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The impact of income adjustments in the Casen Survey on the measurement of inequality in Chile

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  • David Bravo
  • José A. Valderrama Torres

Abstract

The adjustment of the information obtained from household surveys to make the figures compatible with National Accounts is a non-standard and potentially questionable practice given that it alters the structure of income distribution. This paper analyzes the sensitivity of inequality and poverty indicators to the adjustments made by ECLAC so as to enable a consistency between what is reported by the CASEN survey and the National Accounts figures in Chile. The results reveal that this leads to important changes in the top-end of the distribution and to an overestimation in the main inequality indicators in Chile. Chile looks more unequal in international relative terms due to this adjustment.

Suggested Citation

  • David Bravo & José A. Valderrama Torres, 2011. "The impact of income adjustments in the Casen Survey on the measurement of inequality in Chile," Estudios de Economia, University of Chile, Department of Economics, vol. 38(1 Year 20), pages 43-65, June.
    • Handle: RePEc:udc:esteco:v:38:y:2011:i:1:p:43-65
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    References listed on IDEAS

    as
    1. Shorrocks, A F, 1980. "The Class of Additively Decomposable Inequality Measures," Econometrica, Econometric Society, vol. 48(3), pages 613-625, April.
    2. Angrist, Joshua D. & Krueger, Alan B., 1999. "Empirical strategies in labor economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 23, pages 1277-1366, Elsevier.
    3. O. Ashenfelter & D. Card (ed.), 1999. "Handbook of Labor Economics," Handbook of Labor Economics, Elsevier, edition 1, volume 3, number 3.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. François Bourguignon, 2015. "Appraising income inequality databases in Latin America," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 13(4), pages 557-578, December.
    2. Jose De Gregorio & Manuel Taboada, 2022. "Median Labor Income in Chile Revised: Insights from Distributional National Accounts," Working Papers wp532, University of Chile, Department of Economics.
    3. Dante Contreras & Osvaldo Larrañaga & Esteban Puentes & Tomás Rau, 2014. "Improving the Measurement of the Relationship between Opportunities and Income: Evidence from Longitudinal Data from Chile," Development Policy Review, Overseas Development Institute, vol. 32(2), pages 219-237, March.
    4. Channing Arndt & Kristi Mahrt, 2017. "Is inequality underestimated in Mozambique? Accounting for underreported consumption," WIDER Working Paper Series 153, World Institute for Development Economic Research (UNU-WIDER).
    5. Jean-Marc Fournier & Isabell Koske, 2012. "The determinants of earnings inequality: evidence from quantile regressions," OECD Journal: Economic Studies, OECD Publishing, vol. 2012(1), pages 7-36.
    6. Andrés Hernando & Estéfano Rubio, 2015. "Aporte solidario al ingreso de trabajo (ASIT): una mejor alternativa contra la desigualdad," Puntos de Referencia 419, Centro de Estudios Públicos.
    7. Ramírez, Eduardo & Ruben, Ruerd, 2015. "Gender Systems and Women’s Labor Force Participation in the Salmon Industry in Chiloé, Chile," World Development, Elsevier, vol. 73(C), pages 96-104.
    8. Jorge, Abner Campos & William, Foster, 2013. "Medición de la pobreza: consecuencias de compatibilizar ingresos de encuestas de hogares con cuentas nacionales," Estudios Públicos, Centro de Estudios Públicos, vol. 0(130), pages 53-94.
    9. Channing Arndt & Kristi Mahrt, 2017. "Is inequality underestimated in Mozambique?: Accounting for underreported consumption," WIDER Working Paper Series wp-2017-153, World Institute for Development Economic Research (UNU-WIDER).

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    More about this item

    Keywords

    Inequality; Poverty; Income adjustment; Chile;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D3 - Microeconomics - - Distribution
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • N36 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Latin America; Caribbean
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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