**It’s More Than Math**

By Devin Gowdy

I had my first midterm in my Econ 2 class last Friday and one of the questions on the test involved calculating the structural unemployment that would arise from a minimum wage. The math was pretty simple. We were given two linear equations, and calculating the difference between the supply of labor and the demand for workers at the minimum wage was fairly straightforward. But, I do not believe that basic math can accurately capture something as complex as the minimum wage.

I first encountered the relationship between the minimum wage and unemployment in high school when in my 11th-grade English class, I wrote an 18-page essay on why we should not adopt a national minimum wage of 15 dollars an hour. At the core of my essay was the labor market supply and demand graph — the same one that appeared on my Econ 2 midterm and the same one that appears in every introductory economics textbook. I was captivated by its mathematical simplicity. The math removed the subjectivity from the minimum wage debate, and in an attempt to preserve that apparent objectivity, I omitted the contributions of other more subjective disciplines from my essay.

I am telling you this story because my 11th-grade English paper captures the consequences of using math in economics courses like Econ 1 and Econ 2. Math inadvertently paints a picture of economics as an objective physical science and that couldn’t be further from the truth.

For starters, economics is a social science. The use of math gives economics a level of objectivity that elevates it above the other social sciences. In introductory economics courses, that translates to excluding more subjective disciplines like philosophy, psychology, sociology, politics, and history. These other disciplines are not just fun side pursuits for econ majors — they are foundational to a full and complete understanding of economics. The use of math in introductory economics has led to the marginalization of these disciplines, which means that economics students are beginning their studies with an incomplete foundation.

This wouldn’t be a problem if economics was an objective science. But it’s not. When modeling economic relationships, economists necessarily make assumptions to simplify the real world. This is especially problematic in introductory economics courses where the simplicity of the math requires a host of assumptions — most of which go unacknowledged. If given the opportunity, we might choose to rejectthese assumptions.

The depiction of the minimum wage in economics textbooks perfectly illustrates these consequences. Through the labor market supply and demand graph, most introductory economics textbooks say with absolute certainty that raising the minimum wage will lead to greater unemployment, leading economics students to conclude that we should not raise the minimum wage. They don’t mention that the minimum wage debate is highly controversial or that there is no consensus among economists. They don’t acknowledge the myriad of assumptions it took to construct the supply and demand model nor do they include the contributions of the neighboring disciplines, all of which would have been beneficial to understanding the true complexity of the minimum wage debate.

I don’t doubt that there is a place for math in economics more broadly; indeed, it is absolutely necessary, but so too is philosophy, psychology, history, sociology, and politics. While we don’t necessarily need to stop using math in courses like Econ 1 and Econ 2, we should at least acknowledge the impact that an emphasis on math has on our understanding of economics.

*Devin feels physically nauseous when he sees math in his ECON 2 class, and it’s not because he struggles with basic math.*

**The Data Science double major has thoughts too**

By Sury Dongre

6 dollars is a lot for a coffee. For some people. For me, it’s a Saturday morning. But why are some people willing to pay more? What does it say about society? How do we represent this? And most importantly, how does this affect the pricing of a Cajé mocha?

At first glance, it’s easy. I like coffee more, so I’m willing to pay more for it. More questions arise, though. Why do I like Cajé as opposed to Kozy? Is it the beans? The ambiance? The corps of baristas that seem to have been hired from IMG models? Ultimately, questions in this vein (i.e, economics) seems to always lead to more questions. Economics is ultimately the study of choice, and asking questions about basic human behavior that would usually have basic answers.

The question then arises: How should we answer these questions? My answer: math. Some qualifications: math has a lot more use in macroeconomic analysis as opposed to modeling individual choice, and math in lower division economics classes at UC Santa Barbara isn’t taught well. However, quantitative analysis is central to understanding the world around us and provides the happy middle ground of a definitive answer within a more nuanced context.

Let’s start with the lower division economics courses at UCSB. I take issue with Econ 1 and 2 specifically (not because AP credits don’t count. Definitely not.) because of the very basic mathematical models they introduce to model a very complex situation. The math in 1 and 2 is designed to be done in about 2 minutes on a multiple choice exam, which is an incredibly poor way of modeling entire markets or even someone’s demand for coffee. Everything in 1 and 2 is straight lines at 45 degree angles, and it can be demoralizing to think that your major consists of basic algebra and disappointed frat bros for the next 4 years.

However, 1 and 2 aren’t accurate representations of real economic research, much less real people. None of your professors are using the first-order conditions or basic supply and demand graphs in their research papers. It’s important to recognize Econ 1 and 2 for what they are: the basics. The intros. Take those classes with a grain of salt and know that upper divisions will be infinitely more complex and interesting. Classes like “Using Big Data to Solve Societal Problems” use more complex mathematical analyses to directly support qualitative solutions to social inequities and externalities caused by the flawed system we operate under. Being an economics major isn’t the same as being a math major. But it does mean being able to use math to support more theoretical perspectives of the world. Economics is a social science, and implies having to balance a lot of differing ideals (including the gap between statistics and theory) to create impact and innovate in the field.

As for the larger role of mathematical modeling in economics: I’d like to point to this article as a great example. Raj Chetty (the accurately named Beyonce of economics) used a dataset from facebook with 81 billion data points to understand why social mobility varies across the country. This is the type of mathematical model I support in economics, especially with the accessibility of increased computing power. With datasets that large and the capacity to process them and draw out these insights, economic research has entered a new mode: understanding the economic system that the country currently operates on and understanding how we can work within those systems to guarantee the best outcomes for everybody. Basic algebra is not economics. But neither is contained, philosophical, impotent ivory-tower debating. Mathematics brings economics to the real world, and enables it to make real change.

*Sury Dongre thinks that even the most complex statistical model is probably easier to understand than whatever goes on in Econ 1. *

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