Handbook of Economic Forecasting part 3 pps

Handbook of Economic Forecasting part 3 pps

Handbook of Economic Forecasting part 3 pps

... before 1990 25 3. 1.1. Direct sampling 26 3. 1.2. Acceptance sampling 27 3. 1 .3. Importance sampling 29 3. 2. Markov chain Monte Carlo 30 3. 2.1. The Gibbs sampler 31 Handbook of Economic Forecasting, ... 6 83 3.1. Overview of PAR models 6 83 3.2. Modelling procedure 685 3. 3. Forecasting with univariate PAR models 686 3. 4. Forecasting with misspecified models 688 3....

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Handbook of Economic Forecasting part 107 pps

Handbook of Economic Forecasting part 107 pps

... 716, 986 Survey of Blue Chip Forecasters 736 Survey of Consumer Expectations 734 Survey of Household Income and Wealth 749 Survey of Professional Forecasters 186, 729, 733 , 736 , 749, 750, 759–761, ... Layard Volumes 3A, 3B and 3C edited by Orley C. Ashenfelter and David Card 6. HANDBOOK OF NATURAL RESOURCE AND ENERGY ECONOMICS (in 3 volumes). Edited by Allen V. Kneese and J...

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Handbook of Economic Forecasting part 2 pps

Handbook of Economic Forecasting part 2 pps

... models 37 1 7 .3. Dynamic common factors 37 2 7.4. Convergence 37 6 7.5. Forecasting and nowcasting with auxiliary series 37 9 8. Continuous time 38 3 8.1. Transition equations 38 3 8.2. Stock variables 38 5 8 .3. ... regression models 431 4. Forecasting with nonlinear models 431 4.1. Analytical point forecasts 431 4.2. Numerical techniques in forecasting 433 4 .3. Forecasti...

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Handbook of Economic Forecasting part 6 ppsx

Handbook of Economic Forecasting part 6 ppsx

... strong law of large numbers, (37 )M −1 M  m=1 w  θ (m)  h  ω (m)  a.s. → w ·h. The fraction in (35 ) is the ratio of the left-hand side of (37 ) to the left-hand side of (36 ). One of the attractive ... probability of proceeding from step 3 to step 4 is (33 )   ∗  k(θ | I)  a k k(θ | S)  p(θ | S) dθ = c I /a k c S . Let A be any subset of . The unconditional pro...

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Handbook of Economic Forecasting part 18 ppsx

Handbook of Economic Forecasting part 18 ppsx

... 0.1 pω ∗ 1 ω ∗ 2 pω ∗ 1 ω ∗ 2 0.05 0 .34 6 0 .32 4 0.05 0.081 0 .36 5 0.10 0.416 0 .31 4 0.10 0.156 0 .35 3 0.25 0.525 0.297 0.25 0 .35 4 0 .32 3 0.50 0. 636 0.280 0.50 0.620 0.2 83 0.75 0.744 0.264 0.75 0. 831 0.250 0.90 0.842 ... 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...

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Handbook of Economic Forecasting part 20 pps

Handbook of Economic Forecasting part 20 pps

... exp  −  γ 0,i + N  j=1 γ 1,j z t+h,t,j  −1 , z t+h,t,j =  ˆy t+h,t,j −¯y t+h,t  / ˆσ yt+h,t , p ∈{0, 1, 2, 3} . Here ¯y t+h,t is the sample estimate of the mean of y across the forecasting models while ˆσ yt+h,t is the sample estimate of the standard deviation using ... probabilities vary over time as a function of the arrival of new information provided that P is of ra...

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Handbook of Economic Forecasting part 21 pps

Handbook of Economic Forecasting part 21 pps

... 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 ... Combinations 1 83 In one of the most comprehensive studies to date, Stock and Watson (2001) consider combinations of a range of linear and nonlinear models fitted to a very la...

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Handbook of Economic Forecasting part 22 ppsx

Handbook of Economic Forecasting part 22 ppsx

... 1.00 0.95 0.96 1.00 h = 2 0.92 0. 93 0. 93 0. 93 0.95 0. 93 0.94 1.00 h = 4 0.91 0. 93 0.94 0.95 0.98 0. 93 0.96 1.00 h = 8 0.81 0.81 0.82 0.82 0. 83 0.81 0.82 1.00 Economic activity TMB25% TMB50% TMB75% ... 0.86 1.00 h = 8 0.84 0. 83 0. 83 0. 83 0. 83 0. 83 0. 83 1.00 Note: see note of Table 2. Ch. 4: Forecast Combinations 185 derive an approximate solution for the first two...

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Handbook of Economic Forecasting part 24 pps

Handbook of Economic Forecasting part 24 pps

... Li (20 03) , who also draw on results by Hong (2001). Their test is based on the comparison of the joint non- parametric density of  U t and  U t−j , as defined in (3) , with the product of two ... affect the covariance structure of the limiting distrib- ution of the statistic. Theorem 2 .3 below relies on Assumptions CS1–CS3, which are listed in Appendix A. Of note is that CS2...

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Handbook of Economic Forecasting part 27 ppsx

Handbook of Economic Forecasting part 27 ppsx

... constructed as in (29) and (30 ),  θ ∗ t,rec and  θ t,rec with  θ ∗ t,rol and  θ t,rol , and the same statement as in Proposi- tions 3. 7 and 3. 8 hold. Part III: Evaluation of (Multiple) Misspecified ... density models. 19 19 It should be noted that the contents of this section of the chapter have broad overlap with a number of topics discussed in the Chapter 3 in this Hand...

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