The Time-Varying-Parameter Model for Modeling Changing Conditional Variance: The Case of the Lucas Hypothesis
Abstract
The main econometric issue in testing the Lucas (1973) hypothesis in a time series context is estimation of the forecast-error variance conditional on past information. The conditional variance may vary through time as monetary policy evolves and agents are obliged to infer its present state. Under the assumption that a monetary policy regime is continuously changing, a time-varying-parameter model is proposed for the monetary-growth function. Based on Kalman-filtering estimation of recursive forecast errors and their conditional variances, the Lucas hypothesis is tested for the U.S. economy (1964:1-1985:4) using monetary growth as aggregate demand variable. The Lucas hypothesis is rejected in favor of Friedman's (1977) hypothesis--the conditional variance of monetary growth affects real output directly, not through the coefficients on the forecast-error term in the Lucas-type output equation.Download Info
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Bibliographic Info
Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 7 (1989)
Issue (Month): 4 (October)
Pages: 433-40
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Lynda Khalaf & Maral Kichian, 2003. "Testing the Stability of the Canadian Phillips Curve Using Exact Methods," Working Papers 03-7, Bank of Canada.
- Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian, 2004. "Structural Change and Forecasting Long-Run Energy Prices," Working Papers 04-5, Bank of Canada.
- Myeong Hwan Kim & Soung Chan Lee & Kwang Woo Park, 2007. "Income Inequality and Marriage," Economics Bulletin, AccessEcon, vol. 15(20), pages 1-12.
- Michiel D. de Pooter & René Segers & Herman K. van Dijk, 2006. "On the Practice of Bayesian Inference in Basic Economic Time Series Models using Gibbs Sampling," Tinbergen Institute Discussion Papers 06-076/4, Tinbergen Institute.
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