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Classification and Aggregation: An Application to Industrial Classification in CPS Data

Author

Listed:
  • Cotterman, R
  • Peracchi, F

Abstract

In this paper the authors offer a method for deciding how to aggregate a set of elementary industries. The method is then applied to the problem of estimating a wage equation that allows for industry-specific effects. Their method explicitly formalizes the trade-off between goodness-of-fit and parsimony implicit in an aggregation problem. By varying the parameter of the assumed loss function, one obtains a whole sequence of aggregation levels. Further, the resulting sequence is consistent; that is, groupings formed at one level of aggregation will never be undone when one aggregates further. Copyright 1992 by John Wiley & Sons, Ltd.

Suggested Citation

  • Cotterman, R & Peracchi, F, 1992. "Classification and Aggregation: An Application to Industrial Classification in CPS Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(1), pages 31-51, Jan.-Marc.
    • Handle: RePEc:jae:japmet:v:7:y:1992:i:1:p:31-51
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    Citations

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    Cited by:

    1. Chipman, John Somerset & Winker, Peter, 1994. "Optimal industrial classification with heteroskedasticity correction: An application to the Swedish industrial classification system," Discussion Papers, Series II 237, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
    2. Zura Kakushadze & Willie Yu, 2017. "Open Source Fundamental Industry Classification," Data, MDPI, vol. 2(2), pages 1-77, June.
    3. John Mullahy & Stephanie A. Robert, 2008. "No Time to Lose? Time Constraints and Physical Activity," NBER Working Papers 14513, National Bureau of Economic Research, Inc.
    4. Carlos Usabiaga & Fernando Núñez & Pablo Álvarez de Toledo, 2013. "Segmentación del mercado de trabajo, clusters, movilidad y duración de desempleo con datos individuales," Economic Working Papers at Centro de Estudios Andaluces E2013/02, Centro de Estudios Andaluces.
    5. Zura Kakushadze & Willie Yu, 2017. "Open Source Fundamental Industry Classification," Papers 1706.04210, arXiv.org, revised Dec 2017.
    6. Álvarez de Toledo, Pablo & Núñez, Fernando & Usabiaga, Carlos, 2014. "An empirical approach on labour segmentation. Applications with individual duration data," Economic Modelling, Elsevier, vol. 36(C), pages 252-267.
    7. John Mullahy, 2010. "Multivariate Fractional Regression Estimation of Econometric Share Models," NBER Working Papers 16354, National Bureau of Economic Research, Inc.
    8. Ross Stolzenberg & James Lindgren, 2010. "Retirement and death in office of U.S. Supreme Court justices," Demography, Springer;Population Association of America (PAA), vol. 47(2), pages 269-298, May.
    9. John Mullahy & Stephanie Robert, 2010. "No time to lose: time constraints and physical activity in the production of health," Review of Economics of the Household, Springer, vol. 8(4), pages 409-432, December.
    10. Chipman, John Somerset & Winker, Peter, 1994. "Optimal industrial classification: [an application to the German industrial classification system]," Discussion Papers, Series II 236, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
    11. Riccardo Di Francesco, 2022. "Aggregation Trees," CEIS Research Paper 546, Tor Vergata University, CEIS, revised 20 Nov 2023.
    12. repec:cte:werepe:6117 is not listed on IDEAS
    13. repec:cte:werepe:6109 is not listed on IDEAS
    14. Carlos Usabiaga & Pablo Álvarez de Toledo & Fernando Núñez, 2013. "Labour Market Segmentation, Clusters, Mobility And Unemployment Duration With Individual Microdata," EcoMod2013 5688, EcoMod.
    15. John S.nChipman & Peter Winker, "undated". "Optimal Industrial Classification in a Dynamic Model of Price Adjustment," Computing in Economics and Finance 1996 _013, Society for Computational Economics.
    16. Riccardo Di Francesco, 2024. "Aggregation Trees," Papers 2410.11408, arXiv.org.
    17. Mullahy John, 2015. "Multivariate Fractional Regression Estimation of Econometric Share Models," Journal of Econometric Methods, De Gruyter, vol. 4(1), pages 71-100, January.
    18. Ricardo Mora, 2008. "A nonparametric decomposition of the Mexican American average wage gap," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(4), pages 463-485.

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