Arbeitspapier

Semiparametric estimation with generated covariates

We study a general class of semiparametric estimators when the infinite-dimensional nuisance parameters include a conditional expectation function that has been estimated nonparametrically using generated covariates. Such estimators are used frequently to e.g. estimate nonlinear models with endogenous covariates when identification is achieved using control variable techniques. We study the asymptotic properties of estimators in this class, which is a non-standard problem due to the presence of generated covariates. We give conditions under which estimators are root-n consistent and asymptotically normal, derive a general formula for the asymptotic variance, and show how to establish validity of the bootstrap.

Language
Englisch

Bibliographic citation
Series: KIT Working Paper Series in Economics ; No. 81

Classification
Wirtschaft
Semiparametric and Nonparametric Methods: General
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Subject
semiparametric estimation
generated covariates
profiling
propensity score

Event
Geistige Schöpfung
(who)
Mammen, Enno
Rothe, Christoph
Schienle, Melanie
Event
Veröffentlichung
(who)
Karlsruher Institut für Technologie (KIT), Institut für Volkswirtschaftslehre (ECON)
(where)
Karlsruhe
(when)
2016

DOI
doi:10.5445/IR/1000051816
Handle
URN
urn:nbn:de:swb:90-518162
Last update
10.03.2025, 11:45 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Mammen, Enno
  • Rothe, Christoph
  • Schienle, Melanie
  • Karlsruher Institut für Technologie (KIT), Institut für Volkswirtschaftslehre (ECON)

Time of origin

  • 2016

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