Well, don't ask *this* economist anyway...

Greg Mankiw has a informative article up at the New York Times. Well, informative in that it typifies how clueless most mainstream economists are. If economists incorporated stock market behaviors into their theory, instead of sticking with a theory that only works in Fantasyland, they would be able to recommend stocks better than investment "professionals".

Unfortunately, Mankiw is not one of the former set of economists. Therefore, his entire article is a rehash of bad advice he probably got from someone from his own business department. Let's tick down the list of uncritical thinking.

The market processes information quickly. Here is the standard paean to the efficient market hypothesis. The bad logic behind this hypothesis is that if the market was priced based information instantaneously, prices would change infrequently, because usable information about earnings or dividends comes out a few times a year. In the real world, however, prices change all the time and sometimes "inexplicably". This was the thesis of Robert Schiller's 1981 paper analyzing stock price movements: they are far too volatile to possibly be explained under the EMH. However...

Price moves are often inexplicable. Here, Mankiw refutes his first assertion, citing the very same Schiller paper. Make up your mind, dude! Price movements are always explicable. If you don't believe me, read any article about yesterday's stock market trading in the business section. They will invariably report on the stocks which had big price changes that day and tell you exactly why it happened. Of course, the real reason for a big price increase is not what the reporter's financial analyst friend said on record, but that lots more buyers than sellers showed up that day (vice versa for a big decline). And one of the big reasons why that happens has to do with the price movement of the stock itself. Economists literally cannot comprehend this kind of endogenous model that allows investors to have less-than-perfect foresight, because it is the opposite of the models they use.

Holding stocks is a good bet. After regurgitating the EFH, it's not surprising that Mankiw regurgitates the "buy and hold" mantra as well. Holding stocks is never a good bet during a bear market. It is a way to lose money. The reason investment "professionals" recommend buy and hold investing is because a) they aren't any better at investing than us and this way we don't outperform them and b) they don't want to get sued when we lose money from their bad advice. I will show you in a not-too-distant post a very simple investment strategy that is guaranteed to outperform the market. The key principle of this strategy is: SELL STOCKS WHEN THEY ARE OVERVALUED AND OWN SOMETHING ELSE.

Diversification is essential. This is another piece of bad investment advice that Mankiw could only have gotten from a licensed investment professional. Diversification reduces your returns. Always. The reason is that you'll regress to the mean. Always. Now, diversification is surely useful if you don't have the time to spend finding which sectors of the market will outperform and which sectors will underperform. This way you're guaranteed to always get the average. Of course, if you follow Mankiw's previous advice, you'll already be losing when the market goes down. But at least you won't be losing more than average, I guess. Protip: Warren Buffet does not buy index funds. Neither should you, unless you don't have enough information to do otherwise.

Smart Investors think Globally. Here Mankiw is just trying to end his article. I don't think he really understands what he is writing about, but it sounds good to him. HOW, exactly, does thinking globally help investing? Most investors generally invest in their home country because a) they have the most information about their home country and feel most comfortable making investment decisions with sufficient information, or b) investing internationally has high transaction costs or is generally unavailable to investors. Mankiw seems to think this has something to do with diversification, but most global markets are highly correlated over time, so that can't be it. The purpose of diversification is to find investments that are uncorrelated. Stocks and interest rates are somewhat uncorrelated. Stocks and gold are somewhat uncorrelated. Stocks and other stocks are not uncorrelated, be they stocks in one country or many.

So maybe, in the end, it IS a good idea not to go to Greg Mankiw for investment advice. For he'll just steer you toward investment strategies that lost people about $15 trillion this past recession alone. His article is heartening to me, though. It shows the world badly needs economists that understand investing. If you keep reading this blog, I hope I can rescue at least a few of you.

Gamer, Interrupted

I have a level 78 Paladin on the Hyjal server, which my OCD would normally compel me to level to 90 prior to posting regularly on this blog. However, Swarley of the guild "LEGEN (wait for it) DARY" will have to bank three more bars of rest because there's stupid to be dealt with.

Not really stupid, but just sham science. Nothing makes a scientist look worse than abandoning the scientific method. Yet for economists, abandoning the scientific method is somewhat of a badge of honor and could win you a Nobel Prize.

We'll start with an actual research paper brought to my attention by Dean Baker purporting to find a relationship between high homeownership rates and future unemployment. As a general tip for laypeople and reporters on economic issues, the FIRST thing you should do when evaluating suspicious research is to check the source. Economics was called "Political Economy" for years FOR A REASON. It turns out this particular research was published by a researcher from the Peterson Institute and another researcher from someplace in the UK called "Centre for Competitive Advantage in the Global Economy". Now, the Peterson of the Peterson Institute is none other than Peter George Peterson, so read his bio and decide for yourself whether the institute he funds with $1 billion of his money from working for Lehman Brothers and founding the Blackstone Group is more about scientific inquiry or more about collective circle-jerking. (For extra credit, you might want to find out the political leanings and qualifications of the "seminar participants who provided valuable input". To start you off here's the first one.)

Anyway, the paper has all the classic indicators of lazy research and bad analysis. First of all, they take two aggregated data series: homeownership rates and unemployment rates and regress the two together, and are shocked, SHOCKED!, to find that somehow periods of high homeownership rates precede periods of high unemployment rates. This provides all the evidence they need to determine that somehow homeownership is causing unemployment.

Now, hopefully some of you are thinking: "Now, how can a scientist possibly come to such a sweeping conclusion from a single, simple correlation?", especially since they say as much in their own paper (last sentence of the introduction). Well, when you have a particular viewpoint to support, it's really easy.

But basic logic suggests that if there are many things that influence homeownership rates, and there are many things that influence unemployment rates, then there are many * many permutations of relationships between the many that influence the former and the many that influence the latter. For example, if many means 100, then many * many is 10,000 possible correlations between the reasons, going in both directions. If you were scientific, you would have to eliminate the 9,999 false ones to prove the one real one (or at least show that one is more significant than the others). But economic researchers typically don't do that. They choose one that suits their prejudices and just stop.

They also tend to ignore that many correlations just might have to do with the cyclical nature of the economy and have no causal relationship at all. Without looking at the data, I'd make a bet that homeownership rates tend to rise as the economy is growing, people's incomes are rising and their perceived creditworthiness is better; so they have a much better chance to afford to buy a house. I'd also tend to bet large sums of money that unemployment rates tend to rise when the economy is not doing good. Well, here your correlation is nothing more than the natural order of recession following boom. It's not surprising you find it in every country. I'd be really surprised if you didn't!

Anyway, the political thrust of the article is that homeownership is bad because it hurts labor mobility. I mean, if you let people own houses they might have kids and then put them in school and then you couldn't just fire them on a whim because they might not be able to find another job in their school district, or ask them to move to Toledo cause that's where they gave you the best tax breaks. Homeowners might want to not have a giant polluting factory in their backyard, and thus "hold up development through zoning restrictions". And...you know, in cough, certain sectors /cough of public-sector housing there are very high unemployment rates, too. Don't you know.

And there might be externalities, too! It might be good for people to fear for their job and therefore not buy housing...uh, wait. I got the causality reversed a little there. Anyway, I hope you can see that all it takes is a little bigotry and political money to fund reams of bad science. I just hope the reader can now read this type of crap with less credulousness and more humor. I actually giggled at this paper halfway through, reading it in sort of a mock-dramatic tone. A great stress reliever.

Anyway, we move on to another article from the other end of the narrow political spectrum. Here's one in the Atlantic about how Washington saved the economy yet permanently destroyed the labor market. Anyway, the second half of that title doesn't make sense at all, given that net employment has increased about 600,000 jobs over the past three months and unemployment has decreased by 673,000 since January. As the rate of job growth and the decline in unemployment seem to have been increasing in speed in recent months (they are historically weak for this point in the business cycle, yes, but that is not the point). The point is it doesn't seem to make much sense to claim the labor market is "permanently destroyed".

But when you think about it, the first part of the article doesn't seem to make sense either. Washington saved the economy? You mean Congress? You mean the stimulus from 2009? This one? The two problems with this explanation are, first, the obvious one, that the recession ended in June 2009, when the vast majority of the stimulus package was not yet spent. The second problem, usually overlooked by economists (but they will admit to this if you poke them enough with a stick) is that recessions are NOT CAUSED BY PEOPLE NOT SPENDING MONEY.

Let me repeat: recessions are not caused by people not spending money. Therefore, you cannot solve recessions by simply giving people money to spend. Recessions are caused by people not spending money fast enough. GDP is what is called a "flow" variable in the technical jargon. We compute GDP by hitting a stopwatch on January 1 of a year and hitting it again on December 31. We then measure a totally new GDP the next year. If you were meaning to spend $10,000 on the New Year's Eve sale on December 31, but got sidetracked (drank too much) and didn't get to spend it until the next day when you sobered up, your contribution to GDP would not be counted in the previous year not because you didn't spend it (you did), but because you weren't fast enough whipping out the wallet.

People spend money slower in a recession because they aren't getting enough income to spend. Since through a property called the "circular flow" (which isn't circular nor flowing but that's another story for another day) people spending slower tends to propagate the shortage of income, recessions have a self-reinforcing dynamic. If you were able to pump $1 trillion into today's economy by any spending program, yes that would seem like a lot (it's about 7% of GDP). However, if people were spending money just 7% slower, that would cancel out the entire stimulus assuming you could get every recipient the entire amount in the same year AND get them to spend it all in that year (and not do silly things like pay off their credit cards). Hopefully, you can see that even in theory, fiscal spending does not have a chance to work, much less take credit for it. (Now, just because it doesn't work like you want it to, doesn't mean it doesn't have benefits, like keeping people from homelessness and starving and all that, but again, future blog entry...)

It turns out, however, that's not what the article is all about. The Washington they speak of is primarily the Federal Reserve. Monetary policy taking credit for fixing the economy has the opposite problem as fiscal policy. Not that it was implemented too late to have possibly worked in the way its proponents say it did, but because it was being tried, and failing for nearly two years before all of a sudden the economy rallied on its own to validate it.

In theory, monetary policy should not work. The Fed does not print money, despite what a certain well-known representative Keynesian bloggers alleges. What the Fed "prints" is a very specific type of electronic balance sheet entry called a reserve balance. In order to get money out of a reserve balance, the bank will need to lend the reserve balance out to a party that will spend it so it becomes money by entering the circular flow. Of course, anyone with a lick of awareness knows that banks tend to slow down their lending during recessions, and you already know people tend to spend money more slowly. An increase in reserve balances during a recession is likely to either get lent out to really safe credits, like the Federal Government, or just sit on the books as an unlent "excess reserves". The current amount of excess reserves is about $1.5 trillion. This is the majority of what the Fed "printed" since 2008.

Furthermore, as has been already discussed, people are spending money slower in a recession, so even if the banks could find some consumer to lend to, they probably wouldn't turn it into money quick enough to make a difference. Anyway, don't take my word for it. The causation between money supply and GDP has been repeatedly found to be the reverse of economic theory (GDP growth causes the money supply to increase, rather than vice-versa), since economists have had enough data to run the correlations in the early 1950s. So it wasn't the Fed that saved us with quantitative easing, lowering interest rates to zero, or bailing out hedge funds. However, economists are generally content to ignore the painful truths for job security. Why would any rational person say the entity most likely to hire you is useless? Well, that, and he has a nice beard.

Okay, that should hold me for awhile. I'll be back after level 90.

A Trip to Uncertaintyland

I promised myself I'd leave the scolding for a much later date and talk about decision making in economics to make this blog a bit more useful to people.

Uncertainty is not a new topic to economics, but you wouldn't know it from the state of the discipline. Frank Knight wrote the most comprehensive analysis of uncertainty back in 1921. Most certainly it was the basis for uncertainty in Keynes' General Theory fifteen years later. Yet economics not only has not adopted uncertainty, it believes the opposite: people have perfect foresight. Sadly, without perfect foresight, equilibrium and thus most of economic theory would have to be thrown out. This is why Knight, despite his comprehensive understanding of the subject, still accepts this assumption, and also why Keynes discussion of the subject (Chapter 12) was a "digression" (his words) rather than the core of the book.

Let's take a quick tour of the certainty/uncertainty spectrum according to Knight.

We start out in Certaintyland. In certainty land things happen with a probability of 100%. Choice in this land is reduced to cost-benefit analysis. Since all things are certain, we simply weigh costs versus benefits when making decisions and choose the path with the best payoff. Very few choices in real life are made in Certaintyland, but some general broad choices fall into this category.

A personal example is my choice to drop out of grad school in 1996. The math was hard and the theory was ridiculous, but I suppose I could have stuck it out and passed my comps if I cared to. However, the starting salary for economics professors at the time was $40,000; and I already had a Masters Degree. Since the best I could do was known with certainty, it was easy to do the cost benefit analysis and determine it would be better to look elsewhere for future work.

Moving out of Certaintyland, we enter the realm of Probabilistic Certainty. This is also known as "Cards and Dice" Land, because conditions are much like many games of cards and dice. In the realm of Probabilistic Certainty, we know the set of possible outcomes and we know the probability of all individual outcomes with certainty. A single die has six possible outcomes and each outcome has a probability of 1/6. Risk enters into the PC realm, but only in an orderly fashion. We know the distributions of risk and we can write off a string of rolling five consecutive fours as a one in 7776 event.

The realm of Probabilistic Uncertainty is unfortunately where many experimental economists go, thinking it is Uncertaintyland. They design experiments where probabilities are known and payoffs can be calculated. Though uncertainty involuntary enters their experiments by design, they generally write it off as some decision pathology of the test subjects.

For example, Kahneman and Tversky in their work on Prospect Theory discuss the Pseudocertainty Effect, but the games that are played are all defined probability outcomes where an expected value can be calculated. The experiments "prove" that humans have a thinking disorder which craves certainty and thus shuts down logical thought. However, the same outcome would be achieved if the test subjects simply didn't believe in the probabilities given to them by the experiment - preferring to trust their intuition that probability under uncertainty is undefined. We'll return to this concept when we get to Uncertaintyland.

Leaving the PC realm, we enter the tiny, yet quite important, municipality of Probabilistic Uncertainty. This is a land of horse races and sports books, where the set of possible outcomes is known, but the probability of an individual outcome is not. In a horse race, there may be ten horses running. One of them will certainly win, but the odds of each horse winning are determined by the betting, and not the true qualities of the participants. Risk distribution in probabilistic uncertainty can assume any form, yet will tend to resemble a normal distribution with fat tails. Betting on horses will tend to keep the odds close to the true odds, because many bettors weigh indicators of success in the betting process. However, enough freakish events will occur (the 2-5 favorite injures a leg out of the gate) to make the normal distribution seem implausible. In this municipality, choices and risk are as much an analysis of the way people make choices and risk as about the actual risk. For this reason, the stock market and investment markets are located in this realm. Often, success can be reached by analyzing other bettors/investors behavior and looking for a pattern of mistakes: undervaluation or overvaluation of certain characteristics that takes place, due to the municipality's border with Uncertaintyland.

Once we leave the Probabilistic Uncertainty municipality, we enter the wilds of Uncertaintyland. In Uncertaintyland, the set of possible events is unknown and possibly infinite. Probabilities are undefined, because the denominator of the probability function is not known. Things happen in Uncertaintyland that nobody can imagine would happen. In addition, even things that can be forecast to happen with some reasonable expectation lose their meaning. A "bad" event may occur and not be bad. A "good" event may occur and not be good. This is because in Uncertaintyland events have more than one dimension. An outcome may have a magnitude or a duration, or it may be contingent on other uncertain events to determine its payoff.

Think about the possibility of losing your job. What do you think that probability is right now? I, as a Federal Government employee, may determine that probability to be nearly zero, but it is not. I could accidentally do something that is a dismissable offense. There are also things like shutdowns and sequesters that might not have been conceivable even a few years ago. One might not lose their job, but face a pay cut (dimension) or even get promoted to a higher paying position, but under a terrible manager that results in quitting the job soon after (good event being bad). The dimension effects of uncertainty mean that even logical, rational choices may not result in success, and the true meaning of the "odds" of any event reduce to 1 or 0. Things will either happen or not, and until the outcome occurs, the payoffs cannot be calculated.

That's enough for me today. I'll discuss the ramifications of uncertainty on choices in a following post.

Equivalencies

Had a tiling project delay me. Back to normal tomorrow, with no scolding. This first, though.

Dean Baker has a great post up stating the obvious.

Just as an example, suppose the Fed had, instead of recapitalizing banks directly, established a fund called the Negative Equity Removal Fund (NERF). The Fed can do this type of thing. Under this program, homeowners with negative equity could apply for negative equity removal. The application fee would be approximately $400 and would cover an appraisal of the home along with processing costs. Once the homeowner was approved, the NERF would conduct an appraisal of the house and compare its market value to the total mortgage debt and associated liens. The Fed would then purchase or cancel all liens on the home, with the homeowner receiving a new mortgage at current interest rates in the amount equal to the appraised value.

As an Assuming the house was appraised at $400,000 and had three mortgages totaling $600,000. After being accepted, the Fed would purchase all three mortgages from the respective lenders. The first mortgage holder would then have the option to issue a $400,000 mortgage to the homeowner guaranteed by the Fed. The fed would charge a fee to the lending institution of 1/4 percent or so to cover any default risk.

Note this policy would a) eliminate all negative equity for homeowners, lower their monthly payment significantly (smaller loan at lower interest rate), yet not give them any advantage over homeowners with equity; b) reduce the default rate for banks by replacing troubled loans with guaranteed loans; c) not require Federal funding a la TARP, since it would generate cash in the banking system exactly where needed; and d) accomplish the same recapitalization of the banks as a bailout.

The $8 trillion lost in the housing bubble is going to be with us for a generation, because an entire generation had their first or second source of wealth completely wiped out. Ten million homeowners are underwater, but all homeowners lost wealth. Most lifetime spending hypotheses would indicate that unless home prices return to their previous peaks (unlikely), that spending will be depressed until people grow up entirely unaffected by it. In addition, an entire generation is facing a much less financially secure retirement, and Social Security diminishing by the day.