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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

Evaluation of Forecasting Performance Using Bayesian Stochastic Search Variable Selection in a Vector Autoregression

http://hdl.handle.net/20.500.12000/42446
http://hdl.handle.net/20.500.12000/42446
40f25281-875a-48db-a451-2539ae6be39e
名前 / ファイル ライセンス アクション
2018-08_WP01_SSVS-VAR-Sim.pdf 2018-08_WP01_SSVS-VAR-Sim.pdf
Item type デフォルトアイテムタイプ(フル)(1)
公開日 2018-09-21
タイトル
タイトル Evaluation of Forecasting Performance Using Bayesian Stochastic Search Variable Selection in a Vector Autoregression
言語 en
作成者 Sugita, Katsuhiro

× Sugita, Katsuhiro

en Sugita, Katsuhiro

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 examines forecasting performance of a vector autoregressive (VAR) model by a Bayesian stochastic search variable selection (SSVS) method. We use several artificially generated data sets to evaluate forecasting performance using a direct multiperiod forecasting method with a recursive forecasting exercise. We find that implementing SSVS prior in a VAR improves forecasting performance over unrestricted VAR models for either non-stationary or stationary data. As an illustration of a VAR model with SSVS prior, we investigate US macroeconomic data sets with three variables using a VAR with lag length of ten, and find that the SSVS restrictions on insignificant parameters alleviates over-parameterized problem of VAR and thus offers an appreciable improvement in forecast performance.
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
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/20.500.12000/42446
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
書誌情報
号 REWP#01, p. 1-19, 発行日 2018-09-21
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