Sunday, September 29, 2013

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.

Saturday, September 28, 2013

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.

Macroeconomics Models and Force of Habit


The public rightly questioned macroeconomics and academic finance after the 2008 burst. Record housing prices and debt, both relative to income, look a plausible cause for concern and they are. Why, then no one prevented it?

The design of the markets discourages companies from being overly cautious. Banks didn’t quit inflated housing markets because these markets were still inflating. Profits reinforce participation.

The designers of the markets had got obvious signals too late to avoid consequences. And very few wanted to be the person who bursts balloons with a needle at a birthday party anyway. Governments and central banks waited for problems to come first.

Many more versions exist. But none of them can explain the bubble with lack of knowledge alone. People in finance see housing prices every day, and high ratios are quite telling, apart from answering the question, “When will this trend end?”

Designers and players played by the rules, and they certainly had selfish incentives. Academia was relatively free of these rules and incentives. Did macroeconomists have selfish incentives to find a bubble, instead?

Yes and no. You will barely find a major university economist who likes forecasting. Because sometimes the predictions come true. Thus, sometimes they don’t. Economists prefer discussing things that have happened already. And they do it unhurriedly. Operative policy interventions are unlikely in the environment where even publishing an academic paper takes up to several years.

More so, it’s difficult to find a serious academic paper that includes policy recommendations. Scholars explain things that have occurred. Policymakers can use these insights to forecast. By 2008, policymakers had models. Were these models good? They happened to have specific limitations. But even bankers had incentives to use the best models they might get to quit the housing market in time.

There’re no obstacles to adopting models with better predicting power. Then, maybe policymakers did use the best models they had? Rather, they used the most reliable equations: the ones that they understand and used for years. And DSGE models won over various alternatives, including those by heterodox economists, who offered equations that predicted the crisis.

A theory that predicts one-in-fifty-years events is not trusted because it can hardly earn a reputation of a reliable one. No, the theory itself may be predictive and great, but it lacks an empirical base to show its fitness. That makes this theory and underlying models an unlikely candidate for widespread use.

Macroeconomics is responsible for not knowing enough in the sense of biologists who don’t know how to cure cancer. There’re wrong turns and no malicious incentives. Right turns require outstanding efforts and time. Including time for gathering unique data, like the data that came from the terrible Great Recession. Bad theories still can be the best, until we have more evidences. Economics works when we recognize limitations of previous theories and try to build better ones.

Wednesday, September 25, 2013

No-knowledge Land

The previous post discussed detrimental impacts of false knowledge. Now, it’s time for the absence of knowledge.

Only a blind man can say that he sees everything. If not for vision, it’s true for knowledge. Anyone who dealt with knowledge carefully would confirm that we know almost nothing about anything. The quest never ends. The no-knowledge land is everywhere else, so it makes natural for humans recognition of our limitations in understanding the world.

And this acceptance is the first step to finding truth. We say, “Let’s assume we are not sure how this thing works and will try to find out.” This start doesn’t guarantee success. You still need to look into the thing right, or you’ll arrive to something like miracles of bloodletting. This acceptance just helps to start looking.

What’s so interesting about it? First, recognition of own limitations is a painful procedure, and this first step rarely occurs at all. Second, fierce enemies of this blank state are both truthful knowledge and false knowledge.

If I know how to make a wheel, I don’t feel much need to reinvent it. For that, I’m unlikely to invent the car wheel or caterpillar. That’s the place to restate the observation saying that scientific theories disappear as their authors die. Authors and supporters are committed way too much to their old theories than to anything what comes next. When you learn about things working one way, you become less perceptive to alternatives. One famous research says that scientists get Nobel Prizes for research made mainly in their thirties. Clearly, many factors matter here, but one is that mature researchers are less likely to risk for new business.

True knowledge has its own dead ends. That just means there must always be some space for alternative ways. Pluralism in the sense of Paul Feyerabend: let those scientists abandon the rules, since their most important strength is in inventing new rules. Rigid scientific methodology prevents new discoveries. And prolific researchers violated rules. They developed their fields in terms of methodology and criteria of truth. Physics and economics, for instance, are still very different in delivering concepts about the world, despite their rapid convergence over the last 50 years.

As for false knowledge, Cartesian doubts are up to this. You question everything to bring things back onto no-knowledge land. You even question things that came after rigorous research. It’s not a method. It’s a principle.

Science is kind of famous for dealing with no-knowledge lands. The issue is actually more pronounced in business and governance, where doubts are a sign of weakness and recognizing knowledge limits is something to get fired for. A boss can’t tell about her doubts because that may harm her subordinates’ confidence. And a subordinate can’t do either, because his competence would be questioned.

The areas are institutionally protected from doubts. Business and governments proceed in a Darwinist fashion, hoping that confident actors with mistaken beliefs disappear. But they don’t, while all the major decisions affecting humans still happen here. And it’s a great challenge for social sciences to understand how humans make decisions and how to improve these decisions.

Tuesday, September 24, 2013

Knowledge, Witches, and the Church

There are three kinds of knowledge: true knowledge, no knowledge, and false knowledge.

False knowledge is the most dangerous of the three. It gives assurance about things, and we start acting on extremes. Ancient doctors were sure that bloodletting was good for patients. But it was the opposite. It required two thousand years of mistakes to start questioning the practice, and another one hundred years for the doubts to eliminate the practice. Habits die hard, bad habits kill.

These bad habits have their own categories: unintentional delusions and fallacies by design. The latter again deserves more attention. Take one example. The invention of witchcraft by the Church was a tool for eliminating political opponents. Witches appeared pagan competitors, mostly unchecked by official religious authorities, who, in turn, had close connections with political leaders. Joan of Arc happened to be just the most famous victim of this political tool.

Meanwhile, in the medieval society witches served as doctors, more liberal than Church officials. One of the most brutal attacks on their practices occurred in the 15th century. After the Black Death had killed about half of European population, feudal lords sought ways of increasing their rents. Since the lords had their own fallacies about economic wealth coming from the quantity of workers around, they needed to increase birth rates.

And here, as historian John Riddle suggests, witches became an obstacle. You see, they were pro-choice and helped women with abortions and contraception. Feudal leaders couldn’t like the idea of families making independent decisions about the number of children. Still, you can’t attack the entire population that wants fewer children. What you can do is to destroy professionals who knew how to control births.

Witches did remain miles away from what are now clinical trials. But the Church did worse: it declared their practices illegal saying that some of them actually work. Clergy couldn’t just say that witches had skills people needed and elites didn’t want. Clergy had to invent the image of a dangerous woman with spells and black magic. That was false knowledge about demons on one side and angels on another: neither existed, but the illusion kept living thanks to the strong political support.

Carefully designed fallacies bear hundreds of years of attacks and still persist. They are protected because they are important. And overcoming these fallacies is decisive for human survival. It’s easy to see what false knowledge persists now and how it threatens humans. Say, one relates to the average temperature on the globe. It’s far from being clear how to dissolve this false knowledge.

First Post

“The good life is one inspired by love and guided by knowledge.”
— Bertrand Russell, What I Believe