The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Diagnostic tests as residual analysis
Abstract
Many applied workers are strongly oriented to residual analysis for assessing model adequacy. Formal test statistics of adequacy however are frequently derived from likelihood theory, particularly through Lagrange Multipliers. In contraGt, the present paper derives the formal statistics by concentrating Upon the distribution of residuals. It is shown that most existing tests can be derived in this way from a few elementary principles of specification analysis. One advantage of this alternative methodology is that it highlights some difficulties in existing approaches and simultaneously indicates a resolution of them; a good example being testing for heteroscedasticity in simultaneous equations. Other issues such as independence and robustness of diagnostic tests are also easily explored within the proposed framework.
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
Cites
Engle, R. F. (1982) · Econometrica · doi:10.2307/1912773 · Cited by 20,795
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
Self-citation
Cited by
Corporate social responsibility and access to finance
Cheng, B., Ioannou, I., & Serafeim, G. (2014) · Strategic Management Journal · doi:10.1002/smj.2131 · Cited by 3,896
Controlling for endogeneity with instrumental variables in strategic management research
Bascle, G. (2008) · Strategic Organization · doi:10.1177/1476127008094339 · Cited by 1,133
What will take the con out of econometrics
(1986) · International Journal of Forecasting · doi:10.1016/0169-2070(86)90113-5 · Cited by 296
West, K. D. (2006) · Handbook of Economic Forecasting · doi:10.1016/s1574-0706(05)01003-7 · Cited by 182
An analysis of the pricing of traits in the U.S. corn seed market
Shi, G., Chavas, J.-P., & Stiegert, K. (2010) · American Journal of Agricultural Economics · doi:10.1093/ajae/aaq063 · Cited by 52
Metadata
- Authors
- Pagan, A. R., & Hall, A. D.
- Venue
- Econometric Reviews
- Publisher
- Informa UK Limited
- Published
- 1983-01
- Volume
- 2
- Issue
- 2
- Pages
- 159-218
- ISSN
- 0747-4938 (ISSN-L)
- 1532-4168
- OpenAlex
- W1977527537
- Cited by
- 432
- References
- 2
- FWCI
- 16.06
- 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: Diagnostic tests as residual analysis. https://app.cochat.ai/papers/10.1080/07311768308800039
- The paper
- Pagan, A. R., & Hall, A. D. (1983). Diagnostic tests as residual analysis. Econometric Reviews. https://doi.org/10.1080/07311768308800039
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.
