Cited by 18,820Spatial and Panel Data AnalysisAdvanced Causal Inference TechniquesAdvanced Statistical Methods and Models

Specification Tests in Econometrics

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Hausman, J. A.·1978·Econometrica

Abstract

Using the result that under the null hypothesis of no misspecification an asymptotically efficient estimator must have zero asymptotic covariance with its difference from a consistent but asymptotically inefficient estimator, specification tests are devised for a number of model specifications in econometrics. Local power is calculated for small departures from the null hypothesis. An instrumental variable test as well as tests for a time series cross section model and the simultaneous equation model are presented. An empirical model provides evidence that unobserved individual factors are present which are not orthogonal to the included right-hand-side variable in a common econometric specification of an individual wage equation.

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Cites

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  • The Hausman test confirmed that the PMG estimator is more efficient and consistent than the MG estimator.

    “Table 7 above also shows that the Hausman test, which helps to determine whether there is a significant difference between MG and PMG estimators, confirmed that the PMG is more efficient and consistent compared to the MG (Hausman 1978).”

    From Financial Inclusion and Economic Growth in Sub-Saharan Africa—A Panel ARDL and Granger Non-Causality Approach (2023) · cites this paper as Hausman 1978

    The panel-data models and empirical example sections describe a Hausman specification test based on differences between estimators, supporting the methodological part of the citation. They compare fixed-effects and GLS estimators, not MG and PMG, and do not establish that PMG is more efficient and consistent than MG in the citing paper’s Table 7. The source also makes efficiency and consistency conditional on the specification. (LLM, conf=0.85)

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  • The Hausman test was employed to determine the suitable model among MG, PMG, and DFE.

    “In addition, we employed the Hausman test (Hausman 1978) to determine the suitable model to use between the mean group (MG), PMG, and the dynamic fixed effects (DFEs).”

    From Financial inclusion, bank competition and economic growth in Africa (2021) · cites this paper as Hausman 1978

  • Hausman tests indicated that estimates would suffer mildly from omitted variables bias and that the fixed effects model was preferred.

    “The results showed that the estimates would suffer, albeit only mildly, from omitted variables bias and that the use of fixed effects model was preferred.”
  • A Hausman test was performed to test whether factors that differ across countries, such as differing strength of diabetes surveillance systems, would systematically affect the results, ensuring the available data were suitable to answer the research questions.

    “First, a Hausman test [28] was performed to test whether factors that differ across countries such as the differing strength of diabetes surveillance systems would systematically affect our results, ensuring the available data were suitable to answer our research questions.”

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Cites

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Research works printed but not linked: 7

  1. Brundy J., Jorgenson D. W. (1971). Efficient estimation of simultaneous equation systems by instrumen- tal variables. Review of Economics and Statistics, 53 (2), 207-224.
  2. Byron R. P. (1974). Testing structural specification using the unrestricted reduced form. Econometrica, 42 (5), 869-883.
  3. Gordon R. (1976). Essays on the causes and equitable treatment of differences in earnings and ability. Massachusetts Institute of Technology, Ph. D. Thesis, June, 1976.
  4. by W. Hood and T. C. Koopmans. New Haven: Yale University Press, 1953, 113-199.
  5. Liviatan N. (1963). Tests of the permanent income hypothesis based on a re-interview savings study. In: Measurement in Economics, ed. by C. Christ. Stanford: Stanford University Press, 1963, 29-59.
  6. Ramsey J. B. (1974). Classical model selection through specification error tests. In: Frontiers of Econo- metrics, ed. by P. Zarembka. New York: Academic Press.
  7. Rao C. R. (1973). Linear statistical inference. New York: Wiley.

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Authors
Hausman, J. A.
Corresponding author
Hausman, J. A.
Venue
Econometrica
Publisher
JSTOR
Published
1978-11
Volume
46
Issue
6
Pages
1251
ISSN
0012-9682 (ISSN-L)
OpenAlex
W2112352537
Cited by
18,820
References
18
Citations by year
2026: 1074 · 2025: 994 · 2024: 999 · 2023: 922 · 2022: 1010 · 2021: 1016 · 2020: 929 · 2019: 823 · 2018: 675 · 2017: 655 · 2016: 682 · 2015: 631 · 2014: 658 · 2013: 637 · 2012: 606
FWCI
84.19
Type
journal article
Language
en
Open access
Locations
  • Econometrica (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Statistical Methods and Models
Keywords
specification tests, model misspecification, asymptotic efficiency, local power, systems of equations, wage equation, consistent estimators

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