Research


Publications:

"Numerical solution of dynamic equilibrium models under Poisson uncertainty" (with Timo Trimborn), Journal of Economic Dynamics and Control 37 (2013): 2602-2622.  download the full document

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.

"Explaining output volatility: The case of taxation", Journal of Public Economics 95 (2011): 1589-1606.  download the full document

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.

"On the link between volatility and growth" (with Klaus Wälde), Journal of Economic Growth 16 (2011): 285-308.  download the full document

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.

"Risk premia in general equilibrium", Journal of Economic Dynamics and Control 35 (2011): 1557-1576.  download the full document

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.

"Structural estimation of jump-diffusion processes in macroeconomics", Journal of Econometrics 153 (2009): 196-210.  download the full document

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.

Working papers:

"Risk of Rare Disasters, Euler Equation Errors and the Performance of the C-CAPM" CREATES WP 2012-32 (with Andreas Schrimpf, July 2012). download the full document

Abstract:

This paper shows that the consumption-based asset pricing model (C-CAPM) with low-probability disaster risk rationalizes large pricing errors, i.e., Euler equation errors. This result is remarkable, since Lettau and Ludvigson (2009) show that leading asset pricing models cannot explain sizeable pricing errors in the C-CAPM. We also show (analytically and in a Monte Carlo study) that implausible estimates of risk aversion and time preference are not puzzling in this framework and emerge as a result of rational pricing errors. While this bias essentially removes the pricing error in the traditional endowment economy, a production economy with stochastically changing investment opportunities generates large and persistent empirical pricing errors.

"Measuring Convergence using Dynamic Equilibrium Models: Evidence from Chinese Provinces" CREATES WP 2012-26 (with Lei Pan and Michel van der Wel, May 2012). download the full document

Abstract:

We propose a model to study economic convergence in the tradition of neoclassical growth theory. We employ a novel stochastic set-up of the Solow (1956) model with shocks to both capital and labor. Our novel approach identifies the speed of convergence directly from estimating the parameters which determine equilibrium dynamics. The inference on the structural parameters is done using a maximum-likelihood approach. We estimate our model using growth and population data for China's provinces from 1980 to 2009. We report heterogeneity in the speed of convergence both across provinces and time. The Eastern provinces show a higher tendency of convergence, while there is no evidence of convergence for the Central and Western provinces. We find empirical evidence that the speed of convergence decreases over time for most provinces.

"On the estimation of the volatility-growth link" CREATES WP 2012-21 (with Andrey Launov and Klaus Wälde, April 2012). download the full document

Abstract:

It is common practice to estimate the volatility-growth link by specifying a standard growth equation such that the variance of the error term appears as an explanatory variable in this growth equation. The variance in turn is modelled by a second equation. Hardly any of existing applications of this framework includes exogenous controls in this second variance equation. Our theoretical findings suggest that the absence of relevant explanatory variables in the variance equation leads to a biased and inconsistent estimate of the volatility-growth link. Our simulations show that this effect is large. Once the appropriate controls are included in the variance equation consistency is restored. In short, we suggest that the variance equation must include relevant control variables to estimate the volatility-growth link.

"Estimating Dynamic Equilibrium Models using Macro and Financial Data" CREATES WP 2011-21 (with Bent Jesper Christensen and Michel van der Wel, June 2011). download the full document

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.

"Solving the New Keynesian model in continuous time" (with Jésus Fernández-Villaverde and Juan F. Rubio-Ramírez, February 2011). 

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.