This paper provides nonparametric identification results for a class of latent utility models with additively separable unobservable heterogeneity. These results apply to existing models of discrete choice, bundles, decisions under uncertainty, and matching. Under an independence assumption,...

This paper deals with two alternatives to the so-called Hausman test for the exogeneity of instruments, in the context of a model where one or more explanatory variables are possibly correlated with the structural error. These two alternatives are at least as good or better than the Hausman test...

The paper presents a comparison of the two languages Python and R related to the classification tools and demonstrates the differences in their syntax and graphical output. It indicates the functionality of R and Python packages {dendextend} and scipy.cluster as effective tools for the...

Inflation or price level targeting is becoming more popular as a policy objective of the central bank's monetary policy and fiscal policy to guide them. Policy choices calculated price level is as important as the targeted inflation rate due to the different indices can produce different levels...

We present the structure and properties of an aggregate model for the European Union, consisting of 34 equations estimated on annual data aggregated over the twelve-member EU, ranging from 1960 to 1997. Estimation was performed by a two-stage procedure taking into account the possible presence...

We present the structure and properties of an aggregate model for the European Union, consisting of 34 equations estimated on annual data aggregated over the twelve-member EU, ranging from 1960 to 1997. Estimation was performed by a two-stage procedure taking into account the possible presence...

This paper offers a synthesis of a new analytical procedure based on the complementary use of a large number of methods and techniques for categorization of objects, pattern recognition and for structural analysis. It represents an example of a functional clustering [1] and an extension to the...

We propose a Quasi-Bayesian nonparametric approach to estimating the structural relationship ' among endogenous variables when instruments are available. We show that the posterior distribution of ' is inconsistent in the frequentist sense. We interpret this fact as the ill-posedness of the...

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables model...

A Direct Monte Carlo (DMC) approach is introduced for posterior simulation in theInstrumental Variables (IV) model with one possibly endogenous regressor, multipleinstruments and Gaussian errors under a flat prior. This DMC method can also beapplied in an IV model (with one or multiple...