Inference in possibly integrated vector autoregressive models: Some finite sample evidence

DOI10.1016/S0304-4076(97)00109-7zbMath0962.62088OpenAlexW2085292821MaRDI QIDQ1298437

Hiro Y. Toda, Hiroshi Yamada

Publication date: 19 June 2001

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0304-4076(97)00109-7

zbMATH Keywords

cointegrationGranger causalityunit rootsvector autoregressions

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: hypothesis testing (62M07)

Related Items (11)

Short run and long run causality in time series: inference ⋮ Finite-sample simulation-based inference in VAR models with application to Granger causality testing ⋮ Modified two-stage least-squares estimators for the estimation of a structural vector autoregressive integrated process ⋮ A comparison of some common methods for detecting Granger noncausality ⋮ Robust inference for spurious regressions and cointegrations involving processes moderately deviated from a unit root ⋮ Finite Sample Modifications of the Granger Non Causality Test in Cointegrated Vector Autoregressions ⋮ Lag‐augmented two‐ and three‐stage least squares estimators for integrated structural dynamic models ⋮ A note on the causality between export and productivity: an empirical re-examination ⋮ Structural analysis of vector error correction models with exogenous \(I(1)\) variables ⋮ EMPIRICAL LIKELIHOOD TEST FOR CAUSALITY OF BIVARIATE AR(1) PROCESSES ⋮ Subsampling vector autoregressive tests of linear constraints

Cites Work

• Statistical Inference in Instrumental Variables Regression with I(1) Processes
• Understanding spurious regressions in econometrics
• Statistical analysis of cointegration vectors
• Statistical inference in vector autoregressions with possibly integrated processes
• Inference in Linear Time Series Models with some Unit Roots
• Multiple Time Series Regression with Integrated Processes
• Vector Autoregressions and Causality
• Vector autoregression and causality: a theoretical overview and simulation study
• Fully Modified Least Squares and Vector Autoregression
• Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models

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