* A critical attitude towards the use of data and the empirical methods to analyse real world events
* How empirical observations can be interpreted and evaluated from an economic point of view
* Experience in working with Stata

PLEASE NOTE THAT THE INFORMATION ABOUT THE TEACHING AND ASSESSMENT METHOD(S) USED IN THIS COURSE IS WITH RESERVATION. A RE-EMERGENCE OF THE CORONAVIRUS AND NEW COUNTERMEASURES BY THE DUTCH GOVERNMENT MIGHT FORCE COORDINATORS TO CHANGE THE TEACHING AND ASSESSMENT METHODS USED. THE MOST UP-TO-DATE INFORMATION ABOUT THE TEACHING/ASSESSMENT METHOD(S) WILL BE AVAILABLE IN THE COURSE SYLLABUS.

People who retire earlier, die earlier. Would you conclude from this evidence that it is better not to retire early? This course offers you (1) tools with which you can take a critical look at such claims, (2) tools with which you can investigate data yourself. In case of this example, causality might run in the opposite direction: people who are healthier work longer than those who are less healthy. So deceasing earlier might not be caused by earlier retirement but be due to worse health of early retirees. To estimate whether early retirement really increases health risks we need a better research strategy.
This course offers such methods and tools along with assignments to see how it works in practice. It considers both cross-section, time series and panel methods. The course develops an understanding of the main tools with which empirical claims can be established or refuted. The philosophy is to explain the empirical strategies in an intuitive way. We focus on analysing economic phenomena, using applied papers as examples.

Chapters from:
* Stock, J. & Watson, M. (2019), Introduction to Econometrics, Fourth Edition, Pearson.
* Söderbom, M. and F. Teal (2015), Empirical Development Economics, Routledge, London/New York.
A reader with articles and background material.

Basic econometrics, some experience with statistical software such as Stata. An advanced level of English.