Job Market Paper
In this paper I argue that synchronized large-scale investments of large firms can significantly amplify productivity-driven aggregate fluctuations, and lead to investment cycles even in the absence of aggregate shocks. Using U.S. Compustat data, I show that years preceding recessions display investment surges among large firms. Furthermore, after the investment surges, large firms become inelastic to interest rates and display persistent inaction duration. I then develop a heterogeneous-firm real business cycle model in which a firm needs to process multiple investment stages for large investments and can accelerate it at a cost. In the model, following a TFP shock the synchronized timings of lumpy investments are persistently synchronized. And TFP-induced recessions are especially severe after the surge of large firms’ lumpy investments. In support of this prediction, I present evidence for the investment cycle in post-shock period in macro-level data on nonresidential fixed investment.
2021: SED; 2020: WEAI, MEA (Cancelled); 2019 FRB San Francisco (Thomas J. Sargent Dissertation Fellowship)
Top Income Inequality and the Business Cycle (Draft coming soon) [slides(2021AEA)]
This paper studies how the pass-through businesses of top income earners affect the aggregate fluctuations in the U.S. economy. I develop a heterogeneous-household real business cycle model with endogenous labor supply and occupational choice and calibrate the model to capture the observed top income inequality. Compared to the counterfactual economy with the factor-income-driven top income inequality, the economy in the baseline model features the aggregate fluctuations that outperform in explaining the recent changes in the business cycle: 1) stronger negative correlation between labor hour and productivity and 2) higher volatilities of labor hour and productivity relative to the output volatility. Heterogeneous labor demand sensitivities to TFP shocks between pass-through businesses and C-corporations build the core of the aggregate dynamics, and the aggregate employment dynamics display substantial nonlinearity due to this heterogeneity.
Presentation: 2021 AEA/ASSA
This paper develops and tests a novel algorithm that solves heterogeneous agent models with aggregate uncertainty. The algorithm iteratively updates agents’ expectations on the future path of aggregate states from the transition dynamics on a single path of simulated shocks until the expected path converges to the simulated path. The nonlinear dynamic stochastic general equilibrium could be computed with a high degree of accuracy by this method; the market clearing prices and the expected aggregate states are directly computed at each point on the path without relying on the parametric law of motion. Using the algorithm, I analyze a heterogeneous-firm business cycle model where firms are subject to an external financing cost and hoard cash as a buffer stock up to a target level. Based on the model, I discuss the business cycle implications of the corporate cash holdings.