Arbeitspapier

Generalized instrumental variable models

The ability to allow for flexible forms of unobserved heterogeneity is an essential ingredient in modern microeconometrics. In this paper we extend the application of instrumental variable (IV) methods to a wide class of problems in which multiple values of unobservable variables can be associated with particular combinations of observed endogenous and exogenous variables. In our Generalized Instrumental Variable (GIV) models, in contrast to traditional IV models, the mapping from unobserved heterogeneity to endogenous variables need not admit a unique inverse. The class of GIV models allows unobservables to be multivariate and to enter non-separably into the determination of endogenous variables, thereby removing strong practical limitations on the role of unobserved heterogeneity. Important examples include models with discrete or mixed continuous/discrete outcomes and continuous unobservables, and models with excess heterogeneity where many combinations of different values of multiple unobserved variables, such as random coefficients, can deliver the same realizations of outcomes. We use tools from random set theory to study identification in such models and provide a sharp characterization of the identified set of structures admitted. We demonstrate the application of our analysis to a continuous outcome model with an interval-censored endogenous explanatory variable.

Language: Englisch

Bibliographic citation: Series: cemmap working paper ; No. CWP04/14

Classification: Wirtschaft
Econometric and Statistical Methods and Methodology: General
Semiparametric and Nonparametric Methods: General
Single Equation Models; Single Variables: Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
Single Equation Models: Single Variables: Instrumental Variables (IV) Estimation

Subject: instrumental variables
endogeneity
excess heterogeneity
limited information
set identification
partial identification
random sets
incomplete models

Event: Geistige Schöpfung

(who): Chesher, Andrew
Rosen, Adam

Event: Veröffentlichung

(who): Centre for Microdata Methods and Practice (cemmap)

(where): London

(when): 2014

DOI: doi:10.1920/wp.cem.2014.0414

Handle: http://hdl.handle.net/10419/97370

Last update: 10.03.2025, 11:44 AM CET

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Object type

Arbeitspapier

Associated

Chesher, Andrew
Rosen, Adam
Centre for Microdata Methods and Practice (cemmap)

Time of origin

2014

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Arbeitspapier