The last two weeks we have been looking at the problems with models. First we touched on what I called the Economic Singularity. In physics a singularity is where the mathematical models no longer work. For example, models based on the physics of relativity no longer work if one gets too close to a black hole. If we think of too much debt as a black hole of sorts, we may understand why economic models no longer work. Last week, in “The Perils of Fiscal Cliff,” we looked at the use of fiscal multipliers by economists in order to argue for or against governmental economic policies. Do you argue for austerity, or against it? There is a model that will support your case, most likely using the same data that your adversary uses.
These letters have generated a great deal of positive response and conversation. While I very rarely suggest to readers to go back and read previous letters, reading these may help you appreciate why it is so difficult to understand what is happening in the global economy today.
This week, in a somewhat shorter letter, we once again consider the vagaries of measurements and models. Growth of the US economy, we are told, was 2% last quarter. That number will of course be revised, but what is it we are measuring? Should we attach any importance to the measurement at all? The short answer to the last question is yes, but it is important to understand that there is no certainty in that number. Or at least not any certainty according to the generally accepted meaning of that word …
Measuring GDP
… [L]et’s visit this week’s announcement that GDP rose by 2% in the last quarter, up from 1.3% in the second quarter, which itself ended up being revised down almost 2% from the initial estimate. My guess is that we will see the same downward revisions over the next few months, as the other economic data last quarter was not robust. But clearly, we are not in a recession, just a Muddle Through Economy, as predicted here.
A 2% number is not bad, but there is more to it when you look at the underlying components. A large factor in the quarterly growth was defense spending, which leapt by a quite robust 13%. Personal consumption was up just 2%. Then there is inflation. If you think inflation was 2%, then the GDP number is overstated by 0.5%. Couple that with normal defense spending, and growth would have been less than 1%. That would not have been a political winner.
Inflation can be measured in several ways. GDP data does not use the Consumer Price Index, which shows inflation of more than 2%. You can get a much different GDP depending on what inflation number you use, and those numbers are dependent on what assumptions you make about how to figure inflation.
And while we all seem to use GDP, is that really the measure that makes the most sense in today’s world? Might we be better off targeting Gross Domestic Income, rather than looking at a consumption-based number like GDP? And isn’t Gross Private Production what we really need, rather than just an indicator that includes changes in government spending? At the end of the day, government spending can only be a function of what is produced in the private sector.
The Economics of Assumptions
We all want to have numbers that are “real.” But economics is different from accounting. Economics makes assumptions in almost all of the models it uses, and those assumptions come with biases. How many discussions do we get into that proceed along the lines of:
“Look at this statistic. It clearly goes up [or down] with GDP [or employment or …]. Therefore, if we could just fix ‘X,’ we would solve the world’s problems.”
For instance, I can clearly demonstrate to you that raising taxes on the rich will have no effect on their spending, if I use just one or two correlations in certain time frames. Throw in a few good stories, and the obvious conclusion is that we should raise taxes on the rich again and again. Just ask Monsieur Hollande – it’s their fair share.
Then I can just as easily show you that raising taxes on the rich will result in serious economic calamity. “Just see what it did in this situation. And see what cutting taxes did there.”
The counterargument then runs that your interpretation misses some other factor, so your conclusion is wrong. And so on and on. This goes back to a quote from Anne Rice. While her character is talking about another form of knowledge, the observation applies doubly to economics. Here it is:
“Very few beings really seek knowledge in this world. Mortal or immortal, few really ask. On the contrary, they try to wring from the unknown the answers they have already shaped in their own minds – justifications, confirmations, forms of consolation without which they can’t go on. To really ask is to open the door to the whirlwind. The answer may annihilate the question and the questioner.”
Human beings seek certainty. We actually get an endorphin rush when we get an explanation for something we do not understand. Whether it’s religion, politics, philosophy, a crossword puzzle, or economics, we want to be able to come to a definite conclusion that we think is correct. There is psychological rest in certainty, along with the physiological rewards). Models, even flawed ones, give us the illusion of certainty. We need to be careful of what illusions we cling to.
Economics becomes quite a problematic discipline when it tries to create mathematical models that are supposed to guide political philosophy and praxis. So many assumptions have to be made to get to a result, that basing policy on a simplistic model is dangerous.
One size does not fit all, and past performance really does not indicate future results. The entire economic environment must be taken into consideration. We cannot extrapolate simplistically from the Reagan or Clinton years and say, “If we just reverted to those policies, we could get the same results.” Only if you could change all the other variables that are beyond the control of the government!
Models can be useful, but they are not exact. They give us a sense of direction. Using them is more like navigating by the North Star than using a GPS system. The more variables that enter into the actual situation, the less likely we are to be able to come up with that one “easy-button” policy prescription.
In the end, the only real tool we are left with is common sense, guided by our models and an appreciation of history. We “know” that, in general, the lower the price the higher the demand. If you tax something, you will get less of it.
We get that we can’t let financial institutions run amok. There have to be some protections for the public. Debt is useful until it becomes a burden, and we have to be careful in how we use it. We can come up with dozens of such truisms, based on common-sense wisdom.
We elect politicians and then expect that somehow the world will improve in accordance with their promises. What we really need to do is try to see what general direction they are leading us in and base our votes and our personal decisions on whether we like that direction. But to trust an economist, or even worse a politician, with a model? That can be dangerous.
This is an outtake from Thoughts From The Frontline, a free weekly publication by John Mauldin, renowned financial expert, best-selling author and Chairman of Mauldin Economics. Each week John provides his insightful analysis on Wall Street, the global markets and the rapidly changing world economy. Join his over one million readers today! www.frontlinethoughts.com
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