Computer science: Freeing economists to do economics

Polina Zakharov is a Warwick Economics Summit Ambassador at Columbia University, and a guest writer for the Summit blog. She is a Sophomore (second year undergraduate) working towards a degree with a Computer Science major, and an Economics minor.

The role of computers is to ‘free mathematicians to do mathematics’- Grace Hopper, 1952

I would like to extend this famous quotation by Hopper to say that the role of computers is likewise to free economists to do economics. When studying economics, one is inevitably overwhelmed by the highly theoretical models. All theories require you to disregard certain factors that play a role in the real world. As Robert Solow wrote in his original 1956 paper published in The Quarterly Journal of Economics, ‘all theory depends on assumptions which are not quite true. That is what makes it a theory’. However, that is also what makes it so difficult to visualize and conceptualize the numerous theories presented by economists.

Take the example of the Solow-Swan model. According to the Corporate Finance Institute, the Solow model is an ‘exogenous model of economic growth that analyzes changes in the level of output in an economy over time as a result of changes in the population growth rate, the savings rate, and the rate of technological progress.’ In simpler terms, it involves solving a Cobb-Douglas equation while holding certain variables constant. Clearly this economics model, as many others, is based heavily on mathematics. Thus, we can use computer algorithms to solve this system for us and see the kind of growth expected of an economy x years in the future.

Caption: The Solow Growth Model


The use of computer systems to calculate future growth is evident. Governments around the world use algorithms to perform their calculations, and make policy decisions based on those predictions. One example of this is the Boston Street Bump application. The mobile app gathers data about Boston’s streets using a smartphone’s built-in sensors as a resident drives. The City of Boston used the collected data to find and fix problems, as well as plan long-term infrastructure improvements. Similar applications can be found on a much larger scale although examples are not as readily available. Overall, the fact that governments are making their decisions based on mathematically based advice as opposed to human bias can only be a positive for the global economy.

Computer science as a tool for statistical analysis proves another positive for the global economy. One significant recent example is the use of computer systems in handling the global COVID-19 pandemic. In 2009, Richard Anderson talked about Computer Science and Global Development at the CCC Workshop on Computer Science and Global Development in Berkeley, California. His remarks have stood the test of time in our understanding of the importance of computer systems in attempting to solve global health issues. In his words, ‘Technology and information play a major role in developed world health systems’. In particular, he saw the main uses of technology in ‘assessing world health conditions’ and ‘medical logistics’, among others. We cannot know how bad the coronavirus situation would have been without the technological resources available to us today, but we can see the use of technology in almost any part of the response. From charting numbers, to evaluating the effectiveness of lockdown measures, computer scientists have been at the forefront of this crisis.

To conclude, when asked of the importance of computer science in the welfare of the global economy, one can confidently say that almost all of the economy has been or can be improved by the application of computer systems. From mapping theories into concrete graphs, to data gathering, the uses of computer science can only grow from today, and it is exciting to see where they will lead us in the future.


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