Analysis of Current Challenges

Course goals

Learning objectives
At the end of the course the student is able to:

• Demonstrate knowledge of current economic challenges;
• Understand, summarize and critically evaluate contemporaneous scientific articles;
• Replicate empirical analysis and main results of contemporaneous scientific articles;
• Conduct own data analysis using recent software for empirical analysis; 
• Communicate existing research in presentation in small groups;
• Work effectively in teams for a specific project with limited intervention or instruction;
• Provide effective feedback to peers

Content

This course focusses on current economic challenges. The course will contain a weekly lecture and tutorial. The courses consist of a series of lectures which discuss cutting-edge research articles on the three broad topics i) technological progress and changing institutions ii) labor market inequality and iii) sustainable transitions.

Overall, this course develops some of the major theoretical economic models to understand these current challenges. It also discusses recent research designs to evaluate these models, including event-study and instrumented difference-in-differences, shift-share IV, high-dimensional fixed-effects regressions, and welfare simulations of dynamic general equilibrium models.

During the tutorials students will gain experience in applied data analysis by replicating scientific research articles discussed in the lecture. Furthermore, students will be trained to conduct data analysis on their own. By doing so, students are introduced to Stata and/or R, and programming in Python and/or Matlab.

Format
The course consists of 1 lecture and 1 tutorial per week (1h45m each).
The lectures focus on explaining theory and discuss the research design of cutting-edge research articles;
The tutorials focus on practicing applied data analysis by replicating the main results of the cutting-edge research articles discussed in the lecture and by conducting their own data analysis.

Assessment method
The goals of the course contain both a knowledge component and a skills component which is reflected in the way students are assessed. The course will contain a combination of assessment formats.

1. Presentation of empirical data analysis during the tutorial (teamwork in small groups of students): 40% (team grade)
2. Endterm to assess the economic reasoning on topics covered in the lectures and coding skills learnt in all weeks: 60% (individual grade)

Intended Learning Outcomes

• Being able to think and act at an academic level.
• Solving problems, accounting for social aspects.
• Communicating in English at an academic level.
• Being able to give a brief oral presentation on a specific subject.
• Being able to work in a team for a well-designed task or project.
• The graduate has, at an academic level, the knowledge and understanding of how to apply economic theory for addressing contemporary transformations such as technological change, climate change, sustainable transitions, migration, or ageing.
• The graduate is able to interpret economic theories to identify potential causes and consequences of such contemporary transformations.

In case online access is required for this course and you are unable (or do not want) to buy the access code, you are advised to contact the course coordinator for an alternative solution. Please note that access codes are not re-usable meaning that codes from second hand books do not work, as well as access codes from books with a different ISBN number. Separate or spare codes are usually not available.