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  1. その他
  2. 琉球大学経済学ワーキングペーパーシリーズ
  1. 部局別インデックス
  2. 国際地域創造学部

Forecasting with Vector Autoregressions Using Bayesian Variable Selection Methods: Comparison of Direct and Iterated Methods

http://hdl.handle.net/20.500.12000/44365
http://hdl.handle.net/20.500.12000/44365
6ec48045-3c2c-42d1-bf65-b14056182dd9
名前 / ファイル ライセンス アクション
WP2019-05_REWP02.pdf WP2019-05_REWP02.pdf
Item type デフォルトアイテムタイプ(フル)(1)
公開日 2019-05-14
タイトル
タイトル Forecasting with Vector Autoregressions Using Bayesian Variable Selection Methods: Comparison of Direct and Iterated Methods
言語 en
作成者 Sugita, Katsuhiro

× Sugita, Katsuhiro

en Sugita, Katsuhiro

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アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
内容記述
内容記述タイプ Other
内容記述 This paper compares multi-period forecasting performances by direct and iterated method using a Bayesian vector autoregressions with the stochastic search variable selection (SSVS) priors. The forecasting performances are evaluated using the artificially generated data with both nonstationary and stationary process. In theory direct forecasts are more efficient asymptotically and more robust to model misspecification than iterated forecasts, and iterated forecasts tend to bias but more efficient if the one-period ahead model is correctly specified. From the results of the Monte Carlo simulations, iterated forecasts tend to outperform direct forecasts, particularly with longer lag model and with longer forecast horizons. Implementing SSVS prior generally improves forecasting performance over unrestricted VAR model for either nonstationary or stationary data. As an illustration, US macroeconomic data sets with three variables are examined to compare iterated and direct forecasts using the unrestricted VAR model and the SSVS VAR model. Overall, iterated forecasts using model with the SSVS generally best outperform, suggesting that the SSVS restrictions on insignificant parameters alleviates over-parameterized problem of VAR in one-step ahead forecast and thus offers an appreciable improvement in forecast performance of iterated forecasts.
内容記述
内容記述タイプ Other
内容記述 プレプリント
出版者
言語 ja
出版者 琉球大学国際地域創造学部経済学プログラム
出版者
言語 en
出版者 Economics Program, Faculty of Global and Regional Studies, University of the Ryukyus
言語
言語 eng
資源タイプ
資源タイプ other
資源タイプ識別子 http://purl.org/coar/resource_type/c_1843
出版タイプ
出版タイプ AO
出版タイプResource http://purl.org/coar/version/c_b1a7d7d4d402bcce
識別子
識別子 http://hdl.handle.net/20.500.12000/44365
識別子タイプ HDL
収録物名
言語 ja
収録物名 琉球大学経済学ワーキングペーパーシリーズ
収録物名
言語 en
収録物名 Ryukyu Economics Working Paper Series
書誌情報
号 REWP#02, p. 1-18, 発行日 2019-05-14
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