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Estimation with Pairwise Observations

Felix Chan, Laszlo Matyas

arXiv 20 Jan 2024 · Econometrics

arXiv:2401.11229 · PDF · DOI · OpenAlex · Extracted main text

Abstract

The paper introduces a new estimation method for the standard linear regression model. The procedure is not driven by the optimisation of any objective function rather, it is a simple weighted average of slopes from observation pairs. The paper shows that such estimator is consistent for carefully selected weights. Other properties, such as asymptotic distributions, have also been derived to facilitate valid statistical inference. Unlike traditional methods, such as Least Squares and Maximum Likelihood, among others, the estimated residual of this estimator is not by construction orthogonal to the explanatory variables of the model. This property allows a wide range of practical applications, such as the testing of endogeneity, i.e., the correlation between the explanatory variables and the disturbance terms.

Citation extraction

8
references
15
in-text mentions
8
distinct cited
1
self-citations
11,506
main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Chan, F. and L. Mátyás (2023) Estimation with Pairwise Observations – Online Supplement self0.81142100%
2McLeish, D. L (1975) Invariance Principles for Dependent Variables0.73732100%
3Billingsley, P (1999) Convergence of Probability Measures, Second Edition0.64422100%
4Hausman, J. A (1978) Specification tests in econometrics0.51121100%
5Wooldridge, J. M (2002) Econometric Analysis of Cross Section and Panel Data0.40511100%
6Johansen, S (1995) Likelihood-based Inference in Cointegrated Vector Auto-regressive Models0.40511100%
7Phillips, P. C. B (1986) Understanding spurious regressions in econometrics0.40511100%
8Wooldridge, J. M. and H. White (1988) Some invariance principles and central limit theorems for dependent heterogeneous processes0.40511100%

Showing the top 8 of 8 scored citations.