Economics makes you selfish

I was motivated to write this post by fellow Australian young economist Gabriela D’Souza

"After Taking Economics, Students Become More Selfish and Expect Worse of Others" Well that's just common sense.
— Gabriela D'Souza (@gabster0191) October 24, 2013

I disagree. Selfishness is not common sense. It all seems to have started with this article, part of the periodic publicity the sprouts up around new studies into the selfishness of economists and economics students.

There is now quite a deal of evidence that economists are ‘more selfish’ than other groups. Here is some research showing lower rates of donations by economics students. Here is research showing economics students lie more, and here is a good summary of other research. The evidence is overwhelming that economists act in ways which most people find unacceptably selfish.

To me this body of evidence reveals the massive disconnect between mainstream theory in economics, that rests on the fundamental notion that greed or selfishness is the driver of coordination in a market economy, and the reality that social cooperation rests fundamentally on trust.

I would certainly agree with Francis Amasa Walker’s 1879 interpretation of the apparent social “odor” of economists arising from their disregard of “…the customs and beliefs that tie individuals to their occupations and locations and lead them to act in ways contrary to the predictions of economic theory.”

As Frans de Waal explains “Economists are being indoctrinated into a cardboard version of human nature, which they hold true to such a degree that their own behavior has begun to resemble it… Exposure in class after class to the capitalist self-interest model apparently kills off whatever prosocial tendencies these students have to begin with. They give up trusting others, and conversely others give up trusting them. Hence the bad odor.”

Without justifying this behaviour, let me just make it clear that economic indoctrination teaches that this apparently selfish behaviour is both what everyone actually does (despite ample evidence to the contrary), and that through self interest we prosper. They have swallowed this iconic Adam Smith quote hook line and sinker.

It is not from the benevolence of the butcher, the brewer, or the baker that we expect our dinner, but from their regard to their own interest

I want to use this post to provide an example of how such a view, an economic way of thinking, can lead you astray in everyday life. I draw on ideas from my good friend Uwe Dulleck, whose expertise is credence goods.

Credence goods are those whose value or utility can never be known by the buyer due to information asymmetries. The classic examples are doctors, who can prescribe medication for a diagnosed illness which you will never know is what you are truly suffering from. Or car mechanics, who diagnose mechanical failures and sell repairs, without the customer being able to know whether such repairs were either needed or carried out.

As usual Uwe’s research centres on some important questions

Under which conditions do experts have an incentive to exploit the informational problems associated with markets for diagnosis and treatment? What types of fraud exist? What are the methods and institutions for dealing with these informational problems? Under which conditions does the market provide incentives to deter fraudulent behaviour? And what happens if all or some of those conditions are violated?

Uwe introduces a simple example of a behaviour that, by economic reasoning, is expected to reduce fraud in credence goods markets

For some of us a feasible solution might be… to ask the mechanic to put the replaced part in the back of the car and to inspect the defect of this part. 

Uwe is cautious about whether this advice is sound. As am I. But I reckon that most economists would be more than happy to take this advice based on the ‘economic intuition’.

But does the common sense of unselfish non-economists also support this behaviour? Or is this an example of how the economic model of self-interest can lead us astray? I suggest the latter. And as a peek at my conclusion, the behaviour I might advise is to buy the mechanic a six-pack of beer.

Imagine you are a mechanic. Occasionally you realise that a customer is a bit of a sucker with too much money, so you charge them a little extra for some repairs you didn’t do. Most of the time you are pretty straightforward and honest.

One day a new customer comes in. They don’t seem particularly knowledge about cars, and since this is their first visit there is nothing to suggest they will become a regular customer. You diagnose the problem with their car, which is a very typical problem in that model, and explain that the repair could involve replacing certain parts, but you won’t know till you start taking things apart. This new customer agrees to go ahead with the repair, but asks you to put the old parts in the boot when you are done. It’s an odd request.

You realise that by making this request the customer has revealed that they are less knowledgable about cars than you thought, have no trust in you, and are solely relying on seeing a bunch of parts in the boot to judge your service.

What do you do? I’ll tell you what I would do. I would grab a bunch of parts from around the workshop and stick them in the boot, then charge for parts and repairs I didn’t do.

By following the behaviour suggested by a model of selfish individuals you have inadvertently signalled you complete ignorance about cars and a complete lack of trust.

Now imagine you are the mechanic who dealt with this customer and they didn’t ask for you to put the old parts in the boot. Maybe you still fleeced them a little and replaced a couple of parts that really didn’t need replacing. When the customer comes to collect the car they bring you six-pack of beer and thank you for your good work as they are so dependent on having a reliable car.

Would you fleece them again next time?

My point is that society deals with credence goods through the establishment of trust, either through non-market signals, like memberships of reputable societies, or ongoing social relationships. That mainstream economic theory ignores the fundamental role of trust and the cooperative behaviours that results from it, leaves their advice typically unsuited for many circumstances. As experimentalists know, in repeated games many forms of cooperation can become entrenched, yet most economic theory relies on the selfish response to a one-shot game.

Until economics courses around the world move beyond indoctrinating students into “cardboard version of human nature” we will continue to have selfish economists.

Economic models are plausible stories

‘Economists do it with models’ is one of the favourite insider jokes of the econ tribe. I recently tweeted that it would be nicer if economists did it with evidence. One of Australia’s most switched-on young economists responded and I elaborated my original point.

@ZacGross Models can't do that. Caus/corr problem needs knowledge of data generation. Model=assumed knowledge. Value is in predictive power
— Cameron Murray (@Rumplestatskin) October 12, 2013

It is a very common attitude in economics. Models, their solutions and any data correlations consistent with those solutions, are believed to constitute evidence that the assumptions embedded in the model accurately capture causal relations of some real life phenomena.

But of course that’s not the case. The key value of a scientific model is in its ability to predict outcomes in new situations, but also to generate new questions and directions for research. The model is not the answer, its a tool for discovery.

I have been reading Australian sociologist Duncan Watts’ book Everything is Obvious, which reminded me of the importance of evidence and the limitations of the model-building and correlation approach that almost defines economics.

Watts, a physicist turned sociologist whose work on networks is revolutionising the discipline, is completely frank about the near impossibility of determining causality in the one-shot experiment that is real life. In the section ‘Whoever tells the best story wins’, he concludes that 

Part of the problem is also that social scientists, like everyone else, participate in social life and so feel as if they can understand why people do what they do simply by thinking about it. It is not surprising, therefore, that many social scientific explanations suffer from the same weaknesses—ex post facto assertions of rationality, representative individuals, special people, and correlation substituting for causation—that pervade our commonsense explanations as well.

No matter how much your model appeals to your intuitive reasoning, or how well it fits the data, it cannot be shown to be of scientific value unless it offers useful predictions. For the economists out there just consider that models of constrained optimisation are simply a bunch of simultaneous equations, which read equally well in reverse (as do correlations). Moreover, micro-models of this persuasion almost always overlook methods of aggregation, leaving us to guess what sort of aggregate patterns should occur in the data. 

A discussion on the use of economic models would be incomplete without referring to Milton Friedman’s views that the reality of assumptions are unrelated to the usefulness of a model.

Consider the problem of predicting the shots made by an expert billiard player. It seems not at all unreasonable that excellent predictions would be yielded by the hypothesis that the billiard player made his shots as if he knew the complicated mathematical formulas that would give the optimum directions of travel, could estimate accurately by eye the angles, etc., describing the location of the balls, could make lightning calculations from the formulas, and could then make the balls travel in the direction indicated by the formulas. Our confidence in this hypothesis is not based on the belief that billiard players, even expert ones, can or do go through the process described; it derives rather from the belief that, unless in some way or other they were capable of reaching essentially the same result, they would not in fact be expert billiard players. 

My reading of this passage is that models should be judged on their predictive powers rather than their assumptions. Yet it also implies that if more plausible assumptions are possible that yield similar predictions, perhaps these generate more plausible models. 

If I were to propose a model of expert billiard play I wouldn’t start with the laws of physics but rather with a model of learning by trial and error. This simple model not only has more plausible assumptions, but predicts ‘expertness’ in billiards correlates with practice. It is also a general model applicable to such games as lawn bowls, where Friedman’s calculating-man model would require significant modifications to account for the weighted bowls. Friedman’s model is merely an assumption about the data-generating process. It translates to “if I know the data-generation process from the point when a ball is struck, I can use that knowledge to make a useful model that includes a prior point in time”. 

To reiterate, data can’t verify, support or prove (or even contradict) the causal assumptions in a model unless we have controlled part, or all, of the data generation process (either through experiment, natural, field or otherwise). 

Meanwhile, we have a whole field of econometrics that attempts to match models to data - refining the art of assumption-hiding and promoting the illusion of causality testing. For example, Angrist and Pischke’s book Mostly Harmless Econometrics: An Empiricist’s Companion is very loose with notions of causality. They say

Two things distinguish the discipline of econometrics from the older sister field of statistics. One is the lack of shyness about causality. Causal inference has always been the name of the game in applied econometrics. Statistician Paul Holland (1986) cautions that there can be “no causation without manipulation,” a maxim that would seem to rule out causal inference from nonexperimental data. Less thoughtful observers fall back on the truism that “correlation is not causality.” Like most people who work with data for a living, we believe that correlation can sometimes provide pretty good evidence of a causal relation, even when the variable of interest is not being manipulated by the researcher of experimenter.

They go on in the quoted chapter to discuss the use of instrumental variables methods address part of the causality problem. But recall the requirements of a useful instrument 

a variable (the instrument, which we’ll call Zi), that is correlated with the causal variable of interest Si, but uncorrelated with any other determinants of the dependent variable.

If you are thinking a little here you would realise we have simply introduced a second layer of model assumptions about the true data-generation process. You may believe there is a valid reason to do this, but again, the model can’t say whether this reason is sound or not. You are simply deferring one assumption about the nature of the world to an alternative, and perhaps more plausible assumption. 

What is more interesting is that founders of the instrumental variables method where challenged in the 1920s by the problem of causal inference in a model of markets with supply and demand curves. Since price is the simultaneous solution to supply and demand in the model there was no way to differentiate relative movements of the curves. Such problems persist to this day when applying demand/supply models to market analysis. 

Models aren't quite the scientific tools economics often believe them to be. At best they offer plausible stories about a particular phenomena and provide some predictive power. The religious attachment of the economics discipline to its core models is at times quite astounding.

It is genuinely challenging for social scientists to make gains in knowledge under the uncontrollable conditions of real life, and I can only hope that the future of research involves far more experimentation, either in the lab or in the field. In the mean time I hope the profession can be far more honest about the limits to knowledge, more humble in its policy recommendations, and more open to competing views of the world whose claims often stand on equal scientific footing.

Quote of the day

I've started Truman F. Bewley's book Why Wages Don't Fall During a Recession.  The book reports Bewley's research program that involved interviewing "more 300 businesspeople, labor leaders, counselors of the unemployed and business consultants in the Northeast of the United States during the recession of the early 1990s".

Here's the quote.

From the interviews, I conclude that wage rigidity stems from a desire to encourage loyalty, a motive that superficially seems incompatible with layoffs. My findings support none of the existing economic theories of wage rigidity, except those emphasizing the impact of pay cuts on morale. Other theories fail in part because they are based on the unrealistic psychological assumptions that people's abilities do not depend on their state of mind and that they are rational in the simplistic sense that they maximize a utility that depends only on their own consumption and working conditions, not the welfare of others.

To me this type of research is an avenue too rarely employed in economic research (a notable exception being Alan Blinder's work). It suggests that the an economic toolbox that contains only rationality, and is unable to incorporate other crucial elements of human behaviour such as loyalty, is destined to poorly explain real patterns of social organisation.

Top young economists

Believing that the next generation of economists will be for more rigorous and honest about their research keeps me happy. Today I’m not so happy. 

Here’s a list I came across last year, which recently came across my screen again. It compiles the views of 8 top young economists on where economics is going. And it’s bloody frustrating.

It’s frustrating because the more I read of economic research these days, the more it seems to neatly fall into either ‘the optimal control’ game, the ‘label the residual game, or the “correlation game”. And these young guns are simply rehashing these same games.

The ‘optimal control game’ is about mathematising an idea so that it fits into the structure of the calculus of optimal control. Often it doesn’t matter how you squeeze your idea into this mould; simply pluck a term out of thin air, call it optimism, certainty, talent, or some such unmeasurable or knowable thing and stick it in an equation. You then you solve the equations, finding the optimal point, which you can compare to the solutions to the equations when you ‘shock the model’ by changing a parameter - maybe a magical bout of increased optimism.

This method tells us very little about anything, especially when the terms are often vague unmeasurable concepts, and when there is not clue about how the optimal point can be obtained in reality if you don’t actually start there. 

‘Label the residual’ is the game of writing a model that has a term which captures all the unmeasured variation from the other terms. Noah Smith described it here. 

The ‘correlation game’ is about mining data for relationships that suit your audience. 

There is no prediction game, despite this being the true test of a theory. 

There is also no reward for exploring new methods of analysis, and much criticism when it is tried. And to my genuine concern, outcomes of the unscientific games being played are taken seriously not only within the profession, but often in the political arena.

With such self-inflicted constraints the discipline struggles to adequately answer even the most basic questions it is tasked with - why are some people and countries wealthier than others, why is wealth distributed the way it is, what is money, why is there a business cycle, and more. 

So it is of interest that we examine what the insiders, the next leaders of the ‘tribes of econ’, see as the direction the field is heading. Are they ready to break free from these silly games, testing new models of cooperation and interaction, bringing dynamic mathematical tools to the economics toolbox, and gaining qualitative input from the real decision-makers in the sectors they analyse? Will they incorporate political elements, experimental regularities, and the mechanics of real institutions into their research? 

I wish I could be so optimistic. 

* I disclose that I don’t personally know any of these economists and haven’t read their work for this article (I lied, I have poked around their work a little). 

Nicholas Bloom 
Why are developing countries poor? It’s a good question and a fundamental one to economics for a long time. But poor Bloom seems to be playing a new version of the ‘label the residual game’. He says

I think the answer is complex and linked to a combination of factors around history, geography, luck, etc. I am personally working on management practices: people in developing countries are poor because wages are low, and wages are low because firms are very unproductive, and firms seem to be unproductive in large part because of bad management.

The one thing I give him credit for is that he is involved in randomised experiments, avoiding falling into the “correlation game”. But do we believe that poor countries are poor mainly because there are bit disorganised? Doesn’t that beg the question of why they are disorganised? Or is it actually about uncertainty fairy?

Ray Chetty

How can we increase the rate of economic growth and overall well-being, and how can we reduce the rate of poverty? Good questions. Not new at all, but Chetty seems not overly certain about where to look, naming just about every policy there is as a potential mechanism for growth. This seems like a very broad program of labelling the residual.

Gauti Eggertsson 

How to use monetary and fiscal policy to eliminate unemployment and control inflation? These fundamental questions of economics are still on the table after centuries of research and policy experimentation. Why is that?

We seem to know that credit creation is the real inflation driver, and we seem pretty sure it is closely related to capital investment and employment. But if questioning banking and money remains taboo in economics, I can’t see change happening fast, especially when the top young guns seem to think introducing financial frictions into models is the way forward. Back to the 'optimal control game' then.

Xavier Gabaix

How to model realistic economic agents? Now there’s a better question. But Gabaix seems very certain that some form of bounded rationality is the answer here, which is of course to say, that no one wants to drop their foundation methods, prefer to play a more sophisticated version of the ‘optimal control game'.

 
Gita Gopinath

How does one accomplish sustainable growth without large boom-bust cycles? Again, another classic problem of economics still waiting for a decent answer. Gopinath at least raises some important issues routinely ignored in economic research - global imbalances, currency wars, capital controls etc. But again, we here about “understanding the propagation of shocks across economies”, which implies we are playing the “optimal control game” once again and don’t really want to think about the mechanics of economic interactions, investment and so forth. 

Peter Leeson

What is the status of the rationality postulate?

If we view economics as an “engine” for understanding the world, the rationality postulate was that engine in nearly all of economics until quite recently. The rise of behavioral economics has challenged the usefulness and, in a more subtle but radical way, the legitimacy of the rationality engine.

A very vague and non committed response by Leeson. He suggests that beliefs about rationality drive economists views and their interpretations of events. But still, what sort of solution to rationality’s status would Leeson be happy with? 

Glen Weyl

Glen seems to think that the rise of digital information, and the outsourcing of decisions we are making to automated computer systems, is threatening to overwhelm Hayek’s argument that “free markets were necessary in order to allow the incorporation of information held by dispersed individuals into social decisions”.

Which is strange, because every economic model of markets requires that all the information is available to every decision maker before any trade occurs. AS I have said before “if prices can convey all information, then there must also exist an alternative non-price method to convey that information which governments could use for an alternative allocation system.”

Justin Wolfers 

What will economists do with more data? Well, Justin thinks economists will continue expanding their social science empire in the spirit of Gary Becker. Of course, any statistician will tell you that uncontrolled data alone can’t generate any useful scientific findings.  “Economic theory will become the tool we use to structure our investigation of the data”. I hope not. Since economic theory doesn’t usually tell us what to expect in the data at large, given the general failure to consider problems of aggregation.

This is really a sad story. The econ tribes wield so much political influence, yet have so little to offer.  These same questions could have been asked 30 years ago and would have seemed cutting edge.  So much has happened, in the world, and very little it seems in economics [1].

If I was to answer I would say the big question for economics is finding new tools that are able to incorporate dynamic elements and evolving strategies of cooperation, addressing all the aggregation problems that arise from the 'optimal control game'.  I would say that on the policy side the big questions are about the mechanics of real institutions, for example the banking system and credit creation, and of the political games that arise when new institutions are formed.  For me the future of economics includes power, rents, and conflict. 

But today I doubt we will see the future I imagine. 

[1] Many researchers will deny that little has changed.  We do know that the economics community is more empirical now than ever. But without theory, uncontrolled data can’t reveal much of scientific value.  And theory seems stuck in a time warp. 

House price signal flashes green

Back in May 2013 I called the end of Australia's slow melt in home prices.  I based this call on a number of market measures, but the crucial one was my own indicator of when to buy and sell housing.  I developed this indicator two years back as a way to capture the potential success of the investment strategy of 'buy on yields, sell on capital gains'. To reflect this strategy I use the ratio of mortgage interest to rental yields to capture the relative returns from yield versus the expected returns from capital gains.

The buy signal arrived at the beginning of 2013.  Since then prices have been rising again in most capital cities, but especially so in Sydney, which dominates the capital city housing prices indexes.  I have updated my chart to reflect this year's data, and extrapolated with predictions for December 2013.

So why is this relevant now?

Because many people who correctly called the overvaluation of Australian housing prior to the financial crisis have ignored the massive transition that occurred during the past five years. The slow melt really did let out the air from the bubble.

Now we have a situation where just about every Australian economic commentator is picking sides in discussion about whether this year's price gains are a new bubble. A former bubble denier has even switched sides.

So why if the data is so plainly showing that we are very far from a bubble, and in fact prices are relatively low right now, why isn't it obvious to everyone? I can think of just a few reasons for confusion.

1. Australian house prices are still high when compared internationally. This argument doesn't really have much merit. Our wages are also higher, and this is reflected in higher rents, which determine the returns on housing assets. 
2. Individual homes in established suburbs seem to keep increasing in price. But this ignores that the relative position of these homes increases as the city grows. Thus what was last decade's cheap fringe suburb in next decades desirable urban location. 
3. Anchoring bias.  $1,000,000 is still seen as some kind of benchmarks of obscene wealth. Yet, the repayments on this loan amount are about 20% lower now than during 2005-2008, while household incomes are up significantly. 

Today's news is that Sydney and Melbourne home prices are up over 5% for the September quarter. Yes, this is a new cycle, but we are only at the beginning and I believe it will be milder in nominal terms that previous cycles.

Thing I wish economists never said

One thing I find surprising about economics is the misuse of models as tools for reasoning.

Think about the basic micro-models. What do they say? They say all markets are in equilibrium. Okay, if that’s the approach you want to take. So how did they get there? Tatonnement? A Walrasian auction. We get there via a central planner who facilitates the equilibrium price before trade is allowed to take place! 

This lack of substance in the fundamental model of markets should beg the question of why markets are preferred over alternative forms of planning? You actually need some other theory to support the assertion that markets are the best resource allocation tools - but such a theory does not exist. 

One problem you face trying to get economists to think deeply about the real life applications of their beloved models is that you have to pretend to take these nonsense models seriously. Don’t be surprised if you get arguments to the effect that real life commercial behaviours must be wrong because the model is right. 

With that short rant over, I want to share a list of phrases and terms that I wish economists never said. These terms illustrate that vacuous nature of economic reasoning, as as you will see, they test the patience of any thoughtful observer. 

Fundamentals

Probably top of the list of things you say when you have no idea what is happening in a market - “we need to look at the fundamentals”. Okay, WTF are they? Just your pet theory? You actually need a deep understanding of the institutional history, legal and regulatory structures of markets, and a decent technical understanding to even know what the fundamentals might be. Plucking an uninformed notion of supply and demand out of thin air is not understanding fundamentals.

Second best

Most people who use this term actually don’t understand its meaning. In the equilibrium model of markets if one market is not in equilibrium, then no other market can be in equilibrium - it’s all or none. The idea of second best is that if in reality there are some markets that aren’t in equilibrium, improving overall outcomes might mean implementing policies that make other markets diverge further from their theoretical equilibrium.

Basically it means that trying to make an outcome perfect in one market might lead to counteracting effects in other market that negate any beneficial effects.

For me this term implies that the equilibrium model of markets is a poor tool for analysis of the economy. However the term implies that market model is first best, and real life is second best - how truly odd to say that.

Bad equilibrium

A assume the economy is in equilibrium. When shit goes bad, assume that the economy is in a ‘bad equilibrium’. WTF does that even mean?

Free market

Really, the ‘free market’ is just a system of highly rigid social institutions that define rights and constrains activities. One frustrating alternative to this phrase is “let the market decide”, which doesn't actually means anything of interest, because markets are merely a product of alternative regulatory constraints. The term creates a diversion from important social issues because it reinforces the assumption that market allocations automatically fulfil social goals, and any interruption of their operation will have costly social repercussions.

The NBN is a great example of this. The social aim is to provide equitable access at a consistent high standard to fibre internet through cross-subsidies between city and country users. The market alternative is that few high value city location will get access to an almost identical service, possibly at lower prices. We decide whether markets are the appropriate tool to fulfil social aims - markets don't decide anything. 

Remember, we can create institutions to produce whatever social goals we have in mind. Market outcomes are great in many circumstances, but they too have social outcome that might justify alternative forms of allocation. 

Shock

As if the regular business cycle, the subject of now centuries of economic research, somehow arises from somewhere external to the commercial activities of society.

Malinvestment

This Austrian economics terminology is both subjective and confusing at the same time. A school of thought that has its own ideas of creative destruction (implying an unpredictable future and therefore lots of poorly allocated capital) somehow expects all capital to be perfectly allocated or this system will collapse? Unfortunately this term provides an excuse to points the finger for economic woes at whatever your pet hate is at the time (usually government involvement in setting nominal interest rates).

Reform

I will let Zac Gross have a go at this one.

‘Reform’ is very sexy word. It is often deployed to cloak policy in feel good vibes and to create an aura of leadership and vision. So everyone in the policy-sphere wants to think of themselves as reformers and many a complete bastard has appropriated this lovely, but overused, title.

Land and housing are durable goods (or why demand/supply framework fails)

The ‘standard’ urban economic model is based on Alonso, Muth and Mills combined work in the 1960s to fashion a mono-centric urban space into an economic equilibrium model. For some reason this model has gained traction in the literature despite it gross misrepresentation of housing markets.

I will let the reader enjoy the comments from David Pines’ 1987 review of the urban economics literature

The static approach in the Alonso-Mills-Muth model is useless in explaining many stylized facts regarding the urban structure and its evolution through time. In the static analysis... land is continuously utilized within the city boundaries and the city boundaries are continuously extended with income and population size.
...
The reason for the failure of the static model in explaining these ‘irregularities’ is that the housing stock is assumed to be perfectly malleable, which, of course, is highly unrealistic. 

What this means is that every time there is a marginal change in any of the parameters of the model - a new person moves to the city, the rental price of the second best land use increases, or the efficiency of construction methods change - the whole city is wiped clean of housing, and the land owners and people sit down around the camp fire and decide a new optimal allocation of housing under the new conditions, then the whole stock of housing is rebuilt in an instant to that new specification. There is never a vacant site or development opportunity. 

Yes, this bizarre model was used by RBA used just a few years ago to help them understand regulatory impacts on housing supply. 

However we have known since 1989, when Bagnoli, Salant and Swierzbinski explored the durable goods monopoly problem posed earlier by Ronald Coase, that the optimal revenue raising strategy of land owners is withhold new supply of housing to future periods to maintain price levels. 

Thus, the constraint on new supply is the number of buyers willing to pay current prices or above in a given time period. If the number of buyers dries up, the optimal solution for the land owner is not to develop until such demand arises. Thus speculative booms are likely to coincide with construction booms, as investors rush into housing markets allowing developers to sell larger volumes of new stock at current prices. 

This point probably needs an example to really drive it home. Imagine you are subdividing a lot into three smaller housing lots. Your market research suggest that $300,000 per lot should be an achievable price. You put them on the market for that price. It takes 4 months to get the price you are after for one block. 

You get offered $280,000 for the second block after another 4 months. But you know that if you accept this price that you will most likely have to accept that price for the third block as well (especially given that sales prices are public records). 

The big question - the one that determines the rate of housing supply - is how long to wait for sales to maintain prices. Do you make a better return if you accept $280,000 and increase the supply now, or is it better to wait until you can get a price of $300,000 and defer new housing supply? 

The answer that Bagnoli found was that if the sellers are more patient than buyers on average (the have lower discount rates), than it is optimal to wait. It is better to sell one per year at $300,000, than 3 per year at $280,000. 

In the mainstream world of AMM’s economic model you shouldn’t have bothered waiting at all. You should have dropped the price immediately until you sold all three blocks on the first day. 

You might want introduce ‘competitive’ land developers at this point. Say my neighbour also subdivides their block into 3 smaller lots. With this less constrained supply surely now the rate of new housing construction will be higher? 

Actually it is not. 

The return maximising strategy is for each land owner to wait, and still sell just one of the now 6 potential lots each year. The land owners compete with each other for a sale, which encourages innovation in design to better appeal to buyers (to get the sale instead of their competitor), but it doesn’t bring forward supply.

Perhaps a little story from my time with a major residential property developer might help.  Remember the days when people would queue at sales offices for new subdivisions.  By sheer luck we were faced with this sort of crazy demand when we released sales of a new building at the Sunshine Coast.  Early that morning it seemed we would be able to sell the whole building within a day or two. So did we?

Of course not. We crossed all the prices out and wrote new ones 20% higher.  That certainly slowed the sales right down, and it took a couple of years to sell the whole building after that.  We simply did the profit maximising thing of withholding new supply. 

By understanding these fundamental processes at the heart of the housing supply debate it leads to very different conclusions about the types of policies that might trigger increasing housing investment - policies that focus on the discount rate of the land owners. 

This could include rent controls (decreasing future expected returns), incrementally ratcheting up land taxes (decreasing returns from not developing), announcing tighter building height restrictions in future periods (to encourage land owners to develop before the new restrictions are implemented), removing land tax exemptions for approved but undeveloped lots, and more. 

That last one is interesting.  In Queensland developers get a 40% discount on land taxes if they have subdivided a lot, but not sold it.  All this does is provide incentives to withhold land for longer, and the cost of doing so is reduced. Of course, developers will simply change the timing of the subdivision to be closer to the sales (getting approval, pre-sales, and then subdividing). But on average it must be a good move to remove this discount. 

The logic of durable goods means the extensive land banking by developers, which in Australia is currently around 19 years supply at current rates of sales, is actually a rent-seeking strategy - an attempt to buy land at a low price with one zoning, only to have it rezoned for more intensive uses before being developed.  It is not about anticipating supply needs and navigating regulations.

It means that developers stage developments in order to bring forward some construction and make the location more desirable for buyer of future stages.  Staging is about delaying development of new homes. 

Lastly, it means that reasoning of shortages or supply constraints due to land price differentials near zoning boundaries, such as by Grimes and Liang, is faulty at best. Of course differently zoned land at the same location is worth a different amount, because the value of that land is the capitalised income from its highest and best use minus the construction costs of that use. It has nothing to do with expectations of future rents or any such thing. 

I highly recommend reading my previous post in interpreting housing market indicators to fully grasp the potential misinterpretation of housing indicators from using the wrong model.

Thinking like RH Coase

I have often railed against the economic approach to social organisation problems which can be described as ‘assume first ask questions later’. There are too few good economists following more scientific methods of sound reasoning and the reliance on evidence in light of real world institutional structures.

The first approach is often called ‘thinking like an economist’. 

Ronald Coase, who passed away at age 102 earlier this week, was in many ways an outlier in the economics profession. He taught in the the University of Chicago’s Law School, rather than in economics, and was often misinterpreted by his economist peers on important and policy-relevant topics, such as what is known as the Coase Theorem. 

We can see his views in an article he wrote in 2012, at age 101, in the Harvard Business Review.

Economics as currently presented in textbooks and taught in the classroom does not have much to do with business management, and still less with entrepreneurship. The degree to which economics is isolated from the ordinary business of life is extraordinary and unfortunate. 

Coase’s scepticism is so important today, when the dominant ‘economic way of thinking’ is to apply marginalist equilibrium models to ever more obscure situations (a la Gary Becker). Unless one can be certain that the model is capturing the important characteristics of this particular market or social institution, the results of some manipulation to the model will have no relevance to the realities one is trying to understand.

One example of the original thinking that epitomised Coase’s career is his take on durable goods and the potential monopoly power of sellers in these markets. He raised these important questions a mere 41 years ago, yet almost none of the results from the research agenda that sprang up from it have entered the mainstream, and are certainly not found in most undergraduate textbooks. 

You will notice the strong links Coase makes to his descriptive model and ‘business practices’, a phrase you may never read in a whole economics degree. Nor do you much read the phrase “in the twinkling of an eye” to describe the rather arbitrary conceptual compression of time into a single period in economic models. 

One important feature of this and other work is that Coase did not make strong policy conclusions, but conditioned his results and explored reasons they may not hold in reality. 

These reasons were picked up and explored later by Mark Bagnoli and others, who found that certain critical implicit assumptions in Coase’s model were leading to its conclusions. 

Thus the assumption of a continuum of consumers-so innocuous and useful a simplification in other contexts-has proved misleading in the context of durable-goods monopoly. 

They explain that the optimal seller of an infinitely durable good (land) will exercise full market power and perfectly price-discriminate, holding back new sales to the market till future time periods to maintain price levels. They label this strategy for sellers the Pacman Strategy “since the monopolist attempts to eat his way down the demand curve.” 

This improvement and development of theory in the market for durable goods is still detached from empirical testing, but is at least an attempt to maintain links to “business practices” actually employed by land owners. 

Unfortunately, like his work on The Problem of Social Cost, Coase has been repeatedly misinterpreted by other economists. When you read about the Coase Theorem, you are probably reading about George Stigler’s interpretation of Coase’s discussions around social costs (externalities). 

As Coase explains in this interview (at the 0.50) -

It’s not about my work at all. George Stigler, who is a very nice man, wanted to pay me a compliment. So he invented the Coase Theorem, but he named it the Coase Theorem and not the Stigler Theorem.
The reason I don’t like it is that it is a proposition about a system in which transaction costs are zero. Well, that isn’t the way the system actually is. Therefore it is a theoretical proposition. I don’t like that.  

He later laments the difficultly in getting economists to understand reason during the now infamous meeting where he convince some Chicago colleagues of the merits of auctioning radio spectrum. 

All I said that the FCC should award the right to transmit on a given frequency to the person who paid the highest amount for it. To my astonishment this room, which one would of thought would be welcomed it in Chicago, was rejected by them. We went on for, I don’t know how long, and hour or something like that. At the end that time they all thought I was right.

They were very impressed by the fact the I had changed their views. But I wasn’t particularly impressed because all I was doing was stating the obvious. 

Coase relies extensively on real court cases and judgements to describe the apparent arbitrariness of property rights, when examining the judges ruling on Bryant v. Lefever he notes that 

The smoke nuisance was caused both by the man who built the wall and by the man who lit the fires. Given the fires, there would have been no smoke nuisance without the wall; given the wall, there would have been no smoke nuisance without the fires. Eliminate the wall or the fires and the smoke nuisance would disappear.On the marginal principle it is clear that both were responsible and both should be forced to include the loss of amenity due to the smoke as a cost in deciding whether to continue the activity which gives rise to the smoke. (original emphasis) 

Led by Stigler, many economists took this logic and ran with it, turning it into the Coase Theorem, while not fully comprehending that the real contribution of this article is to consider the case where bargaining is costly. 

The key point is that “In these conditions [costly bargaining] the initial delimitation of legal rights does have an effect on the efficiency with which the economic system operates”. He goes on to note that every type of social arrangement, including regulation by means of the “special kind” of “super-firm” that is government, has costs and we should seek social arrangements that minimise costs of cooperation relative to the gains. 

He explicitly says the perfect market model is irrelevant to almost all real social costs. The main message being that property rights are arbitrary constructions and we should consider the social costs and benefits of any changes from a given starting point. Its message was very relevant for legal scholars considering rights for damage claims.

On his work about the Nature of the Firm, he recently noted that firm organisation is really a sociological problem, not an economic problem. Which seems so obvious since internal firm decisions are rarely priced, nor do they take place within an environment of market-style contracts.

Rarely now do we see the type of common sense thinking that the ‘accidental economist’ Ronald Coase showed throughout his long career. In fact, I would be surprised if a Coase was beginning his career today that he would be able to break into the profession at all, given it’s obsession with formalisation of mathematical models, and disdain for verbal reason informed by real world conditions. He joked recently that he made his career stating the obvious.

Morality in economics, paid parental leave edition

Aussie econ blogs are all having a go at deciphering the debate about government sponsored paid parental leave in the lead up to the the Federal election. And they mostly miss the moral foundations of the debate, leaving us with a whole lot of economics wigs on the opinion pig.

Joshua Gans had a go at framing the debate in terms of productivity instead of fairness, but seems oblivious to the moral foundations of productivity itself and the ambiguity surrounding the aggregated macro-economic productivity outcomes from such policy decisions.

Matt Cowgill seemed to hold back in what is a rather respectful comment

You say a productivity claim is more ‘relevant’ than a fairness claim when it comes to assessing competing policies. Fine, that’s a reasonable point of view. But it is a point of view! That’s a normative, values-based, even ideological claim you’re making (that fairness is a low-order priority), yet you assert it here as if it is incontrovertible truth and that anyone emphasising fairness in policy debates is some kind of moron.

So Gans followed up with some nonsense quotes from a cartoonist that proved he is just being idiotic to impress the neoclassical econ club. Despite, as one commenter noted, his moral arguments in favour of science investment.

Rex Ringschott had a go at Club Troppo. His view is pretty clear from his final paragraph

Whatever the justification – the message to the scullery maid couldn’t be clearer. The sooner you get that Marketing degree and join the smart set the sooner your little fetus gets an even break.

Paul Frijters rehashed a post from the lead up to the 2007 election, essentially revealing how economic reasoning can be used to justify just about anything.

Over at the Guardian, Andi Fox does a good job of identifying the motivation for paid parental leave policies, and assesses the two major party’s policies against it.

The introduction of a universal scheme in this country was about helping those women and their babies catch up to the rest of us

Richard T. Green is the only economist I’ve seen actually properly frame the debate in terms of moral motivations, and the potential success of policies in addressing the moral arguments.

• The Rights Motivation Having a baby is a universal right and if people cannot afford to take the time off work that is necessary to have a baby, the state should enable them to do so.
• The Pro-Natalist Motivation We need more babies.
• The Equality Motivation The time taken off will inevitably fall partially on women (since she has to give birth) and then almost always the period of extreme infancy through the choices of the parents (conditioned by culture and economics). It is unfair that a mother cannot earn money by selling her labour in this period whilst a father can, so the state should compensate her for the unfairness of biology and cultural norms.

I'd assumed that the current round of policies were motivated by some blend of all three of Green's potential moral motivations, with a little more weighting perhaps on the Equality Motivation. Essentially the fact that women rather than men bear children is hugely detrimental for their careers. We have a moral stance that women should have equal opportunities in the workplace, so a paid parental leave policy will take some of the burden away from employers who hire more women. Of course, being financially more able to take leave from jobs without any maternity benefits also satisfies the Rights Motivation, as well as the Pro-Natalist Motivation.

Both policies will satisfy these moral motivations to some degree, and perhaps there are other moral considerations about fairness and economic equality that are required to adequately compare the two.

Given the moral ambiguity, and the unwillingness of politicians to actually put forward a coherent moral justification for their preferred policy, social scientists shouldn’t be rushing to calculate the efficiency of one policy choice over another against their own moral benchmark. They should be seeking clarification about what sort of moral position society at large supports, and assessing the degree to which alternative policies support those moral positions.

Which brings me to the much broader point. In practice economics is not some objective scientific endeavour. Anytime costs or benefits are calculated, recommendations are made, policies are assessed, there are moral judgements underlying these calculations. This is not to say that economics does have a scientific part to it. Positive analysis that seeks to understand empirical regularities of the world as it is certainly is scientific. But as soon as we apply this understanding to the world we must make a value judgement about what is desirable.

Simply ask yourself, why is productivity ‘good’ or desirable, and then keep asking why to your answer (yes, just like kids do). At some point you will hit the moral judgement that says more is better, which conflicts with the empirical literature that reveals happiness is mostly about relative status and reference groups, not about total consumption.

The moral foundations of economics are so clear to those outside the profession, yet so hidden as part of the economics indoctrination process. This leads to all sorts of nonsense debates about economics as a science.

To combat this problem not only am I writing about is, I have made a point of including in the new Australian Economics Learning Standards the requirement that economics student learn about the implicit value judgements within economic analysis.

Let’s hope the next generation of economists take their lead from Green and future policy debates are provided with much more substance from the economics profession.

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Musings...

Random things that have been on my mind

Security theatre 
...and to be honest, theatrical displays more generally in society. By this I mean doing something just to give the impression of doing it rather than for the outcome. Maybe it is something to do with David Graeber’s idea of bull$#it jobs. Or maybe it had more to do with Erving Goffman convincing me we are mere actors in our own world.

Think about this idea more generally. In any human institution we find procedures and processes, habits and social norms, that appear to be for a particular purpose, but in reality are mostly for the appearance of that purpose rather than the purpose itself.

To take one recent example, finance approvals. But of course receipts can be easily doctored by computer, and the very fact we rely on this process will decrease suspicion. If someone wanted to scam they system it would be an easy target.

Thinking like an economist
You hear this phrase a lot. I am on a committee to develop national learning standards in economics for Australian universities, and during our philosophical debates about what is economics and what comprises and economics degree, I have been confronted with the idea that “aren’t we just trying to teach students how to think like an economist?”

Unlearning Economics has a brilliant post about this concept. But I would like to add my 2 cents. 

For me thinking like an economist is about starting with the idea of a perfect market and rational choice as a starting point in any analysis and noting that anything that deviates from your newly constructed model to be a ‘market failure’. 

There are two main problems with this.

1. If you start with some kind of rational choice model, there is strictly never a justification to deviate if you accept the foundation premise. If people rationally make their own choices, and you deviate from this, the there is no guidance to how people behave - what sort of irrationality is there? 
2. If you start with a perfect market model, there is strictly no reason to prefer markets over government allocation of resources. As Robert H Nelson writes in his book Economics as Religion, from Samuelson to Chicago and Beyond, “...if transaction costs were reduced to zero, government and market would be equally (indeed perfectly) efficient.” In a more general sense, if prices can convey all information, then there must also exist an alternative non-price method to convey that information which governments could use for an alternative allocation system. 

For economists' preferred role as policy advisors this is absurd. Furthermore, you won’t find these ideas in any undergraduate economic textbook, and if you do, they are squirrelled away so that no graduates will leave with this fundamental understanding. As I have said before, economics education is far too much like indoctrination.

Take one recent example of this approach in action when discussing obesity . Here Frijters starts with the rational choice model and perfect markets for food, and struggles to find a reason to deviate from his ‘real obesity cycle theory’ of the opesity epidemic. Now I know Frijters well enough that he thinks far differently about these cultural phenomena, but the fact he feels compelled to ‘think like an economist’ and start from this point is absolutely absurd.

Another more relevant in this current economic period is blog superstar Noah Smith, who tries to wrap his mind around the notion that public deficits equal private surpluses in the national accounts. And at a deeper level, he struggles with the idea of ‘saving’ at a macro-economic level.

So what does a freshly trained economics PhD do? Thinks like an economist and undertakes a little bit of introspection based on Robinson Crusoe style analogies of the macro-economy. Such analogies are dodgy at the best of time in economics, but are totally absurd in macroeconomics and national accounting.

Libertarians
They bug me. So self-righteous. It might have been my own stupid choice to watch Sh&t$ville Express, or ever look at Catallaxy Files, but I did. Please read anything by Matt Bruenig and escape your fantasy world before it’s too late.

History, free trade and more
A big plug for Unlearning Economics who is now writing with some other fantastic people at Pieria (including John Aziz). One of my favourites on making history is here , and a beauty on ‘free‘ trade is here.

Expectations, norms and cooperation I’ve been running experiments in the lab on group cooperation - particularly on alliance formation by means of trust (which I interpret as the level of accuracy of predicting responses by others to your behaviour). I also attended a workshop in experimental and behavioural economics last week.

The main thing that struck me is that explaining deviations from rationality in almost any cooperative game relies on trust, or more specifically, accurate expectations of others. Moreover, when we repeat games we provide the opportunity to generate trust (expectations) in the lab to levels that might be reflective of reality.

The big puzzle then is how we ensure continued trust in society - a general pattern of behaviour and social norms that facilitates trade and investment and ultimate a fair distribution of the economic surplus.

I guess my thinking on this idea has moved into the realm of path dependency, and ultimately some kind of chaos. The norms we have a result of previous norms, which constantly evolve (are selected) by contemporary conditions. There are no right or wrong norms, but some are more conducive to economic investment than others, some are more conducive to equality than others.

A real puzzle for policy makers is to enhance these ‘free’ norms for social gain.

Capital - still controversial
I honestly can’t believe that the economic profession has not fully grasped the importance of the Cambridge capital debates, nor is it a prime feature of economics degrees.

One particular problem here is the way most economists still believe that the interest rate is somehow the ‘price’ of capital, while completely ignoring the capital value itself. It’s like saying that housing gets cheaper when interest rates fall, yet we use that exact policy to increase the value of capital relative to its nominal income stream.

Arbitrary
If aliens landed during a war, how would they decide which side of the war was 'in the right'.  There is never a moral right and wrong by any objective standard.

Lastly, statistics are an arbitrary human construct. Be wary.