Evolving with Economics

Seems only yesterday that I got an email notification on my phone. I was sharing an Uber with my classmate from Post Graduate Economics. I told him, "I have to go Mumbai." He was curious to know the reason as we were interning together and leaving midway was concerning. The mail was a response to my application to the summer internships at IGIDR , also known as the Visiting Students' Programme. I was among 10 students in the country selected to intern there for the summer after my second semester.

During my internship, I was involved with reading and empirical research from Day 1. My supervisor was extremely friendly and I learnt a lot through him. It was fun interacting with Economics students from different colleges across India, having discussions both academic and casual. It was also during this internship that I had my first experience dealing with large datasets through statistical tools and programming language (Stata). I was quite intrigued when I worked with these datasets. Like a coder with statistical knowledge, I would try permutations and combinations of methods to arrive at analytical insights. Sometimes I would just keep coding for hours and forget to have lunch. We also had evenings after dinner at the mess, when hostel students who stayed back to intern in Mumbai, and some students from France and Italy doing a course, would gather with the summer interns. We would talk and sometimes even play musical instruments.

IGIDR had a 4-storey library for Economics and was a library that attracts even irregular readers, owing to its vast catalogue, its ambience for focussed study with all required facilities for research, both theoretical and empirical. So, although my work during the internship was on Labour Economics, I did read some other interesting books including some books on Behavioral Economics. The very definition of 'Behavioral Economics' fascinated me - "The study of the impact of human behaviour and psychology on Economic decisions." We didn't have a paper on Behavioral Economics for our Post Grads, but neither did most colleges and Universities in India. Most papers were an account of economic theories and thought. Although a significant amount of weightage was given to Mathematics, Statistics and Econometrics (Basic and Advanced) and applied economics was also covered. It was a wholesome Master's Degree. Probably, the scope of Economic Sciences in India was mostly development studies and research apart from the general necessary training in economic theory, thought and practice. After some Googling, I found out that Behavioral Economics studies was quite prevalent in USA. Social experiments were more accepted in the States, compared to India in 2016.

However, human psychology does play a huge role in economic outcomes, especially in the evolving nature of human minds today that does not always succumb to 'herd behavior.' So, after I was back during my final semester, I spoke to the Head of our (the Economics) Department back then and told her that I was interested to write my Dissertation in Behavioral Economics. After some discussion, I did take it up and under the guidance of a Professor in the Department. Incidentally, the year I successfully submitted my dissertation and graduated; the American Economist Richard Thaler received the prestigious Sveriges Riksbank Prize in Economic Sciences (Nobel, 2017) for his contributions to Behavioral Economics.

But after post grads, I thought - What now? After a few months, I saw some ads about data science courses by upGrad and started to join the dots. I've studied economics, statistics, some math, and a bit of coding here since school and did enjoy working with data during my internship. So, I signed up. As it was essentially a PG diploma course with a certification offered by International Institute of Information Technology Bangalore , there were many lectures on various topics by the Professors there. As upGrad was the education partner, there were also sessions as well as lectures by industry experts. To ensure that the learning progress is smooth, there were mentors and discussion forums. Due assessment was done with MCQs, assignments and exams. Towards the end of the course, they also helped prepare learners for career transitions in data science.

Unconsciously, even though my first 'job' was in the domain of data science and most of my colleagues were engineers, it was a management consulting firm. Back then, it wasn't very clear as to who a data scientist was or a data engineer was or a data manager or analyst and so on. But now when I think of it, we were data science consultants. I did learn a lot there, but the stride was short-lived. The infamous pandemic of COVID-19 was causing havoc.

So I left the job and came to my hometown. It was a peaceful time for reflection and working on mental health. Overseeing renovation work at home, I did learn a thing or two about whom to hire for what work and which component goes where. One doesn't learn everything from books alone. I photographed an engagement ceremony for a relative, as I had available hours. Through that, I got myself an Economics student. I really enjoyed learning Economics in my 12th Standard (Grade), so I wanted to share with the expertise that I had gathered from what I had learnt, since school through college from my Professors at St. Joseph's University in both UG and PG, in a simple, practical and interesting way for a 12th standard student. Although it was one student, he said he really enjoyed the classes and performed well.

After that, a few children in the neighborhood wanted to learn guitar, as I used to practice now and then and it could be heard. So, I taught them guitar from what I had learnt since 2005 from my guitar tutors, my self-taught sessions and my Trinity College lessons. The kids learnt well, although it felt more like a crash course than a full-fledged training.

A friend of mine called me towards the end of the music classes. There was a need for a Power BI developer in an Economics team. It had been a while since I coded for data science and machine learning, but at that point of time Power BI seemed do-able and in personal opinion a year ago, "less stressful" compared to what I am trained to do as BI was a part of data science; a desirable option for better mental health. Also, I didn't want to give up on Economics, so I decided to give it a go.

I got in. There was a lot to learn from everyone in the team. Everyone was an expert in something or the other. It became a great place to exchange knowledge and work together. The work culture was good for improving one's delivery and problem-solving approach along with building trust. My existing skills also evolved over a short span of time simply by engaging myself with work, conversation, and continuous learning. It didn't stop at Power BI, of course. I gained confidence to pick up my old tools again.

Being trained in Economics as well as Data Science, I wanted to be a bridge between the two worlds. It often happens that Economists try to solve the same problems as the Data Scientists. But both miss out as they tend to leave out the other. Economists use theory, data, and statistics. Data Scientists use programming, statistics, and accurate measurements. I feel Economists need to use the programming techniques of data science, use their knowledge of Economics and Statistics, and apply them to the wealth of available data. This can bring out the best insights.

It was roughly 10 years ago when I wanted to be a corporate economist. Progress is never peaceful, but evident. Sometimes 'Economists' are the greats, sometimes they are the scholars and sometimes consultants. Sometimes we are there, at other times we are getting there. But look how far 'Economics' itself has grown - from 'household management' to 'international trade,' from the 'stock exchange' to 'trading in cryptocurrency,' from 'banking' to 'FinTech' and from 'econometrics' to 'machine learning.' The use of neural networks for Time series modelling using LSTM and CNN from the statistical methods like AR, MA, ARIMA are indications that economics has evolved.

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