I am a PhD candidate from the Department of Economics and Booth School of Business at the University of Chicago.
My research studies how information frictions affect macroeconomic dynamics, especially their impact on economic uncertainty, volatility and cross-sectional dispersion in outcomes during recessions periods.
I will be joining the Federal Reserve Bank of St. Louis as an economist in June 2021.
You can contact me at email@example.com.
Job Market Paper: Strategic Uncertainty over Business Cycles
Abstract: This paper studies a dispersed information economy in which agents choose how much attention to pay to an unknown aggregate state. I show that under certain conditions, attention and four widely studied measures of uncertainty are countercyclical: agents pay attention when they expect the economy to be in a bad state, and this increase in attention alone leads to higher (i) conditional volatility of aggregate output, (ii) dispersion of individual output, (iii) forecast dispersion about aggregate output, and (iv) forecast uncertainty about aggregate output (i.e., forecast errors expected by each agent). As agents pay attention, they react more to the unknown state, and their response generates high volatility. Because information is dispersed, agents' beliefs and reactions diverge, and each agent faces higher uncertainty about others' aggregate response. All these implications are consistent with data. I evaluate the mechanism quantitatively in a dynamic dispersed information economy calibrated to U.S. forecast-survey data. Due to dispersed information, the economy features an ``infinite regress problem'' under which the equilibrium lacks a finite recursive state space. Existing methods addressing the problem are constrained to first-order approximations; they cannot capture attention and uncertainty fluctuations because these fluctuations are higher-order properties of the model. I solve the model using a new method developed in a companion paper. In the calibrated economy, countercyclical attention generates countercyclical fluctuations in all four measures of uncertainty with cyclicality, magnitude, and persistence roughly consistent with untargeted moments in the data.
A Higher-Order Approximation Method for Dispersed Information Models
Abstract: This paper develops a higher-order approximation method for models with dispersed information. Dispersed information models provide promising explanations for important empirical regularities, but the literature has been constrained to analyzing models with first-order approximation methods. First-order approximations miss important features in these models. With first-order approximations, agents don’t respond to uncertainty in models featuring strategic uncertainty, the distribution of beliefs has no role beyond its average, and attention choices are static in business cycle models. I develop a perturbation-based method that overcomes these limitations. The method generalizes existing first order methods to arbitrarily higher-order approximations. For static dispersed information models, the method allows one to characterize higher-order properties of the equilibrium in closed form. For dynamic dispersed information models with an infinite regress problem, the method provides a simple algorithm for solving higher order dynamics of the equilibrium.
Media Competition for Attention
Abstract: This paper shows competition for attention between information providers, such as media, can lead to a decrease in the information available in an economy. I consider a model where information providers provide content (signals) to maximize how much attention they receive from agents; agents allocate attention optimally to acquire information about an unknown state. Information providers are concerned that, given limited attention, providing too much information in their content makes it hard for agents to ``understand''. If this concern is more severe when attention is scarce, I show an increase in the number of providers motivates each of them to provide less information in their content because agents allocate attention to content that is easy to understand. Moreover, if providers share a common information source and the number of providers is large, an increase in the number of providers leads to a decrease in the information available in the economy as measured by the precision of an average action taken by agents in response to the state.