In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and illustrate the major principles of corresponding Markov Chain Monte Carlo (MCMC) based statistical inference. We provide a hands-on ap proach which is easily implemented in empirical...

Using individual level data from Turkstat Household Labor Force Survey for 2005-2009 period and a variety of parametric and semi-parametric techniques, we test two hypothesis regarding formal and informal labor markets: whether there is a wage gap between formal and informal workers and whether...

Accumulation of education and geographic concentration of educated people in cities are expected to generate urban income growth. New economic geography predicts income divergence across regions. We investigate the dynamic process of accumulating tertiary education and regional income growth in...

It is quite common in convergence analyses across regions that data exhibit strong spatial dependence. While the literature adopting the regression approach is now fully aware that neglecting this feature may lead to inaccurate results and has therefore suggested a number of statistical tools...

This paper investigates how the ordering of variables affects properties of the time-varying covariance matrix in the Cholesky multivariate stochastic volatility model. It establishes that systematically different dynamic restrictions are imposed when the ratio of volatilities is time-varying....