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Logistics Performance Index: Methodological Issues

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  • Satyendra Nath Chakrabartty

Abstract

This article addresses limitations of Logistics Performance Index (LPI) and suggests remedies. Reliability of the instrument used in LPI may be better found by Angular Association method or Bhattacharyya’s measure, using only the frequencies or probabilities of item–response categories without involving assumptions of continuous nature or linearity or normality for the observed variables or the underlying variable being measured. The suggested methods also avoid test of uni-dimensionality, assumption of normality, bivariate normality. The problems of outlying observations and linear assumptions in principal component analysis for finding reliability theta are also avoided in each proposed method. Geometric mean approach provides a better alternative to compute LPI scores avoiding scaling and calculation of weights satisfies many desired properties and reduces level of substitutability between components, facilitates statistical test of equality of two geometric means and identifies critical areas for corrective measures. Such identifications are important from a policy point of view. The graph of LPI for a country over a long period of time reflects pattern of growth of LPI for the country. The method helps to rank and benchmark the countries, if the target vector is taken as LPI score of the best performing country. JEL Codes: C43, C54

Suggested Citation

  • Satyendra Nath Chakrabartty, 2020. "Logistics Performance Index: Methodological Issues," Foreign Trade Review, , vol. 55(4), pages 466-477, November.
  • Handle: RePEc:sae:fortra:v:55:y:2020:i:4:p:466-477
    DOI: 10.1177/0015732520947860
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    More about this item

    Keywords

    Likert scale; reliability; composite index; geometric mean; multi-staged sampling;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

    Statistics

    Access and download statistics

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