January 17, 2012 § Leave a comment
Recently, I read through the latest World Economic Forum “Global Risks 2011” report which is an initiative of the Risk Response Network. It’s an impressive assessment of global risks produced in cooperation with Marsh & McLennan, Swiss Re, Wharton Center for Risk Management, University of Pennsylvania and Zurich Financial. What is compelling about the report is it is not simply a survey result or a list ranking, rather it details and illustrates the interrelationships between risk areas; identifying the causes in an effort to identify points of intervention. The report highlights response strategies and even proposes long term approaches.
As with any risk report, it has a tendency to feel alarmist, but its value and content cannot be dismissed and its emphasis on response is encouraging. The two most significant risks the report identifies are relative to economic disparity and global governance. The main point being that while we are achieving greater degrees of globalization and inherent connectedness, the benefits are narrowly spread with a small minority benefitting disproportionately. Global governance is a key challenge as each country has differing ideas on how to promote sustainable, inclusive growth.
The Rise of the Informal Economy
The report goes on to highlight a number of risks including the “illegal economy”. The illegal economy risk includes a cluster of risks: political stability of states, illicit trade, organized crime and corruption. Specifically, the issue lies with the failure of global governance to manage the growing level of illegal trade activities. In a recent book by Robert Neuwirth entitled, “Stealth of Nations: The Global Rise of the Informal Economy”, the author estimates that off-the-books business amounts to trillions of dollars of commerce and employs half of all the world’s workers. If the underground markets were a single political entity, it’s roughly $10 trillion economy would trail only the US in total size. Further, it’s thought to represent in the range of 7-10% of the global economy and it’s growing. To be clear, underground markets are not only dealing in illegal substances, crime, prostitution or drugs. It’s mostly dealing in legal products. Some of the examples Mr. Neuwirth provide include:
- Thousands of Africans head to China each year to buy cell phones, auto parts, and other products that they will import to their home countries through a clandestine global back channel.
- Hundreds of Paraguayan merchants smuggle computers, electronics, and clothing across the border to Brazil.
- Scores of laid-off San Franciscans, working without any licenses, use Twitter to sell home-cooked foods.
- Dozens of major multinationals sell products through unregistered kiosks and street vendors around the world.
A Global Risk?
Are the underground markets really a global macro-economic risk? Mr. Neuwirth makes solid arguments that these markets provide jobs and goods that are essential to these populations and that it is the corrupt authorities in most developing countries that are being worked around. In some ways, it can be argued that these unlicensed vendors and importers are the purest of capitalists; innovatively providing goods by avoiding intervention. In a recent interview in WIRED magazine, Mr. Neuwirth points out that Procter & Gamble, Unilever, Colgate-Palmolive and other consumer products companies are selling through small unregistered, unlicensed stores in parts of the developing world. He goes on to point out that P&G’s sales in these unlicensed market’s make up the greatest percentage of the company’s sales worldwide. I found this tidbit shocking. Really, a company that brings in over $80 Billion in revenue a year is actually pulling in most of its revenue through unlicensed channels? Now, that doesn’t mean P&G is directly selling through those channels, but they sell through distributors that may use others that do sell through to unlicensed vendors who don’t pay taxes.
The WEF concludes that illicit trade has a major effect on fragile country states given that the high value of commerce and resulting high loss of tax revenues impinge on national salaries and government budgets. An example that’s included in the report is that of Kyrgyzstan. “Members of the Forum’s Global Agenda Councils argue that the undermining of state leadership and economic growth by corrupt officials and organized crime contributed significantly to social tensions which erupted in violent conflict in June 2010, causing widespread destruction, hundreds of civilian deaths and the displacement of 400,000 ethnic Uzbeks.”
The Threat to Quality and Public Safety
So, if you were guess what type of goods top the list of sales that take place in these underground markets, what would you guess? Cocaine? Opium? Software Piracy? Cigarettes smuggling? Small arms? Topping the list with a rough estimate of $200 billion in value is counterfeit pharmaceutical drugs. Just behind at $190 billion is prostitution. Which leads me to the next serious risk issue if global efforts don’t improve to govern these markets: quality. I’m not qualified to address the quality of prostitution, but let’s consider the quality of counterfeit pharmaceuticals and the general issue of public safety. If these markets go unregulated and unmonitored, we are likely to see terrible abuse by profiteers whose only concern is to bring high value products to market quickly. No regulation also means an inability to create safe work environments and to protect rights of laborers all along the supply chain.
On the other hand, the vast majority of workers and consumers in developing countries thrive because of these markets. A strong effort to disrupt or disband these markets would cause a high degree of distress in communities that rely on these markets for access to essential goods. But in return, without tax revenue that can only be gathered from legitimate, licensed businesses can governments function and provide oversight services that would benefit quality and public safety concerns. It’s an endless loop as we say in the software world; a true catch-22. Even relatively well functioning supply chain operations at pharmaceutical companies in developed countries are consistently challenged to maintain a high degree of quality (note recent impact of product recalls at Novartis). Considering how much effort and money is spent on quality assurance, inspections, and FDA audits on legitimate pharmaceuticals, it’s beyond scary to consider the quality of counterfeit pharmaceuticals that are circulating in illicit markets.
Within the US, in the state of California, we’ve seen recent evidence of solutions such as bringing the trade of marijuana within the framework of the law. Potential results include ensuring quality and safety for the public, raising tax revenue and reducing the profits of organized crime. Still, the issue of economic disparity is a much tougher nut to crack. Widening gaps in income within all economies provide incentive for lower income individuals to work outside of established trade structures. This incentive leads to greater illicit trade which in turn hinders a government’s ability to effectively tax businesses and provide services such as regulatory oversight.
Can We Govern Illicit Markets? And If So, Should We?
These are obviously very difficult challenges, but ones that the WEF is analyzing in an effort to form solutions. The relationships between economic disparity, illicit commercial trade, public safety and government corruption becomes glaringly clear. How can the global community govern these illicit markets? They exist everywhere to some degree, even in the US where informal markets are estimated to account for 10-20% of GDP. One solution that WEF recommends is to strengthen financial systems. The implication is that weakened systems are the result of the heightened volatility and risk deriving from the recent capital markets crisis. With diminished confidence comes incentive to work outside the system. Some suggestions include:
- Better surveillance of the financial sector, including all systemically relevant players
- Tighter capital and liquidity ratios for all banking institutions (including non-banks), with higher ratios for systemically relevant institutions
- Risk retention for securitization (so-called “skin in the game”)
- Improved transparency and counterparty risk management in “over-the-counter” derivative markets
Perhaps the most interesting part of this global risk challenge is how interrelated these issues are. The influence that government corruption has on illicit markets is direct, but not the only factor. Further, the ability of governments to regulate, control and tax this commerce is not straight-forward and overly severe policies can prove detrimental to workers and consumers. And how much do other factors such as financial stability contribute to activity moving outside conventional channels? There is no certain view on these underground markets as we must consider why they exist, for whom they exist and how valuable they are for the good of all.
January 3, 2012 § 11 Comments
With each year end, all forms of media spew a tidal wave of predictions. From the apocalyptic to the mundane, we get predictions from prognosticators on who will win an Oscar to which Republican will win in Iowa to how well the market will do in 2012 to who will win the Super Bowl. But it’s not only during year ends that we get a hefty dose of soothsaying. It’s a public non-stop obsession. Dare I say, it’s an addiction. Predictions are in every facet of society – within industry, we are constantly trying to get insight on the level of demand this month for our products; the level of prices within each product type; and which company will gobble up which other company. The fact that foresight can be a key advantage when competing for resources and competitive superiority is not surprising. What is surprising is the amount of noise pollution and the insatiable desire to listen to that noise.
What is an Expert?
I still hear my favorite finance professor lecturing during one of my b-school classes about “experts”. He illustrated quite powerfully (obviously, it’s stayed with me for all these years), how poor predictions were made by economists on interest rates, GDP growth, oil prices, and stock prices among many other measures. In article after article, economists, industry experts, political experts, scientific experts were shown to be just slightly better than random guessing. What’s worse, most “experts” tended to influence each other, so that consensus predictions prevailed. The group of economists’ predicting the direction of interest rates tended to lump together in narrow ranges which indicated that working from the same sets of data with the same sets of assumptions, they also tended to create the same range of estimates.
Risk and Probability
We all know that the future is uncertain and that many unknown factors impact future events, yet we go to great lengths to predict. The bottom line is that we can draw conclusions that are more about probability than actual pinpoint calculation. If we normalize probabilistic outcomes for earnings per share for Apple this coming quarter, we can estimate EPS outcomes within ranges. If we believe published consensus estimates by analysts, we can find that mean estimates are at 9.81 with a coefficient variance of 4.39. Statistically, this variance is only significant for historical relevance and should not be seen as a predictor, but given analysts do not have crystal balls, they still use it as the main factor for setting probabilities. So, if we conclude there is a 95% chance that EPS will fall within the range 8.56 – 11.06 (or two standard deviations), we are essentially placing bets based on probability. Now, the valuation of a share of Apple common stock will vary greatly depending on where in this range actual EPS falls. Of course, there is still the 5% chance that EPS falls outside the expected range. And further, these numbers are purely estimates based on one set of assumptions that no two analysts would ever agree on.
When looking at all these predictions, it can quickly become apparent which “experts” are really viewing their data through a critical lens and which are simply along for the ride by echoing other expert’s viewpoints. What I find most discouraging is how confident some prognosticators are, especially those on television and web broadcasts. They emphatically proclaim their view in an effort to persuade viewers they are right – trying to create self fulfilling prophesies through persuasion – perhaps the most egregious offense. We see this regularly on political discussion panels where party-aligned or candidate-partial analysts make their case for persuading us what people really want and how they will vote. Are they really giving us a scientifically sound viewpoint or simply trying to manipulate our view about what will be?
Predicting Human Behavior
The digital age has provided a powerful platform for gathering information on individuals’ behavior. Companies can gain insight into buying behaviors as well as data on individual and group interests in entertainment, politics, as well as professional and social connections. The usefulness of this information is at once obvious and complex. For instance, if we know that there is better than 50% chance that a person buying a camera will also buy a camera case then it would be an effective sales practice to suggest a camera case at the point the buyer selects a camera. This practice is quite common now with online purchasing. We also see it fairly frequently with phone sales as well as with fast food ordering; e.g.: “Would you like fries with that?”. Recently, I was shopping for a new lawn mower and researching options on the website homedepot.com. Within several minutes, after performing a search on the site, a pop-up offer to chat with a representative came up. I took that offer as I had some questions about the models. After about five minutes, the rep offered me a 10% discount if I’d like to purchase the item online and he’d help me through the purchase process. I had already made the decision to buy the item, so I was happy to get this discount, but I wanted to pick it up at a store near me rather than have it shipped. Their process allowed for this flexibility as I could purchase online and the item would be instantly put aside for me to pick up that evening. This process was ingenious. What percentage of people shop to the point of sale and then drop, reducing the chance of buying the item through the original site or perhaps not buying that item at all? This new discount offer through the chat rep can help homedepot.com reduce that drop percentage. Now, Home Depot does not know if I would have purchased that item that day online anyway and they do not know if I would have gone to the store and been willing to pay full price. The fact is: there will be some percentage of margin they relinquish for the sake of capturing a higher percentage of potential sales. Home Depot, like so many other retailers, banks, insurance companies, and drug companies are in the business of prediction – predicting what you will do if they communicate with you in a certain way at a certain time.
Statistical Sampling – A Foundation for Predictions
Statisticians often tell a joke about a man with his head in a refrigerator and his feet in an oven – on average he feels about right. Sampling is used to determine probabilities and to make decisions on the level of risk we are taking. It’s sampling and probability that determines the rate we pay for life insurance, car insurance, and all other types of insurance. So, when we try to predict Apple’s earnings per share for next quarter or whether a catastrophic disaster will strike an Asia Pacific country next year, we must calculate the odds, the percentages, the probabilities. The fact remains, however, that not all outcome distributions fall into a normalized curve and highly unlikely events can be game changers.
Prediction should be all about risk, uncertainty, and likelihood, but what you’ll hear this week and throughout the year is a chorus of experts telling you with great certainty what the future will bring. Don’t believe them. If you’re jonesing for advice, try listening to those who are providing detail on probability, risk and trends. But know that the future is never about certainty and always about probability. When prognosticators get it right, they were just plain lucky. They may have played the odds. They may have had some truly intuitive insight that others did not. But there is never a sure thing.