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Identification of Time-Inconsistent Models: The Case of Insecticide Treated Nets

Author

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  • Mahajan, Aprajit
  • Michel, Christian
  • Tarozzi, Alessandro

Abstract

Time-inconsistency may play a central role in explaining inter-temporal behavior, particularly among poor households. However, little is known about the distribution of time-inconsistent agents, and time-preference parameters are typically not identified in standard dynamic choice models. We formulate a dynamic discrete choice model in an unobservedly heterogeneous population of possibly time-inconsistent agents. We provide conditions under which all population type probabilities and preferences for both time-consistent and sophisticated agents are point-identified and sharp set-identification results for \naive and partially sophisticated agents. Estimating the model using data from a health intervention providing insecticide treated nets (ITNs) in rural Orissa, India, we find that a little over two-thirds of our sample comprises time-inconsistent agents and that both sophisticated and naiive agents are considerably present-biased. Counterfactuals show that the under-investment in ITNs attributable to present-bias leads to substantial costs that are about five times the price of an ITN.

Suggested Citation

  • Mahajan, Aprajit & Michel, Christian & Tarozzi, Alessandro, 2023. "Identification of Time-Inconsistent Models: The Case of Insecticide Treated Nets," CEPR Discussion Papers 17888, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:17888
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    Cited by:

    1. is not listed on IDEAS
    2. Gizem Koşar & Cormac O'Dea, 2022. "Expectations Data in Structural Microeconomic Models," NBER Working Papers 30094, National Bureau of Economic Research, Inc.
    3. Michel, Christian & Stenzel, André, 2021. "Model-based evaluation of cooling-off policies," Games and Economic Behavior, Elsevier, vol. 129(C), pages 270-293.
    4. Cobb-Clark, Deborah A. & Dahmann, Sarah C. & Kamhöfer, Daniel A. & Schildberg-Hörisch, Hannah, 2024. "Sophistication about self-control," Journal of Public Economics, Elsevier, vol. 238(C).
    5. Chao Wang & Stefan Weiergraeber & Ruli Xiao, 2022. "Identification of Dynamic Discrete Choice Models with Hyperbolic Discounting Using a Terminating Action," CAEPR Working Papers 2022-010 Classification-C, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    6. Sebastian Galiani & Juan Pantano, 2021. "Structural Models: Inception and Frontier," NBER Working Papers 28698, National Bureau of Economic Research, Inc.
    7. Friedman, Willa & Wilson, Nicholas, 2022. "Can nudging overcome procrastinating on preventive health investments?," Economics & Human Biology, Elsevier, vol. 45(C).

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    JEL classification:

    • I1 - Health, Education, and Welfare - - Health
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • D9 - Microeconomics - - Micro-Based Behavioral Economics

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