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In this paper, I provide a structural approach to quantify the forces that govern the joint dynamics of five financial indicators: (i) default risk, (ii) corporate bond credit spreads, (ii) aggregate and (iv) idiosyncratic equity volatility, and (v) corporate bond bid-ask spreads. I build a dynamic structural model and estimate fundamental shocks using a large firm-level database on credit spreads, equity prices, accounting statements, and bond recovery ratios in the U.S. from 1973 to 2014. The model accurately accounts for the historical levels and dynamics of the financial indicators, both over time and in the cross-section. A structural decomposition reveals that the joint dynamics of these financial indicators is driven by fluctuations in firms’ asset values and firms’ aggregate asset volatility. I find that the informational content of the financial indicators for predicting economic activity is captured by fluctuations in firms’ aggregate asset volatility. All together, my results suggest that fluctuations in firms’ aggregate asset volatility are key for the transmission channel that links the fundamental drivers of financial indicators to the real economy.
This paper investigates how productivity growth interacts with financial cycles. We show that movements in stochastic discount factor is a strong predictor of aggregate productivity growth. We rationalize these findings in a macro-finance model with heterogenous risk aversion and endogenous productivity growth where the financial sector is key in screening and absorbing innovation risk. Shocks to innovation levels and volatility generate financial cycles. During financial stresses, the financial sector becomes undercapitalized and reduces its exposure to innovation risk. As a consequence, willingness to take risk in the economy is reduced, and less innovation occurs. We show that the combination of undercapitalization and heightened uncertainty generate large time-varying risk premia, safe asset shortage, and hysteresis in productivity growth following financial crises that are quantitatively consistent with empirical observations. We derive macro-prudential policy implications of the arising trade-off between short-run growth and financial stability.
We propose a robust method for solving a wide class of continuous-time dynamic general equilibrium models. We rely on a finite-difference scheme to solve systems of partial differential equations with several endogenous state variables. This class of models includes the frameworks (among others) of He and Krishnamurthy (2013); Silva (2015); Brunnermeier and Sannikov (2014); and Di Tella (2016).
This paper argues that the capacity of financial markets to aggregate information is an important determinant of capital structure decisions of firms. We build on a rational expectations equilibrium (REE) model with (i) information asymmetries between the issuer of an asset and investors, and (ii) information acquisition constraints faced by investors. We highlight two of the puzzles our model is able to rationalize: high equity risk elasticity of leverage, and the zero leverage puzzle. Standard corporate finance models imply that for reasonable tax shield levels, the sensitivity of leverage to equity volatility is insignificant. Our model introduces an informational wedge between the firm's and the market's valuation of debt to explain the discrepancy. Investors ask for an "informational premium" to price the debt, and therefore reduce the firms' incentives to leverage. Moreover, the interaction between information choice and REE trading motivates specialization. Firms whose projects are perceived to be too risky are not able to borrow in the corporate bond market until they achieve a relatively safe volatility level to trigger investors' specialization incentives. Therefore, a fraction of firms with zero leverage arises as an equilibrium outcome.