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Purchasing Power Parities for Industry Comparisons Using Weighted Elteto–Koves–Szulc (EKS) Methods

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  • D. S. Prasada Rao
  • Marcel P. Timmer

Abstract

This study has three main objectives. First, it develops a generalization of the commonly used EKS method to multilateral price comparisons. It is shown that the EKS system can be generalized so that weights can be attached to each of the link comparisons used in the EKS computations. These weights can account for differing levels of reliability of the underlying binary comparisons. Second, various reliability measures and corresponding weighting schemes are presented and their merits discussed. Finally, these new methods are applied to an international data set of manufacturing prices from the ICOP project. Although theoretically superior, it appears that the empirical impact of the weighted EKS method is generally small compared to the unweighted EKS. It is also found that this impact is larger when it is applied at lower levels of aggregation. Finally, the importance of using sector specific PPPs in assessing relative levels of manufacturing productivity is indicated.

Suggested Citation

  • D. S. Prasada Rao & Marcel P. Timmer, 2003. "Purchasing Power Parities for Industry Comparisons Using Weighted Elteto–Koves–Szulc (EKS) Methods," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 49(4), pages 491-511, December.
    • Handle: RePEc:bla:revinw:v:49:y:2003:i:4:p:491-511
    DOI: 10.1111/j.0034-6586.2003.00101.x
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    Cited by:

    1. Sebastian Weinand, 2022. "Measuring spatial price differentials at the basic heading level: a comparison of stochastic index number methods," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(1), pages 117-143, March.
    2. Daniel Melser & Michael Webster, 2021. "Multilateral Methods, Substitution Bias, and Chain Drift: Some Empirical Comparisons," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 67(3), pages 759-785, September.
    3. Johannes Van Biesebroeck, 2009. "Disaggregate productivity comparisons: sectoral convergence in OECD countries," Journal of Productivity Analysis, Springer, vol. 32(2), pages 63-79, October.
    4. Chihiro Shimizu & Erwin Diewert, 2023. "Scanner Data, Product Churn and Quality Adjustment," Working Papers e185, Tokyo Center for Economic Research.
    5. Robert Inklaar & Marcel P. Timmer & Bart Van Ark, 2007. "Mind the Gap! International Comparisons of Productivity in Services and Goods Production," German Economic Review, Verein für Socialpolitik, vol. 8(2), pages 281-307, May.
    6. Peluffo Adriana & Scasso Juan, 2023. "The Role of Trade Partners on Product Quality: The case of Uruguay," Asociación Argentina de Economía Política: Working Papers 4681, Asociación Argentina de Economía Política.
    7. Jan Nevima & Ingrid Majerová, 2015. "Application of ß – Convergence Approach in Visegrad Four Regions," Working Papers 0004, Silesian University, School of Business Administration.
    8. Hill, Robert J. & Timmer, Marcel P., 2006. "Standard Errors as Weights in Multilateral Price Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 366-377, July.
    9. repec:dgr:rugggd:200473 is not listed on IDEAS
    10. Ludwig Auer, 2012. "Räumliche Preisvergleiche: Aggregationskonzepte und Forschungsperspektiven," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 6(1), pages 27-56, December.
    11. Weinand, Sebastian, 2020. "Measuring spatial price differentials: A comparison of stochastic index number methods," Discussion Papers 12/2020, Deutsche Bundesbank.
    12. repec:dgr:rugggd:gd-89 is not listed on IDEAS
    13. Daniel Melser, 2013. "Multilateral index number theory and generalized repeat sales house price indexes," Applied Economics Letters, Taylor & Francis Journals, vol. 20(8), pages 786-789, May.

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