Abandoning Economic Models

I’m currently reading Nassim Taleb’s latest book “Antifragility: Things That Gain From Disorder“. He doesn’t pull any punches with his dislike for economists. He thinks they’re charlatans who suffer from physics envy and calls their platonified knowledge the symbol of “Soviet-Harvard” intellectualism.

Let’s go back to square one.

Forecasting is impossible.

Taleb argues that we can however recognise things that are fragile (big banks, dictatorships etc.) and make some prediction that they’ll collapse eventually to some external shock.

On the other hand, many economists live in a magical unicorn fairy world – Taleb calls them “fragilistas” or “interventionistas”.

They think the problem with their predictions is that they don’t have enough data.

Ignoring Occam’s Razor, these charlatans are everywhere in our economy and in our institutions.

Would it really be so hard for economists to admit that they are full of it?

The most honest thing economists can do is explain likely consequences of different policies with a huge caveat – there could be stuff we didn’t think about that might make this entire document null and void.

All of this forecasting business is ridiculous.

The idea that a central bank or Treasury economist can be all knowing is hilariously close to Soviet “5 Year Plans”.

We all know how those worked out. And we all know that “Top Predictions For 2013!” never bear out.

Just look at Treasury and the Reserve Bank’s forecasting since the Global Financial Crisis.

They really need to stop embarrassing themselves and just give up.

Focus on reducing fragility in the system – that means elimination of big banks and deficit spending.

Please share your thoughts below. Why do economists keep forecasting when they are always wrong? Do they have substantial ego investments in their predictions so large they ignore sunk costs?

Do We Need Big Banks?

Humans can’t handle more than 150 relationships. It’s a throwback to our caveman past – when tribes exceeded 150 people, bonds of trust started to weaken and no one really knew what was up.

Big banks in New Zealand have thousands of employees and hundreds of thousands of customers. Big banks in the US have tens of thousands of employees and millions of customers. No one really knows what is going on because there are so many people involved in the banking sector.

Back in the olden days, before I was born, you used to have a relationship with a bank manager. When you went to apply for a loan, he knew your banking history, probably your parents and your grandparents too. If you were applying for a farm loan he’d have a decent knowledge of your farming ability.

This meant that the distance between savers and borrowers was small. Relationship banking meant knowing your customers, knowing the local community and knowing that if someone had good character they were likely to pay the bank back eventually.

Back in the olden days, there was also a lower incidence of bad behaviour. Defrauding banks still happened, but it was a lot harder than it is today. Because communities were smaller, the social shame effect could be used to lower the likelihood of default.

This is all in stark contrast to how the banking sector functions today. Credit approval is granted based on points and complicated models that evaluate a potential borrowers prospects.

Putting aside the role that fancy models played in the collapse of Long Term Capital Management, the NASDAQ technology collapse, the housing boom and rise of sub-prime, the derivatives on sovereign debt and even domestic housing developments, the big banks today have enormous distance between the savers and the borrowers.

In any system, when you centralise decision making, you lose knowledge at the coal face that matters. In his essay The Use of Knowledge In Society, F A Hayek argued that the reason central planning failed was because a committee couldn’t make price decisions for every single actor in an economy.

Central planning in the banking system is represented by centralised credit approval systems. They use fancy models that use crap models like “Value at Risk” because the regulators, who know very little about the real world, have mandated that those models are the true representation of the risk a bank is exposed to.

Dispersed knowledge applies just as much as the private sector as it does in the public sector. Dozens of local bank managers making subjective decisions is likely to be more stable than a centralised credit approval system.

The conceit, of course, is that a model is a simplification of reality. It is made up of assumptions, can disregard potentially relevant factors as “not useful” and applied to situations it really shouldn’t be.

Big banks in New Zealand today are walking blind through a minefield. Their loan default models are based on past default rates. Their “worst case scenario” stress testing models forget that the “worst case scenario” is always¬†worse than the last worst case scenario before that!

We don’t really need big banks because the arguments they use to justify their existence, like they provide payment networks and the like, are redundant in the 21st century. They are a utility, the flash offices I see in Wellington belonging to big banks offends me deeply.

They should be as boring as water companies. Not some sexy, profitable, lavish executive pay with no clawbacks for imposing systemic risks on everyone else nirvana. The big banks have to go if we want any return to a realistic distance between savers and borrowers.