Cosmopolitan Axis Update

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Andrew McGill writes,

40 percent of Donald Trump’s likely voters live in the community where they spent their youth, compared with just 29 percent of Hillary Clinton voters. And of the 71 percent of Clinton voters who have left their hometowns, most—almost 60 percent of that group—now live more than two hours away.

I suspect that the cosmopolitan vs. anti-cosmopolitan axis is quite important. It might be interesting to create an index of cosmopolitanism that is based solely on a person’s location history: how much geographic variation in where they have lived and where they have vacationed. My guess is that such an index would be quite predictive of some sorts of political views and even perhaps economic success.

Nature Rebounds

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From the WaPo, an article on the findings of Richard Fuchs.

Fuchs’ fascinating conclusion: Forests and settlements grew at the same time and Europe is a much greener continent today than it was 100 years ago. A closer look at different regions and countries reveals Europe’s recovery from the deforestation of past centuries.

In Specialization and Trade, I cite Jesse Ausubel’s Nature Rebounds on this and other phenomena showing that resource scarcity is a problem addressed by markets.

Why Do Firms Exist?

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Kevin Bryan writes,

A perfect theory of the firm would need to be able to explain why firms are the size they are, why they own what they do, why they are organized as they are, why they persist over time, and why interfirm incentives look the way they do. It almost certainly would need its mechanisms to work if we assumed all agents were highly, or perfectly, rational. Since patterns of asset ownership are fundamental, it needs to go well beyond the type of hand-waving that makes up many “resource” type theories. (Firms exist because they create a corporate culture! Firms exist because some firms just are better at doing X and can’t be replicated! These are outcomes, not explanations.) I believe that there are reasons why the costs of maintaining relationships – transaction costs – endogenously differ within and outside firms, and that Hart is correct is focusing our attention on how asset ownership and decision making authority affects incentives to invest, but these theories even in their most endogenous form cannot do everything we wanted a theory of the firm to accomplish. I think that somehow reputation – and hence relational contracts – must play a fundamental role, and that the nexus of conflicting incentives among agents within an organization, as described by Holmstrom, must as well. But we still lack the precise insight to clear up this muddle, and give us a straightforward explanation for why we seem to need “little Communist bureaucracies” to assist our otherwise decentralized and almost magical market system.

Read the whole post. Pointer from Tyler Cowen.

I still think that Alchian-Demsetz is the best place to start. Suppose that a bunch of computer programmers, loan officers, and bank tellers get together to start a bank. They cannot just bargain with one another on roles, responsibilities, and pay. You need a decision-maker. And that decision maker must serve a definitive owner. The owner is the “residual claimant” on the firm.

I think that this is similar to why we certain key components of infrastructure are centralized. Road systems, sanitation systems, communication wiring, and the electric grid, for example. Imagine a bunch of households get together and say, “Let’s have a road system.” They cannot just each decide to build roads in the vicinity of their homes and then bargain with one another on roles, responsibilities, and tolls to charge drivers. You need a decision-maker. etc.

I think that we know intuitively why firms exist. The challenge is to articulate that intuition.

Ed Glaeser on Science and Economics

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He writes,

Science is ultimately about method, not the degree of certainty. Economics is a science whenever economists use the scientific method, which I understand to mean Karl Popper’s process of starting with particular facts, producing refutable hypotheses and then seeing whether the data reject those hypotheses. Yet the public unfortunately takes the word science to mean “certitude,” and economists (including myself) have too often been guilty of wrapping ourselves in our scientific mantles to make ideological pronouncements seem more compelling. Messrs. Offer and Söderberg suggest that “policy requires more humility” and that economists should face “some downgrading of authority, but not all the way.” I agree with the need for humility but would point out that politicians, pundits and ideologues of all stripes regularly make statements with far less factual basis than most economists.

I think that the public has a sort of binary classification. If it’s “science,” then an expert knows more than the average Joe. If it’s not a science, then anyone’s opinion is as good as anyone else’s. I strongly favor an in-between category, called a discipline. Think of economics as a discipline, where it is possible for avid students to know more than ordinary individuals, but without the full use of the scientific method.

Insight, Proof, and Knowledge

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A commenter writes,

So in your opinion intuition is sufficient. As long as we can tell an intuitive story about something, that is as good as proving it?

I think that “proof” is too high a standard to use in economics. If our knowledge is limited to what we can prove, then we do not know anything. I think that we have frameworks of interpretation which give us insights. This is knowledge, even if it is not as definitive or reliable as knowledge in physics or chemistry.

As an example, take factor-price equalization. The insight is that the easier it is to trade across countries, the more that factor prices will tend to converge. I think that this is an important insight. It is one of what I call the Four Forces driving social and economic trends in recent decades. (The other three are assortative mating, the shift away from manufacturing toward health care and education, and the Internet.)

Paul Samuelson proved a “factor-price equalization theorem” for a special case of two factors, two goods and two countries. However, it is very difficult, if not impossible, to extend that theorem to make it realistic, including the fact that not all industries are subject to diminishing returns. In my view, Samuelson’s theorem per se offers no insight, because it is so narrow in scope. The unprovable broader insight is what is useful.

Incidentally, I also think that factor-price equalization is hard to prove statistically. Too many other things are happening at once to be able to say definitively that factor-price equalization is having an effect, say, on unskilled workers’ wages in the U.S. and China. I believe that it is having an effect, and there are studies that support my view, but it is not provable.

In order to prove something mathematically, you have to make narrow assumptions. In physics or engineering, this often works out well. When you roll a ball down an inclined plane, ignoring friction causes only a small error in the calculation.

In economics, the factors that you leave out in order to build a mathematical model tend to be more important. As a result, the requirement to express ideas in the form of mathematical models is harmful in two ways. We waste time proving false theorems and we miss out on useful insights.

The narrow assumptions lead you to prove something which is false in the real world.. For example, the central insight of the “market for lemons” proof is that a used car market cannot work. However, once we expand the assumptions to allow for warranties, dealer reputations, mechanics’ inspections, and so on, the original theorem does not hold.

Meanwhile, there are insights that are missed because they cannot be represented in an elegant mathematical way. A lot of the insights that I offer in Specialization and Trade fall in that category.

Our goal should be to acquire knowledge. The demand for proof hurts rather than helps with that process.

Two Pointed Questions Posed as Tweets

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1. From Josh Hendrickson:

I don’t get it. Everyone has a model; whether they use math/graphs/words. Why are only models w/math denigrated?

Other things equal, it is harder to understand what is going on in a math presentation. Other things equal, insisting on math restricts the sort of assumptions you can work with to those that you find tractable.

That would suggest that verbal arguments dominate mathematical arguments. I am not going to insist that this is always the case, but I think it does create a presumption in favor of verbal arguments. Yes verbal arguments can be vague. But a lot of hand-waving goes on in mathematical papers as well.

So the way I would put it is that today there is a strong presumption in favor of expressing models (or, to use my preferred term, interpretive frameworks) in mathematical terms. I would like to see the presumption go the other way.

Pete Boettke has an essay/post that is pertinent and aligns with my views. Strongly recommended.

2. From someone with the Twitter handle “representative agent’:

I’m thinking about PSST as a business cycle theory. what are its most distinctive implications?

One important implication is that unemployed workers will not be hired back into the same jobs they had before. I believe that in the 1950s, there were recessions that were primarily inventory corrections, so that after you went through a couple of quarters with automobile manufacturers and their suppliers laying off workers, those workers got recalled. Those examples run counter to PSST.

A related implication is that just “boosting demand” in general will not do much to deal with unemployment. The adjustments that are needed are specific to workers located in specific parts of geographic/industry/skill space. It predicts that just throwing money at, say, the green energy industry, will not necessarily increase employment.

Another implication is that shocks to sectors that are closely connected to other sectors (as might be shown by a network graph) will have more effects than shocks to sectors that are more isolated. That may explain why the crash of the dotcom bubble did very little, but shocks to the energy sector in the 1970s and to the banking sector at other times have had severe impacts.

Libertarianism and the Middle Class

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From a commenter.

The most important reason libertarianism is unpopular is that it has no credible agenda to benefit the middle class. Smart conservative writers have realized this, hence “Reform Conservatism”.

Many intellectuals on the right and the center-left share a perverse way of thinking about policy: they think that the poor are the legitimate recipients of government assistance, the middle class is not, and all the various middle-class-benefitting tax subsidies, entitlements, and other programs are unjustifiable bugs, rather than features, of our policy landscape. They fail to realize that a large, stable, prosperous middle class is not an inevitable or natural product of a market economy. . .

I think of the government currently as using the taxes on the rich to help pay for things like defense and non-defense purchases, while using taxes on the middle class to pay for the rest of that stuff plus transfers to the poor and to others within the middle class.

Given that perspective, what should be the balance of within-middle-class transfers vs. transfers from the middle class to the poor?

Thinking as an economist, I view the within-middle-class transfer system as imposing large deadweight losses. Primarily this is due to the need to have high taxes on work (payroll taxes), which drives down employment. There are also some deadweight losses due to rent-seeking, such as the costs imposed on the rest of us by the housing lobby, net of the gains to suppliers of services to the housing market.

If you got rid of the deadweight losses, and gave nothing additional to the poor, you would make the middle class better off. But that gain will not be politically salient.

My point is that I might agree with the commenter on the politics, but on the economics I would have to disagree. The middle class collectively would be better off without the programs that appear to benefit particular factions within it.

Grumpy About Stock Market Trading Volume

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John Cochrane writes,

We know what this huge volume of trading is about. It’s about information, not preference shocks. Information seems to need trades to percolate into prices. We just don’t understand why.

…If you ask a high speed trader about signals about liquidating dividends, they will give you a blank stare. 99% of what they do is exactly inferring information from prices — not just the level of the price but its history, the history of quotes, volumes, and other data. This is the mechanism we need to understand.

I would be so desperate as to posit a taste for trading, aka Adam Smith’s “propensity to truck and barter.” I would actually want to examine what psychological mechanisms make investment managers decide that the portfolio mix that they held one second ago is not the right mix now.

Alex vs. Tyler on Automation

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A ten-minute video. A bit of talking past one another. In short, Alex says that smart machines are making us rich, and Tyler says that only some of us are getting rich.

My favorite line was Tyler’s, talking about the challenges of adapting to technological change. He pointed out that even though the transition from agriculture to manufacturing was largely completed more than 50 years ago, to this days we still have lots of farm subsidies. I would add that by contemporary standards, the agriculture-to-manufacturing transition was gradual. We might expect even more dislocation from the transition to the New Commanding Heights.

Second Thoughts on This Year’s Economics Nobel Prize

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There is something that I find troubling about the Nobel Prize for Hart and Holmstrom, and I want to try to articulate what it is.

Think of their work as consisting of three steps.

1. Identifying some real-world complexities that affect how businesses operate. For example, output may result from both effort and luck. Output may be joint. A worker’s job description may include more than one objective.

2. Construct a mathematical optimization model that incorporates such complexities.

3. Offer insights into designing appropriate compensation systems, including when to outsource an activity altogether.

A big question is: how important is step 2?

In the eyes of the mainstream economics profession, it is extremely important. Without it, you either do not get to step 3, or your claims in step 3 lack reliability and credibility. Step 2 is why Hart and Holmstrom earned the Nobel Prize.

In my view, step 2 is unnecessary. If anything, it tends to get in the way, often creating a barrier to doing step 1 properly, because economists limit themselves to what is mathematically tractable. I think that Hart and Holmstrom sometimes (often?) made good choices in step 1, and that is what accounts for the value of where they arrived at in step 3.

In Specialization and Trade, I offer a number of asides that go from step 1 to step 3 directly (I will put some examples below the fold). In these asides, I am looking at Hart-Holmstrom issues. But I do not think in terms of mathematical optimization. Instead, I think in terms of a dynamic process of trial and error. A manager tries an approach to compensation. As long as it seems to work, it persists. Once it gets gamed too much by the employees, something happens–the manager makes changes, the manager gets fired, or the firm goes out of business.

Another point is that I believe that managers closer to the problem do a better job of solving it. Writing the problem down in mathematical terms makes it seem as though you can solve the problem remotely. It leads a David Cutler to believe that the government can design a compensation system for doctors that will correctly incent “quality health care.” It ignores what I call the “regulator’s calculation problem.”

I have seen several George Mason economists, including Tabarrok, Cowen, and Boettke, praise the Nobel for Hart and Holmstrom. I certainly think that the Nobel committee could have done worse. But in the end, I think Hart and Holmstrom represent a way of doing economics that is too constrained by the arbitrary requirement to use math, too focused on optimization relative to a given problem rather than the dynamics of trial and error, and too inclined to suggest that decisions can be made effectively by remote algorithms (and potentially by regulators who might use such algorithms) when in fact local decision-makers have important information that is not available remotely.
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