IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v67y2024i3d10.1007_s00181-024-02581-4.html
   My bibliography  Save this article

Hybrid measures of multidimensional poverty

Author

Listed:
  • Tomson Ogwang

    (Brock University)

  • Jean-François Lamarche

    (Brock University)

Abstract

In this paper, we propose a hybrid Watts-MPI multidimensional poverty measure that combines the multidimensional Watts poverty index (MWPI), which can accommodate continuous poverty dimensions, with the multidimensional poverty index (MPI), which can accommodate binary poverty dimensions. Unlike the stand-alone MPI that entails total loss of dimension-specific information on both poverty intensity with respect to shortfall and inequality, the proposed hybrid Watts-MPI measure entails only partial loss of such information since poverty intensity and inequality estimates can still be obtained for the continuous poverty dimensions included in the hybrid measure. The hybrid Watts-MPI also specializes to the stand-alone MWPI and MPI when all the poverty dimensions are continuous and binary, respectively. Furthermore, formation of the hybrid Watts-MPI does not entail loss of normative properties by either the constituent MWPI or MPI. The seemingly unrelated regression approach to the estimation of the hybrid Watts-MPI is described and an empirical example demonstrating its efficacy is provided.

Suggested Citation

  • Tomson Ogwang & Jean-François Lamarche, 2024. "Hybrid measures of multidimensional poverty," Empirical Economics, Springer, vol. 67(3), pages 1211-1233, September.
    • Handle: RePEc:spr:empeco:v:67:y:2024:i:3:d:10.1007_s00181-024-02581-4
    DOI: 10.1007/s00181-024-02581-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00181-024-02581-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00181-024-02581-4?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Suman Seth, Sabina Alkire, 2014. "Measuring and Decomposing Inequality among the Multidimensionally Poor Using Ordinal Data: A Counting Approach," OPHI Working Papers 68, Queen Elizabeth House, University of Oxford.
    2. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
    3. Hajargasht, Gholamreza & Griffiths, William E., 2013. "Pareto–lognormal distributions: Inequality, poverty, and estimation from grouped income data," Economic Modelling, Elsevier, vol. 33(C), pages 593-604.
    4. Sabina Alkire & Maria Santos, 2013. "A Multidimensional Approach: Poverty Measurement & Beyond," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 112(2), pages 239-257, June.
    5. James Foster & Suman Seth & Michael Lokshin & Zurab Sajaia, 2013. "A Unified Approach to Measuring Poverty and Inequality--Theory and Practice : Streamlined Analysis with ADePT Software," World Bank Publications - Books, The World Bank Group, number 13731.
    6. William Griffiths & Duangkamon Chotikapanich & Gholamreza Hajargasht, 2022. "A note on inequality measures for mixtures of double Pareto–lognormal distributions," Australian Economic Papers, Wiley Blackwell, vol. 61(2), pages 280-290, June.
    7. Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2020. "On the construction of a feasible range of multidimensional poverty under benchmark weight uncertainty," European Journal of Operational Research, Elsevier, vol. 281(2), pages 415-427.
    8. Ogwang, Tomson & Rao, U. L. Gouranga, 2000. "Hybrid models of the Lorenz curve," Economics Letters, Elsevier, vol. 69(1), pages 39-44, October.
    9. Robinson, Peter M, 1988. "Root- N-Consistent Semiparametric Regression," Econometrica, Econometric Society, vol. 56(4), pages 931-954, July.
    10. Sarabia, José María & Castillo, Enrique & Pascual, Marta & Sarabia, María, 2005. "Mixture Lorenz curves," Economics Letters, Elsevier, vol. 89(1), pages 89-94, October.
    11. James Foster & Joel Greer & Erik Thorbecke, 2010. "The Foster–Greer–Thorbecke (FGT) poverty measures: 25 years later," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 8(4), pages 491-524, December.
    12. Wang, ZuXiang & Smyth, Russell, 2015. "A hybrid method for creating Lorenz curves," Economics Letters, Elsevier, vol. 133(C), pages 59-63.
    13. Yatchew,Adonis, 2003. "Semiparametric Regression for the Applied Econometrician," Cambridge Books, Cambridge University Press, number 9780521812832, January.
    14. Lungile Ntsalaze & Sylvanus Ikhide, 2018. "Rethinking Dimensions: The South African Multidimensional Poverty Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 195-213, January.
    15. Tomson Ogwang, 2022. "The regression approach to the measurement and decomposition of the multidimensional Watts poverty index," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(4), pages 951-973, December.
    16. Kai-yuen Tsui, 2002. "Multidimensional poverty indices," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 19(1), pages 69-93.
    17. Dwivedi, T. D. & Srivastava, V. K., 1978. "Optimality of least squares in the seemingly unrelated regression equation model," Journal of Econometrics, Elsevier, vol. 7(3), pages 391-395, April.
    Full references (including those not matched with items on IDEAS)

    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. Tomson Ogwang, 2022. "The regression approach to the measurement and decomposition of the multidimensional Watts poverty index," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(4), pages 951-973, December.
    2. Espinoza-Delgado, José & Klasen, Stephan, 2018. "Gender and multidimensional poverty in Nicaragua: An individual based approach," World Development, Elsevier, vol. 110(C), pages 466-491.
    3. Tomson Ogwang, 2022. "The Foster–Greer–Thorbecke Poverty Measures Reveal More," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1481-1503, December.
    4. Satya Paul & Sriram Shankar, 2020. "An alternative single parameter functional form for Lorenz curve," Empirical Economics, Springer, vol. 59(3), pages 1393-1402, September.
    5. WANG, Zuxiang & SMYTH, Russell & NG, Yew-Kwang, 2009. "A new ordered family of Lorenz curves with an application to measuring income inequality and poverty in rural China," China Economic Review, Elsevier, vol. 20(2), pages 218-235, June.
    6. Burhan Can Karahasan & Fırat Bilgel, 2021. "The Topography and Sources of Multidimensional Poverty in Turkey," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 154(2), pages 413-445, April.
    7. Dipesh Gangopadhyay & Robert B. Nielsen & Velma Zahirovic-Herbert, 2021. "Methodology and Axiomatic Characterization of a Multidimensional and Fuzzy Measure of Deprivation," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(1), pages 1-37, January.
    8. Mateusz Piwowarski & Danuta Miłaszewicz & Małgorzata Łatuszyńska & Mariusz Borawski & Kesra Nermend, 2018. "Application of the Vector Measure Construction Method and Technique for Order Preference by Similarity Ideal Solution for the Analysis of the Dynamics of Changes in the Poverty Levels in the European ," Sustainability, MDPI, vol. 10(8), pages 1-24, August.
    9. Coral Río & Olga Alonso-Villar, 2018. "Segregation and Social Welfare: A Methodological Proposal with an Application to the U.S," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 137(1), pages 257-280, May.
    10. Carunia Mulya Firdausy & Dwi Andayani Budisetyowati, 2022. "Variables, Dimensions, and Indicators Important to Develop the Multidimensional Poverty Line Measurement in Indonesia," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 162(2), pages 763-802, July.
    11. Katia Iglesias & Christian Suter & Tugce Beycan & B. P. Vani, 2017. "Exploring Multidimensional Well-Being in Switzerland: Comparing Three Synthesizing Approaches," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 134(3), pages 847-875, December.
    12. Espinoza-Delgado, José & López-Laborda, Julio, 2016. "Las tres Is de la pobreza multidimensional en Nicaragua y el diferencial de género en los primeros quince años del siglo XXI, a partir de un enfoque centrado en la persona [The three I’s of multidi," MPRA Paper 74997, University Library of Munich, Germany.
    13. Zsolt Darvas, 2019. "Why is it So Hard to Reach the EU’s Poverty Target?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 141(3), pages 1081-1105, February.
    14. Ke-Mei Chen & Chao-Hsien Leu & Te-Mu Wang, 2019. "Measurement and Determinants of Multidimensional Poverty: Evidence from Taiwan," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 145(2), pages 459-478, September.
    15. Syed Abul Hasan, 2013. "The impact of a large rice price increase on welfare and poverty in Bangladesh," ASARC Working Papers 2013-11, The Australian National University, Australia South Asia Research Centre.
    16. Sabina Alkire & Mauricio Apablaza & Satya R. Chakravarty & Gaston Yalonetzky, 2014. "Measuring Chronic Multidimensional Poverty: A Counting Approach," OPHI Working Papers 75, Queen Elizabeth House, University of Oxford.
    17. Srinivas Goli & Nagendra Kumar Maurya & Moradhvaj & Prem Bhandari, 2019. "Regional Differentials in Multidimensional Poverty in Nepal: Rethinking Dimensions and Method of Computation," SAGE Open, , vol. 9(1), pages 21582440198, March.
    18. Aysenur Acar, 2014. "The Dynamics of Multidimensional Poverty in Turkey," Working Papers 014, Bahcesehir University, Betam.
    19. Daniel Nowak & Christoph Scheicher, 2017. "Considering the Extremely Poor: Multidimensional Poverty Measurement for Germany," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(1), pages 139-162, August.
    20. Jin, Gui & Guo, Baishu & Deng, Xiangzheng, 2020. "Is there a decoupling relationship between CO2 emission reduction and poverty alleviation in China?," Technological Forecasting and Social Change, Elsevier, vol. 151(C).

    More about this item

    Keywords

    Multidimensional Watts poverty index; Multidimensional poverty index; Hybrid Watts-MPI; Dual cut-off method; Seemingly unrelated regression; Simulation;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

    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:spr:empeco:v:67:y:2024:i:3:d:10.1007_s00181-024-02581-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.