Abstract:

This paper shows how to solve and estimate a continuous-time dynamic stochastic general equilibrium (DSGE) model with jumps. It also shows that a continuous-time formulation can make it simpler (relative to its discrete-time version) to compute and estimate the deep parameters using the likelihood function when non-linearities and/or non-normalities are considered. We illustrate our approach by solving and estimating the stochastic AK and the neoclassical growth models. Our Monte Carlo experiments demonstrate that non-normalities can be detected for this class of models. Moreover, we provide strong empirical evidence for jumps in aggregate US data.

Abstract:

This paper shows that non-linearities from a neoclassical production function alone can generate time-varying, asymmetric risk premia and predictability over the business cycle. These empirical key features become relevant when we allow for non-normalities in the form of rare disasters. We employ analytical solutions of dynamic stochastic general equilibrium models, including a novel solution with endogenous labor supply, to obtain closed-form expressions for the risk premium in production economies. In contrast to an endowment economy with constant investment opportunities, the curvature of the consumption function affects the risk premium in production economies through controlling the individual's effective risk aversion.

Abstract:

A model of growth with endogenous innovation and distortionary taxes is presented. Since innovation is the only source of volatility, any variable that influences innovation directly affects volatility and growth. This joint endogeneity is illustrated by working out the effects through which economies with different tax levels differ in their volatility and growth process. We obtain analytical measures of macro volatility based on cyclical output and on output growth rates for plausible parametric restrictions. This analysis implies that controls for taxes should be included in the standard growth-volatility regressions. Our estimates show that the conventional Ramey-Ramey coefficient is affected sizeably. In addition, tax levels do indeed appear to affect volatility in our empirical application.

Abstract:

This paper presents strong empirical evidence that the observed heterogeneity of output volatility across countries and over time is partly endogenous. In particular, based on a closed-form solution we obtain a (long-run) equilibrium relationship between taxes and output volatility in the stochastic neoclassical model by showing that asymptotically the variance of output growth rates is affected by the level of taxes, without affecting the mean. We estimate the tax semi-elasticities on output volatility and provide convincing empirical evidence that taxes are important to understand differences in output volatility among OECD countries.

Abstract:

We show that including financial market data at daily frequency, along with macro series at standard lower frequency, facilitates statistical inference on structural parameters in dynamic equilibrium models. Our continuous-time formulation conveniently accounts for the difference in observation frequency. We suggest two approaches for the estimation of structural parameters. The first is a simple regression-based procedure for estimation of the reduced-form parameters of the model, combined with a minimum-distance method for identifying the structural parameters. The second approach uses martingale estimating functions to estimate the structural parameters directly through a non-linear optimization scheme. We illustrate both approaches by estimating the stochastic AK model with mean-reverting spot interest rates. We also provide Monte Carlo evidence on the small sample behavior of the estimators and estimate the model using 20 years of U.S. macro and financial data.

Abstract:

We propose a simple and powerful numerical algorithm to compute the transition process in continuous-time dynamic equilibrium models with rare events. In this paper we transform the dynamic system of stochastic differential equations into a system of functional differential equations of the retarded type. We apply the Waveform Relaxation algorithm, i.e., we provide a guess of the policy function and solve the resulting system of (deterministic) ordinary differential equations by standard techniques. For parametric restrictions, analytical solutions to the stochastic growth model and a novel solution to Lucas' endogenous growth model under Poisson uncertainty are used to compute the exact numerical error. We show how (potential) catastrophic events such as rare natural disasters substantially affect the economic decisions of households.

Abstract:

This paper shows that a consumption-based asset pricing model (C-CAPM) with rare disasters can account for several empirical weaknesses of the canonical model. Rare events are able to explain the large pricing errors (Euler equation errors) of the C-CAPM typically found in the data. This is remarkable, since it is known by the work of Lettau and Ludvigson (2009) that leading extensions of the C-CAPM are not able to rationalize large pricing errors. We illustrate (both analytically and in extensive Monte Carlo simulations) that implausible estimates of structural parameters are not puzzling from the perspective of models with rare events. We derive asset prices and Euler equation errors in general equilibrium for both an endowment economy and (as a novelty) a production economy. Our results suggest that rare events not only help explaining the equity premium puzzle but also account for other important dimensions of the empirical failure of the standard consumption-based model.

Abstract:

We show how to formulate and solve the new Keynesian model in continuous time. In our economy, monopolistic firms engage in infrequent price setting á la Calvo. We introduce shocks for preferences, total factor productivity and government expenditure, and then show how the equilibrium system can be written in terms of 8 state variables. Our nonlinear and global numerical solution technique uses the collocation method based on Chebychev polynomials directly computing the continuous-time Bellman equation.