This paper investigates the empirical importance of allowing for multi-dimensional sources of unobserved heterogeneity in auction models with private information. It in turn develops the estimation procedure that recovers the distribution of private information in the presence of two distinct...

The family of Generalized Empirical Likelihood (GEL) estimators provide a number of potential advantages relative to Generalized Method of Moments (GMM) estimators. While it is well known these estimators share an asymptotic distribution, the GEL estimators may perform better in finite sample,...

This paper analyzes alternative empirical strategies for studying the effect of organizational design on performance, as well as the factors which determine organizational design. We begin by developing a general economic model of a firm where multiple organizational design practices are...

We introduce a new methodology for estimating multi-product production functions. It embeds the seminal contributions of Diewert (1973) and Lau (1976) in our extended version of the semi-parametric econometric framework of Olley and Pakes (1996), where we address the simultaneity of inputs and...

We provide a general framework for incorporating many types of micro data from summary statistics to full surveys of selected consumers into Berry, Levinsohn, and Pakes (1995)-style estimates of differentiated products demand systems. We extend best practices for BLP estimation in Conlon and...

This working paper aims to stress the role of the institutional capital and its components, as primary factors, in economic results at the national level, using adequate measurement indicators and econometric models. For this purpose, we analysed the following aspects: the definition of...

Classical regression analysis uses partial coefficients to measure the influences of some variables (regressors) on another variable (regressand). However, a descriptive point of view shows that these coefficients are very bad measures of influence. Their interpretation as an average change of...

Explained variance (R^2) is a familiar summary of the fit of a linear regression and has been generalized in various ways to multilevel (hierarchical) models. The multilevel models we consider in this paper are characterized by hierarchical data structures in which individuals are grouped into...

In the current paper, we study the stability and the survival probabilities of enterprises and banks within a prolonged duration of the debt-crisis, with Monte Carlo simulation. We utilize historical data from banks and enterprises within the debt-crisis to define crisis-variability and...

Two regressions can be interpreted as based on Gini's Mean Difference (GMD): a semiparametric approach, which relies on weighted average of slopes defined between adjacent observations and a minimization approach, which is based on minimization of the GMD of the residuals. The estimators...