State price density (SPD) contains important information concerning market expectations. In existing literature, a constrained estimator of the SPD is found by nonlinear least squares in a suitable Sobolev space. We improve the behavior of this estimator by implementing a covariance structure...

The aim of this paper is to construct a forecasting model oriented on predicting basic macroeconomic variables, namely: the GDP growth rate, the unemployment rate, and the consumer price inflation. In order to select the set of the best regressors, Bayesian Averaging of Classical Estimators...

Firms' labor demand responses to wage changes are of key interest in empirical research and policy analysis. However, despite extensive research, estimates of labor demand elasticities remain subject to considerable heterogeneity. In this paper, we conduct a comprehensive meta-regression...

In this paper we consider the problem of interpreting the signs of the estimated coefficients in multivariate time series regressions where the regressors are correlated. Using a continuous time model, we argue that focussing on the signs of individual coefficients in such regressions could be...

Firms' labor demand responses to wage changes are of key interest in empirical research and policy analysis. However, despite extensive research, estimates of labor demand elasticities remain subject to considerable heterogeneity. In this paper, we conduct a comprehensive meta-regression...

This research contrasts three econometric alternatives for stochastic efficiency frontier analysis: order – inter-quantile – and inverse order regression under the assumption of truncated error term distribution, and replicated moment estimation. The demonstration departs from a simple...

Why are some nations more effective at battling corruption than others? Are there different determinants in the fight against corruption across developing nations? How do wealth effects play-out when existing corruption-control levels matter in the corruption battle? To investigate these...

Why are some nations more effective at battling corruption than others? Are there different determinants in the fight against corruption across developing nations? How do wealth effects play-out when existing corruption-control levels matter in the corruption battle? To investigate these...

In partially linear model selection, we develop a profiled forward regression (PFR) algorithm for ultrahigh dimensional variable screening. The PFR algorithm effectively combines the ideas of nonparametric profiling and forward regression. This allows us to obtain a uniform bound for the...

The intuition behind linear regression can be difficult for students to grasp particularly without a readily accessible context. This paper uses basketball statistics to demonstrate the purpose of linear regression and to explain how to interpret its results. In particular, the student will...