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The role of macroeconometric models in forecasting and policy analysis in the united states

✍ Scribed by Stephen K. McNees


Publisher
John Wiley and Sons
Year
1982
Tongue
English
Weight
881 KB
Volume
1
Category
Article
ISSN
0277-6693

No coin nor oath required. For personal study only.

✦ Synopsis


Abstract

This article stresses how little is known about the quality, particularly the relative quality, of macroeconometric models. Most economists make a strict distinction between the quality of a model per se and the accuracy of solutions based on that model. While this distinction is valid, it leaves unanswered how to compare the‘validity’of conditional models. The standard test, the accuracy of ex post simulations, is not definitive when models with differing degrees of exogeneity are compared. In addition, it is extremely difficult to estimate the relative quantitative importance of conceptual problems of models, such as parameter instability across‘policy regimes’

In light of the difficulty in comparisons of conditional macroeconometric models, many model‐builders and users assume that the best models are those that have been used to make the most accurate forecasts are those made with the best models. Forecasting experience indicates that forecasters using macroeconometric models have produced more accurate macroeconomic forecasts than either naive or sophisticated unconditional statistical models. It also suggests that judgementally adjusted forecasts have been more accurate than model‐based forecasts generated mechanically. The influence of econometrically‐based forecasts is now so pervasive that it is difficult to find examples of‘purely judgemental’forecasts.


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