Relevance of Data Science in Economics

  • Diana George
  • Published 08/03/2022
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Both Economics and Data Science have a lot in common. Both require strong analytical abilities, involve investigation of huge sets of raw data and solving quantitative problems through modeling techniques

Economics and Data Science are closely-related subjects. Data Science as a formal discipline evolved in the 2000s but it made considerable headway as a new and emerging field of study in the 1970s when economists and researchers began widening the scope of statistics from a subject that mainly involved describing the data to a subject that would include not only collection or description of data but also its analysis, using scientific methods and tools.

The term ‘Data Science’ was first used by Professor C.F. Jeff Wu as an alternative name for statistics during a lecture given to the Chinese Academy of Sciences in Beijing in 1985. His reason was simple: the term would prevent statistics from being stereotyped as an accounting subject or a discipline that was just limited to describing the data. Data Science was much wider in scope and apart from statistics, it also included methods and toolkits to analyse and dissect the data to find meaningful knowledge that would inform business decisions, predict outcomes or describe future courses of action.

Economics as a statistical and mathematical subject is heavily dependent upon data. The basic premise of Economics is to find helpful insights from datasets that reveal information about the financial state of an organization in order to take better budgetary decisions. Data analytics thus forms a crucial part of both Economics as well as Data Science and the two subjects have a lot in common. Both require strong analytical abilities and involve investigation of huge sets of raw data in order to discover patterns and solve quantitative problems through modeling techniques. Data Science is, in fact, revolutionizing sectors today in which economists mostly work, such as banking, insurance, finance, healthcare, public policy and consulting.

Below are some of the ways in which a degree in Economics with Data Science can help young graduates step up the career ladder:

Data science is everywhere: Data science has widespread prevalence today. Almost every sector and industry banks upon an army of data scientists and analysts to aid decision-making and strategy planning. Economics graduates with a specialization in Data Science can take advantage of the resulting surge in demand for data scientists and analysts.

Rapid growth of jobs: Data Science is a rapidly growing and ever-expanding field. Data science and analytics jobs are among the fastest-growing jobs today. According to the Bureau of Labour Statistics, data science jobs will grow by a whopping 43.4% by 2029. This rapid growth is going to expand the horizons for economics graduates who have a specialization in data science.

Higher earning potential: Economics graduates with a specialization in Data Science will boost their earning potential as knowledge of data analytics is in high demand these days. Economics graduates with a sound knowledge of data science techniques and toolkits will be able to beat the competition and thrive in a tight job market.

Alternative perspective on data: A degree in Economics will prove to be beneficial to a career in data science as it will give one an alternative perspective on data. An Economics graduate’s ability to understand causal relationships between numerical datasets will enable him or her to interpret data in new and valuable ways which can help organisations refine their strategic planning.

Knowledge of machine learning: A degree in Economics with Data Science will improve graduates’ knowledge of machine learning. Both Data Science and Economics involve a study of algorithms. While Data Science refers to these algorithms as types of machine learning, Economics refers to them as linear regressions or statistical models.

Presentation skills: Economics and Data Science graduates are required to regularly make presentations and this helps finetune their presentation skills such as speaking and listening, while boosting their confidence levels and training them in leadership skills.

Communication skills: An Economics and Data Science degree can train graduates in using simplified language to explain complex concepts or algorithms. This skill can come in handy when trying to explain their findings and reports to individuals or organisations who may not have any prior knowledge of data or analytics.

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Diana George
Diana George

The writer is a part of the UPES editorial team

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