Elements of Research Methods

2 Credits.

The material in this course covers assumptions of multivariate regression and discusses the most common econometric problems and the potential consequences and remedies. Moreover, it discusses heteroscedasticity, time series, autocorrelation, multicollinearity, outliers, logistic regression analysis, pooled cross sections, and the use of dummy variables. The purpose of this course is to provide students with a conceptual understanding of the tools of quantitative analysis used in economics and social sciences research. The course has a strong practical approach, and the emphasis is on how to model, use, and interpret data to perform research analysis. Indeed, the topics will be heavily tilted towards interpreting pre-estimated quantitative output and identifying econometrics issues with estimation or testing procedure that might affect the interpretation of the output. In addition, class examples together with TA sessions will make students familiar with the main software used to perform quantitative research: STATA. This course will enable students to comfortably attend furthermore advanced courses in Economics and Finance. Prerequisite: Statistics for Data Analysis, Elements of Statistics, or Introduction to Statistics.