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...

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,...

We propose a conformant likelihood estimator with exogeneity restrictions (CLEER) for random coefficients discrete choice demand models that is applicable in a broad range of data settings. It combines the likelihoods of two mixed logit estimators--one for consumer level data, and one for...

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...

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...

This paper is a substantially revised version of our earlier working paper, "Truth and Robustness in Cross-country Growth Regressions." The most important revisions concern the handling of missing observations in the cross-country data set. In the earlier paper, these had been handled through...

This paper is concerned with the problems of posterior simulation and model choice for Poisson panel data models with multiple random effects. Efficient algorithms based on Markov Chain Monte Carlo methods for sampling the posterior distribution are developed. A new parameterization of the...

The Greek Shipping Estimation Model aims to provide a coherent statistical framework for the estimation of Balance of Payments (BoP) items related to shipping activity, based on administrative sources and commercial databases. Given the multi-territorial nature of the shipping sector and its...

Particle filtering is a useful statistical tool which can be used to make inference on the latent variables and the structural parameters of state space models by employing it inside MCMC algorithms (Flury and Shephard, 2011). It only relies on two assumptions (Gordon et al, 1993): a: The...