IDEAS home Printed from https://ideas.repec.org/p/zbw/rwirep/526.html
   My bibliography  Save this paper

A Nonparametric Partially Identified Estimator for Equivalence Scales

Author

Listed:
  • Dudel, Christian

Abstract

Methods for estimating equivalence scales usually rely on rather strong identifying assumptions. This paper considers a partially identified estimator for equivalence scales derived from the potential outcomes framework and using nonparametric methods for estimation, which requires only mild assumptions. Instead of point estimates, the method yields only lower and upper bounds of equivalence scales. Results of an analysis using German expenditure data show that the range implied by these bounds is rather wide, but can be reduced using additional covariates.

Suggested Citation

  • Dudel, Christian, 2014. "A Nonparametric Partially Identified Estimator for Equivalence Scales," Ruhr Economic Papers 526, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    • Handle: RePEc:zbw:rwirep:526
    DOI: 10.4419/86788601
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/104732/1/810646617.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.4419/86788601?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Peter Hall & Jeff Racine & Qi Li, 2004. "Cross-Validation and the Estimation of Conditional Probability Densities," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1015-1026, December.
    2. Abbring, Jaap H. & Heckman, James J., 2007. "Econometric Evaluation of Social Programs, Part III: Distributional Treatment Effects, Dynamic Treatment Effects, Dynamic Discrete Choice, and General Equilibrium Policy Evaluation," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 72, Elsevier.
    3. Coulter, Fiona A E & Cowell, Frank A & Jenkins, Stephen P, 1992. "Equivalence Scale Relativities and the Extent of Inequality and Poverty," Economic Journal, Royal Economic Society, vol. 102(414), pages 1067-1082, September.
    4. Sekhon, Jasjeet S., 2011. "Multivariate and Propensity Score Matching Software with Automated Balance Optimization: The Matching package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i07).
    5. Christian Dudel & Jan Marvin Garbuszus & Notburga Ott & Martin Werding, 2014. "Non-Parametric Preprocessing for the Estimation of Equivalence Scales," CESifo Working Paper Series 5103, CESifo.
    6. Szulc, Adam, 2009. "A matching estimator of household equivalence scales," Economics Letters, Elsevier, vol. 103(2), pages 81-83, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dudel Christian & Garbuszus Jan Marvin & Ott Notburga & Werding Martin, 2017. "Matching as Non-Parametric Preprocessing for the Estimation of Equivalence Scales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(2), pages 115-141, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:zbw:rwirep:0526 is not listed on IDEAS
    2. Christian Dudel, 2014. "A Nonparametric Partially Identified Estimator for Equivalence Scales," Ruhr Economic Papers 0526, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    3. Dudel Christian & Garbuszus Jan Marvin & Ott Notburga & Werding Martin, 2017. "Matching as Non-Parametric Preprocessing for the Estimation of Equivalence Scales," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 237(2), pages 115-141, April.
    4. Christian Dudel & Julian Schmied, 2023. "Pension benchmarks: empirical estimation and results for the United States and Germany," Fiscal Studies, John Wiley & Sons, vol. 44(2), pages 171-188, June.
    5. Christian Dudel & Jan Marvin Garbuszus & Julian Schmied, 2021. "Assessing differences in household needs: a comparison of approaches for the estimation of equivalence scales using German expenditure data," Empirical Economics, Springer, vol. 60(4), pages 1629-1659, April.
    6. Guirong Li & Jiajia Xu & Liying Li & Zhaolei Shi & Hongmei Yi & James Chu & Elena Kardanova & Yanyan Li & Prashant Loyalka & Scott Rozelle, 2020. "The Impacts of Highly Resourced Vocational Schools on Student Outcomes in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 28(6), pages 125-150, November.
    7. Alvaredo, Facundo & Bourguignon, François & Ferreira, Francisco H. G. & Lustig, Nora, 2023. "Seventy-five years of measuring income inequality in Latin America," LSE Research Online Documents on Economics 120557, London School of Economics and Political Science, LSE Library.
    8. Fali Huang & Myoung-Jae Lee, 2010. "Dynamic treatment effect analysis of TV effects on child cognitive development," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(3), pages 392-419.
    9. Ralf Becker & Maggy Fostier, 2015. "Evaluating non-compulsory educational interventions - the case of peer assisted study groups," Economics Discussion Paper Series 1509, Economics, The University of Manchester.
    10. Davide Viviano & Jelena Bradic, 2019. "Synthetic learner: model-free inference on treatments over time," Papers 1904.01490, arXiv.org, revised Aug 2022.
    11. Christian Awuku-Budu & Dirk van Duym, 2022. "Developing Statistics on the Distribution of State Personal Income: Methodology and Preliminary Results," BEA Working Papers 0197, Bureau of Economic Analysis.
    12. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    13. Jacquemet, N. & Luchini, S. & Malézieux, A. & Shogren, J.F., 2020. "Who’ll stop lying under oath? Empirical evidence from tax evasion games," European Economic Review, Elsevier, vol. 124(C).
    14. Espen Bratberg & Sigve Tjøtta, 2008. "Income effects of divorce in families with dependent children," Journal of Population Economics, Springer;European Society for Population Economics, vol. 21(2), pages 439-461, April.
    15. Michael S. Delgado & Daniel J. Henderson & Christopher F. Parmeter, 2014. "Does Education Matter for Economic Growth?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(3), pages 334-359, June.
    16. Lars Osberg, 2002. "How Much does Work Matter for Inequality? Time, Money and Inequality in International Perspective," LIS Working papers 326, LIS Cross-National Data Center in Luxembourg.
    17. Cong Li & Qi Li & Jeffrey Racine & DAIQIANG ZHANG, 2017. "Optimal Model Averaging Of Varying Coefficient Models," Department of Economics Working Papers 2017-01, McMaster University.
    18. Boyd H. Hunter & Steven Kennedy & Nicholas Biddle, 2004. "Indigenous and Other Australian Poverty: Revisiting the Importance of Equivalence Scales," The Economic Record, The Economic Society of Australia, vol. 80(251), pages 411-422, December.
    19. Nolwenn Roudaut & Anne Vanhems, 2012. "Explaining firms efficiency in the Ivorian manufacturing sector: a robust nonparametric approach," Journal of Productivity Analysis, Springer, vol. 37(2), pages 155-169, April.
    20. Dirk Bergemann & Benjamin Brooks & Stephen Morris, 2022. "Counterfactuals with Latent Information," American Economic Review, American Economic Association, vol. 112(1), pages 343-368, January.
    21. Clemens Tesch-Römer & Andreas Motel-Klingebiel & Martin Tomasik, 2008. "Gender Differences in Subjective Well-Being: Comparing Societies with Respect to Gender Equality," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 85(2), pages 329-349, January.

    More about this item

    Keywords

    household equivalence scale; partial identification; matching estimator;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:rwirep:526. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/rwiesde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.