Program
Who is this program for?
The Economics Summer School of UNSW Sydney is taught at the graduate level. As such, it is ideal for current (or aspiring) graduate students, but also for participants from Central banks, government institutions, thinktanks or private companies with needs in economic analysis.
Our program provides its participants with at least three key benefits. First, it offers a deep dive into state-of-the-art approaches in Economics. Second, it also equips its participants with practical skills necessary for independent economic analysis in the future. Finally, aside from the coursework itself, our program offers an excellent networking and socializing opportunity. Sign up to our program, enhance your economic knowledge and expand your network!
Course delivery
The Economics Summer School is a full day (9am-4pm) event held in person at UNSW Business School. However, we have designed our schedule to allow for the possibility of attending only half of the program and enrolling only into the morning or afternoon sessions, respectively.
The program will be taking place in Room 207, Level 2, UNSW Business School building E12.
Big Data Econometrics
Big data evokes notions of an era where data plays a ubiquitous role in problem solving and decision-making in organizations. The data deluge has also been a catalyst for greater awareness of machine learning (ML) methods and their usefulness for data analysis.
This course introduces ML methods and examines their relevance for empirical researchers in economics. For many applications, off-the-shelf ML tools are a natural alternative to traditional predictive methods. However, the use of ML in combination with traditional econometric methods has become an active and productive research area, with an emphasis on causal inference rather than prediction. This will be the focus of this course.
The lectures cover the following topics:
- Evolution of tools and methodology for data analysis: Prediction vs. causal inference
- Lasso and friends for high dimensional data
- Tree-based ML methods
- Prediction policy problems
- Double selection and double machine learning
- Heterogeneous treatment effects
Search Frictions in Macro:
An important development in modern macroeconomics is the construction of models that incorporate search frictions in goods and labor markets. Traditionally, models implicitly assume that a fictional Walrasian auctioneer magically announces the price at which market participants should trade. Instead, search models take into account the notion that market participants face frictions in finding a suitable trading partner. Search frictions create a surplus when a match has been formed which has another advantage, namely it allows for bargaining.
This course will introduce you to macroeconomic models with search frictions. In addition, it will also equip you with tools necessary to describe dynamics observed in the data and when evaluating modern macroeconomic models. This practical set of tools that can be applied in different fields includes econometric techniques to formally take into account sampling variation when constructing data statistics and evaluating models.
The lectures will cover the following topics:
- Development of macroeconomic models with search frictions
- The joint surplus and bargaining
- Impulse response functions, variable co-movement
- Filter: Hodrick-Prescott and band-pass filters