How do Central Banks think? A crash course. A set of educative videos explaining simple monetary policy in layman's terms.
Teaching experience:
- Big Data and Business Intelligence (Business degree) using the R language. Based on Data Mining with R Learning with Case Studies , Second Edition, Luis Torgo.
- Quantitative Methods applied to Politics and Economics (Bachelor level).
- Time Series Econometrics with Applications in Macroeconomics and Finance (Master level). Lectures can be downloaded from here. Acknowledgements to Christian M. Dahl his help with the material.
- Statistics for General Management and Manufacturing Engineers (Bachelor level) based on Essentials of Business and Statistics, Bruce Bowerman, Richard O'Connell and J. Burdeane Orris.
- Microeconometrics (Master level) based on Econometric Analysis of Cross Section and Panel Data, Jeffrey M. Wooldridge. Lectures can be downloaded from here. Acknowledgements to Christian M. Dahl and Martin Nielsen for their help with the material.
- Econometrics (Bachelor level) based on Introductory Econometrics: A Modern Approach, Jeffrey M. Wooldridge.
Impressions from a cooperative learning (CL) experiment:
I incorporated cooperative learning in the Time Series course of 2013. Acknoledgements to Richard Felder for his amazing material. Students were divided in heterogenous groups of 3 or 4 after answering a questionnaire about their background and study schedules.The final grade consisted of three marks and measures the following skills:
- Individual skills (written exam) 30%.
- Collaboration skills. Two group essays of weight 35% each. The mark of this essay is measured taking into account:
- the essay content (25%);
- the group interdependency (25%). The lecturer randomly chooses one member of the group who will have to report on the group assigment. The performance of this member will affect the final mark of the group;
- feedback (25%). A different group (choosen randomly) will review the initial draft and provide positive feedback to improve the final version of the essay; and
- peer assessment (25%). Each student give a mark to all other members in the group measuring their performance and commitment.
Positive outcomes: It was possible to identify which groups worked well together and free-riders. The peer assessment made them more committed to group work.
Negative outcomes: It requires a lot of work both from lecturers and students, therefore it might not be a good methodology for an elective course.