Arbeitspapier

Individual counterfactuals with multidimensional unobserved heterogeneity

New nonparametric methods that identify and estimate counterfactuals for individuals, when each is characterized by a vector of unobserved characteristics, are developed and applied to estimate systems of individual consumer demand and welfare measures. The unobserved characteristics are allowed to enter in unrestricted ways. Identification is delivered through two fundamental assumptions: First, the system is invertible in the vector of unobserved heterogeneity. Second, there exist external, individual-specific, covariates that are related to the unobserved heterogeneity and do not enter directly into the system of interest. The observed external variables can be either discrete or continuously distributed. Estimators based on the identifying restrictions are developed and their asymptotic properties derived. Using UK micro data on consumer demand, we apply the methods to estimate individual demand counterfactuals subject to revealed preference inequalities.

Language
Englisch

Bibliographic citation
Series: cemmap working paper ; No. CWP60/17

Classification
Wirtschaft
Single Equation Models; Single Variables: General
Consumer Economics: Empirical Analysis
Subject
simultaneous equations
nonseparable models
constructive identification
nonpara-metric methods
consumer behaviour
structural demand functions
revealed preference
bounds

Event
Geistige Schöpfung
(who)
Blundell, Richard W.
Kristensen, Dennis
Matzkin, Rosa Liliana
Event
Veröffentlichung
(who)
Centre for Microdata Methods and Practice (cemmap)
(where)
London
(when)
2017

DOI
doi:10.1920/wp.cem.2017.6017
Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Arbeitspapier

Associated

  • Blundell, Richard W.
  • Kristensen, Dennis
  • Matzkin, Rosa Liliana
  • Centre for Microdata Methods and Practice (cemmap)

Time of origin

  • 2017

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