in continuous time models. Using PMP, one can derive Euler equations and other relationships that explain the channels through which the shadow values affect the dynamics of the model.