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パネルベクトル自己回帰(Panel VAR)×最小二乗法 (OLS) 回帰×ベクトル自己回帰(VAR)モデル×
分野計量経済学計量経済学計量経済学
系統Regression modelRegression modelRegression model
提唱年198820192005
提唱者Holtz-Eakin, Newey & RosenWooldridge (textbook treatment); classical least squaresLütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
種類Panel vector autoregressionLinear regressionMultivariate time-series model
原典Holtz-Eakin, D., Newey, W. & Rosen, H. S. (1988). Estimating Vector Autoregressions with Panel Data. Econometrica, 56(6), 1371-1395. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
別名PVAR, panel vector autoregression, Panel VAR (PVAR)ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonuvector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
関連354
概要Panel VAR extends the vector autoregression model to panel data, modelling the dynamic interactions among several variables while controlling for cross-unit heterogeneity through fixed effects. It was introduced by Holtz-Eakin, Newey and Rosen in 1988 and produces impulse-response functions and variance decompositions at the panel level.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).
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ScholarGate手法を比較: Panel VAR · OLS Regression · VAR Model. 2026-06-18に以下より取得 https://scholargate.app/ja/compare