![]() ![]() familiarity with macroeconomic and financial statistics as presented in international databases (e.g.an excellent command of at least one of the following high-level programming languages: MATLAB, Stata, Python or R.macroeconomic forecasting, textual data) modelling, solving and estimating dynamic stochastic general equilibrium (DSGE) models experience in at least one of the following areas of technical expertise: analysing macroeconomic or financial time-series data (using, for example, vector autoregression, state-space models, factor models or nonlinear econometric techniques) compiling and analysing large microeconomic databases, such as high-frequency data, household or firm-level survey data, or bank/firm balance sheet data (using, for example, fixed and random effects estimation in cross-section and panel data, difference-in-difference estimators or propensity score matching estimators) applying machine learning techniques to big data (e.g.for a traineeship paid at €1,940, at least two years of PhD studies in economics, statistics, finance, computer science, mathematics or a related field. ![]() for a traineeship paid at €1,070, a bachelor’s degree or higher in economics, statistics, finance, computer science, mathematics or a related field. ![]()
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