What if Regulation was a Finite Resource?

Alternative Title: Conservation of Regulation

Think of the fuels that have provided the energy for human civilization so far – coal, oil, gas. They existed for thousands of years, largely inert. A small part of them (mainly coal) was used by humans for forges and the like. But then we discovered them during the industrial revolution. We put them to good use, but there’s only a limited supply.

What if regulation was the same? There’s only a finite amount available. For most of history, this existed in a largely inert fashion, regulating the atmosphere, evolution, and so on. A small part of it was used by humans to regulate their habits and bowl movements.

But then during the industrial revolution regulation was discovered by socialists and paternalists. They started using it on a massive scale, trying to regulate all of society.

Unfortunately, there’s only a finite amount of regulation available. We’ve been using so much over the last few hundred years that there’s not enough to regulate the climate – hence climate change. It caused a breakdown in virtue when people’s ability to regulate their habits was reduced. It also caused the obesity crisis because we can no longer regulate our bowl movements properly.

Now, leading scientists are warning about an even greater threat: we might be using up so much regulation that the earth’s orbit will cease to be regular. This will have dramatic consequences, ranging from disruptions to the seasons and day-and-night cycle, to the earth crashing into the sun.

Leading scientists say we need to rapidly reduce our regulation consumption if this is to be avoided. They recommend bring our regulation uses back down to 1990s levels by 2020, and 1900 levels by 2050, and 1700 levels by 2100. Unfortunately, it may already be too late to avoid changing the day-and-night cycle by 1-2 hours, in an effect scientists have dubbed ‘daylight savings time’.

Economists are divided on the best way to respond to the crisis. Some favor a regulation tax, where anyone who implemented or enforced a regulation would have to pay a tax equal to the negative externality they caused. Others suggest a cap-and-trade system, whereby rich countries would be able to buy regulation credits from poor countries. Some politicians prefer a command-and-control approach, where they would pass regulations limiting the use of regulations in industry.

Some progress has been made – most countries have signed up to the Hong Kong Protocol, promising to reduce their regulation levels. The US risks becoming an international pariah by refusing to sign; the Obama administration defended its intransigence:

Hong Kong is, in many ways, unrealistic. Many states do not want to meet their Hong Kong targets. The targets themselves were arbitrary and not based upon political science. For America, complying with those mandates would have a positive economic impact, with increased hiring by small businesses and price decreases for consumers. And when you evaluate all these flaws, most reasonable people will understand that it’s not sound public policy.

But you too can make a difference! There are many easy steps you can take. Maybe turn off your thermostat – doesn’t the earth need that regulation more than your central heating? Write to politicians expressing your concern. Join a local libertarian group.

Remember, preventing the world crashing into the sun is more important than regulating your heartbeat, so ask yourself: do I really need a pace-maker?

Advertisements

Betting the House, not the Economy

Òscar Jordà, Moritz Schularick and Alan Taylor recently put out an interesting paper on the relationship between interest rates, the housing market and financial crises. It’s been reviewed very positively, for example here and here. They take advantage of the macroeconomic trilemma – countries with fixed exchange rates and open capital markets ‘import’ the monetary policy of other countries –  by treating these imported interest rates as exogenous, providing them with an independent random variable.

People seem to be interpreting it as saying that loose monetary policy causes financial instability through the transmission mechanism of a housing bubble.

To be fair, the opening line of the abstract does give that impression:

Is there a link between loose monetary conditions, credit growth, house price booms, and financial instability?

as does the first paragraph’s use of ‘thus’:

Do low interest rates cause households to lever up on mortgages and bid up house prices, thus increasing the risk of financial crisis?

So one could be forgiven for thinking their conclusion was basically

  • Loose Monetary Policy -> Mortgage & Housing Bubble -> Financial Instability

… Well, one could be forgiven for thinking that unless one was going to write about the article. If you were going to do that, you should actually read the article. Then you would realize they in fact show two separate things:

  • Loose Monetary Policy -> Lower Long-term interest rates + Mortgage & Housing Increases
    • (with reasonable p-values in general)

InterestRatesAndHousingMarket

and

  • Mortgage & Housing Market Bubble -> Financial Instability
    • (with ok p-values, and some suspicion about how canonical their independent variable was)

HousingMarketAndFinancialCrisis

Despite having a clever way of treating monetary policy as an independent variable, they never directly test

  • Loose Monetary Policy -> Financial Instability

even though this would be a major victory for the ‘low interest rates caused the bubble and crisis’ crowd.

Why not test this directly? The authors don’t say, but I suspect it’s because the test would fail to yield significant results. Absence of evidence of such a connection is evidence of its absence. And looking at the significance levels of the two results they did provide, I suspect that combining them would cease to be significant (unless their is another, parallel causal mechanism).

Which is a shame! Their independent variable looked really cool, as did their data set.

I think there’s an underlying theoretical reason to not expect it to work, however (quite apart from nothing ever working in macroeconomics. They rightly make much of their finding that exogenous low interest rates cause increases in housing prices. But this is not necessarily caused by increased demand ‘bidding up’ the value of housing in a bubble.

Rather, consider what sort of an asset housing is. Houses allow you to avoid paying rent in the future; their value is the capitalized value of avoided future rent. When interest rates are low, those future rent payments are discounted at a lower rate, so are more valuable: low interest rates increase the inherent value of housing. House prices rising when rates are low isn’t a bubble unless the interest rates themselves are a bubble; it’s rational cross-asset pricing. So we should expect exogenous falls in interest rates to increase house prices.

But wait there’s more!

Exogenous falls in interest rates probably mean rates are now too low (from a Taylor Rule perspective, or similar), or at least not-as-excessively-high as before. This will tend to increase inflation. And as home ownership represents a hedge against rent inflation, higher inflation yet again increases the value of home-ownership. So once again we have a non-bubble based reason to expect exogenous falls in interest rates to increase house prices.

So we have two reasons to think that low interest rates should cause non-bubble increases in house prices, and journal article that is mildly supportive of this thesis.

What Diversity can do, Design can do better.

People sometime argue that diversity in an organization is good because it improves the quality of ideas generated. Different backgrounds bring different perspectives, which provide different insights, whereas having many people with the same background causes partial redundancy.

This argument seems to be mainly made as a rationalization rather than as a true reason. It’s typically employed to support hiring more blacks, or less frequently more women and hispanics. But rarely do advocates explain exactly what new perspectives these people are meant to bring. Does one’s race give one a unique insight into how to write good code? If not, this argument seems pretty poor as a justification for discriminating in favor of blacks for programming jobs. Do women have special, vagina-based insights into maths or physics? If not, it doesn’t seem to work as a justification for discriminating in favor of women for STEM positions.

Indeed, if you actually wanted a diversity of opinions, you would probably just seek to hire that directly. Maybe your investment team should have majored in Economics, Physics, History and Statistics rather than Economics, Economics, Economics and Economics. Perhaps you should hire some social conservatives to your sociology department rather than actively and openly discriminating against them. Sometimes this strategy is employed – Corporate Boards do try to have people from a wide variety of backgrounds, both inside the company, different companies and even different industries. But I’ve never seen the pro-diversity crowd realize this purported benefit of racial diversity could be much more directly achieved.

Indeed, suppose different races did have different insights into programming. Then you would probably benefit from seeing each race represented. But while you might want some people from each race, there’s no reason to think you’d want them in the same fractions as appear in the overall population. At the moment having a racial breakdown significantly different from the US is enough to have you branded as un-diverse, but is there any reason to think the overall US has the optimal racial make-up for your company? Probably not. Indeed, as the racial make-up of the US is changing over time, even if your organization’s optimal make-up was fashionably diverse at the moment, it won’t be in the future, as the hispanic share increases and the white share decreases.

And if you were actually looking to take advantage of different racial perspectives and advantages, you wouldn’t have a corporate-wide quota or such. Instead, individual job openings would come with desired races attached. We would see a return to “No Blacks or Irish” notices on job postings, brought back at the auspices of political correctness.

Economies of Scale in Individual Labor Supply

Here are two stylized facts about labor economics:

  1. Utility is roughly logarithmic in income
  2. People who earn more per hour also work longer hours.

Together they present a puzzle – those higher income people are higher income primarily because they earn more dollars/hour, not because they work more hours. Yet if utility is logarithmic, there are diminishing returns to income, so we should expect people with higher hourly rates to work fewer hours.

Essentially, the first stylized fact suggests the income effect dominates, while the second suggests the substitution effect dominates.

One solution to this conundrum would be if the hourly rate changed with the number of hours worked. Maybe there are some jobs that simply cannot be done unless you put a huge amount of effort into them: you can’t be a part-time investment banker or corporate lawyer. If so, your productivity would increase dramatically with hours worked, so the demand curve for your labor would be upwards sloping. It’s a bit like a Giffen Good, except the causation goes

  • Higher Quantity -> More Valuable -> Higher Demand -> Higher Price

rather than

  • Higher Price -> More Valuable -> Higher Demand -> Higher Quantity

At the same time, every extra dollar is worth less and less to you, and each hour of leisure lost hurts more than the previous one, so you demand a higher hourly wage the more hours you work. So your supply curve is upwards sloping, roughly exponentially (to offset the logarithmic dollars->utility conversion)

When both supply and demand curves and upwards sloping, it is not clear there is a unique equilibrium – there could be multiple equilibria.

This could explain why we see such a difference between the incomes of

  1. The increasing number of people who do not work at all
  2. People who do ordinary jobs for around 40 hours a week
  3. Extremely high earning extremely hard working people

each group occupies a different one of these equilibria.