Handbook of Economic Forecasting part 5 doc

... special case of the frequentist formulation of the forecasting problem described at the end of Section 2.4.1. As such, it inherits the internal inconsis- tencies of this approach, often appearing ... Bayesian Forecasting 19 2.4. Forecasting To this point we have considered the generic situation of J competing models relating a common vector of interest ω to a set of observ...

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... Subsequent developments 49 5. Some Bayesian forecasting models 53 5. 1. Autoregressive leading indicator models 54 5. 2. Stationary linear models 56 5. 2.1. The stationary AR(p) model 56 5. 2.2. The stationary ... stationary AR(p) model 56 5. 2.2. The stationary ARMA(p, q) model 57 5. 3. Fractional integration 59 5. 4. Cointegration and error correction 61 5. 5. Stochastic v...

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... same. Sections 5. 2.1 and 5. 5 provide applications of Metropolis within Gibbs in Bayesian forecasting models. 3.3. The full Monte We are now in a position to complete the practical Bayesian agenda for forecasting ... assessments of the accuracy of the approximations; these require more advanced, but publicly available, software; see Geweke (1999) and Geweke (20 05, Sections 4.1 a...

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... between x t and y t . 5. 2.1. The stationary AR(p) model One of the simplest models of serial correlation in ε t is an autoregression of order p. The contemporary Bayesian treatment of this problem ... matrix. The paper offers an extensive comparison of root mean square forecasting errors for all of the variables. These are summarized in Table 3, by first forming the ratio of...

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... bibliography”. International Journal of Forecasting 5, 55 9 58 3. Cogley, T., Morozov, S., Sargent, T. (20 05) . “Bayesian fan charts for U.K. inflation: Forecasting and sources of uncertainty in an evolving ... (1987). “Macroeconomic forecasting using pooled international data”. Journal of Business and Economic Statistics 5, 53 –67. Geisel, M.S. (19 75) . “Bayesian compariso...

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... Realized event A’s forecast B’s forecast A’s 5- year score B’s 5- year score A’s 10-year score B’s 5- year score 1 good good good ⎫ ⎪ ⎪ ⎪ ⎪ ⎬ ⎪ ⎪ ⎪ ⎪ ⎭ H A 1 5 = 1 F A 1 5 = 3 4 KS A 1 5 = 1 4 ⎫ ⎪ ⎪ ⎪ ⎪ ⎬ ⎪ ⎪ ⎪ ⎪ ⎭ H B 1 5 = 0 F B 1 5 = 1 4 KS B 1 5 =− 1 4 ⎫ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎬ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎪ ⎭ H A 1−10 = 2 5 F A 1−10 = 3 5 KS A 1−10 =− 1 5 ⎫ ⎪ ⎪...

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... Swanson (20 05) . Alternatively, one can swear off MSPE. This is discussed in the next section. 7. A small number of models, nested, Part II Leading competitors of MSPE for the most part are encompassing ... P −1 T  t=R  ˆy 1t+1 −ˆy 2t+1  2  (6.10)≡ˆσ 2 1 −  ˆσ 2 2 -adj  . 7 Note that (4 .5) and the left-hand side of (6.8) are identical, but that Section 4 recommends the use...

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... shopping-time model: An out -of- sample-prediction application to Canada”. Journal of Economics and Business 51 , 489 50 3. Hueng, C.J., Wong, K.F. (2000). “Predictive abilities of inflation -forecasting models ... American Economic Review 85, 201–218. McCracken, M.W. (2000). “Robust out of sample inference”. Journal of Econometrics 99, 1 95 223. McCracken, M.W. (2004). “Asymptotic...

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... approach of DGT) should be of interest from the perspective of out -of- sample evaluation. For this reason, and for sake of completeness, in this section we provide out -of- sample versions of all of the ... values of π, and choice thereof can have a discernible impact on finite sample test performance. 3.2. Out -of- sample implementation of Bai as well as Hong and Li tests We...

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... of the estimation scheme used, the contribution of parameter estimation error is asymptotically negligible. 3.3. Out -of- sample implementation of Corradi and Swanson tests We now outline out -of- sample ... following sections, application of Theorem 3.6 allows us to capture the contribution of (recur- sive) parameter estimation error to the covariance kernel of the limiting distr...

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