By M. Clements
Financial econometrics is without doubt one of the maximum on-going luck tales of contemporary a long time, because it has turn into probably the most lively components of analysis in econometrics. during this booklet, Michael Clements offers a transparent and logical clarification of the main strategies and ideas of forecasts of financial and fiscal variables. He exhibits that forecasts of the only probably end result of an fiscal and monetary variable are of constrained worth. Forecasts that supply additional info at the anticipated most probably levels of results are extra suitable. This booklet presents a entire therapy of the assessment of alternative varieties of forecasts and attracts out the parallels among the several techniques. It describes the tools of comparing those extra advanced forecasts which supply a fuller description of the diversity of attainable destiny outcomes.
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Additional resources for Evaluating Econometric Forecasts of Economic and Financial Variables
2 plots the estimated densities of the changes in the two interest rates, with matched Gaussian densities, illustrating the fatter tails, and the QQ plots3 against Gaussian densities (with the same means and variances) conﬁrm the departures from normality of the unconditional distributions. Non-linear ARCH models are also capable of capturing the empirical ﬁnding that negative shocks or ‘bad news’ affect volatility differently from positive shocks. ARCH implies that there may be more uncertainty surrounding the point prediction at some times than at others.
Tests are carried out at a 5% nominal level. 20 Evaluating Econometric Forecasts DM The Diebold–Mariano test for equal forecast accuracy applied to testing for forecast encompassing. 1 the test for equal forecast accuracy (assuming squared-error loss) was based on 2 2 testing whether dt = e1t −e2t = 0. If instead we deﬁne dt = e1t (e1t −e2t ), testing whether dt = 0 is now a test of forecast encompassing. The resulting test statistic is compared to the standard normal distribution. MDM Harvey et al.
1. However, published forecasts of macroeconomic variables based on large-scale macro-econometric models usually reﬂect in varying degree the properties of the model and the skills of the models’ proprietors. Forecasts are rarely based on the model alone. Moreover, forecasters’ adjustments tend to improve accuracy: see, for example, Marris (1954), Wallis et al. 8), Wallis et al. 4) and Wallis and Whitley (1991). That being the case, tests of the predictive accuracy of the model-based forecasts may have little bearing on assessing the published forecasts.