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The ARAR Error Model for Univariate Time Series and Distributed Lag

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Author Info
Richard Carter (University of Western Ontario and University of Calgary)
Arnold Zellner (GSB, University of Chicago)

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Abstract

We show that the use of prior information derived from former empirical findings and/or subject matter theory regarding the lag structure of the observable variables together with an AR process for the error terms can produce univariate and single equation models that are intuitively appealing, simple to implement and work well in practice.

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Publisher Info
Article provided by Berkeley Electronic Press in its journal Studies in Nonlinear Dynamics & Econometrics.

Volume (Year): 8 (2004)
Issue (Month): 1 ()
Pages: 1132-1132
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Handle: RePEc:bep:sndecm:8:2004:1:1132-1132

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Keywords: time series analysis model formulation model choice Bayesian inference

References listed on IDEAS
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  1. Monahan, John F., 1983. "Fully Bayesian analysis of ARMA time series models," Journal of Econometrics, Elsevier, vol. 21(3), pages 307-331, April. [Downloadable!] (restricted)
  2. Nicholls, D F & Pagan, Adrian R & Terrell, R D, 1975. "The Estimation and Use of Models with Moving Average Disturbance Terms: A Survey," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 16(1), pages 113-34, February. [Downloadable!] (restricted)
  3. Andrew Caplin & John Leahy, 1999. "Durable Goods Cycles," NBER Working Papers 6987, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  4. Zellner, Arnold & Hong, Chansik, 1989. "Forecasting international growth rates using Bayesian shrinkage and other procedures," Journal of Econometrics, Elsevier, vol. 40(1), pages 183-202, January. [Downloadable!] (restricted)
    Other versions:
  5. Zellner, Arnold & Tobias, Justin, 2001. "Further Results on Bayesian Method of Moments Analysis of the Multiple Regression Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 42(1), pages 121-40, February.
    Other versions:
  6. Shiller, Robert J, 1973. "A Distributed Lag Estimator Derived from Smoothness Priors," Econometrica, Econometric Society, vol. 41(4), pages 775-88, July. [Downloadable!] (restricted)
  7. Zellner, Arnold & Geisel, Martin S, 1970. "Analysis of Distributed Lag Models with Application to Consumption Function Estimation," Econometrica, Econometric Society, vol. 38(6), pages 865-88, November. [Downloadable!] (restricted)
  8. Russell Cooper & Alok Johri, 1999. "Learning by Doing and Aggregate Fluctuations," NBER Working Papers 6898, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  9. Schotman, Peter C & van Dijk, Herman K, 1991. "On Bayesian Routes to Unit Roots," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 387-401, Oct.-Dec.. [Downloadable!] (restricted)
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  10. Zellner, Arnold & Hong, Chansik & Min, Chung-ki, 1991. "Forecasting turning points in international output growth rates using Bayesian exponentially weighted autoregression, time-varying parameter, and pooling techniques," Journal of Econometrics, Elsevier, vol. 49(1-2), pages 275-304. [Downloadable!] (restricted)
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