In applied microeconometric panel data analyses, time-constant random effects and first-order Markov chains are the most prevalent structures to account for intertemporal correlations in limited dependent variable models. An example from health economics shows that the addition of a simple...

An alternative to using normally distributed random effects in modeling clustered binary and ordered responses is based on using a finite-mixture. This approach gives rise to a flexible class of generalized linear mixed models for item responses, multilevel data, and longitudinal data. A test of...

This paper proposes a new method for approximating vector autoregressions by a finite-state Markov chain. The method is more robust to the number of discrete values and tends to outperform the existing methods over a wide range of the parameter space, especially for highly persistent vector...

This paper compares the performance of three methods for pricing vanilla options in models with known characteristic function: (1) Direct integration, (2) Fast Fourier Transform (FFT), (3) Fractional FFT. The most important application of this comparison is the choice of the fastest method for...

Even if the name futures indicates a simple instrument, bond futures are complex. Several special features are embedded in the instrument. In particular the future is not written on one specific bond but on a basket of bonds, from which the short side can deliver the cheapest. This paper focuses...

We address the problem of seasonal adjustment of a nonlinear transformation of the original time series, such as the Box-Cox transformation of a time series measured on a ratio scale, or the Aranda-Ordaz transformation of proportions, which aims at enforcing two essential features: additivity...

In empirical regional economics, returns to scale are typically estimated at the regional level in search for evidence on alternative theories of growth and agglomeration. However, returns to scale may also have a firm-level dimension. In this paper, we exploit micro level data and estimate the...

This study considers how firms’ internal variables and regional factors affect the total factor productivity of Italian manufacturing firms. Due to of the hierarchical structure of data in estimation, we employ a multilevel model. Results, which refer to 2006, show the importance of...

The aim of this paper is to assess the quality of the ranking of institutions obtained with multilevel techniques in presence of different model misspecifications and data structures. Through a Monte Carlo simulation study, we find that it is quite hard to obtain a reliable ranking of the whole...

The predictions that economic freedom is beneficial in reducing corruption have not been found to be universally robust in empirical studies. The present work reviews this relationship by using firms' data in a cross-country survey and argues that approaches using aggregated macro data have not...