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Efficient Estimation of the Headcount Index

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  • J. Muñoz
  • E. Álvarez-Verdejo
  • R. García-Fernández
  • L. Barroso

Abstract

The headcount index is an important poverty indicator that analyzes the proportion of people classified as poor. The headcount index is often used in comparisons of poverty across countries. In practice, the population headcount index is unknown, and survey data derived from official surveys are used to obtain an estimation of this indicator. The use of more accurate estimation methodologies may provide a better knowledge about the real headcount index. We describe alternative estimation methods for the headcount index. Proposed methods use the known ratio and regression techniques after transforming an auxiliary variable related to the variable of interest into a dummy variable. Monte Carlo simulation studies are carried out to evaluate numerically the performance of the various estimators of the headcount index discussed in this paper. Results indicate that the proposed estimation methods can be more accurate than existing methods. Confidence intervals are also evaluated and desirable coverage rates are obtained. Simulation studies are based upon real survey data extracted from official surveys on income and living conditions. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • J. Muñoz & E. Álvarez-Verdejo & R. García-Fernández & L. Barroso, 2015. "Efficient Estimation of the Headcount Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 123(3), pages 713-732, September.
    • Handle: RePEc:spr:soinre:v:123:y:2015:i:3:p:713-732
    DOI: 10.1007/s11205-014-0757-9
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    1. P. M. Lerman, 1980. "Fitting Segmented Regression Models by Grid Search," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(1), pages 77-84, March.
    2. Jekaterina Navicke & Olga Rastrigina & Holly Sutherland, 2014. "Nowcasting Indicators of Poverty Risk in the European Union: A Microsimulation Approach," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 119(1), pages 101-119, October.
    3. Yves G. Berger & Chris J. Skinner, 2003. "Variance estimation for a low income proportion," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(4), pages 457-468, October.
    4. Marcelo Medeiros, 2006. "The Rich and the Poor: The Construction of an Affluence Line from the Poverty Line," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 78(1), pages 1-18, August.
    5. David Madden, 2000. "Relative Or Absolute Poverty Lines: A New Approach," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 46(2), pages 181-199, June.
    6. Madden, David, 2000. "Relative or Absolute Poverty Lines: A New Approach," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 46(2), pages 181-199, June.
    7. Foster, James E, 1998. "Absolute versus Relative Poverty," American Economic Review, American Economic Association, vol. 88(2), pages 335-341, May.
    8. Francesca Giambona & Erasmo Vassallo, 2014. "Composite Indicator of Social Inclusion for European Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 116(1), pages 269-293, March.
    9. Eric Crettaz & Christian Suter, 2013. "The Impact of Adaptive Preferences on Subjective Indicators: An Analysis of Poverty Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 114(1), pages 139-152, October.
    10. M. Rueda & J. Muñoz & Y. Berger & A. Arcos & S. Martínez, 2007. "Pseudo empirical likelihood method in the presence of missing data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 65(3), pages 349-367, May.
    11. María Mar Rueda & Juan Muñoz, 2011. "Estimation of poverty measures with auxiliary information in sample surveys," Quality & Quantity: International Journal of Methodology, Springer, vol. 45(3), pages 687-700, April.
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    1. Domingo Morales & María del Mar Rueda & Dolores Esteban, 2018. "Model-Assisted Estimation of Small Area Poverty Measures: An Application within the Valencia Region in Spain," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 138(3), pages 873-900, August.
    2. J. F. Muñoz & E. à lvarez-Verdejo & R. M. García-Fernández, 2018. "On Estimating the Poverty Gap and the Poverty Severity Indices With Auxiliary Information," Sociological Methods & Research, , vol. 47(3), pages 598-625, August.

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