The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the fact that these models are complicated often makes the bootstrap extremely slow or even practically infeasible. This paper proposes an alternative...

Bootstrapping methods have so far been rarely used to evaluate spatial data sets. Based on an extensive Monte Carlo study we find that also for spatial, cross-sectional data, the wild bootstrap test proposed by Davidson and Flachaire (2008) based on restricted residuals clearly outperforms...

In this paper, we propose a simple dependent wild bootstrap procedure for us to establish valid inferences for a wide class of panel data models including those with interactive fixed effects. The proposed method allows for the error components having weak correlation over both dimensions, and...

In presence of panel data, technical efficiency is used to compare the performances of Decision-Making Units (DMUs). The novelty of this paper is the consideration of the dependence between the two error terms in the case of panel data and the introduction of time effect models in the Stochastic...

Machine learning and artificial intelligence methods are often referred to as \black boxes" when compared to traditional regression-based approaches. However both traditional and machine learning methods are concerned with modeling the joint distribution between endogenous (target) and exogenous...

Haavelmo's seminal 1943 paper is the first rigorous treatment of causality. In it, he distinguished the definition of causal parameters from their identification. He showed that causal parameters are de fined using hypothetical models that assign variation to some of the inputs determining...

The widely used Oaxaca decomposition applies to linear models. Extending it to commonly used nonlinear models such as duration models is not straightforward. This paper shows that the original decomposition that uses a linear model can also be obtained by an application of the mean value...

This paper shows how a great philosopher, like Popper, can easily fall back to a common superstitious person. This paper also criticizes the general practice by statisticians to invent ad hoc method or manipulate data to suppress errors. Instead, this paper promotes the Xenophanes spirit of...