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Estimating flexible income processes from subjective expectations data: Evidence from India and Colombia

Author

Listed:
  • Manuel Arellano

    (CEMFI)

  • Orazio Attanasio

    (Yale University and NBER)

  • Sam Crossman

    (UK Government Economic Service)

  • V’ctor Sancibri‡n

    (Bocconi University and IGIER)

Abstract

We develop a methodology for modeling household income processes when subjective probabilistic assessments of future income are available. This allows us to flexibly estimate conditional cdfs directly using elicited individual subjective probabilities\, and to obtain empirical measurements of subjective risk and subjective persistence. We then use two longitudinal surveys collected in rural India and rural Colombia to explore the nature of perceived income dynamics in those contexts. Our results suggest linear income processes are rejected in favor of more flexible versions in both cases; subjective income distributions feature heteroskedasticity\, conditional skewness and nonlinear persistence.

Suggested Citation

  • Manuel Arellano & Orazio Attanasio & Sam Crossman & V’ctor Sancibri‡n, 2025. "Estimating flexible income processes from subjective expectations data: Evidence from India and Colombia," Cowles Foundation Discussion Papers 2478, Cowles Foundation for Research in Economics, Yale University.
  • Handle: RePEc:cwl:cwldpp:2478
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    References listed on IDEAS

    as
    1. Hu, Yingyao, 2017. "The econometrics of unobservables: Applications of measurement error models in empirical industrial organization and labor economics," Journal of Econometrics, Elsevier, vol. 200(2), pages 154-168.
    2. Manuel Arellano & Stéphane Bonhomme, 2012. "Identifying Distributional Characteristics in Random Coefficients Panel Data Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(3), pages 987-1020.
    3. Jappelli, Tullio & Pistaferri, Luigi, 2000. "Using subjective income expectations to test for excess sensitivity of consumption to predicted income growth," European Economic Review, Elsevier, vol. 44(2), pages 337-358, February.
    4. Luigi Pistaferri, 2003. "Anticipated and Unanticipated Wage Changes, Wage Risk, and Intertemporal Labor Supply," Journal of Labor Economics, University of Chicago Press, vol. 21(3), pages 729-754, July.
    5. Manuel Arellano, 2014. "Uncertainty, Persistence, And Heterogeneity: A Panel Data Perspective," Journal of the European Economic Association, European Economic Association, vol. 12(5), pages 1127-1153, October.
    6. Delavande, Adeline & Giné, Xavier & McKenzie, David, 2011. "Measuring subjective expectations in developing countries: A critical review and new evidence," Journal of Development Economics, Elsevier, vol. 94(2), pages 151-163, March.
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    2. Orazio Attanasio & V’ctor Sancibri‡n & Federica Ambrosio, 2025. "New Measures for Richer Theories: Some Thoughts and an Example," Cowles Foundation Discussion Papers 2477, Cowles Foundation for Research in Economics, Yale University.

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    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs
    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development

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