Ralf is professor of economics education and deputy head of department at The University of Manchester
What qualifications did you study and where?
I earned an undergraduate degree in economics at The University of Mainz in Germany with one year Erasmus exchange at The University of Glasgow. I then completed my PhD at the Queensland University of Technology in Brisbane, Australia.
Why did you decide on a research career?
I learned to code to answer a research question with empirical data as part of my undergraduate dissertation and my curiosity and desire to learn more drove me to pursue econometrics. I was fortunate to find a PhD supervisor whose interests aligned with mine, and ever since, econometrics has been my passion.
What type of research have you been involved with?
My methodological work in econometrics focuses on modelling nonlinear time-series data. This has led to research on modelling and forecasting as diverse things as inflation, electricity prices, financial volatility and covariances. Lately, my focus has shifted to the pedagogical aspects of my job.
Tell us a bit about the subjects you're a lecturer for.
I teach a large first year unit in statistics for economists. This is the students’ first exposure to using empirical data to study real life problems. We help students to understand the conceptual foundations of statistics, as well as how to handle data.
In a follow-on unit, I teach students techniques useful to use data to establish causal relationships. Most people are aware that correlations we discover in data are not the same as identifying causal relationships but understanding how to establish causal relationships is much more challenging. This is an exciting area of study with powerful concepts and techniques. For students to be able to implement these techniques, they have to learn how to code.
I also teach a first-year unit that supplements the core units in micro- and macroeconomics. These core units often focus on abstract concepts and models, while my unit helps students to understand the power of these ideas and how they can help you to think about real life problems. I am also helping students to see the limits of the economic toolset.
What do you enjoy most about the job?
Undoubtedly, the most rewarding part of my job is working together with students to help them wrap their head around difficult ideas, formulate questions, and guide them through approaches to find answers.
I occasionally discover a student in one of my units was encouraged to change career paths because of the coding skills they learned. Many economics students come to university without an understanding of how important coding is for the discipline and how transformational it can be for their careers.
I also enjoy mentoring new university teachers. I want to help them on their journey to becoming an enthusiastic educator. I get so much enjoyment out of seeing students develop, and I want to help colleagues experience that same satisfaction.
What are the challenges?
Time. I wish had more time to talk to students and colleagues individually, discover what their issues are and how I can help.
I also have not even started getting my head around the impact artificial intelligence (AI) tools will have on the way how we work in future, and therefore what our students should learn and how we should support them. This is worrying in general but has immediate impacts on the ways in which we assess students at university. The pandemic forced many of us to adopt online assessments, which opened up new possibilities, but the rise of tools like ChatGPT and Google Bard has raised concerns about cheating. It feels like we have to re-invent the way we assess yet again, without really understanding the impact of the technology.
What advice would you give to students looking to study economics or economics and data science at The University of Manchester?
Economics is such an exciting subject. Understand why you want to study economics, what you think the pressing economic issues are, and then talk to fellow students and the teaching staff to ensure that they can help you to find out how economics can help answer that question. That isn’t something that you need to do in every lecture or every tutorial, but you need to keep it in mind throughout your time at university. Only you can do this, and we can only help you if you take the initiative.
For those of you interested in the empirical aspects of economics and how econometric techniques overlap and complement the newer field of data science, Manchester is a great place to study, at both undergraduate or postgraduate level.