Showing 1 - 10 of 139
parametric and nonparametric identification. Prior studies rarely found wages to affect MNE employment. We document a …
Persistent link: https://www.econbiz.de/10005248690
censored population. We then correct the derivative for the effects of the selection bias. We propose nonparametric and … semiparametric estimators for the derivative. As extensions, we discuss the cases of discrete regressors, measurement error in …
Persistent link: https://www.econbiz.de/10005774908
We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of … obtain nonparametric estimates for the sharp and fuzzy RKD. We then use a fuzzy RKD approach to study the effect of …
Persistent link: https://www.econbiz.de/10010950873
This paper shows that the asymptotic normal approximation is often insufficiently accurate for volatility estimators based on high frequency data. To remedy this, we compute Edgeworth expansions for such estimators. Unlike the usual expansions, we have found that in order to obtain meaningful...
Persistent link: https://www.econbiz.de/10005248985
Many dynamic problems in economics are characterized by large state spaces which make both computing and estimating the model infeasible. We introduce a method for approximating the value function of high-dimensional dynamic models based on sieves and establish results for the: (a) consistency,...
Persistent link: https://www.econbiz.de/10009652758
Using nonparametric techniques, we develop a methodology for estimating conditional alphas and betas and long …
Persistent link: https://www.econbiz.de/10009359903
This paper considers nonparametric identification and estimation of a generalized Roy model that includes a non …-pecuniary component of utility associated with each choice alternative. We develop nonparametric estimators corresponding to two …
Persistent link: https://www.econbiz.de/10005714411
This paper introduces an instrumental variables estimator for the effect of a binary treatment on the quantiles of potential outcomes. The quantile treatment effects (QTE) estimator accommodates exogenous covariates and reduces to quantile regression as a special case when treatment status is...
Persistent link: https://www.econbiz.de/10005832286
We propose a nonparametric method for automatically selecting the number of autocovariances to use in computing a …
Persistent link: https://www.econbiz.de/10005779052
Propensity score matching estimators (Rosenbaum and Rubin, 1983) are widely used in evaluation research to estimate average treatment effects. In this article, we derive the large sample distribution of propensity score matching estimators. Our derivations take into account that the propensity...
Persistent link: https://www.econbiz.de/10005108404