Economics Really Is an Exact Science

 

In Colombia, we’ve grown used to trusting the diploma. Someone graduates in economics and we assume they understand the economy. But anyone who has worked closely with economists, at universities, at banks, in government, knows that isn’t always true. There is an enormous difference between memorizing concepts and understanding a system, and that difference, I suspect, explains a good share of the bad economic decisions we make as a country.

Economics is not a list of definitions you can learn by heart. It is a complex system: millions of people, companies, and governments making decisions every day, whose interactions produce outcomes that no one fully planned. Understanding inflation isn’t just knowing the definition of “a sustained increase in prices”; it means understanding how money moves, how credit responds, how people react to expectations, and how all of that feeds into everything else. It is a web of causes and effects that twists back on itself, and truly understanding it, not just naming it, is much harder than the average curriculum suggests.

Here is the first problem: many economics departments in Colombia treat mathematics as an accessory, not as the heart of the discipline. Some professors, and a whole school of thought, maintain that economics is not an exact science and that demanding mathematical rigor means importing a foreign standard, borrowed from physics. Under that logic, understanding the economic world would be more a matter of intuition, rhetoric, or ideological stance than of evidence.

I think that idea is deeply mistaken, and it’s worth explaining why.

The first argument is a more philosophical one. Mathematics is not an arbitrary human invention that we impose on reality; it is, to a large extent, the language in which reality is written. The laws that govern how bodies move, how heat spreads, or how a population grows are expressed precisely in equations, not in paragraphs. There is no reason to think social systems are the exception. If mathematics describes how the physical universe behaves, it is also the natural tool for describing how a system made of interconnected human decisions behaves. Rejecting mathematics is not taking a different stance on economics: it is giving up the tool that lets us see it clearly.

The second argument is more recent, which is why it often goes unnoticed. For much of the twentieth century, it made sense to doubt that economics could be analyzed with the rigor of an exact science: data was scarce and the ability to process it was limited. That world no longer exists. Today, nearly two hundred countries generate, year after year, data on inflation, employment, trade, investment, and public policy decisions, and we have the computing power to cross-reference that information, find patterns, and test theories in ways that were simply impossible thirty years ago. The excuse that economics is “too messy” to analyze rigorously no longer holds. What’s missing is not the data or the tools, but the willingness to use them.

The third argument is more uncomfortable, but it has to be said. A good part of the insistence that economics “doesn’t need” advanced mathematics comes from people who, to be honest, never felt comfortable with it. It’s easier to declare a tool unnecessary than to admit you haven’t mastered it. Not every economist who questions mathematical formalism does so for that reason, but when the argument is repeated so often in classrooms, it’s worth asking how much of it reflects a genuine intellectual position and how much is simply comfort disguised as principle.

One more clarification: saying that economics needs mathematics is not saying it should become physics. That comparison, so common, is really a distraction. The underlying argument comes not from physics but from general systems theory: everything in the universe, the physical, the biological, the social, is, in some sense, a system of interacting parts that produces a joint result. Economics is a particular case of that broader logic, just like the climate, an ant colony, or the human brain. What looks chaotic when you examine an isolated part often reveals a clear pattern once you look at the whole system. That is perhaps the scarcest and most valuable skill an economist can have: the ability to think in whole systems, not in loose fragments.

And that, in my view, is the real underlying problem. It’s not just that mathematics is lacking: many students move through classrooms accumulating information, formulas, definitions, graphs, without ever building a real understanding of how the system works as a whole. They graduate knowing how to name the pieces, but not necessarily how to explain how those pieces move together. And when that happens, a gap remains, one that, all too often, gets filled with ideology instead of evidence.

That gap is not harmless. When economic training is not anchored in data and systems thinking, it opens the door to policy decisions made out of ideological conviction rather than evidence. And that hands politicians ammunition: it lets them sell populist decisions, with immediate benefits but enormous long-term costs, backed by economists who, instead of testing those proposals against the available evidence, endorse them because they fit their view of the world. We see the result again and again across the region: decisions that sound good in the short run and, years later, leave a bill much higher than the one promised.

The good news is that economics has, in fact, an advantage few social sciences possess. Every country in the world is, in a sense, an ongoing experiment. Every policy decision, a tax reform, an interest rate change, a trade opening, generates data that can be compared across countries and over decades. Few disciplines have access to a body of evidence so broad and so alive. If economics took advantage of that with the same rigor demanded in physics or biology, it could well be one of the sciences most capable of producing reliable knowledge about human behavior at scale.

That is why I believe we need a complete reorientation in how we train economists in Colombia, and probably across much of Latin America. It isn’t about adding one more calculus class to the curriculum, but about changing the very goal of the training: to stop producing people who repeat theories and narratives, and start training people capable of analyzing complex systems with mathematical rigor and with the data that today, for the first time in history, is available in abundance.

A good economist, at bottom, should resemble less someone who defends a position and more someone solving an enormous puzzle: someone who understands that the economic system is just one particular expression of something more general, the way the parts of any complex system interact, and who has the mathematical tools and the data to read that system clearly, rather than imposing a borrowed narrative on it. That, I believe, is the economist’s true responsibility: not to say how the world ought to behave, but to understand, as precisely as possible, how it actually behaves.

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