While the classical framework has a rich set of limited information procedures such as GMM and other related methods, the situation is not so in the Bayesian framework. We develop a limited information procedure in the Bayesian framework that does not require the knowledge of the full likelihood. The developed procedure is a Bayesian counterpart of the classical GMM but has advantages over the ...

This paper addresses the choice of an optimal smoothing parameter for local polynomial matching. A version of Empirical Bias Bandwidth Selection (EBBS) proposed by Ruppert (1997) is applied to account for the MSE computation of the matching estimator. Thereby, an estimator for the large sample variance of the local polynomial matching estimator is also provided. A Monte Carlo study indicates be...

We suggest a non-parametric heteroscedasticity and autocorrelation consistent (HAC) estimator of the variance–covariance (VC) matrix for a vector of sample moments within a spatial context. We demonstrate consistency under a set of assumptions that should be satisfied by a wide class of spatial models. We allow for more than one measure of distance, each of which may be measured with error. Mon...

This paper considers the estimation of average autoregressive roots-near-unity in panels where the time-series have heterogenous local-to-unity parameters. The pooled estimator is shown to have a potentially severe bias and a robust median based procedure is proposed instead. This median estimator has a small asymptotic bias that can be eliminated almost completely by a bias correction procedur...

This paper provides implied measures of higher-order dependencies between assets. The measures exploit only forward-looking information from the options market and can be used to construct an implied estimator of the covariance, co-skewness, and co-kurtosis matrices of asset returns. We implement the estimator using a sample of US stocks. We show that the higher-order dependencies vary heavily ...

This paper uses a new non-parametric, unconditional, hyperbolic order-α quantile estimator to construct a hyperbolic version of the Malmquist index. Unlike traditional non-parametric efficiency estimators, the new estimator is both robust to data outliers and has a root-n convergence rate. We use this estimator to examine changes in the efficiency and productivity of U.S. banks between 1985 and...

Minimizing Bias in Selection on Observables Estimators When Unconfoundness Fails We characterize the bias of propensity score based estimators of common average treatment effect parameters in the case of selection on unobservables. We then propose a new minimum biased estimator of the average treatment effect. We assess the finite sample performance of our estimator using simulated data, as wel...

This paper investigates the determinants of intraindustry trade IIT , horizontal IIT HIIT , and Vertical IIT VIIT in the automobile industry in Portugal. The trade in this sector between Portugal and the European Union EU-27 was examined, between 1995 and 2008, using a dynamic panel data. We apply the GMM system to solve the problems of serial correlation and the endogeneity of some explanatory...

In a general classification, the economy of any country is divided into two parts of official and invisible economies. Invisible activities drop outside the scope of the law and official economy and strongly affect socioeconomic development and the formal sector of all countries.These activities which are known under various titles including the shadow economy are influenced by various factors....

When in a linear GMM model nuisance parameters are eliminated by multiplying the moment conditions by a projection matrix, the covariance matrix of the model, the inverse of which is typically used to construct an efficient GMM estimator, turns out to be singular and thus cannot be inverted. However, one can show that the generalized inverse can be used instead to produce an efficient estimator...