Computational Methods in Econometrics - Period 1

In this course we discuss numerical and simulation-based methods for their use in econometrics and data science. In the first part we review matrix computations, numerical methods for optimization and Monte Carlo integration. We illustrate how these methods are used for estimation of parameters in statistical models. In the second part we investigate properties of estimators, test statistics and residuals using simulation studies. In particular, we simulate distributions of parameter estimates under different data generation processes, but also distributions of test statistics such as unit-root tests, of R-squared goodness-of fit in spurious regressions, and of model selection criteria such as Akaike information criteria. We finally use simulations to verify the accuracy of diagnostic tests related to normality and heteroskedasticity.

Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.