Econometrics and Forecasting
Dublin City University
Area of Study
Taught In English
Course Level Recommendations
ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.
Recommended U.S. Semester Credits2
Recommended U.S. Quarter Units3
Hours & Credits
The purpose of this module is to introduce students to basic regression methods that are used in analyzing social science data. The emphasis is on the application of statistical methods to analyze economic and/or financial data. In this module students will develop knowledge and skills in applying statistical methods to analyze data, using appropriate statistical software to analyze data, using regression models to test hypotheses, making and evaluating predictions based on statistical models. Students will participate in the following learning activities: attend and participate in lectures, familiarize themselves with the use of statistical software, work on take home assignments that replicate some previous empirical research, critically evaluate some of the literature in empirical research.
1. carry out basic statistical inference procedures using regression models
2. use statistical software to produce and evaluate forecasts of real economic time series data
3. select appropriate econometric techniques to analyse particular data sets
4. evaluate empirical statistical work and critically assess econometric approaches
5. explain how to produce and evaluate forecasts using time series models