Archives for posts with tag: public policy

Capitalism vs. Corporate Management

May 16, 2013 //
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Our economy isn’t working as it should. There’s economic unfairness, unemployment remains stubbornly high, and there seem to be few political answers to the great mass of people feeling the pinch of hardship. There is an enormous and seemingly accelerating concentration of wealth at the top, and a questioning of whether our economic system serves the majority.

To misappropriate Churchill, capitalism is the worst possible choice of economic system – except for all the others. We do not, in any case, live in a purely capitalist world. All economies are mixed to some degree, by necessity. Without an independent arbitrator (The government) to control the relationship between economic actors, there could be no capitalism anyway, just a quick devolution to a system of monopolies, practically (and ironically) indistinguishable from communism.

This preamble isn’t meant to moan about how things are. It’s just useful to remind ourselves that the world as it is can be changed, if we keep a firm grasp on the obstacles preventing us from getting there. One of the biggest sources of rot in our current economic climate is the perception and reality of unfairness, and one of the worst exemplars is executive pay. Most of us have at some point heard some variant of these statistics: a CEO decades ago earned about 20 to 30 times what the average worker did, but now he earns hundreds of times more. Sure, apologists can quibble about how certain sectors see less of this effect than others, and how bankers, in particular, are now somehow exempt from ordinary industrial concepts of economic effort and reward, but it is indisputable that there has been a change in what constitutes wealth accumulation at the top, compared to the past.

Even worse, from the perspective of someone who wants to see a functional, efficient system of wealth creation spread across society, is the reward of incompetence, if not outright malfeasance, to corporate heads who run their companies into the ground, shortchange their workforces and damage the environment (Both literally and figuratively) in the quest for short-term personal reward. Much was made a few years back of how the mechanism of stock options was the culprit for much of this economic short-termism and bad leadership. Managers given stock options planned and managed the actions of the company just to make sure the stock was high at whatever point in time they could cash out those options, rather than managing with the goal of making sure the company could thrive long term. Cutting the employee count to the bone was one favorite method, since chopping off payroll shows up as profit on the balance sheet. Short-changing R & D another. But both those actions, and similar ones which trade off future investment for a better short-term balance sheet, incapacitate the company when it comes to future growth. How can a company make better products when there’s no investment in research and development? How can it meet future growth when employees with institutional knowledge have been sacked? That isn’t capitalism, it’s cronyism run rampant.

However, while stock options have been a destabilizing factor in high-level corporate management, they are just a mechanism of reward. If we take away options, people in charge of reward will find something else, similar enough to have the same effect, but different enough to escape complaints for a while.

No, to fix the problem you have to change who gets rewarded and by whom. Ivory tower economists, an unfortunate number of whom make a living apologizing for the real faults of capitalism without addressing their causes, make the argument that corporations are run for the benefit of shareholders. Pure horse manure. If that system ever really worked, it is demonstrably broken at present. Too many corporations in America are nowadays run for the benefit of the top managers and the board members themselves. In the idealized classic capitalism of Friedman et al, the board is supposed to represent the shareholders and see to it that managers run the corporation well. Which is why people could at one time claim with a straight face that a corporation’s only function was to maximize shareholder value. But what happens when the managers of one corporation are the board members of another? When they are all the same people, where is the incentive to ensure good management, an abstract ideal, rather than just pillage the corporation for personal pay and wealth (and the individual shareholder can go hang)?

Our American system of capitalism has become infested with corruption at the top, where the highest levels reward themselves at the expense of the company they are supposed to serve. And who can blame them, when there is no sanction against such behavior?

I propose a simple rule. No single person working for one company or corporation can serve on the board of any other. Period. And to prevent a revolving-door effect of cronyism, no person may serve on a board who has worked for any other company, until at least ten years have passed. The intent, of course, is that managers who retire will only be able to serve on the board of their old company. Might that have the effect of concentrating their minds on the long-term effects of their decisions? Might it also mean that companies are led by people who align their own interests with that of the company for the long run, rather than seeing it as a cow to be milked for short-term personal gain? Might boards then make decisions of executive pay and reward based on the best interests of the company as a whole, which is what they’re supposed to do?

One can certainly hope so.

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Finance and Physics. And math.

May 4, 2013 //
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There’s a interesting interview in Scientific American about the possible intersection in advanced mathematics of physics and economics (http://blogs.scientificamerican.com/cross-check/2013/05/01/author-of-the-physics-of-wall-street-ponders-strings-black-swans-and-a-final-theory-of-finance/).

While I’m all for any kind of cross-fertilization of ideas across different disciplines (A great quote I once heard is that Universities shouldn’t teach Psychology, History, Literature or other liberal arts disciplines but just one thing, “Human Studies”. And Math), I feel there’s an elephant in the room in this discussion that isn’t mentioned, and that’s the fact that economics/finance differs from Physics in their fundamental inputs.

Both of the disciplines use math to attempt to explain, and thus accurately predict, reality. However, economics is attempting to describe reality while looking through the rear-view mirror, as it were, while physics by definition describes reality in a more all-encompassing sense. Physics is independent of what’s gone before, so predictive behavior is just that: a mathematical physics model will accurately say what we can expect in future. To choose just one example, the idea of a red shift, of an expanding universe, was understood to be correct even if we couldn’t see it with the tools at our disposal when first posited. With more advanced telescopes, the theory was shown to be demonstrably true. One can attempt an economics experiment which ignores basic human behavior, but the predictive qualities are, to be kind, lacking (Soviet Union, anyone?).

The study of economics and finance also has a completely different rewards system than that of physics. While a finance mathematician is looking to, in a very real sense, maximize profits, a physicist is looking only to validate theory. Rewards come only if the theory is true, not if it proves a temporary benefit relative to other researchers. This is important because we don’t have any notion of objectivity in finance equivalent to the objectivity found in physics (Demonstrable and replicable testing to prove validation). Instead, finance and/or economics is a rolling road of constant experimentation where the inputs are not fully understood, and the experiment cannot be easily replicated, if at all. In addition, there is a financial incentive to misdirect others in order to maximize gain (On the most basic level, something like insider trading of classified information, on a macro level, lobbying for financial policies which are detrimental to the economy at large but serve a narrow,parochial, temporary interest). Math is that circumstance is just a tool, to be used for “good” (accurate, predictive, explanation of behavior) or “ill” (temporary profits at the cost of understanding).

The ideal in both cases is to explain the world we live in. Attempting to understand the world in an all-encompassing way through math is not a recent human endeavor. Descartes, for example, used the clockwork analogy of the universe to explain reality: the universe is predictable, like a clock, working with predictable mechanisms. Our lack of understanding the future is dependent on the fact that we simply don’t know what all the pieces are, what they do, or how they interact. If one could have a massive consciousness (He used this to argue for the existence of God, since such an understanding was obviously beyond our limited human brain capacity), one could see the future, because we could see how the interaction of everything, from the proverbial beating of a butterfly’s wings in Brazil to the marching of an army, interacts and affects reality.

Math in the service of science, whether economics or physics, has the same primary purpose: to predict what will happen next. But economics in general, and finance in particular, does not start from a truly scientific base. Simply put, there is no objective reality when it comes to money. Our economic system “works” in the sense that people can have jobs, earn money, procure goods and services, and hopefully enjoy a rising physical standard of living, but there is little that is objectively demonstrable or replicable in this field of human behavior. To take it to the most fundamental level, the dollar bills in my wallet are nothing but pieces of paper, of no inherent value, without the collective notion of the world in which I live, that they do, indeed, have a value commensurate with the numbers printed on them. The digital flow of ones and zeros that make up “money” in the modern financial world is even more arbitrarily connected to any physical value.

This is a far cry from classical physics. A hydrogen atom does not gain electrons or protons because of changes in politics, tax or fiscal policy or the movements of markets. The element table we all learned (In my case, sort of learned) in High School doesn’t change due to social change. But the value of a dollar, or of any currency, does in fact change, rather arbitrarily at times. It changes because although there are hard, physical factors which make up part of the input data base of economics (A factory turned out x number of widgets this month. An oil well produced so and so many barrels last year), there are also factors which, though influential, are incredibly hard to predict because they are disconnected from that type of real, physical thing or process (For example, political instability in a country causing a run on banks).

In this case, the seeming certainty of mathematical models can have a detrimental effect on economic studies because the mathematical model will only be as reliable as the information on which it is based. To be truly accurate, mathematical economic models must be able to incorporate all the incredibly diverse sources of information, from crop yields in Argentina to the housing market in Singapore, which might possibly have an impact on any economy in our interconnected world. Not only that, but the model must incorporate this information in correct proportion to its effect. Not only that, but it must also incorporate those “non-economic” factors, mainly but not solely political, which affect economies, again in proper proportion to likely effect. Not only that, but the data itself has to be valid and trustworthy, and ideally, immutable.

This is an extremely tall order.

Now, this essay is a bit of a red herring, in the sense that these quasi-philosophical musings are not, strictly speaking, what the article cited above is about. The two individuals in the discussion are talking about math in the service of financial models such as what hedge funds use to maximize their returns, and whether the math models of physics might have some useful influence. But those financial models remain divorced from the sort of real, verifiable data from which physics benefits. It is for this reason that, despite some of the best mathematical minds residing and working in Wall Street, we have “unexplained” financial catastrophes that no one supposedly sees coming. As the saying goes, it’s hard to build a castle on sand, and the economic data which goes into the models Wall Street uses are really just that.

This is not to argue that finance or economics doesn’t benefit from advanced mathematics. But as useful as economic models are, whether derived from physics and applied to finance, or created in situ, they can only serve with the constant understanding that just because they are numbers, and therefore seemingly certain and distinct, they remain at best estimates based on a sea of informational uncertainty.

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Social Capital Index – Measuring success?

April 23, 2013 //
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When can we say we’ve won a war? As Americans, we have a tendency to mobilize for collective action only when our leaders declare war, whether actual military wars against other countries or entities, or more nebulous concepts like wars on terrorism, drugs, poverty or homelessness. This is the devilment at the heart of attempts to analyze things which can only be understood in a complex context. Of course, that shouldn’t stop us from trying. However, numbers have a validity, and take on a life and importance of their own, outside of more discrete methods. Anyone who’s worked in a bottom-line oriented organization knows how difficult it is to convince on the basis of “feelings”, even if they may be, sometimes especially if, they are correct. So how do we get to a place where leaders, decision makers and the general public can have some idea of how we’re doing on our various attempts to battle social ills? If it’s true that data shapes policy, then we should make sure we use data that accurately reflect broad policy goals.
What are the numbers, where do they come from, what are they actually showing, and what is the context in which they’re interpreted? Every bureaucracy, whether the military or a neighbourhood soup kitchen, tends to see data through the prism of their expectations, which might be at odds with the larger strategic goal. Whether counting victory as larger body counts while losing the greater war, or serving more meals while the homeless population steadily increases, it’s problematic to be blindsided by smaller tactical issues if we have no way of knowing whether we’re succeeding in our larger goals.
The biggest problem is the human tendency in fighting vaguely-defined ills is that their very nature enables rent-seeking, which is an economic term meaning the individual desire to collect rents without any actual economic contribution. We see this across all human activity, and it can be an incredibly powerful driver of behavior. As some anonymous wag once said, nothing is as difficult as persuading someone of the untruth of a fact when his paycheck depends on it being true. Much waste and fraud can be seen in this context where the outside situation changes, but the individual or group tasked with dealing with the original problem refuses to change their behavior to suit. After all, growth is the only goal, why act against it in the present even if ancillary costs (future pollution, non-competition, etc.) might well strangle it in the future. Bureaucracies set up to fight one battle may find the war won, but continue anyway through inertia and the individual interests bound up in that collective. I mention bureaucracies because they tend to be concerned with their own survival, and thus place on premium on creation of their own brand of social capital, whatever form it may take.
Social scientists use the term social capital to explain why the neoclassical theory of economics doesn’t actually explain human behavior, and why simplistic truisms of human behavior (Everyone just tries to maximize their individual good always and forever no matter the consequences to others) are insufficient to explain actual human behavior in the real world, at least the behavior of that majority percentage which isn’t clinically sociopathic.
On the one hand, a group tasked with a mission may have sky-high social capital reserves within that group, but if their actions become misaligned from the larger goal which they’re supposed to serve, society as a whole suffers. To take just one, obvious, example, consider the Mexican Zeta drug cartel, which began as, of all things, a group of elite soldiers, which are traditionally some of the groups with the very highest forms of internal trust, self-sacrifice and other hallmarks of social capital. As such lurid examples show, “social capital” as a term (just like other potentially open-ended terms such as “economic growth”) must have defined boundaries, if it is to be useful. Therefore, in this essay social capital has meaning only when used in terms of the nation-state as a whole, which remains, despite such experiments as the EU, the defining social grouping of our era.
There are a multitude of historical examples showing that in the absence of strong national government institutions imbued with regulatory power, and a sense of professional integrity, national society will devolve into tribes which exhibit, rather than a Rawlsian veil towards others, a starting point of hostility towards all outsiders. This has real and serious consequences for the economy and nation as a whole. To put it in simple terms, when there is no social capital, groups will fight over getting a bigger piece of a steadily-diminishing pie, rather than having a smaller piece of a pie that is growing. In the context of the developing world, this ties in neatly with the concept of the resource curse, which describes the difficulties non-developed countries have to harness the income of exported natural resources for the benefit of the population as a whole. Growing economies is a real and measurable goal, and economics has given us many different ways to measure the success or failure of policy, from GDP to GNP to PPP. Yet social science has not provided any equivalent tools with which to note the success or failure of policies geared towards making countries better communities, with enhanced levels of trust and certain shared, universal, values. This matters to “hard” economics policy because trust is a vital component of of any economic activity. How do you write a contract with another corporation is you don’t trust them, or they trust you, to carry out each side of the bargain, or if there is no fair method to enforce compliance? How can you make an investment in a country if the government has shown it might nationalize it, or that it might arbitrarily devalue the currency? How about simple pilferage by employees, or conversely, nonpayment of wages or benefits by employers? Such issues are difficult to quantify, but governments and businesses need to take such national and/or social attitudes and characteristics into account when making policy or investments. Although is seems a soft concept, social capital matters in a concrete way.
How then to measure this nebulous concept?
Well, it’s not as if there haven’t been attempts. The nation of Bhutan has a “Happiness Index” instead of measuring GDP, which might be considered as something of a proxy for social capital. Although I’m not aware of any attempts to create anything similar in the US, there have been arguments in Europe for measuring something other than income as a denominator of a nation’s progress. How would one create, measure and use such a metric?
Polling is potentially useful, but currently faulty on a couple measures. Mostly, any questions have to be consistent over time if they’re to have any validity, and social changes, for example immigration, can change the context of such questions to the point where they become questionable. Instead I propose an index based on several factors the correlations of which are varied, some positive and some negative:

 

Rate of violent crime (Self-evidently negative)

Rate of incarceration (Ditto)

Community participation outside of one’s group (Positive)

Gini index (Neutral, but lower would generally indicate more of a communal spirit than all-against-all in economic matters at least. One would not expect economic matters to be completely irrelevant when examining social capital.)

Employment level (Weakly positive, but strongly subject to external and independent factors such as the business cycle, tax and labor market regulations, etc.)

Donations to charities (Positive)

Cross-denominational religious participation (Strongly positive)

Education and/or literacy for women (Strongly positive according to all current development research)

Employment and/or wage-earning for women

Single-religion or single-group primary education (Negative correlation)

 

Positive correlating factors would be balanced by negative, and out would come one number which would give an idea of how high or low the level was of social capital in the country in question.

An SCI which is repeatable across cultures, valid through different time periods and consistent would be a valuable tool for politicians, policy makers and researchers. Such an index would provide a deeper picture of a country’s progress for the majority of its citizens beyond that simply available from raw GDP, GNP or CPI figures. While GDP if, for example combined with the Gini index, does provide one tool of interpretation of a national population’s general economic well-being, it is not by itself applicable to analysis of heterogenous societies, which, in an age of increased travel, migration and interconnectedness, seems to be the reality for increasing numbers of countries. It is a sad reality that while violent conflict between countries is increasingly rare, violent conflict within countries has seen a surge since the end of the cold war and the destruction of old political certainties. Thus more than ever we need a way to chart how countries (“we”) are doing in providing the primary service of a nation: safety for its citizens, and wide-spread economic growth.
Combining crime rates, economic development and factors such as literacy and giving is a way of measuring this which takes into other elements which tend to be ignored.
Some may note that in this proposed model index there is no provision made to measure levels of internet use or penetration (Ironic for something posted on a blog). This is by design. While an argument may be made that the web and the infinite number of forums therein provide a virtual space for furthering interconnectedness, an increasing body of evidence suggests that this is a false conclusion. The proliferation of fora has seen a concurrent, and well-noted, rise in the echo chamber effect, wherein dissenting views are not encouraged, and individuals seek only reinforcement for pre-existing views. This is actually inimical to the creation of social capital in any form. Will the internet be a force for the formation of social capital in the future? It seems on present evidence not. In any case, the starry-eyed utopians who believed “information wants to be free” have been decisively crushed by a combination of the forces of commerce on the one hand, and “security” on the other, with a strong dash of criminality thrown in for good measure. Also, internet use and penetration varies wildly even within the OECD countries, let alone those less developed.
A further possible weakness of this index is the inability to account for economic parasites, rent-seekers and other criminal or semi-criminal elements antithetical to growth and social capital creation which exist outside the measurable justice/penal system. This is not by design, but by lack of capacity. The underground economy can be estimated in most countries, but by such a variety of country- and culture-specific methods that there is little to no transference. In addition, the very nature of hidden activity means that it is useless in a hard, data-driven sense. How to measure the unmeasurable?
On the bright side, an SCI which is universal, reliable and consistent would provide policymakers with a useful tool to measure progress beyond that provided simply by raw economic numbers. Aggregation of information of “soft” social developments can help point out what we do right and wrong as countries and societies, and can indicate what works and what doesn’t in providing greater welfare and well-being to citizens. Isn’t that that the goal of policymakers everywhere?

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