Mechanics of forming and estimating dynamic linear economies
AbstractThis paper catalogues formulas that are useful for estimating dynamic linear economic models. We describe algorithms for computing equilibria of an economic model and for recursively computing a Gaussian likelihood function and its gradient with respect to parameters. We display an application to Rosen, Murphy, and Scheinkman's (1994) model of cattle cycles.
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Bibliographic InfoPaper provided by Federal Reserve Bank of Minneapolis in its series Staff Report with number 182.
Date of creation: 1994
Date of revision:
Other versions of this item:
- Anderson, Evan W. & McGrattan, Ellen R. & Hansen, Lars Peter & Sargent, Thomas J., 1996. "Mechanics of forming and estimating dynamic linear economies," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 4, pages 171-252 Elsevier.
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
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- Ellen McGrattan & Richard Rogerson & Randall Wright, 1993. "Household production and taxation in the stochastic growth model," Staff Report 166, Federal Reserve Bank of Minneapolis.
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- Rosen, S. & Murphy, K.M. & Scheinkman, J.A., 1993. "Cattle Cycles," University of Chicago - Economics Research Center 93-2, Chicago - Economics Research Center.
- Sherwin Rosen & Kevin M. Murphy & Jose A. Scheinkman, 1993. "Cattle Cycles," NBER Working Papers 4403, National Bureau of Economic Research, Inc.
- Imrohoroglu, Selahattin, 1993. "Testing for sunspot equilibria in the German hyperinflation," Journal of Economic Dynamics and Control, Elsevier, vol. 17(1-2), pages 289-317.
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- McGrattan, Ellen R., 1994. "A note on computing competitive equilibria in linear models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 149-160, January.
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3479, National Bureau of Economic Research, Inc.
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