Projection Minimum Distance: An Estimator for Dynamic Macroeconomic Models
This paper introduces an estimator for dynamic macroeconomic models where possibly the dynamics and the variables described therein are incomplete representations of a larger, unknown macroeconomic system. We call this estimator projection minimum distance (PMD) and show that it is consistent and asymptotically normal. Many times, PMD can provide consistent estimates of structural parameters even when the dynamics of the macroeconomic model are insufficient to account for the serial correlation of the data or correlation with information omitted from the model. PMD provides an overall specification chi-squared test based on the distance between the impulse responses of the model and their semi-parametric estimates from the data. PMD only requires two, simple, least-squares steps and can be generalized to more complex, nonlinear environments.
|Date of creation:||22 Aug 2006|
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- Jeffrey C. Fuhrer & Giovanni P. Olivei, 2005.
"Estimating forward-looking Euler equations with GMM estimators: an optimal-instruments approach,"
Board of Governors of the Federal Reserve System (U.S.), pages 87-114.
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0225, National Bureau of Economic Research, Inc.
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- Roger E. A. Farmer, 1999. "Macroeconomics of Self-fulfilling Prophecies, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262062038, June.
- Lewis, Richard & Reinsel, Gregory C., 1985. "Prediction of multivariate time series by autoregressive model fitting," Journal of Multivariate Analysis, Elsevier, vol. 16(3), pages 393-411, June.
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