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Sharing rule identification for general collective consumption models

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Listed:
  • Laurens CHERCHYE
  • Bram DE ROCK
  • Arthur LEWBEL
  • Frederic VERMEULEN

Abstract

We propose a method to identify bounds (i.e. set identification) on the sharing rule for a general collective household consumption model. Unlike the effects of distribution factors, it is well known that the level of the sharing rule cannot be uniquely identified without strong assumptions on preferences across households of different compositions. Our new results show that, though not point identified without these assumptions, bounds on the sharing rule can still be obtained. We get these bounds by applying revealed preference restrictions implied by the collective model to the household’s continuous aggregate demand functions. We obtain informative bounds even if nothing is known about whether each good is public, private, or assignable within the household, though having such information tightens the bounds. An empirical application demonstrates the practical usefulness of our method.

Suggested Citation

  • Laurens CHERCHYE & Bram DE ROCK & Arthur LEWBEL & Frederic VERMEULEN, 2012. "Sharing rule identification for general collective consumption models," Working Papers of Department of Economics, Leuven ces12.05, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
  • Handle: RePEc:ete:ceswps:ces12.05
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D13 - Microeconomics - - Household Behavior - - - Household Production and Intrahouse Allocation
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General

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