Instrumental variables estimation can, in principle, avoid biases that ordinary least squares estimation suffers when explanatory variables are correlated with the disturbances. Finding appropriate instruments is a challenge. This paper uses seven recently published empirical papers to...

This paper studies the relationship between lobbying, free emission allowance allocation and firm outcomes in the European Union Emissions Trading System (ETS). I draw on administrative data from the EU Transpareny Register (TR) and the European Union Transaction Log (EUTL), and construct a...

In this paper, I try to tame "Basu's elephants" (data with extreme selection on observables). I propose new practical large-sample and finite-sample methods for estimating and inferring heterogeneous causal effects (under unconfoundedness) in the empirically relevant context of limited overlap....

We decompose the Pearson correlation coefficient into two components. We recommend the first component for detecting linear relationships and the second for recognizing patterns of two parallel lines, providing robust versions to outliers. The significance of the Pearson coefficient without...

This paper derives asymptotic power functions for Cramer-von Mises (CvM) style tests for conditional moment inequality models in the set identified case. Combined with power results for Kolmogorov-Smirnov (KS) tests, these results can be used to choose the optimal test statistic, weighting...

The standard approach to indirect inference estimation considers that the auxiliary parameters, which carry the identifying information about the structural parameters of interest, are obtained from some recently identified vector of estimating equations. In contrast to this standard...

This paper proposes a bootstrap-based procedure to build confidence intervals for single components of a partially identified parameter vector, and for smooth functions of such components, in moment (in)equality models. The extreme points of our confidence interval are obtained by...

In a recent paper Johnson and Kuosmanen (2011) propose a new, semi-parametric, general cost-frontier model, the stochastic nonparametric envelopment of data (StoNED). The model is semi-parametric in the sense that the cost function is estimated nonparametrically, while the functional form of the...

We define a non-parametric estimator of the integrated leverage effect as the covariance between the logarithmic asset price and its volatility. In Curato and Sanfelici (2015), a consistent estimator of the leverage effect has been introduced through a pre-estimate of the Fourier coefficients of...

Purpose - The purpose of this study is to show that closure-based classification and regression models provide both high accuracy and interpretability. Design/methodology/approach - Pattern structures allow one to approach the knowledge extraction problem in case of partially ordered...