Solving economic problems IRL

Alexander has always been torn between Finance and Economics, but was finally convinced that Economics was simply put – just more fun.

 “Economics just seemed more intuitive with regard to all of the models, even if there are many similarities. I also wanted to learn more about data science technique and data analysis. We got familiar with the models at the bachelor but we did not fully dive into them using a quantitative approach. The focus was more on theory.”

After talking to Alexander for just a few minutes, it becomes clear that he is a person who truly enjoys crunching numbers, analysis and learning as well as making useful models – basically, everything associated with quantitative skills.  

Economics at the master level

Already while doing his bachelor, Alexander became interested in predicative models that can be applied to business, or even on a societal level. He also learned that he was quite good at Economics, but he wanted to immerse himself more in the field.

“There are a lot that I like about studying here – the lecturers as well as the student life, among other things. Everyone works very hard, so it influences you to do the same. You get a large network and it’s good to know that there are good job opportunities waiting at the end.”

As an MSc in Applied Economics alumni, one could work as an Economics consultant, or as a macro analyst, Alexander explains. He is still not sure which direction he wants to go after he graduates, but he enjoys analysing economic situations and solving economic problems of the real world. For now, he is focused on soaking as much knowledge as possible to get a good overview of the field.

“You learn a fair share of technical skills through this programme. You get really comfortable with mathematics as a tool, through general optimisation in several variables, linear algebra, differential equations and those kinds of things. And there’s a lot of econometrics.”

The power of numbers

Alexander also learns several analysis tools – some STATA, but most of all MATLAB which is used a lot in the industry, and where one can make models. So far, the emphasis seems to be on macro-economic models. Learning the tools will be useful later in work life, especially for those who want to get analytics related positions, he explains.

“I guess Applied Economics is a bit overlapping with the field of Business Analytics, but they use more open source software like Python among other things.”

Alexander explains that the applied economics students generally use more expensive tools that doesn’t require previous experience with programming. In general, analytics is an area he would like to explore more, so he looks forward to learning about big data analysis the next semester.

“I hope that we in the future can take more advantage of machine learning and big data to create good predicative models, and use this knowledge in research to make better economic predictions.”

We always try to interview former students in working life, but certain programmes are so new they have yet to produce their first graduates. In this case, you get a current student’s perspective instead.