On the distribution of information in the moment structure of DSGE models
There is a long tradition in macroeconomics of using selected moments of the data to determine empirically relevant values of structural parameters. This paper presents a formal approach for evaluating the implications of DSGE models for the distribution of information in the moment structure of their variables. Specifically, it shows how to address the following questions: (1) what are the efficiency gains from using more instead of fewer moments; (2) what is the efficiency loss from assigning suboptimal weights on the used moments; and (3) which particular dimensions of the data - first and second order moments in the time domain, and sets of frequencies in the fre quency domain - are most informative about individual structural parameters. The analysis is based on the asymptotic properties of maximum likelihood and moment matching estimators and is simple to perform for general linearized models. A standard real business cycle model is used as an illustration.
|Date of creation:||2013|
|Contact details of provider:|| Postal: Society for Economic Dynamics Marina Azzimonti Department of Economics Stonybrook University 10 Nicolls Road Stonybrook NY 11790 USA|
Web page: http://www.EconomicDynamics.org/
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- José-Víctor Ríos-Rull & Frank Schorfheide & Cristina Fuentes-Albero & Maxym Kryshko & Raül Santaeulàlia-Llopis, 2009.
"Methods versus Substance: Measuring the Effects of Technology Shocks on Hours,"
NBER Working Papers
15375, National Bureau of Economic Research, Inc.
- Fuentes-Albero, Cristina & Kryshko, Maxym & Ríos-Rull, José-Víctor & Santaeulàlia-Llopis, Raül & Schorfheide, Frank, 2009. "Methods versus Substance: Measuring the Effects of Technology Shocks on Hours," CEPR Discussion Papers 7474, C.E.P.R. Discussion Papers.
- José-Víctor Ríos-Rull & Frank Schorfheide & Cristina Fuentes-Albero & Raul Santaeulalia-Llopis & Maxym Kryshko, 2009. "Methods versus substance: measuring the effects of technology shocks on hours," Staff Report 433, Federal Reserve Bank of Minneapolis.
- Peter A. Zadrozny, 1988. "Analytic Derivatives for Estimation of Linear Dynamic Models," Working Papers 88-5, Center for Economic Studies, U.S. Census Bureau.
- Ruge-Murcia, Francisco J., 2007.
"Methods to estimate dynamic stochastic general equilibrium models,"
Journal of Economic Dynamics and Control,
Elsevier, vol. 31(8), pages 2599-2636, August.
- RUGE-MURCIA, Francisco J., 2003. "Methods to Estimate Dynamic Stochastic General Equilibrium Models," Cahiers de recherche 17-2003, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
- RUGE-MURCIA, Francisco J., 2003. "Methods to Estimate Dynamic Stochastic General Equilibrium Models," Cahiers de recherche 2003-23, Universite de Montreal, Departement de sciences economiques.
- Ruge-Murcia, Francisco J., 2002. "Methods to Estimate Dynamic Stochastic General Equilibrium Models," University of California at San Diego, Economics Working Paper Series qt4fc8x822, Department of Economics, UC San Diego.
- Francisco J. Ruge-Murcia, 2004. "Methods to Estimate Dynamic Stochastic General Equilibrium Models," 2004 Meeting Papers 83, Society for Economic Dynamics.
- Ben S. Bernanke & Julio J. Rotemberg, 1997. "Editorial in "NBER Macroeconomics Annual 1997, Volume 12"," NBER Chapters, in: NBER Macroeconomics Annual 1997, Volume 12, pages 1-6 National Bureau of Economic Research, Inc.
- Zhongjun Qu & Denis Tkachenko, 2012. "Identification and frequency domain quasi‐maximum likelihood estimation of linearized dynamic stochastic general equilibrium models," Quantitative Economics, Econometric Society, vol. 3(1), pages 95-132, 03.
- Ben S. Bernanke & Julio J. Rotemberg, 1997. "NBER Macroeconomics Annual 1997, Volume 12," NBER Books, National Bureau of Economic Research, Inc, number bern97-1, April.
- Jondeau E. & Le Bihan H. & Galles C., 2004. "Assessing Generalized Method-of-Moments Estimates of the Federal Reserve Reaction Function," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 225-239, April.
When requesting a correction, please mention this item's handle: RePEc:red:sed013:339. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christian Zimmermann)
If references are entirely missing, you can add them using this form.