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The Time-Varying-Parameter Model for Modeling Changing Conditional Variance: The Case of the Lucas Hypothesis

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  • Kim, Chang-Jin
  • Nelson, Charles R

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.

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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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Handle: RePEc:bes:jnlbes:v:7:y:1989:i:4:p:433-40

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Cited by:
  1. Tim BOLLERSLEV & Ray Y. CHOU & Narayanan JAYARAMAN & Kenneth F. KRONER, 1991. "Les modéles ARCH en finance : un point sur la théorie et les résultats empiriques," Annales d'Economie et de Statistique, ENSAE, issue 24, pages 1-59.
  2. Giovanni Calice & RongHui Miao & Filip Sterba & Borek Vasicek, 2013. "Short-Term Determinants of the Idiosyncratic Sovereign Risk Premium: A Regime-Dependent Analysis for European Credit Default Swaps," Working Papers 2013/13, Czech National Bank, Research Department.
  3. Francisco Nadal De Simone, 2001. "Inflation Forecasting in Chile," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 4(3), pages 59-85, December.
  4. Jean-Thomas Bernard & Lynda Khalaf & Maral Kichian, 2004. "Structural Change and Forecasting Long-Run Energy Prices," Working Papers 04-5, Bank of Canada.
  5. Myeong Hwan Kim & Soung Chan Lee & Kwang Woo Park, 2007. "Income Inequality and Marriage," Economics Bulletin, AccessEcon, vol. 15(20), pages 1-12.
  6. de Pooter, M.D. & Segers, R. & van Dijk, H.K., 2006. "Gibbs sampling in econometric practice," Econometric Institute Research Papers EI 2006-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  7. Michiel D. de Pooter & Ren� 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.
  8. Lynda Khalaf & Maral Kichian, 2003. "Testing the Stability of the Canadian Phillips Curve Using Exact Methods," Working Papers 03-7, Bank of Canada.
  9. Michiel D. de Pooter & Ren� 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.
  10. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.

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