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


  • Kim, Chang-Jin
  • Nelson, Charles R


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.

Suggested Citation

  • Kim, Chang-Jin & Nelson, Charles R, 1989. "The Time-Varying-Parameter Model for Modeling Changing Conditional Variance: The Case of the Lucas Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 433-440, October.
  • Handle: RePEc:bes:jnlbes:v:7:y:1989:i:4:p:433-40

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    References listed on IDEAS

    1. Nijman, T E & Palm, F C, 1986. "The Construction and Use of Approximations for Missing Quarterly Observations: A Model-based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 47-58, January.
    2. Weiss, Andrew A., 1984. "Systematic sampling and temporal aggregation in time series models," Journal of Econometrics, Elsevier, vol. 26(3), pages 271-281, December.
    3. Lutkepohl, Helmut, 1984. "Linear transformations of vector ARMA processes," Journal of Econometrics, Elsevier, vol. 26(3), pages 283-293, December.
    4. Palm, Franz C & Nijman, Theo E, 1984. "Missing Observations in the Dynamic Regression Model," Econometrica, Econometric Society, vol. 52(6), pages 1415-1435, November.
    5. Tiao, G. C. & Guttman, Irwin, 1980. "Forecasting contemporal aggregates of multiple time series," Journal of Econometrics, Elsevier, vol. 12(2), pages 219-230, February.
    6. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
    7. Geweke, John F, 1978. "Temporal Aggregation in the Multiple Regression Model," Econometrica, Econometric Society, vol. 46(3), pages 643-661, May.
    8. Rose, David E., 1977. "Forecasting aggregates of independent Arima processes," Journal of Econometrics, Elsevier, vol. 5(3), pages 323-345, May.
    9. Litterman, Robert B, 1983. "A Random Walk, Markov Model for the Distribution of Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 169-173, April.
    10. Nijman, T.E., 1985. "Missing observations in dynamic macroeconomic modeling," Other publications TiSEM e37098ab-3c29-4f7c-b860-8, Tilburg University, School of Economics and Management.
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