The Source of Our Sources

Not today’s news, but The New York Times and other major newspapers have a great influence on public policy. Key government documents, like budgets and congressional hearings, mention “the new york times” about 38,000 times (see Government Printing Office website with Google Search), while an economist from the top 10—who studies his topic for decades but doesn’t write for the public regularly—gets mentioned in the same documents just 10 times. So, even if economists know something (like a big secret about inflation), it’s up to the media to deliver this knowledge.

Where do the media source their information from, in turn? The Times explains:

Source
Mentions in NY Times articles, Source

If someone doesn’t see the black line for the references to researchers, it’s because the line had been drawn over the zero axis.

(That was a post of envy, of course.)

Nontrivial Economics

In his biography Surely, You’re Joking, Mr. Feynman, Richard Feynman recalled a story about mathematicians at Princeton challenging him with counterintuitive possibilities. One example they gave him was an orange:

It often went like this: They would explain to me, “You’ve got an orange, OK? Now you cut the orange into a finite number of pieces, put it back together, and it’s as big as the sun. True or false?”

And that was true for the special orange that we can keep cutting indefinitely. A mathematical orange. After some time spent listening such examples, Feynman just responded to each such case with “It’s trivial!”—parodying his interlocutors.

It happens in economics, too. Mathematician Stanislaw Ulam famously asked Paul Samuelson to name an economic idea that is true and nontrivial. Samuelson took a long pause and suggested Ricardian comparative advantage as an example: a country with absolute technical advantage in producing any goods still benefits from trading with less efficient nations. Like the US buying vegetables from Liberia, in which agriculture still contributes more than a half to the GDP.

The definition of “nontrivial” is itself a trivial question: you can define it as you like and get the desired property. But generally, “nontrivial” is something that goes against popular opinion. Mathematicians hold an advantage here because in math you define your own rules, and other people remain too far from this world to make educated guesses. Economists pursue a different task: finding nontrivial results in the everyday world. If the results don’t go against popular opinion, then what’s the point?

And these nontrivial results happen to be more numerous than Ricardo’s logic exercise in the 19th century. Each field offers its own examples:

Growth theory. Geography is a long-standing favorite in explaining the income gap between countries. The impact of bad weather on work is so natural, and who needs more? Still, the geographical hypothesis is far more advanced than, say, the assertion that countries are poor because of natural intellectual limitations of their populations.

In contrast to both these stories, the institutional hypothesis suggests endogenous causes of growth. It warns against the China hysteria: the opinion that this model is viable for economically advanced societies, and we soon may see the demise of democracy. Third, it suggests that direct financial aid to developing countries not necessarily improves these countries’ growth prospects.

Macroeconomics. Anything that we find out about relations between inflation and employment, or the absence of thereof, is non-trivial. What about the efficiency of fiscal policy in economic downturns? Important arguments here cannot be discovered with just common sense.

Labor economics. In the well-known 2000 study of New Jersey and Pennsylvania fast food restaurants, David Card and Alan Krueger discovered that the minimum wage increases employment. The result was so counterintuitive for economists themselves that David Card had to clarify their position to explain political attacks that followed.

The wage example shows that most interesting findings basically inform us about our gaps in understanding. We had a too-simple model of labor markets: here is one reason to look deeper. Unlike mathematics, economics has little a priori knowledge. Whether the first derivative of a labor demand function is greater or less than zero depends on our ability to discover this function’s parameters. When we discover these parameters, they necessarily surprise us compared to our previous experience. Non-triviality in science is just new facts uncovering old mistakes.

Unethical Economics

Introduction to The Oxford Handbook of International Relations edited by Reus-Smit and Snidal (2008):

Instead of a proper engagement between normative and scientific positions, we typically see either mutual neglect or mutual critiques that fall on deaf ears. The result is a divide, with “science” on one side and “normative” on the other. This separation severely impairs the ability of international relations to speak to practical concerns. On the one hand, the unwillingness of “scientists” to tackle ethical and seemingly unscientific problems means it often has little to say on the important problems of the day; on the other hand, insofar as normative international relations is insufficiently well grounded in empirical knowledge, it is not competent to say what we should do in specific cases.

Christian Reus-Smit and Duncan Snidal’s concerns about normative and positive studies in international relations remind those in economics.

In economics, ethical issues about allocation of resources appear mostly in heterodox works or lobbying. Mainstream economics resolved the issue by referring to preferences, Pareto efficiency, equilibrium, and descriptive research in general. It does have inquiries in fairness, but fairness there is a factor affecting decisions, not recommendations about “fair” distributions. For instance, have a look at Matthew Rabin’s paper on incorporation of fairness in game theory or Ernst Fehr’s theory of fairness, competition, and cooperation. They are like, “Yes, we study economics ignoring a significant factor, and let’s move closer to a more realistic description of reality.”

Economists leave decision making to decision makers. That’s the division of labor. Economists do research, people and their selected representatives make decisions, which are, after all, about their own lives. No philosopher kings involved.

Why scholars in international relations concern about themselves making decisions? Maybe the field is much closer to practical policymaking than economics is to business and government.

Economics separated from policymaking not so long ago. While Malthus and both Mills still were advisers on practical matters, Alfred Marshall is already academic economics. Well, Adam Smith was in the ivory tower as well and didn’t hesitate to make recommendations, but the tower itself was different by that time. The century that followed after Smith had transformed the approach to economics.

Gaps happen to be not in normative judgments, but in positive understanding. Say, governments can redistribute income, but generally the consequences are too foggy. We barely understand the tradeoffs. Taxes distort incentives, but inequality leads to unstable economy. We would like to increase social welfare, but only started to understand behavioral foundations of utility functions. We can subsidize education for some, but why does tuition increase?

Taxes, social welfare, and subsidies are ethical questions because we know too little about their impact. And our beliefs about “right” things not necessary lead to the outcomes we would like to have. Economics tries to connect our desires, sometimes ethical, to actions necessary to achieve that desires. Again, this definition of economics is an invention of the 19th century.

Scientists can make normative judgments as humans, not as scientists. Science itself is about discovering facts and explaining them. If some scientific field is struggling with normative judgments, it’s either not scientific or does someone else’s job.

Translating Economics

The last post was about things we know that we don’t know. This one is about things we don’t know that we know.

Macroeconomics is a difficult subject. Not only the aggregate economy is extremely complex, but the data is lacking. You may ask, “What about 148,000 time series from FRED?” 148,000 series help a little. Well, physicists have 10^80 atoms in the universe and still struggle with some unified field theory. You need right data.

Unfortunately, macro needs bad events to collect evidences that help prevent bad events in the future. Macroeconomists are not so evil to knock down the world financial system for research purposes. They have to wait. After a crisis had come, they get their part of criticism for bad economics and then collect the new facts about the economy.

But economists from other fields have more alternatives. They conduct experiments, use natural experiments to isolate certain factors, and reach facts no one previously cared about. Results attract much less attention than macro does. Unlike macro, which concerns everyone in a pretty straightforward way, broader economics studies events that have an indirect impact on people. Public demand for these studies is lower, studies rarer get into news, and politicians worry only about a small fraction of respective topics.

The public is mostly unfamiliar with academic research outside macro. Actually, economists are unfamiliar with it either once they get outside their home field. But it’s more important to establish a intergroup connection from researchers to users, rather than among distant researchers themselves.

Mostly political discussions about economic aggregates in public show that intergroup connections are possible when both sides have personal interest in understanding the subject. The most popular economic blogs either discuss politics, which cause fury and is always in demand, or tell about practical matters.

The most promising way of delivering knowledge is its framing into either emotional or practical matters. It’s easier now because research itself became more specific. Take Al Roth’s school matching or Esther Duflo’s works on education in India. Fifty years ago it was Gale–Shapely matching algorithm and Becker’s or Schultz’s returns on education. Too abstract to be accepted outside academia. Once the matching algorithm got its specific application in schools and hospitals, it was accepted. As for education, the World Bank now has to pay more attention to the efficiency of its programs.

But any economics still requires translation into the language of public interests. Communication problems leave too much knowledge unnoticed. And if you look around, you notice thousands of things that would benefit from this missing knowledge.