Simulation -based smoothing and filtering in factor stochastic volatility models : two econometric applications (July-2001)

The past decade has wítenessed a series of (well accepted and defined) financial crises periods in the world economy. Most of these events aI,"e country specific and eventually spreaded out across neighbor countries, with the concept of vicinity extrapolating the geographic maps and entering the contagion maps. Unfortunately, what contagion represents and how to measure it are still unanswered questions. In this article we measure the transmission of shocks by cross-market correlation\ coefficients following Forbes and Rigobon's (2000) notion of shift-contagion,. Our main contribution relies upon the use of traditional factor model techniques combined with stochastic volatility mo deIs to study the dependence among Latin American stock price indexes and the North American indexo More specifically, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. From a theoretical perspective, we improve currently available methodology by allowing the factor loadings, in the factor model structure, to have a time-varying structure and to capture changes in the series' weights over time. By doing this, we believe that changes and interventions experienced by those five countries are well accommodated by our models which learns and adapts reasonably fast to those economic and idiosyncratic shocks. We empirically show that the time varying covariance structure can be modeled by one or two common factors and that some sort of contagion is present in most of the series' covariances during periods of economical instability, or crisis. Open issues on real time implementation and natural model comparisons are thoroughly discussed.

What causes violent crime?

This study uses a new data set of crime ratesfor a large sample of countriesfor the period 1970- 1994, based on information from the United Nations World Crime Surveys, to ana/yze the determinants ofnational homicide and robbery rates. A simple model of the incentives to commit crimes is proposed, which explicit/y considers possible causes of the persistence of crime over time (criminal inertia). Several econometric mode/s are estimated, attempting to capture the . determinonts of crime rates across countries and over time. The empirical mode/s are first run for cross-sections and then applie'd to panel data. The former focus on erplanatory variables that do not change markedly over time, while the panel data techniques consider both the eflect of the business cyc1e (i.e., GDP growth rate) on the crime rate and criminal inertia (accountedfor by the inclusion of the /agged crime rate as an explanatory variable). The panel data techniques a/so consider country-specific eflects, the joint endogeneity of some of the erplanatory variables, and lhe existence of some types of measurement e"ors aJjlicting the crime data. The results showthat increases in income inequality raise crime rates, dete"ence eflects are significant, crime tends to be counter-cyclical, and criminal inertia is significant even after controlling for other potential determinants of homicide and robbery rates.

Evolución de modelos de gobierno y regulación de empresas estatales en América Latina: análisis del período 1975-2014

CERI - Centro de Estudos em Regulação e Infraestrutura