Handbook of Economic Forecasting part 1 pptx

... 09 10 10 9 8 7 6 5 4 3 2 1 HANDBOOK OF ECONOMIC FORECASTING VOLUME 1 INTRODUCTION TO THE SERIES The aim of the Handbooks in Economics series is to produce Handbooks for various branches of economics, ... FRANCISCO • SINGAPORE • SYDNEY • TOKYO CONTENTS OF THE HANDBOOK VOLUME 1 Introduction to the Series Contents of the Handbook PART 1: FORECASTING METHODOLOGY C...

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... Conditional on S t = 1:  e 1t e 2t  ∼ N   (1 − β 1 )μ 1 μ 1 − β 2 μ 2  ,  (1 − β 1 ) 2 σ 2 f 1 + β 2 1 σ 2 ε 1 + σ 2 ε y (1 − β 1 )σ 2 f 1 + σ 2 ε y (1 − β 1 )σ 2 f 1 + σ 2 ε y σ 2 f 1 + β 2 2 σ 2 f 2 + ... holds: ( 31) 1 3  p 1 − p  2 1 + ψ 2 1 + ψ 1 < σ 2 f 2 σ 2 f 1 < 3  p 1 − p  2 1 + ψ 2 1 + ψ 1 . 15 8 A. Timmermann M...

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... 306 3 .1. The echelon form 306 3 .1. 1. Stationary processes 307 3 .1. 2. I (1) processes 309 3.2. Estimation of VARMA models for given lag orders and cointegrating rank 311 3.2 .1. ARMA E models 311 3.2.2. ... results 316 Handbook of Economic Forecasting, Volume 1 Edited by Graham Elliott, Clive W.J. Granger and Allan Timmermann © 2006 Elsevier B.V. All rights reserved DOI: 10...

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... estimators of underlying change, relative to RMSE of corresponding estimator from the local linear trend model q = σ 2 ζ /σ 2 η r 0 .1 0.5 1 10 1 1.92 1. 41 1.27 1. 04 3 1. 20 1. 10 1. 20 2.54 12 1. 27 1. 92 ... covariance matrix  σ 2 1 σ 12 σ 12 σ 2 2  the distribution of y 2 conditional on y 1 is normal with mean μ 2 + (σ 12 /σ 2 1 )(y 1 − μ 1 ) and var...

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... Series Analysis 7, 17 8 19 0. Clements, M.P., Franses, P.H., Swanson, N.R. (2004). Forecasting economic and financial time-series with non-linear models”. International Journal of Forecasting 20, 16 9 18 3. Clements, ... Journal of Forecasting 20, 18 5 19 9. Corradi, V., Swanson, N.R. (2006). “Predictive density evaluation”. In: Elliott, G., Granger, C.W.J., Timmer- mann, A. (Eds...

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... choice of the basis itself or of the elements of the dic- tionary. Section 8 of DeVore’s (19 98) comprehensive survey is devoted to a discussion of the so far somewhat fragmentary degree of approximation ... thought of as a very carefully constructed special case of ANNs. Ridgelets arise by taking ψ j (x) = γ 1/ 2 1j   ˜x  γ 2j − γ 0j  /γ 1j  , where ˜x denotes the vect...

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... 0.3 914 4 ∗ 91. 07860 1. 36222 0.83499 0.36325 0 .19 582 0. 215 14 10 1. 1 719 6 1. 515 68 0.89399 0.30 814 0 .10 522 0 .15 968 11 1. 013 25 1. 44063 0.73 511 0.4 018 3 0 .14 952 0.30902 12 1. 04729 1. 5 712 2 0.89255 0.3 817 4 ... −0 .11 766 −0 .10 375 10 1. 66726 1. 93842 0.59673 0. 015 73 −0 .14 434 −0 .10 666 11 1. 66305 1. 94770 0.59 417 0. 018 22 −0 .14 982 −0 .10 193...

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... 57), Klein (19 71) , Klein, Howrey and MacCarthy (19 74), and the sequence of reviews by the UK ESRC Macroeconomic Modelling Bureau in Wallis et al. (19 84, 19 85, 19 86, 19 87), Turner (19 90), and Wallis ... is given by (46)y t +1 = 1 (tτ) β  1 x t + (1 − 1 (tτ) )β  2 x t + u t +1 so that the pre-break observations are t = 1, ,τ, and the post-break t = τ +1, ,T. There is...

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... DVECM 1- step forecasts of U r,t and R r t , 19 19 19 38. Figure 7. VECM 1- step and 10 -step forecasts of U r,t and R r t , 19 48 19 67. Ch. 12 : Forecasting with Breaks 647 Figure 8. VECM 1- step and 10 -step ... Statistics 21, 19 6– 211 . Clements, M.P., Smith, J. (19 99). “A Monte Carlo study of the forecasting performance of empirical SETAR models”. Journal of Appl...

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... and Economic Statistics 7, 11 17 11 27. Otto, G., Wirjanto, T. (19 90). “Seasonal unit root tests on Canadian macroeconomic time series”. Economics Letters 34, 11 7 12 0. Paap, R., Franses, P.H. (19 99). ... Statistics 21, 420–436. Canova, F., Ghysels, E. (19 94). “Changes in seasonal patterns: Are they cyclical?”. Journal of Economic Dynamics and Control 18 , 11 43 11 71. Canova,...

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