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TUPD-2022-006

表 題 ardl: Estimating autoregressive distributed lag and equilibrium correction models
著 者 Sebastian Kripfganz

英国 エクセター大学ビジネス・スクール 講師
東北大学経済学研究科 客員准教授

Daniel C. Schneider

マックス・プランク人口研究所

P D F
要 旨

We present a Stata package for the estimation of autoregressive distributed lag (ARDL) models in a time-series context. The ardl command can be used to estimate an ARDL model with the optimal number of autoregressive and distributed lags based on the Akaike or Schwarz/Bayesian information criterion. The regression results can be displayed in the ARDL levels form or in the error-correction representation of the model. The latter separates long-run and short-run effects and is available in two different parameterizations of the long-run (cointegrating) relationship. The popular bounds testing procedure for the existence of a long-run levels relationship is implemented as a postestimation feature. Comprehensive critical values and approximate p-values obtained from response-surface regressions facilitate statistical inference.

キーワード 自己回帰分布ラグモデル Autoregressive distributed lag model, 誤差修正モデル Error-correction model, 境界テスト Bounds test, 長期にわたる関係性 Long-run relationship, 共和分 Cointegration, 時系列データ Time-series data
発行年月 2022年4月

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