Mechanics of forming and estimating dynamic linear economies
In: Handbook of Computational Economics
This 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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- King, Robert G. & Plosser, Charles I. & Rebelo, Sergio T., 1988. "Production, growth and business cycles : II. New directions," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 309-341.
- Rosen, Sherwin & Murphy, Kevin M & Scheinkman, Jose A, 1994.
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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.
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- 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.
- Ates Dagli, C. & Taylor, John B., 1984. "Estimation and solution of linear rational expectations models using a polynomial matrix factorization," Journal of Economic Dynamics and Control, Elsevier, vol. 8(3), pages 341-348, December.
- Lars Peter Hansen & Thomas J. Sargent, 1993. "Recursive linear models of dynamic economies," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
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- King, Robert G. & Plosser, Charles I. & Rebelo, Sergio T., 1988. "Production, growth and business cycles : I. The basic neoclassical model," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 195-232.
- Ellen R. McGrattan & Richard Rogerson & Randall Wright, 1993. "Household production and taxation in the stochastic growth model," Staff Report 166, Federal Reserve Bank of Minneapolis. Full references (including those not matched with items on IDEAS)
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