Keywords
Spurious relationshipEconometricsMathematicsStatisticsStatisticAsymptotic analysisRegressionRegression analysisLinear regressionContext (archaeology)Statistical hypothesis testingTest statisticCointegrationAutocorrelationAsymptotic distributionGranger causality
Affiliated Institutions
Related Publications
Multiple Time Series Regression with Integrated Processes
This paper develops a general asymptotic theory of regression for processes which are integrated of order one. The theory includes vector autoregressions and multivariate regres...
Testing for Regression Coefficient Stability with a Stationary AR(1) Alternative
A bstract-We discuss the problem of testing for constant versus time varying regression coefficients. Our alternative hypothesis allows the coefficients to follow a stationary A...
Time Series Regression with a Unit Root
This paper studies the random walk, in a general time series setting that allows for weakly dependent and heterogeneously distributed innovations. It is shown that simple least ...
Statistical Inference in Regressions with Integrated Processes: Part 1
This paper develops a multivariate regression theory for integrated processes which simplifies and extends much earlier work. Our framework allows for both stochastic and certai...
Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models
This paper contains the likelihood analysis of vector autoregressive models allowing for cointegration. The author derives the likelihood ratio test for cointegrating rank and f...
Publication Info
- Year
- 1986
- Type
- article
- Volume
- 33
- Issue
- 3
- Pages
- 311-340
- Citations
- 1767
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
1767
OpenAlex
Cite This
Peter C.B. Phillips
(1986).
Understanding spurious regressions in econometrics.
Journal of Econometrics
, 33
(3)
, 311-340.
https://doi.org/10.1016/0304-4076(86)90001-1
Identifiers
- DOI
- 10.1016/0304-4076(86)90001-1