Model Identification in Dynamic Regression (Distributed Lag) Models

Ruey S. Tsay

34 citations0/0 files storedJournal of Business and Economic Statistics

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Forecasting Techniques and Applications Control Systems and Identification Statistical Methods and Applications

Abstract

Dynamic regression models (also known as distributed lag models) are widely used in engineering for quality control and in economics for forecasting. In this article I propose a procedure for specifying such models in practice. The proposed procedure requires no prewhitening and can directly handle the nonstationary series. Furthermore, the procedure cross-validates prior beliefs about causal relationships between variables with empirical findings to ensure the suitability of model structure. An illustrative example is given.

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1969Investigating Causal Relations by Econometric Models and Cross-spectral Methods 1977Time Series Analysis: Forecasting and Control 1972MONEY, INCOME, AND CAUSALITY 1982Measurement of Linear Dependence and Feedback Between Multiple Time Series 2000Forecasting Economic Time Series 1979Forecasting Economic Time Series 1977Forecasting Economic Time Series 1977Causality in temporal systems

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