A simple root n consistent, asymptotically normal semiparametric estimator of the coefficient vector $\beta$ in the latent variable specification y = L($\beta$'x + e) is constructed. The distribution of e is unknown and may be correlated with x or be conditionally heteroscedastic, e.g., x can contain measurement error. The function L can also be unknown. The identification assumption is that e is uncorrelated with instruments u and that the conditional distribution of e given x and u does not depend on one of the regressors, which has some special properties. Extensions to more general latent variable specifications are provided.
MLA
Lewbel, Arthur. “Semiparametric Latent Variable Model Estimation with Endogenous or Mismeasured Regressors.” Econometrica, vol. 66, .no 1, Econometric Society, 1998, pp. 105-121, https://www.jstor.org/stable/2998542
Chicago
Lewbel, Arthur. “Semiparametric Latent Variable Model Estimation with Endogenous or Mismeasured Regressors.” Econometrica, 66, .no 1, (Econometric Society: 1998), 105-121. https://www.jstor.org/stable/2998542
APA
Lewbel, A. (1998). Semiparametric Latent Variable Model Estimation with Endogenous or Mismeasured Regressors. Econometrica, 66(1), 105-121. https://www.jstor.org/stable/2998542
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