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We develop a practical way of addressing the Errors-In-Variables (EIV) problem in the Generalized Method of Moments (GMM) framework. We focus on the settings in which the variability of the EIV is a fraction of that of the mismeasured variables, which is typical for empirical applications. For...
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Purpose – The purpose of this paper is to study the pricing efficiency of convertible bonds and arbitrage opportunities between the convertible bonds and the underlying stocks thus improve market efficiency. Design/methodology/approach – Using nonparametric fixed effect panel data model, the...
Persistent link: https://www.econbiz.de/10014694547
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This paper establishes the asymptotic normality of series estimators for nonparametric regression models. Gallant's Fourier flexible form estimators, trigonometric series estimators, and polynomial series estimators are prime examples of the estimators covered by the results. The results apply...
Persistent link: https://www.econbiz.de/10005762851
We introduce a kernel-based estimator of the density function and regression function for data that have been grouped into family totals. We allow for a common intra-family component but require that observations from different families be in dependent. We establish consistency and asymptotic...
Persistent link: https://www.econbiz.de/10005797505
This paper derives the asymptotic distribution of nonparametric neural network estimator of the Lyapunov exponent in a noisy system proposed by Nychka et al (1992) and others. Positivity of the Lyapunov exponent is an operational definition of chaos. We introduce a statistical framework for...
Persistent link: https://www.econbiz.de/10005797511
This paper adapts an already existing nonparametric hypothesis test to the bootstrap framework. The test utilizes the nonparametric kernel regression method to estimate a measure of distance between the models stated under the null hypothesis. The bootstraped version of the test allows to...
Persistent link: https://www.econbiz.de/10005807722
In this paper we are concerned with analyzing the behavior of a semiparametric estimator which corrects for endogeneity in a nonparametric regression by assuming mean independence of residuals from instruments only. Because it is common in many applications, we focus on the case where endogenous...
Persistent link: https://www.econbiz.de/10008506227