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The joys of politics

I recently wrote about the theoretical arguments surrounding fiscal stimulus by governments (here). Anna Bligh in her election campaign promised to 'create' 100,000 jobs in her next term. We know that these actions and promises are all rubbish, so why to we accept it? Why not vote for the guy who is reasonable? Or is it that reasonable people avoid politics and we have to vote for the best of the worst.

I want to bring your attention to comments by economics super-professor Greg Mankiw about the US stimulus bill. Apparently the US government has promised to monitor the effects of the bill and report periodically on the number of jobs created.

It is an absolute mystery as to what these guys will actually do. My cynical side might suggest they will simply pluck numbers from the air. Then possibly vote on what number would by not too high, not too low, but just right, as far as the public perception of their validity goes. They may even dabble in economic tricks.

These are the joys of politics.

Political renovation rescue

Economists are often deluded into believing that their years of diligent research into how government intervention can maximise the wellbeing of the populous may one day result in tangible gains to wellbeing. I must apologise. I am about to shatter the one way mirror currently shielding economists from reality.

A workable economic theory, once in the hands of a politician of any significance, stature, or importance, from local councillors to world leaders, will be utilised as a weapon for vote winning amongst a well studied, segregated and predictable bunch of right-wing, left-wing, religious, environmentalist voters who are easily convinced that ‘full of shit’ equates to knowledgeable and caring.

Let me take a Channel 9 reality TV analogy further than it should ever be taken. Imagine your lovable host Damie Jurie is wearing a toolbelt, complete with hammer and tape measure, talking the talk about fixing trusses to A-frames using through-bolts and nail-plates. The public immediately thinks he actually knows how to use those tools on his belt, and when he does so, we would trust that he does it right.

But if the tool is actually cost-benefit analysis, and the Damie Jurie is actually your favourite rhyming Prime Minister, Treasurer, Mayor, Premier, or any such figure, when they apply the economic tool that they are so fond of, the public has no expertise with which to criticise its application. If we saw Jurie using a hammer to drive in a screw we would be alarmed, question his intelligence as well as his sexuality, and change the channel, if not before we have circulated a series of new Damie Jurie jokes by email. But our politicians can get away with nonsensical applications of technical economic tools because we are ignorant about how they are best used - and they know it.

As a public sector economist I have been shocked at the prominent disinterest in economic models that attempt to capture flow-on effects of policy. Politicians like to know the economic benefits of policies to their target group. But if you live across the road from a working family, especially if they are farmers, and worse if they are a vocal minority group, the cost burden you face will be completely ignored in the ‘cost-benefit’ or impact analysis of their proposed policy.

Imagine my surprise when Federal Government documents explaining how to develop a project plan for a water buyback scheme explicitly state the any flow-on effect should be ignored. It may well have said

‘We need to sell this policy to the ignorant public, please use the most confusing economic terminology to make us look like that ever popular Jurie fellow. Please don’t explain how we’re taxing the general public and putting money directly into the pockets of an arbitrarily selected group of vocal farmers. And while you’re at it, make it look like we care about climate change’

Now, that may be a little cynical. Or maybe it’s extremely cynical. But to intentionally ignore these effects makes the whole thing look like a sales pitch. This time it is to the farming communities in the Murray-darling Basin. Who knows who will get the handouts next time (try working mothers), but gee I wish I was a farmer.

How about an example of the distorted analysis expected in the public sector. A recent ABARE report attempted to quantify the loss from a 10% reduction in water available in the Murray-Darling basin. They used an input-output matrix as one tool (that does not consider flow-on effects to any particular degree). They found about a 6% reduction in total production from the MDB region as a whole. But when using a CGE model (which iterates flow-on effects until a new equilibrium is met) they found that national production decreased a mere 0.04%! Given there are no statistical tests on this outputs of this model one has to wonder whether that is actually distinguishable from zero, or whether it is just a rounding error!

This rant has left me no closer to changing the world for the better. I comfort myself knowing that our political system is the best of the worst. We live in an imperfect world, and this type of vote manipulation, pork barrelling and bribery is a small price to pay for the freedoms we take for granted. I also think about the automatic stabiliser inherent in government, knowing that my salary is an important component of containing the excessive fluctuations of markets, and then give myself a pat on the back for being a great stabiliser!

But at least I feel better for getting it all out of my system. I’m off to buy a farm. Can you help me build a shed Damie?

Randomness, risk and uncertainty: How do we know what we don’t know?

Being a habitual sceptic (and an economist), the insights offered by Nassim Nicholas Taleb in The Black Swan have struck a chord. I have never found a receptive audience in academia for my dislike of the assumptions of the characteristics of randomness that determine the probability density function (amongst other assumptions) in most statistical analysis – especially in social phenomenon. But finally I have a wing man.

The general attitude I face is that if we don’t make these (sometime radical) assumptions, we can’t do any analysis of the data, and draw any conclusions. My response is; what use are conclusions based on flawed assumptions?

The book poses the challenge to think rationally about probabilities, and the impact of improbable events. In particular, Taleb challenges us to acknowledge the limits of knowledge. Real risks and randomness come from the unknown unknowns.

He uses an example of casino to explain the difference between known risks that occur in a world he calls mediocrastan, and the wild unknowns and events from the world of extremistan. The mediocristan risks are those involving the gambling itself. Each individual bet has a risk that is essentially Gaussian, so with a large number of bets taking place, and limits on the size of each bet, these risks are eliminated.

Taleb suggests that most of our concerns about risk, and the high impacts of improbable events, are from the world of extremistan, where complex systems result in variations at all scales. The point is that in extremistan, large variations and extreme events WILL HAPPEN, and much more often than we think. Such large complex systems include financial markets, the global economy, and the climate.

While attending a statistical conference at a Las Vegas casino, Taleb discovered that the four largest losses incurred by the casino did not involve the gambling itself (whether cheating or otherwise). The first was when a tiger performing in a stage act maimed one of the performers. The next was when a disgruntled contractor who became injured on job threatened to blow up the casino with dynamite because he was insulted by the settlement offered. The third was when an employee failed to mail paperwork to the Internal Revenue Service for a number of years, which ended in a monstrous fine. And finally, the casino owner’s daughter was kidnapped and held ransom, which forced the owner to dip into casino funds.

These events are Black Swans. Unpredictable, outside the scope of expectations, and have massive consequences.

He makes a number of interesting points that I want to share. These are particularly relevant in current environmental debates. For example, where I work we try to estimate the environmental impacts from changes to stream flow in rivers. The number of assumptions in unbelievable, and any output from this type of modelling has to be taken with a grain of salt. It is merely some background information that either confirms or challenges the experiences on the ground. When I write about the economic impacts of changing water regimes I repeatedly make the point of acknowledging the unknowns and the limitations of my analysis. Can you imagine the complexity of climate models, and the staggering number of assumption built into them? One wonders whether climate scientists understand statistics at all.

The first point of interest may be familiar for those who are statistically inclined. It is the statistical regress argument and it is a cause for concern. It goes as follows:

Say you need past data to discover whether the probability distribution is Gaussian, fractal, or something else. You will need to establish whether you have enough data to back up your claim. How do we know when we have enough data? From the distribution – a distribution tells you whether you have enough data to “build confidence” about what you are inferring. If it is a Gaussian bell curve, then a few points will suffice. And how do you know if the distribution is Gaussian? Well, from the data. So we need the data to tells us what the probability distribution is, and a probability distribution to tell us how much data we need. This causes a severe regress argument.

Given that our data samples for global temperatures are extremely limited, climate scientists face this problem at the outset.

Another interesting point is how the nature of Black Swan events, and the resulting silent evidence distort our interpretation of history. Any act that aims to prevent a Black Swan event goes unnoticed because its success can never be observed. Imagine there is a bureaucrat who decides to implement aviation rules in August 2001 that would have prevented the September 11 events in New York. We could never judge the success of these measures in preventing terrorist attacks, and the bureaucrat would never gained any credit for the measures. Possibly, due to the complexity, cost and frustration of travellers, he would have had to overturn the rules in 2002. He would be labelled as someone whose best skill is to waste time and money. Learning from history is very, very distorted due to silent evidence. I can imagine in the not too distant future that the history book will explain how we should have seen an event like September 11 coming, due to such things as ‘rising tensions between terrorist groups and the US’, but they would simply be wrong. The crashing planes were the sign of rising tension!

Another great insight is the problem of induction. He uses an analogy of a melting ice cube. If we know the shape of the ice-cube, we can fairly well predict the size of the puddle of water when it melts. But, if we have the puddle of water as our source of information, there is not much we can say about the shape of the ice-cube. In economics we constantly go about measuring puddles of water, and through flawed statistics, try and make outrageous claims about the shape of the ice-cube. The herd mentality of the global economics profession and media seem to have induced that overzealous lending in a few sub-prime locations in the US has led the whole world into a massive recession. My question is, the given how many other more significant events were happening around the globe during this time, how can anyone be so sure of that the ice-cube was shaped like a few bad loans, and not like a oil shock? Or why was the cause not simply a unique combination of unforeseeable events? This same question can be applied to climate change. If we agree that the climate is changing (which itself is questionable due to the previous two reasons), how can we isolate a single cause in a complex system?

I will stop now because I don’t really think I can do justice to the ideas of Taleb and his philosophical predecessors here. I just want to reiterate that we know a lot less than we think we know.

My main concern is that for someone who preaches a precautionary approach to making claims of knowledge, Taleb is a devoutly religious man who has used arguments such as ‘religion has not killed so many people as the concept of the nation state’. So, if religion is the root cause of, say, 10 million premature deaths, while fighting for or defending a nation state (which coincidently have often been religious states) has killed, say, 20million people prematurely, does this mean that religion is good for society? Taking this argument elsewhere and we get such things as ‘murder kills 100 people annually, but motor vehicle accidents kill 300 people’. For a guy who we are meant to believe has a solid grasp of logic, reason, argument, and science, this seems a rather appalling justification for his beliefs. But of course, nobody is perfect, and we need to judge each argument on its merits.

Tagcrowd - heard of it?

I recently ran across a very interesting website called Tagcrowd. It counts word frequency in text and presents a neat cloud of words that provides a good visual summary. I did it with my whole blog and got the following result. Seems to sum it up nicely.

Can governments be more innovative than private enterprise?

I have had some interesting thoughts lately regarding the trends towards the privatisation of infrastructure and the user pays principle which underpins this trend. My theory suggests that private infrastructure based on user pays principles locks society into a particular path of development which becomes increasingly self-reinforcing, thus excluding innovative solutions to transport, communications, energy and water supply.

Let me explain in more detail.

Consider two countries, A and B. Previous governments of country A have spent the past century investing heavily in a rail network for both passengers and freight, while country B has spent the past century ignoring rail and building roads as the major land transport system.

Now imagine that a technology, X, is developed that can massively increase the efficiency of rail transport, but not road transport. Think along the lines of mag-lev trains or some such thing.

Now both country A and B believe that this technology is superior to their current land transport system and aim to develop a network based on private investment. Country A already has the land, the stations, and the infrastructure in place, while country B has none of it. One would expect that the compared with country B, country A is more likely to find potential private investment for such a project given the likely lower costs but equal benefits.

Thus due to historical capital investment, country A continues along a rail based path towards the most efficient outcome available with technology X, while country B continues along a road based path and will never reach technology X through private investment alone and will remain 'stuck' with a less efficient land transport network. This is the problem of path dependence, a situation encountered in both evolutionary theory and economics –“the cheapest manufacturing method may not be achievable by “evolutionary steps” but may require a complete change in method”.

The question then arises that if country B is ‘stuck’ on a more costly trajectory of land transport development, how does it become ‘unstuck’. This is where I believe governments can intervene to make the decision to become unstuck by directing investment into the superior new infrastructure. Rather than the user pays principle of privatisation, the government can justify funding such scheme due to benefits to the user, but also benefits to non-users in society.

For example, if a rail line is established along a popular road corridor, both the rail users and the road users benefit - the rail users from cheaper transportation, and the road users from less congestion. Unless a private enterprise can charge the road users for the rail line, a publicly funded outcome is far superior.

The inability for private infrastructure owners to capture external benefits limits their opportunity to innovate and provide broad social benefits.

Governments on the other hand can consider all external benefits and consciously ‘invest’ a region out of their current development trajectory on the basis of providing indirect social benefits.

The problem then is getting a government to even perceive these potential social benefits, let alone act on them.

The other problem is that if governments do ‘invest’ a region out a of a particular development path, they are now stuck in the new path, unless they invest heavily once again. For example, Brisbane ditched trams back in the 1960s, and successive governments ever since have been considering getting them back. But each change in trajectory is more expensive than the last.

So what then should a government do to maximise social welfare? Should they just stick to the path they are on and hope that future technologies are advantageous, or should they embrace innovation and change the development path?