Testing for autocorrelation in the presence of lagged dependent variables
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Publication:1318997
DOI10.1016/0304-4076(94)90046-9zbMath0800.62808OpenAlexW1530522398MaRDI QIDQ1318997
Jerry G. Thursby, Hashem Dezhbakhsh
Publication date: 12 April 1994
Published in: Journal of Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0304-4076(94)90046-9
Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Parametric hypothesis testing (62F03)
Related Items (2)
Hausman tests for autocorrelation in the presence of lagged dependent variables. Some further results ⋮ The wild bootstrap and heteroskedasticity-robust tests for serial correlation in dynamic regression models
Cites Work
- Finite-sample power of tests for autocorrelation in models containing lagged dependent variables
- A point optimal test for autoregressive disturbances
- The small sample bias of Durbin's tests for serial correlation when one of the regressors is the lagged dependent variable and the null hypothesis is true
- A note on an efficient two-step estimator
- Equivalence properties of the Hausman statistic based on a generalized inverse
- An efficient two-step estimator for the dynamic adjustment model with autoregressive errors
- A New Test for Autocorrelation in the Disturbances of the Dynamic Linear Regression Model
- A Remark on Hausman's Specification Test
- On the Rigour of Some Misspecification Tests for Modelling Dynamic Relationships
- Some Small Sample Properties of Durbin's Tests for Serial Correlation in Regression Models Containing Lagged Dependent Variables
- Tests for Serial Correlation in Regression Models with Lagged Dependent Variables and Serially Correlated Errors
- An Alternative Derivation of Durbin's h Statistic
- Specification Tests in Econometrics
- Power of the Noncentral F-Test: Effect of Additional Variates on Hotelling's T 2 -Test
- Computing the distribution of quadratic forms in normal variables
- Distribution of the Serial Correlation Coefficient
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