Thomas Winberry

University of Chicago
Thomas Winberry
Assistant Professor of Economics

  Working Papers

Financial Heterogeneity and the Investment Channel of Monetary Policy
, with Pablo Ottonello (revise and resubmit, Econometrica)
We study the role of heterogeneity in firms' financial positions in determining the investment channel of monetary policy. Empirically, we show that firms with low leverage or high credit ratings are the most responsive to monetary policy shocks. We develop a heterogeneous firm New Keynesian model with default risk to interpret these facts and study their aggregate implications. In the model, firms with high default risk are less responsive to monetary shocks because their marginal cost of external finance is high. The aggregate effect of monetary policy therefore depends on the distribution of default risk across firms.

Lumpy Investment, Business Cycles, and Stimulus Policy (revise and resubmit, American Economic Review)
I study the implications of two key facts for aggregate investment dynamics: micro-level investment mainly occurs along the extensive margin and the real interest rate is mildly countercyclical. I build a dynamic general equilibrium model which captures these facts and find two key results. First, the elasticity of aggregate investment with respect to productivity shocks or policy stimulus is procyclical because in expansions more firms are likely to make an extensive margin investment. Second, targeting firms close to the extensive margin can substantially increase the cost effectiveness of stimulus policy.

Publications (including forthcoming and accepted)

When Inequality Matters for Macro and Macro Matters for Inequality
, with SeHyoun Ahn, Greg Kaplan, Ben Moll, and Christian Wolf (forthcoming in the NBER Macroeconomics Annual 2018)
Matlab Toolbox available on github here
We develop an efficient and easy-to-use computational method for solving a wide class of general equilibrium heterogeneous agent models with aggregate shocks. Our method extends standard linearization techniques and is designed to work in cases when inequality matters for the dynamics of macroeconomic aggregates. We present two applications that analyze a two-asset incomplete markets model parameterized to match the distribution of income, wealth, and marginal propensities to consume. First, we show that our model is consistent with two key features of aggregate consumption dynamics that are difficult to match with representative agent models: (i) the sensitivity of aggregate consumption to predictable changes in aggregate income and (ii) the relative smoothness of aggregate consumption. Second, we extend the model to feature capital-skill complementarity and show how factor-specific productivity shocks shape dynamics of income and consumption inequality.

A Method for Solving and Estimating Heterogeneous Agent Macro Models (forthcoming, Quantitative Economics)
Dynare codes and user guide (heterogeneous firm codes coming soon)
I develop a computational method for solving and estimating heterogeneous agent macro models with aggregate shocks. The main challenge is that the aggregate state vector contains the distribution of agents, which is typically infinite-dimensional. I approximate the distribution with a flexible parametric family, reducing its dimensionality to a finite set of endogenous parameters, and solve for the dynamics of these endogenous parameters by perturbation. I implement the method in Dynare and show that it is fast, general, and easy to use. As an illustration, I use the method to perform a Bayesian estimation of a heterogeneous firm model with aggregate shocks to neutral and investment-specific productivity. I find that the behavior of investment at the firm level quantitatively shapes inference about the aggregate shock processes, suggesting an important role for micro data in estimating DSGE models.

Work In Progress

How Does Firm Heterogeneity Matter for Aggregate Dynamics? Evidence from Factor Allocation, with Pablo Ottonello

Investment, Price Changes, and Monetary Policy: Models and Micro Data, with Joe Vavra

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