Arbeitspapier

Estimating average marginal effects in nonseparable structural systems

We provide nonparametric estimators of derivative ratio-based average marginal effects of an endogenous cause, X, on a response of interest, Y , for a system of recursive structural equations. The system need not exhibit linearity, separability, or monotonicity. Our estimators are local indirect least squares estimators analogous to those of Heckman and Vytlacil (1999, 2001) who treat a latent index model involving a binary X. We treat the traditional case of an observed exogenous instrument (OXI)and the case where one observes error-laden proxies for an unobserved exogenous instrument (PXI). For PXI, we develop and apply new results for estimating densities and expectations conditional on mismeasured variables. For both OXI and PXI, we use infnite order flat-top kernels to obtain uniformly convergent and asymptotically normal nonparametric estimators of instrument-conditioned effects, as well as root-n consistent and asymptotically normal estimators of average effects.

Sprache
Englisch

Erschienen in
Series: cemmap working paper ; No. CWP31/07

Klassifikation
Wirtschaft
Estimation: General
Semiparametric and Nonparametric Methods: General
Multiple or Simultaneous Equation Models: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
Thema
derivative ratio effect, endogeneity, indirect least squares, instrumental variables, measurement error, nonparametric estimator, nonseparable structural equation
Schätztheorie
Nichtparametrisches Verfahren
Methode der kleinsten Quadrate
Statistischer Fehler

Ereignis
Geistige Schöpfung
(wer)
Schennach, Susanne
White, Halbert
Chalak, Karim
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2007

DOI
doi:10.1920/wp.cem.2007.3107
Handle
Letzte Aktualisierung
20.09.2024, 08:21 MESZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Schennach, Susanne
  • White, Halbert
  • Chalak, Karim
  • Centre for Microdata Methods and Practice (cemmap)

Entstanden

  • 2007

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