I originally wrote this for a class I took a couple weeks ago. Here’s an interesting blog post by Noah Smith he published a couple days after I wrote this piece that connects well with this post.
I entered college as a biology major. Unfortunately, I was bored to tears in a biology class I took during my first semester. During the same time, I was in an introduction to macroeconomics class. While I fell asleep listening to biologists explain their worm experiments, I was fascinated by economics and looked forward to every class. After that semester, I switched majors from biology to economics. When I told my parents I had made this switch, I could not help but notice their disappointment. Both of them had majored in engineering, and my brother studied physics; when I switched majors I became the non-science black sheep. However, after taking many economics classes since coming to college, I now see it as a science on the same level as physics, chemistry, or mathematics.
Providing an exact definition of science is difficult, but for the most part, science is the discipline of organizing ideas and theories about the universe using observations and repeatable tests. This can be as simple as mixing water with oil to make claims about their densities, or as complex as smashing atoms together in an electromagnetic particle accelerator to make claims about the nature of atomic particles. Both experiments organize ideas (albeit polar opposites in complexity) through observations, and both can be tested again (given a large enough budget) in a laboratory.
Given that science is broad and encompasses many fields, there are distinctions used to categorize it. One way to divide scientific fields is to group these fields into “hard sciences” and “soft sciences.” Math, physics, and chemistry are typically most often thought of as “hard sciences,” because they use a high degree of objectivity and rely heavily on the scientific method of testing hypotheses through observations and mathematical models. Psychology, political science, and sociology are generally regarded as “soft sciences,” because these fields make claims that may be difficult to replicate in a laboratory and rely less on empirical data. There is no definitive way to rate different fields based on “hardness,” but a 2000 paper published in Social Studies of Science suggests that the “harder” sciences use more graphs in their publications. That is, “hard” sciences are mostly grounded in data and observations.
Where does economics fit into the picture? Is it a “hard” science, such as physics or chemistry, or a “soft” science like sociology or psychology? Economics is the study of how people choose to allocate limited resources. The study of an individual’s choice of allocating his resources is referred to as microeconomics, while the study of how nations and larger systems choose to allocate their resources is referred to as macroeconomics. Because of its reliance on mathematical models, and the credible claims it can make about the world, economics should be considered more “hard” than it is “soft.”
One way economics is more of a “hard” science is that it analyzes data from the world’s economy to produce ideas and theories about the economy. Just as an oceanologist studies the movement of ocean currents or a chemist studies chemical equilibrium during an experiment, economists use real data to study movements and equilibria in an economy. Once economists analyze the economic data available to them, they construct mathematical models to explain a certain phenomenon. Indeed, formulating these mathematical models requires many years of education, and to be able to understand them requires the same degree of education. Though the complexity of high-level economics does not add to its “hardness,” the construction of these models does. “Hard” sciences requires the use of empirical observations to explain systems, and economists are doing just that by organizing ideas about the economy through observed economic data.
There is a clear contrast between the process used in economics and the methods used in “soft” sciences. “Soft” sciences use theories about human actions to make claims about society. While “soft” sciences might use experiments to arrive to their conclusions, the scientists who conduct these studies are ultimately influenced by how they think humans are influenced by their nature—a vague notion that cannot be objectively measured. Economics throws away these complications by assuming all humans act rationally and all markets compete perfectly. These are strong assumptions to make, but they remove subjectivity from the equation which contributes to economics’ “hardness.”
A common criticism of economics is that the claims economists make are difficult to reproduce in the real world. Economists do not rule the world or any single nation, so they lack a laboratory to perform their tests. This lack of despotism leads some to argue that economists cannot test their models in a fair or accurate way—that economic theory is simply theory that is only important to academia. Nobel Prize winning economist Robert Lucas rebuts this notion in his 1988 Commencement Address at the University of Chicago. Lucas compares economists to story tellers who tell stories about smaller economies and then apply those stories to larger economies. In his speech, Lucas tells a story about a carnival and ticket sales to point out the connection between changes in the money supply and economic depressions in the United States. Through his story, Lucas’s speech suggests that when it is applied, economic theory can make strong claims about the world’s economy. Just as physicists must use a large, manmade hadron collider to tell stories about how atoms work, economists must often rely on smaller economies to tell stories about larger scale economic systems.
Another major tenet of the “hard” sciences is that they contain a higher degree of accuracy and objectivity than the “soft” sciences. Taking this into consideration, economics better resembles a “hard” science because the claims economists make are widely accepted by the outside world. For example, economists such as Nobel Prize recipient Paul Krugman are regularly featured in the op-ed section of the New York Times, and economists often report for finance and business publications, such as Noah Smith of Bloomberg View. The United States Federal Government is another employer of economists, which hires hundreds of them to research and recommend monetary and fiscal policies the government should support. Similarly, Wall Street hires thousands of economists, who are highly prized for their mathematical expertise and ability to study complex systems to make market predictions. Clearly, economists’ knowledge is highly valued in both the public and private sector. This value comes from economists’ ability to make scientific-like claims about the global economy.
Another criticism economics regularly receives is its inability to predict economic crises. Indeed, seven years after the 2008 financial crisis, many non-economists resent those in the field who failed to see the bumpy road ahead. In a blog post from April, economist Noah Smith sums up these grumbles against macroeconomics as: failing to predict the crash, acting too confidently before the crash, failing to focus enough on finance, and being too complacent in their models. However, just as it is unreasonable to blame a seismologist for not anticipating an earthquake, it is unreasonable to blame an economist for not anticipating a financial crisis that is totally out of his control. As Bob Lucas points out in a 2009 article he wrote for The Economist:
One thing we are not going to have, now or ever, is a set of models that forecasts sudden falls in the value of financial assets, like the declines that followed the failure of Lehman Brothers in September. This is nothing new. It has been known for more than 40 years and is one of the main implications of Eugene Fama’s “efficient-market hypothesis” (EMH), which states that the price of a financial asset reflects all relevant, generally available information. If an economist had a formula that could reliably forecast crises a week in advance, say, then that formula would become part of generally available information and prices would fall a week earlier.
This section from Lucas defends economists from criticism that they should—but always fail to—predict financial crises.
Ironically, the financial crisis of 2008 helps define economics as a “hard” science. Just as the fields of physics or chemistry change as new, unforeseen developments arise, economic theory constantly changes as a result of observed data from the economy. Using the lessons of the 2008 financial crisis, economists have developed new theories and models, and have gained new knowledge that will help guide their future prescriptions for the economy.
Last February, I went to my economics professor’s office hours to ask him a question about an assigned problem set. When I was in his office, I noticed his mathematics undergraduate degree on the wall. When I asked him why he decided to pursue economics and not math, he told me that while in math there were infinite problems to solve, in economics, there are more defined questions to study and answer through using economic analysis. By using mathematical models and observing data to make credible inferences on the economy, economics better resembles the “hard” sciences than it does the “soft” sciences. As the field of economics continues to develop and grow in the 21st century, I know my parents will be happy I chose to study economics.