Statistics & Econometrics, Empirical Microeconomics, Empirical Macroeconomics, Empirical Finance, Operations Research

Brief statement of research interests of the people holding mixed, research and teaching, positions

Econometrics, financial econometrics, Bayesian inference, life insurance mathematics, time series models, Bayesian diffusion and jump-diffusion models, Bayesian structural VAR models.

Financial econometrics, time series analysis, Bayesian inference, regime-switching models, stochastic volatility models, market risk analysis.

Bayesian inference, demand systems, nonlinear time series, macroeconomic forecasting, business cycle analysis, numerical methods for Bayesian analysis, financial econometrics.

Stochastic frontier analysis, Bayesian inference, productivity and productive efficiency measurement, growth and development accounting, models for panel data.

Applied microeconometrics, Bayesian inference, stochastic frontier analysis, efficiency and productivity in banking and agriculture, econometric analysis of (micro) panel data, discrete choice models in credit risk measurement.

Bayesian statistics and econometrics; inference robustness; elliptical distributions and their generalizations; time series models and forecasting; Bayesian analysis of GARCH and SV models, multivariate hybrid SV-GARCH models; stochastic frontier production and cost models, efficiency analysis; decomposition of economic growth and international growth comparisons; discrete choice models.

Financial econometrics, stochastic volatility processes, volatility models, risk assessment and forecasting, portfolio analysis, derivatives pricing, exogeneity and non-causality in econometrics, time series analysis, Bayesian inference, Monte Carlo methods.

Financial econometrics, econometrics of the business cycle, forecasting macroeconomic time series, Bayesian inference, subsampling methods, Markov Chain Monte Carlo, asymmetric multivariate distributions, empirical finance.

Operations research, productivity and efficiency analysis, Data Envelopment Analysis (DEA) - theory and applications.

Vector autoregression (VAR) processes, cointegration, structural vector autoregression models (SVAR), structural vector error correction models, co-feature analysis, common cyclical factors, modelling of the empirical autocorrelation function, Bayesian analysis.

Dynamic Stochastic General Equilibrium (DSGE), Dynamic Stochastic General Equilibrium Vector Autoregression (DSGE-VAR), Bayesian inference, Markov Chain Monte Carlo, stochastic frontier models.