The DOI matches its Crossref record.
Testing for Serial Correlation in Least-Squares Regression When Some of the Regressors are Lagged Dependent Variables
Abstract
The construction of tests of model specification is considered from a general point of view. The results are applied to testing the serial independence of the disturbances in a regression model where some of the regressors are lagged dependent variables. It is shown that the asymptotic distribution of the lag-1 serial correlation coefficient calculated from the least-squares residuals differs from that of the coefficient calculated from the true disturbances. A consequence of this is that tests of serial independence based on the residuals from regression on fixed regressors are invalid when applied to models containing lagged dependent variables even when the null hypothesis of serial independence is true. Tests which are asymptotically valid for the large-sample case are suggested.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
A Simple Test for Heteroscedasticity and Random Coefficient Variation
Breusch, T. S., & Pagan, A. R. (1979) · Econometrica · doi:10.2307/1911963 · Cited by 5,647
Several Tests for Model Specification in the Presence of Alternative Hypotheses
Davidson, R., & MacKinnon, J. G. (1981) · Econometrica · doi:10.2307/1911522 · Cited by 1,747
Modeling and pricing long memory in stock market volatility
Bollerslev, T., & Ole Mikkelsen, H. (1996) · Journal of Econometrics · doi:10.1016/0304-4076(95)01736-4 · Cited by 1,208
DIAGNOSTIC CHECKING ARMA TIME SERIES MODELS USING SQUARED‐RESIDUAL AUTOCORRELATIONS
McLeod, A. I., & Li, W. K. (1983) · Journal of Time Series Analysis · doi:10.1111/j.1467-9892.1983.tb00373.x · Cited by 1,123
Clustering of teenage suicides after television news stories about suicide
Phillips, D. P., & Carstensen, L. L. (1986) · New England Journal of Medicine · doi:10.1056/nejm198609113151106 · Cited by 387
Metadata
- Authors
- Durbin, J.
- Venue
- Econometrica
- Publisher
- JSTOR
- Published
- 1970-05
- Volume
- 38
- Issue
- 3
- Pages
- 410
- ISSN
- 0012-9682 (ISSN-L)
- OpenAlex
- W2036601475
- Cited by
- 1,182
- References
- 0
- FWCI
- 149.00
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Testing for Serial Correlation in Least-Squares Regression When Some of the Regressors are Lagged Dependent Variables. https://app.cochat.ai/papers/10.2307/1909547
- The paper
- Durbin, J. (1970). Testing for Serial Correlation in Least-Squares Regression When Some of the Regressors are Lagged Dependent Variables. Econometrica. https://doi.org/10.2307/1909547
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.