| CHAPTER 6 A Comparison of the Michigan and Fair (2008) | |||||||||||||
Abstract | |||||||||||||
| This chapter compares the predictive accuracy of the Michigan and Fair models using the method developed in Fair (1980). These models are compared to each other and to an eighth-order autoregressive model. The method accounts for the four main sources of uncertainty of a forecast: uncertainty due to (I) the error terms, (2) the coefficient estimates, (3) the exogenous variables, and (4) the possible misspecifica-tion of the model. Because it accounts for these four sources, it can be used to make comparisons across models. In other words, it puts each model on an equal footing for purposes of comparison. The method has been used to compare the Fair model to autoregressive models, vector autoregressive models, Sargent’s classical macroeco-nomic model, and a small linear model, but this is the first time it has been used to compare two relatively large structural models. Ideally, model builders should not be the ones comparing their models to others. Although one may try to be objective, there is always the suspicion that one has stacked the cards in favor of her or his model. This chapter is not intended to be the final word on the relative merits of the Michigan and Fair models. Its primary aim is | |||||||||||||
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