Abstract: This systematic and integrated framework for econometric modelling is organized in terms of three levels of knowledge: probability, estimation, and modelling. All necessary concepts of econometrics (including exogeneity and encompassing), models, processes, estimators, and inference procedures (centred on maximum likelihood) are discussed with solved examples and exercises. Practical problems in empirical modelling, such as model discovery, evaluation, and data mining are addressed, and illustrated using the software system PcGive. Background analyses cover matrix algebra, probability theory, multiple regression, stationary and non-stationary stochastic processes, asymptotic distribution theory, Monte Carlo methods, numerical optimization, and macro-econometric models. The reader will master the theory and practice of modelling non-stationary (cointegrated) economic time series, based on a rigorous theory of reduction.

Keywords: cointegration, data mining, econometric modelling, encompassing, exogeneity, maximum likelihood, model discovery, model evaluation, non-stationarity, reduction