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...

The optimal minimum distance (OMD) estimator for models of covariance structures is asymptotically efficient but has much worse finite-sample properties than does the equally-weighted minimum distance (EWMD) estimator. This paper shows how the bootstrap can be used to improve the finite-sample...

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...

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...

This study was carried out to estimate underlying inflation in Nigeria using Unobserved Component (UC) model. Also, different channels were used to identify the source of inflation persistence and volatility. This was estimated using Bayesian analysis in order to examine the role of priors in...

Data insufficiency and reporting threshold are two main issues in operational risk modelling. When these conditions are present, maximum likelihood estimation (MLE) may produce very poor parameter estimates. In this study, we first investigate four methods to estimate the parameters of truncated...

An agent is asked to assess a real-valued variable Y_{p} based on certain characteristics X_{p} = (X_{p}^{1},...,X_{p}^{m}), and on a database consisting (X_{i}^{1},...,X_{i}^{m},Y_{i}) for i = 1,...,n. A possible approach to combine past observations of X and Y with the current values of X to...

In certain circumstances, both researchers and policy makers are faced with the challenge of determining individual efficiency scores for each decision making unit (DMU) under consideration. In this study, we use a Monte Carlo experimentation to analyze the optimal approach to determining...

We consider the problems of derivative pricing and inference when the stochastic discount factor has an exponential-affine form and the geometric return of the underlying asset has a dynamics characterized by a mixture of conditionally Normal processes. We consider both the static case in which...