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Biases on variances estimated on large data-sets

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Abstract

The inverse dependency of the estimated variances onver the sample size throws a fundamental question on the validity of the usual statistical methodology, since any hypothesis on the value of a coefficient can be tested negatively by increasing the size of the data-set. I suppose that large data-sets are characterized by a concentration of information on homogenous sub-populations, a spatial autocorrelation of the error terms and the covariates may bias the estimation of variances. Using the corrections of variances under spatial autocorrelation, we obtain variances comparable to an estimation on sub-samples (named efficient sub-samples) the sizes of which are sufficient to contain the information which gives rise to similar estimates to those obtained on the whole population. Moreover, the estimation on efficient data-sets does not necessitate the specification of the spatial autocorrelations which are supposed to bias the estimated variances

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  • François Gardes, 2021. "Biases on variances estimated on large data-sets," Documents de travail du Centre d'Economie de la Sorbonne 21022, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    • Handle: RePEc:mse:cesdoc:21022
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    References listed on IDEAS

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    1. François Gardes, 2019. "The Estimation of Price Elasticities and the Value of Time in a Domestic Production Framework: an Application using French Micro-Data," Post-Print hal-03281830, HAL.
    2. MacKinnon, James G., 2020. "Wild cluster bootstrap confidence intervals," L'Actualité Economique, Société Canadienne de Science Economique, vol. 96(4), pages 721-743, Décembre.
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    7. François Gardes, 2019. "The Estimation of Price Elasticities and the Value of Time in a Domestic Production Framework: an Application using French Micro-Data," Annals of Economics and Statistics, GENES, issue 135, pages 89-120.
    8. Kloek, T, 1981. "OLS Estimation in a Model Where a Microvariable Is Explained by Aggregates and Contemporaneous Disturbances Are Equicorrelated," Econometrica, Econometric Society, vol. 49(1), pages 205-207, January.
    9. François Gardes, 2019. "The Estimation of Price Elasticities and the Value of Time in a Domestic Production Framework: an Application using French Micro-Data," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03281830, HAL.
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    More about this item

    Keywords

    dataset; estimated variance; spatial autocorrelation; grouped observations;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis

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