Saturday, 31 October 2009

Falsifiable economics

So, let's say I claim that all swans are white.

Prove it, you insist. Well, say I, here's a white swan - here's another one - and here's another. Therefore it's quite likely that the rest of them are white too.

You probably wouldn't consider that to be much of a proof. Quite rightly, you'd insist on the scientific standard. Make clear what a counterexample would look like (a black swan) and show that a reasonably comprehensive effort to find black swans has failed. Second best might be a detailed biological analysis of swan DNA and physiology to convince you that they simply don't have the capability to produce black pigment - but even that is not very reliable. After all, by definition I am only analysing the white ones.

So why in economics do we accept the equivalent of white swans as "evidence" for macroeconomic theories?

If a Keynesian wants me to believe her theory about government borrowing resolving the paradox of thrift, she should tell me what evidence would disprove her story. For instance, if we could see two different countries, one with an substantial change in government borrowing which did not bring about the expected change in aggregate demand.

If an Austrian wants me to believe his story about credit booms, business cycles and reallocation of resources, he should similarly explain what evidence he would accept as a counterexample.

Don't worry about who's going to go out and collect the data - I'll send the Keynesian to disprove the Austrian theory and vice versa. It's called "gains from trade".

Mostly in economics we see people invent stories and then come up with reasons why their story could be true. It's time for economists to be willing to explain how they could be wrong, and let us go look for evidence that they are.

Friday, 30 October 2009

Why can finance be hacked?

There are lots of reasons why finance is different from normal markets, but I am particularly interested in why it is difficult to model economically.

It's not fundamentally because "finance markets deal with money, which is essential to all other markets". On this basis, energy markets would have the same problems, as no other markets can operate without energy; equally, computer hardware or telephones.

Instead, it's because finance has a special characteristic in information-theoretic terms: it creates contracts which operate on other contracts, which in turn operate on the first contract again.

This is what George Soros calls reflexivity - but I will use another term: self-referential.

Self-referential systems behave very differently to "normal" systems. Douglas Hofstadter has made a whole career out of analysing them. In his famous book Gödel, Escher, Bach he compares the self-referential patterns in Escher's art and Bach's music to Gödel's Incompleteness Theorem and the philosophical revolution it brought to the study of mathematical systems.

From this analysis he draws some deep insights into how cognition works: his idea is that the essence of human intelligence is our ability to think about ourselves, refer to ourselves in language, and mix up multiple levels of reference.

Finance is just like that. A contract can relate to the outcome of another contract; options can be designed over other options; and a payment for services can be made on the basis of another payment for services (when your bank charges you for transferring money?) And if a bank makes a loan, increasing the money supply, it affects the value of money across the economy, changing the probability of a recession and thus influences the loan's own chance of being repaid.

This is essentially different from linear or equilibrium systems, where the effect of any change is relatively simple and predictable. If I decide to buy zinc, the demand for zinc is higher than otherwise expected, and its price rises. If I buy a bit less zinc, the price rises a bit less. And those prices are expressed in money, which is a completely different thing than zinc, and doesn't affect it significantly.

Equilibrium systems tend to return back to their previous state after a change. Linear systems change in proportion to their inputs. Self-referential systems can do completely different things.

Which is not to say that we can't work with them or predict how they behave. We simply need different tools to do it.

The traditional economic tools of maximisation, equilibrium analysis, supply and demand functions: all have some applicability to finance, but they must be supplemented with additional tools which can handle self-reference.

Fortunately humans have come across this challenge before. There are three major fields which all contain self-referential structures, and each of them can shed light on how to deal with financial modelling.

Mathematics. Gödel, and others before him such as Bertrand Russell, struggled with the concept of self-reference in concepts such as sets which contain themselves and mathematical statements that make assertions about their own proofs. There is a rich body of work explaining what we can and cannot know for sure about mathematics, and we know of constraints which we can place on mathematical systems to eliminate some of the unmanageable scenarios which emerge.

Language. This statement is false. Or in its original, 3000-year-old form, Cretans are always liars - or at least so said Epimenides, a Cretan. Language is a very fluid medium with few strict rules, but the addition of statements which talk about themselves makes it even more unpredictable. The linguistic equivalent of Glass-Steagall is to ban simple statements like This statement is false; but this victory only holds until someone discovers that an economics professor can still say "The economics profession right now is useless" and thereby impugn the logic of their own claim.

Software. Unlike mathematicians and linguists, software developers actually have to make something work in the real world. So they've been obliged to find ways to build and control self-referential systems without destroying the world. Software is self-referential because software code resides in memory, and also has the ability to change whatever is in memory.

This problem can lead to software bugs which make your programs crash: but it has also bedevilled software security experts for decades. The classic mechanism by which viruses (or trojan horses) work is to overrun the normal memory limits within which a program is designed, and to put new program instructions into memory where they shouldn't be. This is how your computer can get infected and start sending out Vi@gr@ adverts.

People try to solve this problem in many ways. Some are restrictive (all those Windows security popups asking your permission to change the network settings); others are really annoying (Illegal instruction - this program is shutting down); some are clever, such as automated cloud-based malware detection; others crude and simplistic, like those 5 megabyte security updates that your antivirus software downloads every night. Sometimes a privileged person has permission to do things that others don't; but sometimes the goal is to protect people from their own mistakes as well as from the malicious actions of others.

Just like financial regulations, as it happens. In fact, the finance market has nearly all the characteristics of an insecure, unstable, hackable multi-user computer.

So who should we get to design new financial institutions, structures and the regulatory environment? Perhaps it would be worth letting some programmers loose on things. Start by reading this book if you're interested in a readable introduction to the subject.

Thursday, 29 October 2009

The economics zeitgeist, 25 October 2009

This week's word cloud from the economics blogs. I generate a new cloud every Sunday, so please subscribe using the RSS or email box on the right and you'll get a message every week with the new cloud.

I summarise around four hundred blogs through their RSS feeds. Thanks in particular to the Palgrave Econolog who have an excellent database of economics blogs; I have also added a number of blogs that are not on their list. Contact me if you'd like to make sure yours is included too.

I use Wordle to generate the image, the ROME RSS reader to download the RSS feeds, and Java software from Inon to process the data.

You can also see the Java version in the Wordle gallery.

If anyone would like a copy of the underlying data used to generate these clouds, or if you would like to see a version with consistent colour and typeface to make week-to-week comparison easier, please get in touch.

Wednesday, 28 October 2009

Behavioural economics for marketers

I had a very interesting conversation yesterday with the head of a branding agency who shares our vision of developing a scientific foundation for the practice of marketing. My view (and that of Rory Sutherland of the IPA and Ogilvy) is that behavioural economics can provide this foundation. But as a discipline, behavioural economics is not yet mature. It has a hole at its centre which needs filled before we can genuinely say that there is a science of marketing. Filling this hole is the goal of my research and this article outlines how it can be done.

The key step in the development of behavioural economics is to close the gap in our understanding between neuromarketing and phenomenological descriptions of behaviour.

The practice and underlying science of marketing can be represented as a multi-layered set of disciplines, from highest to lowest level:
  • The craft and folk wisdom of sales and marketing
  • Experimental phenomena from behavioural economics
  • ???
  • Neuromarketing and the application of brain science
  • Biology of human needs
  • Organic chemistry and physics
This gap is where cognitive models provide the missing link in both explaining and predicting human behaviour.

Beneath this level, neuroscientists are discovering the specific physiology of the brain and how it responds to certain stimuli. There is a lot of useful work on how the limbic and motor systems control certain responses below our conscious awareness.

Above this level, there are experimental results which show statistical patterns of behaviour: experiments for example on self-control, hyperbolic discounting, valuation heuristics and relative price judgments. However, these experiments generally come with no underlying model to explain the results. The behaviour of the subjects can be shown to be inconsistent with the conventional economic model of rational preference, but to date there has been no alternative model.

Neuroscience gives some indication of the basic underlying mechanisms, but no neurological theory can explain hyperbolic discounting or give any insight into the actual discount rates that people apply in different circumstances. Neither can neurology explain why people who are primed with words or phrases about age and frailty walk more slowly than those who are cued with words about vibrancy and youth. Nor can it explain how people judge value by relative price instead of absolute numbers.

The reason for this is that we are intelligent, thinking beings; we are not driven purely by dumb emotions and drives; our brains are powerful tools for translating those emotions into actions via knowledge, and for learning new kinds of actions over time. To understand these processes, and close that gap in the understanding of marketing, cognitive models are required.

Cognitive models provide insight into how people think, learn and know; show us how people make decisions; clarify what motivates people and what they value; and shows how much of one value they are willing to trade off for another, and under what circumstances.

How do we build a cognitive model?

A cognitive model needs to have a plausible basis in the neurological capabilities of the brain and simultaneously to explain the observed behaviour of real people.

Neurological constraints provide some limitations on the processing capacity of our cognition, and on the degree of attention and focus we have. Observational constraints show that we are capable of powerful high-level thought and decision making, while highlighting specific consistent biases or flaws in our reasoning, which shed light on the mechanisms that provide that capacity for thought.

No model gives a perfect prediction of behaviour - that is in the nature of a model. But can we build a model which is sophisticated enough to successfully predict a high proportion of experimental results, while still being simple enough for us to use in practice?

The way to do this is to make two simplifying steps. First, move one level back from the experimental phenomena to understand their proximate causes - that is, the direct reasons that people take the actions they do in experiments. These reasons or motivations can be modelled, and their relative strengths can be estimated either via lab experiments, or by placing individuals in specific simulated decision contexts and recording their answers.

Second, move up from the neurological level to a scale that is more understandable on a human level: the scale of individual concepts and facts. The relationships between these contexts and facts can be determined for a given individual partly via the language they use, and partly by examining their problem solving mechanisms (by experiment or by posing puzzles).

Once we are dealing at the level of motivations and concepts, the relationships between them start to become clearer and it is possible to derive functions relating the two. Individual behaviour can then be represented as a stimulus-response cycle; and we can understand how to influence those responses by analysing the communication processe with information theory and the adoption of new ideas via the psychology of learning.

A mathematical interlude: feel free to skip this

I will briefly outline here a mathematical model of the stimulus-response process. This is not the only possible model, but it has proven to be a highly practical and manageable way to represent and understand cognition and behaviour.

First we develop a value model whose purpose is to represent a relevant subset of human motivations. The scope of this model depends on the application: if you are a law firm the relevant motivations are to do with reducing risk and winning court cases, while the relevant motivations for a branding agency are the desire for innovation, growth and a positive social or self-image.

The internal structure of this model is a hierarchy of motivations which ultimately are based on underlying neurological processes in the brain, pain-avoidance, pleasure-seeking and the satisfaction of physical and material needs. Because the brain is a highly malleable construct and very efficient at developing heuristics, people are not generally conscious of pain-avoidance and pleasure-seeking in their day to day decisions, but use proxy motivations. Maslow's hierarchy of needs is a good example of how to understand the way we build up multiple levels of motivation which become more abstract and gain a broader scope at higher levels.

In an economic context, one of the key motivations is money (with a critically important distinction between the individual's own money and the money they control on behalf of an organisation). Our goal as marketers, ultimately, is to get people to trade off one value against another: specifically, money in return for some other value that we can satisfy with our product or service.

Having constructed this network of motivations, we transform it into a multi-dimensional vector space, whose base is a set of vectors v = v1, v2, ..., vn, each representing a single motivation or value.

At any given time the individual is considered to be at a single point within this space, and we define a function u = u(v1, v2, ..., vn) representing their utility at that point.

[In fact, utility is not an invariant function over time but has a path dependence. However, for purposes of this model it is easier to represent it as a non-path-dependent function but incorporate a time variable instead: u = u(v1, v2, ..., vn, t). This does not affect the current analysis. Similarly, we can use a model with no concept of utility but where individuals attempt to independently maximise each value. This is appropriate for simple computational models, but in all biological contexts agents ultimately face tradeoffs between multiple goals. A separately differentiable utility function is a good way to model these tradeoffs, but it is possible, equivalently, to specify a matrix of "exchange rates": x(m, n) = δvm/δvn.]

An individual's goal is to seek maximum utility in this space by achieving the highest possible value of u. Classical economics assumes that they have visibility of the entire space and how it will change over time, and can choose the path which provides highest total utility, integrated from the current time to infinity. This is where cognitive/behavioural economics diverges from the classical model in three ways.

First, individuals cannot move at will within this space. There are only a limited number of actions available to them: these represent the economic transactions or other decisions that are open to them at a given time. Each of these represents a tradeoff: a reduction in value on one dimension and an increase in value on another (the tradeoff is present in all non-trivial situations, because we assume that if people can make a gain with no corresponding tradeoff they will immediately do so until that opportunity is exhausted. Decisions of economic interest take place once the "free lunches" have already been eaten).

Second, individuals only have local visibility over this utility function. They do not have certainty about the utility that will be available to them at some distant point. People do have a reasonable idea of how their utility will increase or decrease if they make a change in certain values (such as "amount of food consumed", "money in wallet" or "prestige of brand image"). Any long-term goal can only be evaluated by extrapolating its effect from local changes in these values. This is one reason why we often take actions which make us happy in the short term, but from which we suffer in the long run.

Third, we have limited attention. We cannot simultaneously calculate the effect of changing dozens of variables all at the same time. So in general it is rarely practical for us to make tradeoffs between three or more values; mostly we will only focus on two at a time. It seems that the brain has an internal mechanism for shifting our focus from one point to another periodically (the boredom reflex) so that we are encouraged to regularly re-evaluate the tradeoffs that are available. When we shift focus, it is likely that we have learned which tradeoffs are particularly attractive to us: for a tradeoff (x<->y), that's where the value of δU/δx is substantially greater than δU/δy. Importantly, our focus and our awareness of which actions are available is strongly impacted by sensory input - this has major importance for the advertising industry.

The coefficients of these tradeoffs (the derivatives of the utility function) are dependent on several factors, some of which marketers can influence:
  • where the individual is within the value space
  • the individual's cognitive state and the magnitude of the different weights in their motivation hierarchy
  • which components of the motivation hierarchy they are currently present to

So, what should marketers do?

On the basis of this model marketers need to take the following five types of action to encourage buyers to purchase their products or services or to increase the prices they can achieve:
  1. create additional actions (available tradeoffs) in the buyer's value space
  2. prime the buyer so that your actions are cognitively present
  3. influence the "exchange rates" between different value dimensions - for instance to persuade consumers that the exchange rate between safety and money is high
  4. build "bridges" between different parts of the value space so that people can be persuaded to undergo short-term pain (e.g. spending money) in return for long-term benefit (e.g. a comfortable retirement)
  5. in the longer term, inventing and communicating new values which can add another dimension to the value space, and ensuring that their brand is the individual's key association with that value

And behavioural economics? It fits into this model very well. Each of the key experimental phenomena of behavioural economics is an expression of one of those actions:
  • priming (2)
  • anchoring effects on pricing (2) and (3)
  • branding in general (5)
  • interest-free credit and other hyperbolic discounting phenomena (4)
  • memory effects and availability (1)
Applying the insights from this theory can increase both the quantity of sales you make and the prices you can achieve.

All that remains to complete your sales and marketing plan is to model the values, measure the exchange rates and invent the right techniques and actions to apply this theory. I'll give some examples of those processes over the coming weeks.

Tuesday, 27 October 2009

Social media for small and big businesses

The idea of businesses using social media for marketing has bubbled up to the BBC, which I guess means it is now mainstream.

The article talks about some relatively low-key applications: market research, networking with potential suppliers and local promotions. Not sure about this quote:
Companies that have jumped on the Twitter and Facebook bandwagon are reporting a surge in customers while others struggle.
But of course social networking - just like traditional networking - is a good channel for businesses to talk to customers, create relationships and get introduced to new prospects via their existing clients - always a good way to build a quick reservoir of trust.

The question for the economy as a whole - and especially for larger companies - is whether and how social marketing can be used for a mass market. One of the commercial benefits of large companies - and equivalently, the economic benefits of a liquid market - is that they reduce the transaction costs associated with small-scale relationship building and exchange.

Social media, potentially, have a role in enabling this. Chris Dillow asks whether the Trafigura viral marketing campaign of last week vindicates Marx by showing that technology has created new social relations.

He queries whether it has actually changed "power relations" in the sense that Marx intended, but I think that misses the point. Even if the formal political structure is broadly the same as twenty years ago, huge changes in the way society transfers and consumes information have transformed our world's real power dynamics. Political power is only one aspect of how influence is exerted on people, and the boundaries of politicians' ability to affect behaviour are certainly changing as technology evolves. More importantly, other types of power - commercial, social, educational, media, family, religious, community and employment-related influences - have all been thoroughly disrupted by the Internet, mobile technology and ongoing changes in the media landscape.

Now (as you'll see from the last paragraph) it's very easy to be glibly journalistic about "revolutions". To understand this properly, we have to do some hard modelling work. These models will be closely linked with the kind of effects Henry Farrell talks about here.

But in the meantime, it doesn't seem too far a leap to suggest that social media will enable an important new channel for mass marketing; but only if we develop technology to actively mediate or catalyse the social effects [plug: my own company's attempt is here]. Individual conversations between entrepreneur and customer, which is the model promoted by Thomas Power (no relation to Marxist Power Relations), can never scale up enough.

Monday, 26 October 2009

Justifying insider trading

Greg Mankiw apparently thinks insider trading is a good least, he links approvingly to this defence of it by Donald Boudreaux in the Wall Street Journal [An analysis of Greg Mankiw's clever "link deniability" strategy is coming in another posting].

An intriguing notion. It is broadly based on the idea that information is going to be hidden by companies anyway, so we may as well hope that insiders accidentally give it away by buying and selling stock.

Doesn't that seem rather defeatist? If public companies aren't providing the right information to investors, so the investors can't make accurate decisions, shouldn't we find a mechanism to make them do so?

Insider trading, because it enriches executives at the expense (at least in the short term) of other investors, destroys the trust which is a key variable in how well capital markets work. There is always an agency problem inherent in one person managing an asset on behalf of another. Trust is an important way in which this is overcome.

A narrow libertarian view of markets might imply that investors are purchasing management services from executives at arms length, and that it doesn't really matter whether they trust each other, because both parties are applying rational criteria of service quality and price. But a moment's reflection about the nature of organisations, work relationships, leadership and motivation makes it clear that intangible trust factors are really important.

And I believe that - in our present cultural context at least - if insiders are allowed to use privileged information at the expense of investors, trust will be destroyed.

An alternative proposal, then: insiders are only allowed to buy and sell shares by announcing a month in advance (or a week, perhaps) that they are planning to do so. This provides the same signalling benefits as Boudreaux's proposal but gives investors a chance to evaluate why the insider wants to transact, and decide whether to follow them in.

Some kind of protection would be needed against price movements and faking: the executive should enter into a conditional future contract, with the company or a broker, to buy or sell their shares provided the market price is within a certain range. The fixed range protects the executive against price movements; the future contract protects against people announcing their intention and then backing out after investors have acted.

This would give investors a chance to ask why the transaction is happening. If anything appears to be suspect, large investors will have the leverage (and resources) to conduct a proper investigation with a good chance of finding out whatever information they don't have.

As a nice bonus, this rule solves the other problem Boudreaux highlights: that executives can currently benefit from inside information by choosing not to buy or sell shares. At any given time when the insider has not announced a sale one month ahead, they have implicitly announced that they will not sell in the next month. Thus making clear to the market whatever it is that that signal implies.

Sunday, 25 October 2009

Links: A few thoughtful pieces

I'd like to write a full article on each of today's links, but I may never get around to it. In the meantime, you may have your own conclusions to draw:
  1. Tim Haab has a good defence of economics as a mathematical discipline. While the particular maths we have to use will evolve, as we incorporate more psychology, theory of organisations and financial institutions into the orthodoxy, economics will and should still use lots of mathematics - because that's the only way we can build and apply successful models.
  2. In this review of Create Your Own Economy, Henry Farrell starts to build an argument that the internal mental orderings which add value to our own lives, can also add value to other people's. My own review (not out yet) touches on the converse idea - can ready-made (or at least part-cooked) mental orderings be provided to us as a service?
  3. A mini-Easterlin paradox from Stephanie Flanders: as a country, are we more interested in comparative measures of GDP (against other countries) than the absolute figures? After all, we can never know for certain whether our 2% growth or 0.7% contraction is better or worse than we could otherwise have done; but we certainly know whether the Germans have beaten us.
  4. From Scientific American, does economics violate the laws of physics? Answer: no, and the reason why can be found in Henry Farrell's review above, and Rory Sutherland's TED video to which I linked on Friday.

Saturday, 24 October 2009

Should rich people throw away their litter?

One of the problems we face in economics is that our theoretical solutions do not always work in the real world, because the key assumptions of liquid markets, no transaction costs etc often do not hold. In these cases, we have to spend time working out second-best solutions. But even the second-best may still hold surprises.

Here's an example. Does it make sense for Bill Gates go to the trouble of disposing of his own litter?

Let's say Bill drinks a can of Coke. As Andy Warhol said (h/t Russell Howard):
...the President drinks Coke, Liz Taylor drinks Coke, and just think, you can drink Coke too. A Coke is a Coke and no amount of money can get you a better Coke than the one the bum on the corner is drinking.
So Bill drinks Coke just like the rest of us. He finishes it and needs to get rid of the can somehow. But, as it happens, he's spending the afternoon in Sixty Acre Park near Redmond, and the nearest trashcan is half a mile away (amusingly, the description starts with "Sixty Acre Park is a 93 acre park...").

Of course, the civilised thing to do is walk to the bin and throw it away. But walking there and back will take about 15 minutes (depending on how fit Bill is). Despite his recent unemployment, Bill's annual income is still $175 million in dividends, and up to $5 billion in stock appreciation, depending on how the market goes. So that 15 minutes walk will cost him between $5,000 and $142,000.

(This calculation partly inspired by Brad Templeton, who generated the famous 'what size of bill should Bill Gates not pick up' index a few years back).

Clearly it would make more sense for Bill to pay another park user $100 to throw the can away for him. Surely almost any tourist would be happy to accept $100 for 15 minutes work (not to mention the story you'd be able to tell for the rest of your life). If not, then would $1000 do it? It's still easily worth Bill's while.

But this is where illiquid markets cause a problem. First, there might not be any other tourists around at that precise moment. Second, the cost of negotiating the price will impose its own overhead on the transaction. Third, Bill surely wouldn't be so crass as to actually offer money to someone to pick up his trash. That would just be rude. In fact, politeness only allows us to pay poor people to clean up after us via a psychological distancing mechanism called "local government".

So Bill may end up just carting his own can to the bin. But he does have an alternative, and here's where the second-best solution comes in. He could just toss it on the ground.

Surely not, you cry! What a terrible thing to do. Bill isn't like that! He is a humanitarian, after all. He's fixing malaria!

But as an intelligent utilitarian, maybe he should do exactly that. If he can earn an extra $5,000 in the 15 minutes, he'll pay around $2,000 in taxes which will easily cover the cost of a municipal employee picking up the can. If we use the $142,000 figure, taxed at capital gains rate instead of income rates, he'll pay $21,000 which is even better.

Whatever is left over after paying the cleanup cost can go to healing sick children, paying for cancer research, reducing crime, increasing Social Security, fighting the Taliban, or even educating new economics researchers - whatever you think is a worthy use of public resources. And whatever's left after taxes he'll spend in the private sector, providing someone else with a wage.

So if it applies to Bill Gates, does it apply to you? How much - or little - do you have to earn before it becomes better for society for you to toss your trash on the ground instead of putting it in the garbage yourself?

Well, let's work it out.

First, assume that street sweepers are paid around 60% of the average national wage (US figures appear to be around $32,000, in the UK £11,100 - which is about half the average UK wage but perhaps more than half in Birmingham). It isn't a highly skilled job, and I suspect due to contracting out of council services it's not as unionised as it would have been in the past.

Next, assume it takes the street cleaner twice as long to get rid of your rubbish as it would take you. There are many factors involved here: asymmetric information (you know where the rubbish is - it's in your hand - while the street cleaner has to look around and find it); the balance between the fixed costs of a street sweeper patrolling the roads and the marginal cost for them to walk to your can and pick it up; the extra efficiency of a specialised employee, with their own portable wheelie bin, compared to you having to go to the fixed trashcan, and the reduced frequency of emptying the bins on the street.

Finally, assume a marginal tax rate of around 33% (this is a conservative estimate in the UK and US, when you include income, payroll, state and local taxes - it's certainly higher at higher incomes).

For ease of demonstration we'll assume it takes you one minute to throw away a can (though this figure disappears in the calculation so it does not affect the end result).

Then, for each can you throw on the ground, you impose a cost on society of 2 minutes at 60% of average wage, or about 23p. In return, you are earning 1 minute of extra income and paying tax of 33% of that. If you earn more than 68p a minute, you are contributing more to society by throwing the can on the ground than by putting it in a bin. This works out to about £41/hour or £82,000 a year.

So anyone in the UK earning more than £82,000 should toss their rubbish onto the pavement and use the time saved to make some extra money. In the US, the figure is around $115,000.

If you tweak the assumptions a bit, so that street sweepers are just as efficient at cleaning up as you (in the City of London where there are almost no bins on the street, this may well be true) and assume a marginal tax rate of 40% (which is definitely true in the City of London) then you only need to earn 1.5 times the average national wage to justify tossing your cans. And don't forget, as soon as you earn anything above this threshold, you aren't just paying the cost of collecting your rubbish - you are also contributing to all the other functions of the public good!

So I call on all high earners across the world to do their bit for society: dump your waste on the street and let someone else sweep it up.

The least useful statistic ever?

From Freakonomics...
Economists estimate that the costs of reducing carbon emissions are likely to be upwards of $1 trillion per year....These cost estimates are obviously highly speculative, but the true cost of reducing carbon emissions is likely to be within two orders of magnitude of this number.
Only two orders of magnitude?

In other words, the costs will be somewhere between $10 billion and $100 trillion per year.

That is, the same as the difference between a hundred and a million dollars; or dividing the cost out between everyone on the planet, choose between a $1.50 newspaper or a $15,000 car; or if the developed world pays for it all, you can either spend $10 on a glass of wine or give up your entire $100,000 annual salary.

So: to prevent global warming by reducing carbon emissions, every human being will either have to work for an extra 15 minutes once a year, or give up their entire income FOREVER.

Well, I'm glad we've got the scale of the issue clear...time to get down to work fixing it.

Friday, 23 October 2009

Behavioural economics for advertising

Rory Sutherland of the IPA is leading a push for behavioural economics in the advertising business.

This video is an excellent summary of how ad agencies should turn "human understanding into business value for clients".

Here is his TED video about intangible goods, which has plenty in common with the best bits of Tyler Cowen - he even mentions Tyler and Marginal Revolution in the talk.

And here is the event on Wednesday that I missed - thanks (but no thanks!) to Mark Earls for mentioning it after the fact. I guess I should have checked his blog before Wednesday too...

I agree entirely with the message that behavioural economics is a critically important discipline for marketers to master. It has the potential to finally bring science and rigour to the practice of marketing, which has for many years been a craft - a well-practised craft, but still one with no basis in testable, predictive theory.

Thursday, 22 October 2009

The Roger Farmer paradox

Roger Farmer likes unorthodox monetary policy.

At the turn of the year he proposed that central banks should buy and sell equities, targeting a stock price index as a method of controlling asset prices. My own version of this proposal was slightly different.

Now he's suggesting that they use quantitative easing as a monetary tool, independently of interest rates. The idea is that even once central banks have started to raise interest rates to control inflation, they should separately adjust their balance sheet, changing the composition of the stock of savings in the economy, to combat unemployment. If QE is a useful tool now to help raise economic output, why shouldn't it be useful later, when inflation is taking off?

Now admittedly I'm not a trained monetary economist, but I have a bad feeling about this idea. Aren't interest rate targets and QE both different manifestations of the central bank's ability to control the money supply?

Crudely speaking: if money is tight, interest rates are high. If money is loose, interest rates are low [Update: see comment from Rob and my response below]. If interest rates are at zero, money can be loosened through QE instead. The reason the central bank can influence interest rates throughout the economy is that it can create or absorb unlimited money until the market rate rises or falls to meet its target.

So let's say we are back in the realm of normal monetary policy, with interest rates at (say) 3%. Does the composition of the central bank's balance sheet matter? If the Fed holds lower-quality commercial loans instead of Treasuries, will that make a difference to the economy? I can't see that it will.

Let's say they sell $1 trillion of government bonds and buy $1 trillion of commercial loans. This affects the overall return on savings in the private economy, as the average return on the purchased commercial loans was higher than that on the government bonds which have replaced them. This lowered return on savings will slightly increase the demand for investment.

But a lower return on savings is exactly equivalent to a lower interest rate - which will lead to higher inflation than the bank's target. So to achieve its inflation target it will have to increase interest rates by reducing the money supply, and this will sterilise the change in balance sheet composition.

Farmer says:
A high fed funds rate is bad for the employment outlook because it depresses the values of corporate bonds and public and private equity. Investors move out of real assets that create jobs and into barren federal securities.
But a high fed funds rate depresses the value of Treasury bonds too! Investors don't move into "barren federal securities" because of collapsing corporate bond prices. Instead, companies issue fewer bonds because the coupons they'd have to pay makes it more expensive to borrow for investment, and some projects are no longer worth doing. Governments are less likely to be able to reduce deficits in response to expensive financing, so they will probably keep issuing bonds. And to be able to increase interest rates, the central bank has reduced the money supply; which means there simply is less money to invest, and a higher proportion of this smaller pool goes to financing public deficits.

QE, in other words, is just another tool for adjusting interest rates. It should be effective only when the normal way of changing market interest rates is ineffective, because the central bank's policy rate is zero. And even then, monetary transmission mechanisms seem to make it less effective than standard theory would predict.

It happens that I agree with Roger Farmer on several things: his approval of Tom Sargent's quote "it takes a model to beat a model", his emphasis on psychology in macroeconomics (though I haven't read his books) and that Akerlof and Shiller's Animal Spirits is a bad book. But I think he's got this one wrong.

The end of the Akerlof and Shiller review highlights his focus on the 1970s stagflation episode and the breakdown of the Phillips curve tradeoff between unemployment and inflation.

No doubt this explains his appetite to find independent tools to control inflation and unemployment; but MV = PY is a single equation, and we'll need more finely distinguished mechanisms than pure monetary tools to independently manage P and Y. There is the potential for central banks to influence investment behaviour, but I don't think buying corporate bonds - unless there is a clear market failure, which will probably not be the case with policy rates at 3% - will be an effective one.

The abstract of Farmer's new book, Expectation, Employment and Prices, says:
Central bankers throughout the world are talking now about developing a second instrument of monetary policy in addition to controlling the interest rate. This book directly addresses this issue and offers new creative monetary policy proposals and suggestions for the design of new financial institutions for the 21st century.
I'll be interested to read whether there are any more subtle - or indeed logically possible - proposals than this QE idea.

Tuesday, 20 October 2009

The economics zeitgeist, 18 October 2009

This week's word cloud from the economics blogs. I generate a new cloud every Sunday, so please subscribe using the RSS or email box on the right and you'll get a message every week with the new cloud.

I summarise around four hundred blogs through their RSS feeds. Thanks in particular to the Palgrave Econolog who have an excellent database of economics blogs; I have also added a number of blogs that are not on their list. Contact me if you'd like to make sure yours is included too.

I use Wordle to generate the image, the ROME RSS reader to download the RSS feeds, and Java software from Inon to process the data.

You can also see the Java version in the Wordle gallery.

If anyone would like a copy of the underlying data used to generate these clouds, or if you would like to see a version with consistent colour and typeface to make week-to-week comparison easier, please get in touch.

Saturday, 17 October 2009

Who should get swine flu vaccines?

David Karp comments on the Hamilton city government's policy for swine flu vaccines (also here):
I think part of the problem trying to figure out how to allocate vaccines is figuring out what our policy goal is. Is it to cut down on externalities? Giving preference for emergency workers and child care workers makes sense in that regard, because most people in society benefit from these people being healthy enough to work during a pandemic. Is it about fairness? If so, is it really fair that some people are considered more worthy of a vaccine than other people simply because of their age, how they caught the flu, or the type of work they do? Is it about using the vaccine available to cure as many people as possible? In that case, the fifth criteria -- giving the vaccine to those most likely to survive a particular strain -- seems like the best to use. Or should the criteria be economic efficiency: those who have the highest maximum willingness to pay for the vaccine get it?
Actually I suspect the health authority has another criterion in mind: to vaccinate people who are likely to be highly-connected nodes in the swine flu network, i.e. those who may pass it to others. The economic interpretation is to consider the vaccine in this case not as a consumption but an investment good, and direct it to where it makes the highest return.
My guess is that the "textbook" economic answer to this problem would be to hold an auction for the vaccine, which would mean people who want the vaccine most (at least in terms of their willingness to pay) would get it. But it's an unappealing option because it means that rich people have an upper hand over poor people...
He suggests a lottery instead, then allowing recipients to sell the vaccine if they way. But in classical economic terms, that has all the same disadvantages as an auction - and, instead of the money going to society as a whole, it goes privately to a small number of people randomly selected - many of whom will be quite well-off.

But - though I'm not sure if David was thinking this way - the psychology of the auction approach is probably weaker, and the lottery may be more appealing to the non-economist public.

First, the auction more obviously reduces the transaction to a financial one; because the sale is conducted in public instead of as a series of private transactions, it makes it obvious that it is going with the money, and this weakens legitimacy among the public.

Second, the money in an auction is perceived as going to "the government" instead of to real people. Presumably the government will (to a first approximation) use the money for the benefit of citizens, but the impersonality of the state weakens people's belief in that outcome.

Third, because it will actually be economically efficient. While this seems like it would be a good thing, many people will feel that efficiency makes the process somehow soulless and cynical. The fact that, under a lottery, some middle-class people would end up holding onto their vaccine instead of selling it (endowment effect, anyone?) and thus some lucky person would be saved when they aren't willing to pay for it, may make the required compromises more acceptable in the public's eyes. Often, a bit less rationality is what people relate to.

Some would say these considerations are not the job of an economist. But it simply depends on where we draw the boundaries around our models. If our goal is to achieve maximum public welfare, then understanding psychology and how it affects the public's utility is a requirement. If our goal is to create stable institutions which result in a successful society (economically and otherwise) then legitimacy is a valid attribute to explore.

Economists have done a reasonable job in recent decades of convincing some parts of the public that considerations of economic efficiency are good criteria on which to set policy. But in certain fields - public health being one - sentiment has a big influence. And instead of pretending to live in a rational world, we are better off accepting that factor and modelling it.

Friday, 16 October 2009

Predictably unfashionable

Copyblogger last week told me to cross-dress my blog - to write an article from the point of view of the opposite sex, or someone of a different age.

So I have been wondering "What would missmarketcrash write?" And it became clear that the ideal article would blend a cynical attitude to the financial markets with a comment about the latest fashion accessories.

Fortunately, the perfect news story showed up in yesterday's paper. The Philips Rationalizer consists of an Emobracelet, worn on the wrist, and an Emobowl which displays your emotional responses to warn you if you are getting too irrational and need to step away from the terminal for a while.

It's recommended for use by stockmarket traders who may be susceptible to asset price bubbles. Mainly targeting the home day-trader market, but who's to say professional traders wouldn't benefit from it too? While that research claims to show that higher testosterone results in higher trading profits, I suspect that was only true in a broadly rising market. In a market which is more volatile and not producing returns above the long-run average, returns should be risk-neutral or possibly risk-negative, depending on the trading strategy.

But the important thing is that according to this site - admittedly not quite the November issue of Vogue - it "is actually cool looking" when you wear it.

Perhaps it will be the hot accessory of the fall season among hedgefundistas keen to demonstrate that their quantitative strategies are purely rational and have no basis in market sentiment. This item may give some insight into the fashion choices of such people, but I am not sure if that research has yet been carried out. Or whether the industry really wants to go there.

Tuesday, 13 October 2009

Austrians III

Sometimes I think you should stop reading my blog and just read Steve Randy Waldman's Interfluidity instead.

His last two articles, like nearly everything else he writes, are full of brilliant insights.

In "Information is stimulus", he answers Paul Krugman's (and my) question about asymmetry clearly and convincingly, making a thoroughly true case for certainty as a source of economic strength.

In "Vanilla afterthoughts", he neatly clarifies the argument for vanilla financial products while providing an entirely new insight into its public choice consequences.

I have noticed several times that he seems to be thinking more or less what I want to think, but is about three steps further ahead. Maybe that's because he used to be a Java programmer before taking up economics. Whereas I...used to be a Java programmer before taking up economics.

Hoping to see Steve writing a bit more in future, as he's been quiet this summer.

Monday, 12 October 2009

Austrians II

Thanks to Lucas Engelhardt for a thoughtful answer to my questions about Austrian economics.

He points out a few ambiguities and flaws in my posting and explores the "something happens" phrase which I neglected.

I would like to continue the debate on three main points:

Why those sectors?

Lucas says:
When money is cheap, interest rates drop. When interest rates drop, assets that provide payoffs further in the future gain value relative to assets that provide payoffs closer to the present. Therefore, sectors that are expected to offer high returns in the far future will see resources diverted toward them.
So on this argument, all investment assets rise in value compared with goods for immediate consumption.

But is this what we saw in 2001-07? Lucas and I agree that there were too many resources in residential construction, but on his argument we should have seen a general excess of investment as a whole, and a reduction (relatively) in consumption. Contrary to that, most people would say there was not enough investment. What investment there was (which was lower than the long-run average, in the US and UK at least) mostly went specifically into housing and not into productive business investment.

It's too simple to classify business investment as "productive" and housing as not; but the point is, the "misallocation" of resources was sector-specific and not just into all assets with a long-term return.

Logical deduction versus empirical demonstration

Lucas points out that:
Austrian economics is founded on a deductive epistemology. If one has true premises and reasons deductively, then the conclusion absolutely must be true. "Tests" are superfluous. (Similarly, the Pythagorean theorem is true because of the logic underlying it, not because we've failed to find a right triangle for which it wasn't true.)
The problem is that we don't all accept the premises of Austrian economics - or its deductions - as obviously and demonstrably true. They might be, but this is why we have empirical tests - to check whether models and deductions are correct.

The Pythagoras example is a good one. Based on its premises and logical deduction, it appears to be indisputably true. But Einstein managed to set up an empirical experiment after 2500 years which proved it isn't correct after all. General relativity shows that our universe is non-Euclidean, and therefore the Pythagoras theorem is not perfectly true in this world. This is the value of scientific experiment - because we make too many mistakes, or false assumptions, to trust ourselves always to be right.

So what about those numbers?

Lucas points out that my question about numbers didn't exactly fit with my other points. But the question still stands: does Austrian economics predict any specific measurable facts?
Part of the reason that Austrians generally don't provide "the numbers" is because they are keenly aware: (1) that relevant economic data is highly dispersed, (2) the economy is a complex structure and (3) relevant economic laws are all counterfactual.
I feel this makes things a little too easy. A model which essentially makes no predictions is not very useful.

Now of course the economy is complex and the data is dispersed; this comment applies to all economic models. Nobody says it's easy to estimate that NAIRU is 5% or work out a Taylor rule like this one. But these are still valid outputs from standard macroeconomic models, which allow us to test if the models broadly work. If unemployment is 9% and inflation still rises, or unemployment is 3% and inflation falls, that encourages us to question the model that gives rise to a prediction of 5% NAIRU.

Similarly, if the Austrian model makes a strong claim (that recalculation takes time and this time is the main cause of recessions) there should be some way to estimate that length of time and understand the factors that may influence it.

Even if it's impossible to determine the speed of recalculation in a recession, the theory should surely give an understanding of the factors that control recalculation/reallocation in a non-recessionary environment. Then we'd know what to do to help the economy find its natural resource allocation as quickly as possible.

I imagine the Austrian answer to this is that the free market will always allocate to the correct sectors, and only government intervention, if not oriented to correcting market failures (externalities, provision of public goods), interferes with that process. But few economists would disagree with that basic principle - so I am left again wondering what the specific predictions of Austrian economics are.

If it makes no predictions, I'm equally free to accept or disregard the theory and it has no effect on my life. Leaving aside the positivist question of whether the theory is even meaningful, a theory with no predictions is of little value.

There is lots more conversation about this going on in the blogs this week:

...there is another asymmetry. As the housing market expands in the 1990s through 2006, people are drawn into construction because they see the higher wages. They begin to invest in the skills of the construction business.

When it collapses, they have to decide what to do instead and how long to wait before doing it.

I think he falls into a Say's Law style trap here. Let me unpack that more carefully:
Say's Law sounds very plausible when you first hear it: if someone lends money to the government, of course that money is no longer available to spend or invest. But it isn't true, because of the dynamic interaction between saving and lending on the one hand, and spending and income on the other. Income and savings are not exogenously given but are dependent on each other and change quickly in response to various factors.

Similarly, it sounds plausible to say it's easier to move into a sector when it's growing than to find a new sector when the one you're in is shrinking. convincing as this sounds, it pushes back the question beyond the scope of the Austrian model.

Naturally if demand in a sector collapses, there will be dislocation while people find a new job. But what causes demand to collapse?

Bryan Caplan debates Pete Boettke on Austrian economics in a video from 2002. Now I thought 1934 was a long time ago, but 2002 is positively prehistoric.

James Hamilton has some comments suggesting that recalculation is real, and to the extent that it is, simple monetary or fiscal stimulus to increase aggregate nominal demand won't help. But is this true? Surely if general demand is increased, and demand in one sector is falling, it will be much easier for other sectors to absorb the layoffs (indeed this scenario should be equivalent to the recalculation-in-a-growing-economy mechanism which Russ Roberts thinks will work fine). Hamilton mentions "hydraulic macro" which is a nice way to describe an approach which looks at the response of individual actors or sectors in an environment of an overall growing or shrinking volume of demand.

And Tyler, as usual, says something useful. (Update: And something else too)

Sunday, 11 October 2009

The economics zeitgeist, 11 October 2009

This week's word cloud from the economics blogs. I generate a new cloud every Sunday, so please subscribe using the RSS or email box on the right and you'll get a message every week with the new cloud.

And this week's moves are listed here: no surprise to see "Obama" up 187 places and "Nobel" a high new entry at 147!

I summarise around four hundred blogs through their RSS feeds. Thanks in particular to the Palgrave Econolog who have an excellent database of economics blogs; I have also added a number of blogs that are not on their list. Contact me if you'd like to make sure yours is included too.

I use Wordle to generate the image, the ROME RSS reader to download the RSS feeds, and Java software from Inon to process the data.

You can also see the Java version in the Wordle gallery.

If anyone would like a copy of the underlying data used to generate these clouds, or if you would like to see a version with consistent colour and typeface to make week-to-week comparison easier, please get in touch.

Saturday, 10 October 2009

Those links on the right

Regular readers will have seen the blog links on the right hand side which show the latest headlines from lots of economics blogs.

All of them are worth reading, but once in a while something really nice shows up.

This time, two beautifully juxtaposed headlines from Daniel Indiviglio at The Atlantic and Justin & Barbara's column at Time.

No relation, as it turns out, to each other at all. Nor, of course, to Brian Clark's Copyblogger advice further down...

Update: Talking of headlines, Paul Mason's latest one "My return to Leigh" gave me a quick double-take...

Friday, 9 October 2009

Nobel prize for economics (and politics)

Surprising but (I think) nice news that Barack Obama has won the Nobel Peace Prize. I thought it was a joke when I first saw it, but on balance it is a good decision. Obama's inspiring message, philosophy and personal example are worth remembering, especially when obscured by fights over healthcare and climate change policy.

It's a somewhat risky prize - presuming a successful presidency before it's a quarter (and probably not even an eighth) finished. But the Peace Prize committee is a strange beast - always keen to be topical, even more than is the Economics committee.

Talking of which, Greg Mankiw has a sneak preview of the winner of that prize.

Update: Michael Tomasky's well-judged take on how Obama should respond and the political consequences.

Tuesday, 6 October 2009

The economics zeitgeist, 4 October 2009

This week's word cloud from the economics blogs. I generate a new cloud every Sunday, so please subscribe using the RSS or email box on the right and you'll get a message every week with the new cloud.

I summarise around four hundred blogs through their RSS feeds. Thanks in particular to the Palgrave Econolog who have an excellent database of economics blogs; I have also added a number of blogs that are not on their list. Contact me if you'd like to make sure yours is included too.

I use Wordle to generate the image, the ROME RSS reader to download the RSS feeds, and Java software from Inon to process the data.

You can also see the Java version in the Wordle gallery.

If anyone would like a copy of the underlying data used to generate these clouds, or if you would like to see a version with consistent colour and typeface to make week-to-week comparison easier, please get in touch.

Monday, 5 October 2009

Can feelings be modelled?

Karl at Modeled Behavior responds to Richard Posner (I am surprised to hear Posner emphasising psychology - I thought he was talking about Richard Thaler at first):
I am not sure exactly what Posner means by psychology. I have never been optimistic about feelings as an economics model. Perhaps people spend more when they feel better but how do we get a consistent measure of feelings and even more to the point how does policy consistently effect them.

What I do think makes a difference is expectations.
Expectations do fit nicely into macroeconomic models because they bear a simple relationship to real events. Macro models mostly deal with visible events such as monetary transactions. And an expectation is just an event, translated in time and perhaps given a probability weighting.

But we do model things in economics that are not that simple. The most obvious example: preferences.

Preferences are very complex - just think of all the factors that impacted on your choice of what dinner to have last night. How much money you have in your pocket, whether you're going to a movie, what was on TV, what you have left in the fridge, which foods go together, the expiry date on that piece of chicken, the leftovers from the previous day versus your desire for variety, calorie content and other nutritional values, whether you were still hung over from Saturday, the special offer at the local restaurant, whether you saw that Domino's sponsorship of the X Factor and simply what you felt like eating at the time. And that's just one decision out of dozens you make every day, multiplied by billions of people worldwide.

Clearly it would be very hard to model all that. But microeconomists still have some useful ways to model preferences. The most common is rational utility functions.

Of course rational utility functions do have some drawbacks: there are many aspects of behaviour that they fail to describe accurately. But behavioural economists are busy incorporating a more sophisticated understanding of decision making into this utility model. The basic concept is not a bad one.

The Arrow-Debreu theorem is an extrapolation from the idea of rational utility functions to describe how free markets bring about a position of maximum welfare for a society. These simple models of preferences do provide powerful theoretical outcomes.

So if we can model something as complex as preferences, couldn't we also build a model of feelings?

A cognitive model incorporating feelings is definitely possible to build. The question is how to choose the foundations of the model so that it still accurately describes behaviour, and is also mathematically tractable when extended to the level of a goods market, and then to the macro level of a whole economy.

While I don't have an immediate answer for that, the (relative) success of models based on utility functions shows that it is often possible to find a suitable model that can work at both levels.

One challenge is the divide between micro and macroeconomists - the micro people are better at developing these types of models but the macro crowd are the ones who need to use them in this case. We need people willing to work across both fields.

Another key is to have not less, but more, understanding of mathematics in economics. The application of mathematics to psychology is what led to many of the historical successes of the economics discipline. A deep understanding of underlying mathematical principles, not just a knowledge of how to apply them, is needed. This will let us develop unified economic models to transcend the splits between Keynesian, new Keynesian, monetary, new growth theory and Austrian macro.

Sunday, 4 October 2009

Hey Austrians - where are the numbers?

Greg Ransom comments on Marginal Revolution today that we have:
...a Hayekian artificial boom and inevitable bust with a very, very slight secondary deflation, and non-market clearing price controls on entry level labor.
This is a reasonable summary of the Hayekian story, for which Greg consistently argues on my three favourite libertarian/monetarist blogs: MR, TheMoneyIllusion and Worthwhile Canadian Initiative.

The idea is that easy money leads to overinvestment in certain sectors, which end up consuming more resources than their stable long-term share of the economy. Housing being the key example in the 2001-07 boom, or Internet technology in the previous one.

When something goes wrong, the availability of capital rapidly shrinks and there's no more money to spend on all those houses in Nevada or foosball tables in San Francisco. Lots of housebuilders or programmers are thrown out of work and need to learn a new trade.

In this story, government stimulus just delays the inevitable transition of people and other resources from sectors which no longer add much value to those where they can be more productive. Therefore, not only is stimulus expensive but it acts as a brake on recovery and future economic growth. So do labour market regulations such as the minimum wage.

One appeal of this explanation is that it works reasonably well whether the boom is fuelled by credit (this time) or equity (last time). And it does seem intuitively right that there have been more people working in construction than is sensible.

But it does leave some key gaps.

First, why should easy money go into these sectors particularly? If money is cheap, why do people systematically spend it on houses or shares? Why don't they buy more cars, holidays or gold? Is there a behavioural tendency to spend on some things and not others, and if so why?

Second and more importantly, this reallocation process is going on all the time, even when there is a boom. During the last 15-20 years the number of Internet software developers has consistently increased, even with a small slowdown in 2001-2. Fewer people work as secretaries and more work as reiki trainers (many of them are even the same people). So what is the difference now, and why will a stimulus package stop it from happening?

In short: what are the numbers? What is the natural, sustainable rate of reallocation of people between sectors; how fast was it happening over the last six years, how fast is it now, and how fast should it be for optimal recovery and growth?

Keynesian and monetary macroeconomics, whatever their weaknesses, at least provide empirical data to support their hypotheses and calibrate the theories. Austrian economics, despite its useful insights, doesn't seem to bring any testability with it.

Austrians - please give me some data and prove me wrong.

Saturday, 3 October 2009

Windfalls, incentives and Monopoly

Markets and economies generally work because people have incentives to find welfare-enhancing trades.

If you can keep the profit you make from a trade and spend it on something nice, you are more likely to make the trade. The same applies to working an extra few hours, or selling your car to someone who needs it more than you do.

This is why incentives are important. And it is the basis of the major objection to high taxes and redistribution - it is meant to dilute incentives and discourage people from achieving maximum economic productivity.

So what if the tax is a complete surprise?

If a government creates a straight one-off windfall tax, it cannot affect economic behaviour before the windfall, because it is unforeseeable. It should not, in theory, affect economic behaviour after the windfall, because it is a one-off tax and therefore there is no reason to expect it will happen again.

So why don't governments finance all their operations by a series one-off windfall taxes? Because of course, then they wouldn't be one-offs. People would come to expect some kind of random tax in the near future and it would undoubtedly affect their behaviour just as much - or more - than a regular income or consumption tax.

But where does a windfall stop being a windfall and start being a predictable tax event?

I have been dabbling in a game called Monopoly City Streets, which is based on the board game Monopoly - I trust I don't have to explain to readers of this blog how that works. The key point is that you spend money to buy properties, and make it back by charging rent.

A few days ago Monopoly City Streets underwent a major unannounced rule change, and the amount of rent paid on the most expensive properties was cut drastically.

Should this have affected behaviour? Well, it did change the incentives in the game, by affecting the relative returns on different assets. So future investments will be quite different than those before the change.

But should it change how people relate to the game itself? The change caused a storm of protest among players who had been investing on the basis of the old rule...many of whom threatened to stop playing. They had, as they saw it, invested hours or days of time in building up a portfolio whose value had just been arbitrarily cut by the "government".

If they'd known their time would be wasted, they might not have spent any time on the game in the first place. Should they stop playing now? Should they simply adjust their strategy to the new rules and carry on?

Classical economic theory doesn't shed a great deal of light on this dilemma. Rationally, decisions should be affected only by a cost-benefit analysis of the future, not past. Costs incurred in the past - time or money - are sunk. If you've just had $1 billion confiscated, it should just be as if you never had it in the first place.

But two factors mean that these windfall actions are relevant. The first is this: expectations about the future are based on experience of the past. If people believe that the government has a habit of imposing capricious taxes, they'll act as if more taxes are in their future.

The second is resentment, originating in a desire to be treated fairly. People who feel they are not, or have not been, treated fairly are less willing to participate in a social system.

In fact, these two factors may come from the same place: the need for simple ways to predict the future. If people are going to act on anything other than the immediate influences on them in the present, they need to have enough certainty about the future to take that into account too.

Since we usually can't predict the future with any degree of precision, two straightforward heuristics can be used:
  1. The future will be like the past
  2. The world is fair
The danger, then, of windfalls and other economic surprises is that they weaken our heuristics about the future. The economic damage this can do will be the subject of a future article.

Monopoly City Streets also presents a number of other good economics lessons, and I'll write more about those soon too.

Update: this is all a bit like the Paradox of the Unexpected Hanging. If you haven't seen that one, it's one of the classic logical paradoxes. Solutions welcomed!

Thursday, 1 October 2009

Worrying, bizarre defences of corruption

Robert Peston's article today is about the potential for BAE to be prosecuted over alleged bribery.

The article itself is interesting but the reader comments are what staggers me.

Page after page of comments passionately defend the corruption. "It's just the way things are done"..."do you really think the French and Germans don't do this?"..."it's not as if they were bribing British officials, but foreign ones, which is how you do business in these places".

You need to get through 23 comments defending BAE before finding a single one condemning illegal and immoral actions that hurt millions of desperately poor third world citizens (well done to DrDelbert, PorterRockwell and a few others for having a bit of integrity).

I am left wondering if this is really how the majority of Peston's readers feel...or is it, in fact, an organised campaign?