Econometrics

This course introduces the basics of econometric analysis. We deal with cross-sectional and time-series analyses. The course starts with the foundations of classical multiple linear regression models. After that, we present the tools of model building and the choice between nested models. The discussion is continued with the requirement of spherical disturbances in classical linear models and the treatment of heteroskedastic error terms by robust standard errors and generalised least squares. We also deal with models which are non-linear in their explanatory variables. We discuss the topic of nominal explanatory variables and their incorporations into regression models.

Mathematics I.

Review of elementary functions, their graphs, and applications. Linear, quadratic and power functions. The exponential and logarithmic functions. Composition of functions. Mathematical models. Limits of functions and continuity. The number e. Differential calculus of real-valued functions. The concept of the derivative at a point and its interpretation as rate of change, as slope and as a linear approximation. The derivative functions. Derivatives of the power, exponential and logarithmic functions. Differentiation rules. Applications of the derivative. Increasing and decreasing functions, optimal values. Percentage changes: the logarithmic derivative and elasticity. Functions of several variables. Partial derivatives and local optimum. Level curves, optimum problems with constraints. The definite integral as area. The fundamental theorem of calculus. Indefinite integrals. Improper integrals. Applications of the definite integral to probability.