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Observability and Social Interactions in Consumption

Author

Listed:
  • Tullio Jappelli

    (University of Naples Federico II, CSEF, and CEPR)

  • Luigi Pistaferri

    (Stanford University, SIEPR, NBER and CEPR)

Abstract

This paper examines how social context affects consumption responses to transitory income shocks. Using a randomized survey experiment embedded in the Italian Survey of Consumer Expectations, we vary whether an unexpected €1,000 employer-specific bonus is observable to coworkers and whether it is received only by the respondent or by all coworkers. The design separately identifies the effect of observability for an idiosyncratic bonus and the incremental effect of making a publicly observable bonus common within the workplace, a well-defined social context. Making an idiosyncratic bonus publicly observable reduces the MPC by about 3 percentage points relative to a private idiosyncratic bonus. Conditional on observability, making the bonus common among coworkers raises the MPC by about 6 percentage points. Interpreted through a linear social-interactions model, the latter effect implies a socialinteraction parameter of approximately 0.16 and a social multiplier of about 1.2. These findings suggest that aggregate consumption responses to fiscal policy depend not only on individual behavior but also on the social context in which income changes occur.

Suggested Citation

  • Tullio Jappelli & Luigi Pistaferri, 2026. "Observability and Social Interactions in Consumption," CSEF Working Papers 793, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
  • Handle: RePEc:sef:csefwp:793
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    Keywords

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    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • D15 - Microeconomics - - Household Behavior - - - Intertemporal Household Choice; Life Cycle Models and Saving
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C99 - Mathematical and Quantitative Methods - - Design of Experiments - - - Other

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