Structural Estimation of Jump-Diffusion Processes in Macroeconomics

61 Pages Posted: 23 Jun 2008 Last revised: 16 Jun 2012

See all articles by Olaf Posch

Olaf Posch

Universität Hamburg, Department of Economics; CREATES

Date Written: September 14, 2007

Abstract

Understanding the process of economic growth involves comparing competing theoretical models and evaluating their empirical relevance. Our approach is to take the neoclassical stochastic growth model directly to the data and make inferences about the model parameters of interest. In this paper, output follows a jump-diffusion process. By imposing parameter restrictions we derive two solutions in explicit form. Based on them, we obtain transition densities in closed form and employ maximum likelihood techniques to estimate the model parameters. In extensive Monte Carlo simulations we demonstrate that population parameters of the underlying data generating process can be recovered. We find empirical evidence for jumps in monthly and quarterly data on industrial production for the UK, the US, Germany, and the euro area (Euro12).

Keywords: Jump-diffusion estimation, Stochastic growth, Closed form solutions

JEL Classification: C13, E32, O40

Suggested Citation

Posch, Olaf, Structural Estimation of Jump-Diffusion Processes in Macroeconomics (September 14, 2007). Journal of Econometrics, Vol. 153, No. 2, 2009, Available at SSRN: https://ssrn.com/abstract=1150134 or http://dx.doi.org/10.2139/ssrn.1150134

Olaf Posch (Contact Author)

Universität Hamburg, Department of Economics ( email )

Von-Melle-Park 5
Hamburg, 20146
Germany

CREATES

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

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