Beggs is a Ph.D. Candidate at Harvard and focuses on behavioral economics (incentives, generally).  She has a great sense of humor and does a great job of relating the sometimes complex and arcane concepts of economics to the average reader through her humor.  As she notes:

In a perfect world I would be some sort of odd hybrid of Steve Levitt (see Freakonomics), Demetri Martin (see here) and Jon Stewart (hopefully you don’t need any clarification on that one). Stated another way, I want to trick people into learning stuff and entertain them in the process.

Enjoy!

Traditionally, credit rating agencies–such as S&P, Moody’s and Fitch–served as a sort of signal or barometer for investors as to the level of risk attached to specific corporate bonds.  Over time, they began rating additional types of investment products, including new financial instruments such as collateralized debt obligations (CDOs) that consisted of massive bundles of subprime mortgages.  Amazingly, these agencies rated these products AAA–the highest possible rating, indicating “the highest level of capacity of the obligor to honor its financial commitment on the obligation.”  The importance of this cannot be understated.  What makes this particularly troublesome is that the firms that issued the debt were the ones paying the CRA’s for the ratings, creating a significant conflict of interest.  Common practice, sure.  But given what transpired in this particular case such a conflict cannot help but be scrutinized.

What was once a reliable indicator for measuring the level of risk attached to an investment has now come into question as possibly nothing more than a rigged instrument.  Now, US Congressional leaders are focusing aspects of their financial reform bill on the CRA’s.  Senator Dodd’s version of the bill included a number of provisions aimed at restoring trust and confidence in these vital agencies.  Just yesterday, the Senate passed an amendment offered by Sen. Franken (MN) that would require a newly-formed government body to assign the task of rating a specific asset-backed security to a specific CRA.  The hope is that such a move would end the practice of ratings shopping that many believe led to creation of perverse incentives by CRA’s and the misleading rating of unstable securities.

I am not by any means an expert on the CRA industry (I know just enough to be dangerous, I guess), but here is my take.

The overall goal should be to create a ratings system that is both widely used and viewed as credible by the investment community. The major issue here is that we need to end the conflict of interest (or perception thereof) that exists when you have a ratings agency being paid to evaluate and rate the level of risk of a complex financial instrument by the very organization that is issue the instrument.  I think the Franken amendment is coming from the right place, but in the end it might be misguided.  Creating a federal agency to determine who gets to rate which security may continue and further perpetuate the false sense of security that investors have in the accuracy of these ratings.  The governmental seal of approval can also induce perverse behvavior.

What I would suggest is the creation of an agency that would manage the oversight of CRA’s in a way that still allows for the market to not only evaluate risk but also evaluate the CRA’s and the ratings they issue.  Here are a few approaches that I think would be helpful:

• (Good) Require multiple ratings for any single security: As with anything, there is power in numbers.  If the government agency is going to determine who rates a single security why not involve more than one firm?  Why not three CRA’s and the eventual rating is some kind of weighted average of all three?  This could help remove the false sense of security from the government seal as well as the conflict of interest between issuer and CRA.
• (Better) Provide greater transparency into the ratings process: A better understanding of how the CRA came to it’s conclusion would allow investors to contextualize the rating and how reliable that rating is.  How we cast the die is important when it comes to risk analysis.  Knowing the model, the assumptions, and the data sources provides investors a chance to weight how reliable the rating actually is.  Even if the issuer pays off the CRA investors can independently evaluate the reliability of the particular rating.  Requiring a standard period of review before the security is available for sale would allow for independent evaluation.
• (Best) Institute rigorous evaluations and independent rankings of ratings agencies (Moneyball-approach): Right now I believe the federal government can register a CRA, but lacks the tools and ability to continuously evaluate and possibly deregister a poorly performing CRA.  What we should be able to do is come up with a way to rank CRA’s against each other based on the reliability of their risk assessment for securities over time.  Think of it as a Value-Over-Replacement-Rater or VORR, similar to the way that professional athletes are now rated and their value determined (Value-Over-Replacement-Player or VORP).  Given the mass of historical data on securities ratings and their performance it shouldn’t be too hard to create a VORP-like rating system that could be updated in real-time as the value of securities rise and fall.  This way, it isn’t simply a government’s stamp of approval or a firm’s reputation that determines the level of trust investors should have in a CRA’s ratings.  Instead, investors can see in real-time how reliable a firm’s AAA ratings are versus the average CRA.  With such a methodology we might be able to avoid both the government providing a misleading seal of approval as well as the damaging conflicts of interest between raters and issuers.  Issuers could still shop around, however if they choose to use a CRA that will give them a favorable rating but has a very low, public VORR they will likely suffer in the end as investors will be less likely to buy the security.  In fact, you would likely see the buy-side institute rules that incorporate VORR ratings into their buy decisions (i.e. no security may be purchased if rated by a CRA whose VORR is less than X).

Like I said, this is not an area I know particulary well.  Any readers at there more steeped in the CRA area that can offer some perspective.

At a time when many economists and financial commentators where underplaying, if not downright ignoring, the looming credit crunch, Roubini was warning of the impending chaos of the markets.  Some may claim that he was simply lucky (even a broken clock is right twice a day), but Roubini’s arguments were always couched in explicit logic and backed by relevant data.  I can remember reading his musings while still in graduate school and hoping that his analysis was flawed.  Unfortunately, it wasn’t.  Lately, he has been warning about the potential problems of sovereign debt and there are signs that once again his perspective should be taken quite seriously.

Even if he never goes on to predict another major economic event he still managed to be on point with the meltdown of 2008, and that is no small accomplishment.

Some folks are leveraging newly available data in urban areas as analytical shortcuts:

Ted Egan, chief economist in the San Francisco Controller’s Office, said he could wait six months for California to release the detailed sales-tax data he needs for city revenue projections. But it’s quicker to look at passenger tallies from the station closest to the Union Square shopping district, which generates roughly 10% of the city’s sales-tax revenue. The Bay Area Rapid Transit District releases the data within three days, he said: “Why should I have to wait?”

Mr. Egan is among a growing number of economists and urban planners who scour for economic clues in unconventional urban data—oddball measures of how people are moving, spending and working.

Egan has essentially found an analytical shortcut which allows him to see the world as it is more quickly.  Rather than wait for the actual tax receipts, Egan can look at a related measure and extrapolate from there about tax revenues.  Notice, Egan isn’t interested in why tax revenues and sales activity is low or high, he’s just trying to quickly get a handle on what the amount is.

This is illustrates the utility of correlational analysis and the promise of Big Data and data mining.  The danger, of course, is that many of these new indicators may be untested and more volatile.  On the other hand, new data may actually do a better job of capturing people’s patterns and motivations under certain circumstances and such a preview allows for business and policy makers to adjust more quickly to a rapidly changing environment.  For example:

Mr. Leamer discovered that truckers’ diesel purchases on Interstate Highway 5 from California to Oregon, a major timber-trucking route, are a leading indicator of construction employment in California. Diesel sales on Interstate Highway 80 from Sacramento to Salt Lake City, a trucking route for the San Francisco Bay area’s manufactured goods, can help predict California’s manufacturing employment, he said.

If only he had the diesel-fuel data in the first half of 2008, when major government-issued indicators failed to hint at the U.S. economy’s impending downward spiral. At the time, Mr. Leamer said, UCLA forecasters chose not to announce a recession because GDP was still growing and the Bureau of Labor Statistics was reporting relatively mild job losses.

Bad call. The government later revised the GDP and jobs data downward, and the National Bureau of Economic Research concluded that the recession started in December 2007. The jobs data are unreliable because they are based on sample surveys and don’t adequately capture company openings and closings, Mr. Leamer said in hindsight.

When the UCLA economists reviewed the fuel-purchases data late last year, they saw diesel buying had peaked in mid-2007, indicating that fewer goods were being made and moved across the country in the months after. “Had we been aware of that data in 2008,” Mr. Leamer said, “we would have made a different call.”

In business and government, sometimes quickly knowing “what” is happening is more valuable than waiting to know precisely “why” it is happening.

Further confirming this notion is Anna Katherine (A.K.) Barnett-Hart and her brilliant senior thesis from Harvard on the subprime mortgage CDO meltdown.  Her thesis has been getting tons of attention, including praise from leading economists and author Michael Lewis who, in the acknowledgments to his new book, said the thesis was “more interesting than any single piece of Wall Street research on the subject”.  The data collection alone is masterful and a coup given the opaque nature of this market.

Barnett-Hart concludes that the meltdown in the CDO market resulted from “poorly constructed CDOs, irresponsible underwriting practices, and flawed credit rating procedures.”

A pdf  version of her thesis can be found here.

The problem is not just that specific rules – higher bank capital requirements, for instance – threaten profits and are therefore opposed. It is that all governments see themselves as partners of their industries in world competition. Regulators seek not a level playing field but one tilted to their own groups’ advantage. This is not a hidden bias. It is proudly advertised. A government that did less than stand up for its own companies would be seen as failing in its duty.

In finance, a footloose industry, this striving for regulatory advantage undermines rules imposed by other countries. Financial regulation will underperform until regulators work more closely with counterparts abroad than with those they police.

[...] Pieces of the needed reforms are reasonably clear. They include higher capital and liquidity requirements, linked to size and to the credit cycle. Orderly resolution arrangements must be designed for non-bank financial groups as well as banks. There is growing support for requiring contingent capital (bonds that convert to equity under stress) and subordinated debt (increasing creditors’ exposure to writedowns). These should strengthen market discipline over risk-taking.

Such measures will meet resistance, especially if done unilaterally. The industry will cry competitive disadvantage. International co-operation is therefore essential. But discussions among regulators are moving slowly. While America’s turf fights remain unresolved, it is not even clear who should speak for US regulators.

I would agree with Crook.  If policy makers focus too much on the domestic arena their best efforts will be doomed to fail.  Not only must they take into consideration how the effectiveness of their reforms will be partially determined by similar actions in other countries, but they should be using the international arena to their advantage.

One way would be to use international negotiations and commitments as a way to gain leverage over the powerful interests of the financial industry who see less regulation (even sensible regulation) as against their interests. There is a rich literature on the use of international organizations and agreements as commitment mechanisms, a way of “tying one’ hands” so that what are normally tough reforms domestically due to lobbying and special interest pressure become easier to resist. If the Obama administration wants to pass sensible financial reform it might consider focusing more on finalizing international standards across, say, the OECD in order to shift the domestic playing field to its advantage.

As he eloquently demonstrates, the old terms of First World and Third World really no longer apply. Rather, the majority of the world is either highly developed or moving significantly in that direction. However, there is a portion of the world—about 1 billion people—whose countries are on the outside looking in when it comes to economic development. Collier’s work, and this book, offers an explanation as to why the countries that make up the bottom billion have failed to develop and what can be done about it. Books of this nature typically stake out a position along one of the ideological poles and hammers away at the other pole for three-hundred pages or so—Aid is bad and does nothing but fill the coffers of corrupt leaders and make the population dependent and lazy! Capitalism is the enemy! Rich countries use their power to exploit the labor and resources of these countries for profit, therefore protectionism and transfers of wealth from the developed world are needed! As it so often does, the truth can be found in the middle.

Collier lays out various “traps” that countries can find themselves in–conflict, resources, geography, and governance–all of which provide extensive barriers to economic development. All of these have been hypothesized by others, but Collier & Co. tease out the specific ways that these traps work. For example, while landlocked countries generally find themselves without realistic alternatives to growth there does appear a way out–development by their neighbors (particularly in terms of infrastructure) leads to increased growth for the landlocked country. Understanding that geography is a powerful variable, but does not equate to fate, leads to various policy prescriptions that can credibly be applied to these particular cases. It also highlights the friction that is politics. Collier acknowledges the powerful role of politics in both his explanations and his prescriptions for the least developed nations. Countries and leaders are generally self-interested, and this makes political solutions difficult to come by when dealing with the poorest countries in the world. Collier has a few ideas, some of which have been adopted by leading countries and organizations. However, it is too early to tell if they have the kind of effect he hopes they will.

My one complaint is that Collier does not provide a graphical summary of the numerous hypotheses that he confirms and nullifies. Nor does he provide a summary guide to the additional theories and mechanisms that he proposes. The book is stuffed with propositions and results that after a while it was hard to remember just what was proven and falsified, what mechanisms Collier suggested that may explain the peculiar relationship between, say, aid and coups. Now, I read the Kindle version, so maybe such graphics were available in the dead-tree version.

Overall, Collier’s book was well worth my time. I am excited to read his follow up, War, Guns and Votes, but it will have to wait as I’ve got a few others ahead of it in the queue.

Lewis’ new book, The Big Short, focuses on the instruments of the crisis as well as those few individuals that profited from the crash–those who shorted not a particular company or sector, but the entire system.  On the way back from a meeting today I heard Lewis talk about the book on NPR’s Fresh Air.  His account sounds fascinating, to say the least.  In typical Lewis fashion, he focuses on a few protagonists and uses their stories to explore a larger, more complex story–in this case, how the financial industry become enamored with mortgage-backed securities, the process of selling (through CDO’s) and insuring them (through CDS’s), and how that lead to the exponential increase in systemic risk. In the case of The Big Short, Lewis introduces us to a few of the contrarians who realized early on that the market was set for failure. As Lewis explains:

“Everybody [on Wall Street] was working with the same set of facts about subprime mortgage lending — about how subprime mortgage loans were turned into bonds and repackaged and turned into CDOs and so on and so forth,” Lewis tells Terry Gross. “[And] the vast majority of the people in the markets took those facts and painted one kind of picture with it; it was a very pleasant picture. And a very small handful of people took the same facts and painted a completely different kind of picture with it. [I wanted to find out] ‘What is it that enables [the people who bet against the market] to paint that picture?’ and ‘Why do these people look at the world differently?”

“This is the story of human perception as much as it is anything else. And their attitude toward the financial markets was peculiar,” Lewis says. “It was peculiar to be running around the world looking for unlikely things that might happen. … And it told you something about Wall Street and … the way the markets were functioning when they were dysfunctional. There weren’t enough people thinking this way. There weren’t enough people taking into account the real likelihood of extreme change in the world.”

I’ve got The Big Short on my to-read list (there are currently two books ahead of it in the queue). I’ll be sure to post a review once I’ve finished it.

You can listen to the entire interview here.

A pair of researchers have developed a similar test to determine whether humans can tell the difference between actual financial market returns and randomly generated data:

[Jasmina Hasanhodzic and Andew Lo] have devised a simple experiment.

They have created a computer game in which a player is shown two time-series of data. One is real data from a financial market such as the US Dollar Index, or the spot price of Gold. The other is the same data randomly rearranged. The player has to guess which is the real series and is immediately told whether the guess is right or wrong.

They found that very quickly subjects were able to determine what was randomly generated data and what was actual data.  Actual data was much smoother and therefore easy to spot against the bumpy, randomized data.

It is an interesting experiment, but it doesn’t break any ground in terms of human cognition.  We’ve long known that humans seem hardwired to quickly visualize patterns, likely for evolutionary reasons since it is advantageous to quickly recognize predators.  We’ve all experienced the sensation of effortlessly seeing faces or objects in clouds, for example.  This experiment just confirms the notion.

Nobody wins forever. It just doesn’t happen.

What we see in reality are millions of corpses of businesses and ideas that have made their impact (or not) and then petered out into oblivion without leaving much more than a memory. Some of them get bought and swallowed by a bigger company, others have their ideas copied and commodotized and many just don’t have the business or financial chops to make it all work for more than a few years.

So what if instead of worrying about all that you just decided at the beginning you were going to end it all six years in?

I love questions like this, and Noah is great at asking them.  He suggests that such an arrangement may solve the problems that arise when management sacrifices the long-term interests of the company for the short-term, making decisions that optimize their current job security but may create problems for the firm down the road:

Company management doesn’t know how long the company will last, so they optimize for the now (they also don’t know how long their jobs will last, but I’ll get to that in a minute). It may be overly hopeful, but as long as one choose a reasonable time-frame (5-10 years) I wonder if you couldn’t lift the decision-making out of the immediate.

It is an interesting idea, but I think that what Noah is mostly interested in here is a shift in how employment is structured (i.e. knowing up front when one’s job will terminate), rather than how businesses as a whole are set up.   (If the business will shutter its doors in 10 years what precisely are the long-term interests of the firm?)  Additionally, he focuses more on the employment issue towards the end of the post.  In either case, I think that on the whole the uncertainty that exists in terms of business and employment termination is superior to expiration dates.  Here’s why: If businesses were set up at the outset with a planned time frame at the end of which the business would wind down it would likely play havoc with their ability to compete in the marketplace. Additionally, the beneficial economic conditions that obtain through competition would be warped. Why? Because businesses would not have to operate in the shadow of the future.

The shadow of the future is a concept that comes from game theory and relates to how actors’ incentives and behaviors change depending on whether they are playing a game that ends after only one round or if it will go on indefinitely.  In a single-round prisoner’s dilemma, each actor knows that they will not have to interact with the other after they make their decision to either stay quite or rat their partner out.  Since they’ll never interact again, their preferred choice will be to rat the other out in the hopes that they receive a mild sentence or get to go free.  In an iterated prisoner’s dilemma, the same choices will obtain unless the players are unaware of when the game will end.  The fancy term for this is backwards induction, but basically the idea is that if players know when the game will end it will create the same incentives as if the game was only one round.  However, if the game is repeated indefinitely, if players must operate within the shadow of the future, then cooperative behavior is more likely to evolve.

Businesses

In a market, we do not want businesses cooperating too closely.  Partnerships, licensing deals, sure.  But we abhor collusion.  Why?  Because it distorts the very market dynamics that are supposed to give rise to all the benefits of a market economy.  Open competition by individual businesses will lead to better products for lower prices.  Collusion amongst businesses or the formation of monopolies works against this.  And while collusion is to be feared, so to should any development that threatens the existence of competitive pressures on businesses.  If dominant businesses in a market are known ahead of time to be set to expire after, say, 6 years, other businesses that have not set an expiration date will feel little pressure to improve their product or service.  Why?  Because they realize that in a few years consumers will not have the superior products or services to turn to.  This being the case, the businesses that will survive the expiration of the dominant businesses will have no incentive to bring their performance up to the level of the best businesses.  When businesses are unsure as to the viability of their competitors they must assume continued competition and therefore better manage their firms in order to compete and survive.  Artificial expiration, particularly that which is decided up front, would likely decimate the competition mechanism.

Employees

But what about employees?  Would management and other employees make better decisions, decisions geared towards the long-term interests of a firm, if they knew ahead of time when their tenure would come to an end?  This argument has been floating around for some time, particularly with regards to GM’s in professional sports.  While GM’s are given long-term contracts, they can be fired at any time.  Towards the end of their contracts the amount of money due to them decreases and therefore the amount of money the team would have to eat if they fired the GM also decreases.  This can create perverse incentives to create short-term success at the expense of long-term competitiveness.  Think of a baseball team where a GM is on the hot seat.  If they don’t produce a playoff team the following year they will likely be fired.  One option is to empty the farm system in order to trade for older, proven players.  By bringing in proven talent, the GM increases the chances that the team will perform better in the short-term, securing their job and possibly another contract.  But by emptying the farm system the GM risks crippling the team in the long-term.  They will have less low-cost talent to deploy while having taken on large, guaranteed contracts which will reduce the team’s ability to build competitive teams in the future.

So what if management doesn’t have the uncertainly of a new contract hanging over their head?  Would they then shift to making decisions that are in the long-term interests of their companies (this assumes the firm has no expiration date)?  I am not so sure.  Since no new contract is possible, employees in this scenario would likely be motivated by reputation.  Their legacy becomes more important than short-term financial incentives.  But the problem with the long-term is that, well, it’s long-term.  It could be 15-20 years or more down the road.  The farther away we get from decisions the harder it becomes to connect future results with previous policies.  Whether or not the long-term fortunes of the company will be associated with the legacy of a former employee becomes less of a clear-cut issue.  So while expiration dates for management may not increase incentives for selfish short-term behavior, it may not decrease them either.  Incentivizing long-term decision-making requires creating the shadow of the future for employees, even after they’ve left the firm.  Stock options that are valued and redeemed years after management has left is one potential (but not unproblematic) mechanism.

All of this is not to say that the answer to Noah’s question is that it’s a bad idea.  However, I think that, on balance, there must be a prominent role for the shadow of the future in order to prevent the market from being distorted.