On the application of automatic differentiation to the likelihood function for dynamic general equilibrium models
AbstractA key application of automatic differentiation (AD) is to facilitate numerical optimization problems. Such problems are at the core of many estimation techniques, including maximum likelihood. As one of the first applications of AD in the field of economics, we used Tapenade to construct derivatives for the likelihood function of any linear or linearized general equilibrium model solved under the assumption of rational expectations. We view our main contribution as providing an important check on finite-difference (FD) numerical derivatives. We also construct Monte Carlo experiments to compare maximum-likelihood estimates obtained with and without the aid of automatic derivatives. We find that the convergence rate of our optimization algorithm can increase substantially when we use AD derivatives.
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Bibliographic InfoPaper provided by Board of Governors of the Federal Reserve System (U.S.) in its series International Finance Discussion Papers with number 920.
Date of creation: 2008
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- Christopher J. Erceg & Luca Guerrieri & Christopher Gust, 2005.
"Can Long-Run Restrictions Identify Technology Shocks?,"
Journal of the European Economic Association,
MIT Press, vol. 3(6), pages 1237-1278, December.
- Christopher J. Erceg & Luca Guerrieri, 2004. "Can Long-Run Restrictions Identify Technology Shocks?," Computing in Economics and Finance 2004 3, Society for Computational Economics.
- Christopher Erceg & Luca Guerrieri & Christopher Gust, 2004. "Can long-run restrictions identify technology shocks?," International Finance Discussion Papers 792, Board of Governors of the Federal Reserve System (U.S.).
- Anderson, Gary, 1987. "A procedure for differentiating perfect-foresight-model reduced-from coefficients," Journal of Economic Dynamics and Control, Elsevier, vol. 11(4), pages 465-481, December.
- Anderson, Gary & Moore, George, 1985. "A linear algebraic procedure for solving linear perfect foresight models," Economics Letters, Elsevier, vol. 17(3), pages 247-252.
- Erceg, Christopher J. & Henderson, Dale W. & Levin, Andrew T., 2000.
"Optimal monetary policy with staggered wage and price contracts,"
Journal of Monetary Economics,
Elsevier, vol. 46(2), pages 281-313, October.
- Andrew Levin & Christopher J. Erceg & Dale W. Henderson, 1999. "Optimal Monetary Policy with Staggered Wage and Price Contracts," Computing in Economics and Finance 1999 1151, Society for Computational Economics.
- Christopher J. Erceg & Dale W. Henderson & Andrew T. Levin, 1999. "Optimal monetary policy with staggered wage and price contracts," International Finance Discussion Papers 640, Board of Governors of the Federal Reserve System (U.S.).
- Tom Doan, . "RATS program to solve Erceg-Henderson-Levin model," Statistical Software Components RTZ00051, Boston College Department of Economics.
- Ryo Kato & Takayuki Tsuruga, 2002. "Matlab code for a sticky wage/price model," QM&RBC Codes 114, Quantitative Macroeconomics & Real Business Cycles.
- Cristian Homescu, 2011. "Adjoints and Automatic (Algorithmic) Differentiation in Computational Finance," Papers 1107.1831, arXiv.org.
- Adolfson, Malin & Lindé, Jesper, 2011. "Parameter Identification in a Estimated New Keynesian Open Economy Model," Working Paper Series 251, Sveriges Riksbank (Central Bank of Sweden).
- Tore Selland Kleppe & Jun Yu & Hans J. Skaug, 2011.
"Simulated Maximum Likelihood Estimation for Latent Diffusion Models,"
CoFie-04-2011, Sim Kee Boon Institute for Financial Economics.
- Tore Selland Kleppe & Jun Yu & Hans J. Skaug, 2012. "Simulated Maximum Likelihood Estimation for Latent Diffusion Models," Working Papers 12-2012, Singapore Management University, School of Economics.
- Tore Selland Kleppe & Jun Yu & Hans J. skaug, 2011. "Simulated Maximum Likelihood Estimation for Latent Diffusion Models," Working Papers 10-2011, Singapore Management University, School of Economics.
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