Econometric Evaluation of Linear Macro-Economic Models

Macro-economic models are generally designed to achieve a multiplicity of objectives and correspondingly, they have been evaluated using a vast range of statistical, econometric, economic, political and even aesthetic criteria. However, in so far as they claim to represent economic behaviour, empirical macro-economic systems are certainly open to direct evaluation and testing against data information. The last few years have witnessed a substantial growth in the literature on econometric evaluation techniques, but despite important improvements in formalising evaluation procedures and their increased scope, formidable problems confront any investigation of a high dimensional, non-linear, stochastic, dynamic structure. Since system characteristics are the prime concern of economy-wide models, it might be the case that the validity of every individual component is not essential to adequate overall performance. While this viewpoint is debatable it does draw attention to the need for system evaluation procedures, at which point data limitations pose serious constraints on formal tests. Thus a new "limited information" test of forecast encompassing is proposed, based only on forecasts and requiring no other data from a model's proprietors. The derivation, merits and drawbacks of such a test are presented together with some suggestions for testing entailed relationships and inter-equation feedbacks.

[1]  C. Granger,et al.  Forecasting Economic Time Series. , 1988 .

[2]  Jean-Francois Richard,et al.  The encompassing principle and its application to non-nested hypotheses , 1986 .

[3]  P. Malgrange,et al.  Contemporary macroeconomic modelling , 1984 .

[4]  D. Hendry.  ECONOMETRIC MODELLING: THE “CONSUMPTION FUNCTION” IN RETROSPECT* , 1983 .

[5]  J. B. Ramsey,et al.  Large-Scale Macro-Econometric Models. , 1983 .

[6]  G. Chow,et al.  Econometric analysis by control methods , 1983 .

[7]  Adrian Pagan,et al.  Diagnostic tests as residual analysis , 1983 .

[8]  Richard M. Young,et al.  An Introduction to Econometric Forecasting and Forecasting Models. , 1981 .

[9]  C. Granger.  Some properties of time series data and their use in econometric model specification , 1981 .

[10]  Anil K. Bera,et al.  Efficient tests for normality, homoscedasticity and serial independence of regression residuals , 1980 .

[11]  Adrian Pagan,et al.  The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics , 1980 .

[12]  W. Fuller,et al.  Distribution of the Estimators for Autoregressive Time Series with a Unit Root , 1979 .

[13]  Andrew Harvey,et al.  The econometric analysis of time series , 1991 .

[14]  Peter Schmidt,et al.  Some Small Evidence on the Distribution of Dynamic Simulation Forecasts , 1977 .

[15]  George E. P. Box,et al.  Comparison of Forecast and Actuality , 1976 .

[16]  Chris Chatfield,et al.  Introduction to Statistical Time Series. , 1976 .

[17]  R. Lucas.  Econometric policy evaluation: A critique , 1976 .

[18]  D. Hendry.  Stochastic Specification in an Aggregate Demand Model of the United Kingdom , 1974 .

[19]  C. Nelson,et al.  The Stochastic Structure of the Velocity of Money , 1974 .

[20]  Michael D. Intriligator,et al.  Frontiers of Quantitative Economics. , 1972 .

[21]  Michael D. Geurts,et al.  Time Series Analysis: Forecasting and Control , 1977 .

[22]  James Durbin,et al.  Testing for Serial Correlation in Least-Squares Regression When Some of the Regressors are Lagged Dependent Variables , 1970 .

[23]  C. Granger.  Investigating causal relations by econometric models and cross-spectral methods , 1969 .

[24]  G. Chow.  Tests of equality between sets of coefficients in two linear regressions (econometrics voi 28 , 1960 .