Handbook of Economic Forecasting part 70 pps

... applications in economics, it is typically assumed that the stochastic process is of the autoregressive form, so that θ(L) = 1. As a result of the influential work of Box and Jenkins (1 970) , seasonal ... would be taken of the autocorrelation inherent in (24). Nevertheless, it is indicative of potential forecasting problems from using an overdifferenced model, which implies the pr...

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... Throsby HANDBOOK OF LAW AND ECONOMICS Editors A. Mitchell Polinsky and Steven Shavell HANDBOOK OF THE ECONOMICS OF EDUCATION Editors Eric Hanushek and Finis Welch HANDBOOK OF ECONOMICS OF TECHNOLOGICAL ... TITLES HANDBOOK OF EXPERIMENTAL ECONOMICS RESULTS Editors Charles Plott and Vernon L. Smith HANDBOOK ON THE ECONOMICS OF ART AND CULTURE Editors Victor Ginsburgh and...

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... 102 3. A small number of nonnested models, Part I 104 4. A small number of nonnested models, Part II 106 5. A small number of nonnested models, Part III 111 6. A small number of models, nested: ... v Contents of the Handbook vii PART 1: FORECASTING METHODOLOGY Chapter 1 Bayesian Forecasting JOHN GEWEKE AND CHARLES WHITEMAN 3 Abstract 4 Keywords 4 1. Introduction 6 2. B...

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... 696 5. Forecasting, seasonal adjustment and feedback 701 5.1. Seasonal adjustment and forecasting 702 5.2. Forecasting and seasonal adjustment 703 5.3. Seasonal adjustment and feedback 704 6. ... FORECASTING JOHN GEWEKE and CHARLES WHITEMAN Department of Economics, University of Iowa, Iowa City, IA 52242-1000 Contents Abstract 4 Keywords 4 1. Introduction 6 2. Bayesian infe...

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... application utilizing a combination of heterogeneous data and Bayesian model averaging. 2.4.4. Conditional forecasting In some circumstances, selected elements of the vector of future values of y may be known, ... linear combinations of elements of future values. The simplest such situation arises when one or more of the elements of y become known before the others, perhaps...

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... ˆy 2 has a bias equal of μ 2 . Then the MSE of ˆy 1 is σ 2 , while the MSE of ˆy 2 is σ 2 +μ 2 2 .The MSE of the combined forecast ˆy c = ω ˆy 1 +(1−ω) ˆy 2 relative to that of the best forecast (ˆy 1 )is MSE( ... (2004): If the joint distribution of (y t+h ˆ y  t+h,t )  is elliptically symmet- ric and the expected loss can be written as a function of the mean and variance of...

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... probabilities vary over time as a function of the arrival of new information provided that P is of rank greater than one. 4.2. Nonlinear combination schemes Two types of nonlinearities can be considered ... Letting σ 2 f e be the variance of f et , the co- variance matrix of the forecast errors becomes (70)  ef = σ 2 f e ββ  + D ε , where β = (β 1 β N )  is the vector of fa...

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... model irrespective of the length of the backward-looking window used to measure past forecasting perfor- mance. 7.3. Trimming of the worst models often improves performance Trimming of forecasts can ... the best in-sample performance often leads to poor out -of- sample forecasting performance; (iii) trimming of the worst models and clus- tering of models with similar forecast...

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... the inverse of their MSE-values. Out -of- sample forecasting performance is reported relative to the forecasting performance of the previous best (PB) model selected according to the forecasting ... low values of the discount factor. In a combination of forecasts from the Survey of Professional Forecasters and fore- casts from simple autoregressive models applied to six macroe...

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... remains of interest to know whether the rejection is due to violation of uniformity or to violation of independence (or both). Broadly speaking, violations of independence arises in the case of dynamic ... estimator of θ 0 . Visual inspection of the plot of this difference gives also some information about the deficiency of the candidate conditional density, and so may sugges...

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