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Income Differentials & Rate of Time Preference: A Developing Country Perspective

Author

Listed:
  • Ayona Bhattacharjee

    (International Management Institute, New Delhi)

  • Mausumi Das

    (Department of Economics, Delhi School of Economics & Shiv Nadar University)

  • Mukta Jain

    (Department of Economics, Delhi School of Economics & University of Bath)

Abstract

Estimating time preferences in developing countries like India, is essential for designing public policies that influence savings and investment decisions. However, limited data availability and various economic constraints restrict the estimation process and its analysis. Following Lawrance (1991) framework, this paper adopts Euler equation approach to estimate individual time preferences and assess its relation with one’s income level, in the context of India. Using a national level household survey, the CMIE CPHS dataset spanning 2014-2019, the average RTP for the Indian population is estimated to be 0.0689. It means that on average, individuals in India are willing to forgo 6.89% of future consumption to have the same amount of consumption today. Furthermore, the results show that wealthier individuals are marginally more patient than poorer ones, exhibiting decreasing marginal impatience. These findings have significant policy implications for shaping redistributive, welfare, and growth policies in India.

Suggested Citation

  • Ayona Bhattacharjee & Mausumi Das & Mukta Jain, 2025. "Income Differentials & Rate of Time Preference: A Developing Country Perspective," Working papers 354, Centre for Development Economics, Delhi School of Economics.
    • Handle: RePEc:cde:cdewps:354
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    More about this item

    Keywords

    rate of time preference; euler equation; household survey data; India. JEL codes: E21; C61; D91;
    All these keywords.

    JEL classification:

    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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