Status concordance, the Peter principal, and an idiosyncratic theory of startups

Executive summary:

In this post, I want to try to pull together a couple of puzzles I’ve been thinking about, and suggest that these puzzles have a sociological explanation which often gets left out of economic theorizing—and that this explanation, in turn, has some startling implications for a theory of the firm, particularly the question of why independent startups seem to be more successful at radical innovation and growth than are more established firms.

The puzzles I am interested in are: (1) The Peter Principal: Why employees tend to ‘rise to their level of incompetence’ within organizations; (2) The relative infrequency in real-life organizations of ‘compensating differentials,’ and other mutually agreeable trades between employees and employers, which seem so logical and figure so strongly in economic theory; and (3) What is meaningfully different about ‘startups’ that allows them to do activities that cannot be done inside of more established firms—or, in other words, why startups per se should exist, rather than start-up like activities taking place inside the ownership structure of, and with all the supports of, established firms.

My proposal for answering these questions is that, contrary to workhorse models of economic theory, employee compensation and benefits do not function solely as incentives and rewards for our contributions. Rather, most humans tend to see compensation and benefits as recognition of status and social standing within the organization. And humans are highly social animals, who are very anxiously attentive to these symbols of our social standing, particularly as they compare to those of our relevant reference group, such as other members of our organization. Altogether, this means that humans tend to demand what I will call ‘status concordance’ in compensation, authority, benefits, perks, and rights within a firm—we want all of them to increase in lockstep as we move up in the firm in tenure and responsibilities—and we become very uncomfortable with status dissonance, when one person has more authority but less pay, etc., (unless that dissonance is between people who are members of different perceived peer groups, due to having a different educational background, skillset, or career track).

Thus, a human social constraint stops organizations from making certain kind contracts and agreements with employees which, from an economic perspective, would be extremely efficient. A particularly interesting application of my theory is the question of why so many extreme innovation and growth activities take place in startups rather than inside more established firms. Startup innovation activities are often driven by very aggressive, ambitious, and creative young people, who must, in order to innovate, be given the leeway and authority to make risky decisions, who often work extremely long hours, and who have very high-powered equity incentives that could make them extremely, extremely wealthy if they succeed. If such a startup were owned in-house as a division of a larger firm, it would generate status discordance and angst among the firm’s employees. In one direction, the firm would not be able expect one division’s employees to work longer hours than other employees in the firm; on the other it would not be able to give aggressive upstart young people high-powered incentives, scope to make risky decisions, and the potential to get very rich;… without inviting status discordance and outrage within the organization. 

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The Peter Principal

My thinking about this question was prompted by the job-market paper of a doctoral colleague and friend of mine. Her paper focuses on an employee-evaluation system that a company implemented in order to mitigate the well-known ‘Peter principal.’ (Since my friend has not chosen to publicly post a working paper online, I won’t share many more details about the author or paper.)

The economic explanation for the ‘Peter principal’ is simple. Organizations use employee promotion for two distinct purposes: (#1) To match people to jobs to which they and their skills are well-suited, and (#2) to incentivize and reward employees for good performance in their current job. If #1 factors in substantially, this means that if I perform well in Job Level 1, I get promoted to Job Level 2; and if I perform well in Job Level 2, I get promoted to Job Level 3, and so on. But once I reach Job Level N, and do not perform well in that position, I do not get promoted, and I stay in that position until I retire. So, people get promoted to the level of their incompetence, and stay there, and as an organization ages, it tends toward a state in which everybody is in the position in which they are incompetent.

From an economic perspective, the Peter Principal should be pretty simple to solve. We’ve been aware of this problem since 1969, so organizations should just recognize that it exists and stop using promotions for the purpose of #2, for incentives and rewards. Instead, they should just reward employees in the most efficient way, by giving them more money, while keeping them in the roles to which their capabilities and talents are most well-matched. Organizations should communicate to their employees that they should not think about the level of pay of a particular job, but instead think of the level of pay as a function of performance, and think of job ‘level’ as a simple matter of matching and sorting of skills and roles.

But, of course, organizations have not solved this problem yet, and they continue to suffer from the Peter Principle. Think, for example, how natural it is—how much we take it for granted—that we talk about the pay level of a particular job, assuming that the variation of pay within each job level should be trivially small, and that the variation in pay between job types is the most relevant determinant of pay. We have all largely internalized the idea that pay is a function of position, not a function of performance. The Peter Principle has three large costs:  (1) organizations get people making decisions in roles at which they are incompetent; (2) organizations lose the gains they once had from employees who were highly competent in their positions; and (3) organizations end up committed to paying out large yearly dividends to people who are not doing well in their roles (assuming a reluctance to fire employees).

Why is the Peter Principle so hard to overcome, when it is so very costly and when in theory it should be solvable? One obvious factor is that promotion is not just a blunt tool to give employees higher pay; rather, employees value promotions for status and recognition. So, you might think that the explanation is that the sorting-and-matching role of promotions can’t be completely, cleanly separated from incentives and rewards—in short, because people value status and recognition, you can’t motivate people without promotions.

Now, I think that this is definitely part of the explanation for why the Peter Principle still plays a role—for why firms don’t just match employees to jobs on skills and reward them with payment—but it’s not totally satisfactory, just yet. After all, economic theory models people with rational preferences as willing to make trade-offs among the goods that they desire. So, in this vein, perhaps employees long for more status and recognition, but they have a price: for the right salary or bonus, they’ll be just as happy to stay in their current position, where they are most competent. Given the costs of the Peter Principle, my intuition is that this price would be lower than the price of the alternative. Moreover, it would seem logical that organizations would evolve other ways to give employees status and recognition, less stark and blunt than permanent hierarchical promotion.

So this is, I think, a very interesting puzzle and a challenge for conventional economic approaches to modeling employee incentives—and this puzzle is only partially, not completely, resolved by the claim that people value status and recognition within their organizations.

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Compensating differentials and other nice trades:

As discussed, economic theory assumes that rational people are willing to trade off among the various goods that they desire. In labor economics, these tradeoffs are often called ‘compensating differentials.’ For example, it is often supposed that jobs that are dangerous or unpleasant (say, being a garbage man) will have to pay higher wages than other jobs that require similar skillsets but are less dangerous or unpleasant, in order to attract workers. As a matter of economic theory, the idea that such compensating differentials should exist follows axiomatically from the simple assumptions that people have preferences (things they like, and things they dislike) and labor markets are competitive. It would be simple to model an equilibrium in which workers had roughly equal skillsets and sorted into jobs with differing levels of pay vs. other benefits and detriments, based on their diverse preferences for those goods.

Now, it turns out that, empirically, there is some evidence for compensating differentials in some settings—but compensating differentials are surprisingly rare and small, in my reading of the literature. This is, I hasten to emphasize, a surprising fact, given that the existence of compensating differentials should follow axiomatically from three simple assumptions (a.) people are willing to trade off the goods that they desire, (b.) people have diverse preferences, and (c.) labor markets are competitive. From this perspective, compensating differentials should not be occasional curiosities that we can just detect with very clever statistical methods—they should be everywhere. Not just between jobs, but within jobs as well. But they don’t seem to be. There are no law firms that I am aware of that offer two possible career tracks: one with lots of document review, but enormously high pay, and one with less document-review, but lower pay. All corporate law firms seem to impose both a decent portion of document review, and high pay packages, on all of their prospective associates. There is one entry level. There is one track. There is one job description. There is one pay package. (For people entering the same role with the same educational credentials.)

The near non-existence of compensating differentials is actually just a subset of a bigger phenomenon, which is the general reluctance of firms to negotiate various kinds of mutually-agreeable trades with their employees. Consider the inefficient, but ubiquitous, practice of giving business travelers unconstrained expensing, or travel budgets, or doing in-house travel procurement: Employees get to spend as much as they want on first-class flights, hotels, and meals on the road, up to a usually quite high ceiling, but do not get to take home any savings. How can firms which seem to be obsessed with cost-cutting in many areas continue to do things this way? Why not just pay the employees more, and then let them choose how much of that money they want to spend on eating out vs. saving? From the perspective of economic theory, giving people money to make their own choices among these tradeoffs is clearly superior. In practice, there are several easy or clever ways the firm could arrange for employees to make their own choices around the costs and benefits of hotels and flights, while allowing them to take home savings from cheaper options.

One common justification for allowing unconstrained or budgeted business expensing or is that business expenses are tax-favored. But I’m skeptical that this justification suffices: Can the percentage difference in marginal costs arising from taxes account for the order of magnitude difference in the cost of first-class vs. coach-class flights? Would all the business travelers in first-class really prefer flying first class and taking home no extra cash to the alternative of flying coach and taking home an extra 60% of the $1000+ cost savings? It seems hard to believe. It seems equally hard to believe, as well, in the case of hotels—it is hard, I think, to suck $300+ of utility of from a room in which we spend most of our time unconscious. 

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A unifying theory: status concordance

I suggest that all of these puzzles can be explained by a single theory of compensation, which runs contrary to the canonical economic approach. (The canonical economic approach sees compensation as functioning to provide incentives ex ante by giving rewards ex post.) I propose that, instead, people interpret compensation—in all of its forms—as a recognition of their standing within an organization.

Compensation as status symbol has many implications, given that human beings are hierarchical, social animals who are extremely attentive to these symbols. (Usually unconsciously: We consider it unseemly to be explicitly attentive to status, but we also consider it unseemly to do millions of other things that have been implicitly  deemed low status, so I will not believe most people who claim they are an exception to this rule.)

The first implication is that, rather than observing a world in which employee compensation packages trade off among many different goods (less pay in return for more freedom, etc.), we would expect to see people and organizations demanding what I call status concordance. When compensation is not an incentive, but a status symbol, people will not accept reasonable tradeoffs between the different dimensions of compensation, but will demand that the various dimensions of compensation move up in lock step—because now deficiency on a single dimension of compensation, relative to some peer reference group, is interpreted as a slight, and such slights are extremely, extremely pricey.

So, in a world of status concordance, the people with higher pay get more freedom get better health insurance (even though their higher wealth should already reduce their demand for insurance) get more prestigious titles, get better offices, get more authority, and so on. And the people in the same status levels are offered the same pay packages, same authority, same freedoms, same benefits, etc. and variations and tradeoffs among those goods are not discussed, considered, or negotiated by the many diverse people all being matched to one particular job description.

Now, of course, the fact that a senior corporate lawyer gets both more pay and a better office than an college intern is largely explained by differences in bargaining power, as is classically modeled in economics. The senior corporate lawyer has better outside options, and she can use this to negotiate better pay and a better office. So differences in bargaining power can surely explain why the correlations between the various components of compensation are greater than zero. But I do not think it can explain why they are so very close to one. Given that there are many people who are close together in terms of their outside options/bargaining position, and quite diverse in their preferences, you would still expect to see more examples of discordance, in the classical economic world of stable individual convex preferences and Nash bargaining.

So, I propose that status concordance is important to understanding firms’ compensation practices, and can explain many of the above mysteries and inefficiencies, and many more as well.

Given status concordance, the Peter Principle becomes highly intractable. If you have an extremely high performer in Job Level 1, that person will reasonably be able to demand recognition and status for that performance. Can you just offer that person gobs more money to stay in Job Level 1, where he is well-matched, rather than Job Level N, where he will be at his level of incompetence? In economic theory you can, but in practice, we humans just can’t deal with this: This employee would hardly be able to tolerate seeing his peers who performed less well than him but were better matched to higher roles promoted to authority over him. Paying him gobs of money while keeping him in Job Level 1 would make everyone in the organization uncomfortable: his superiors would feel less comfortable giving him instructions; his superiors would feel outraged at their own pay. Common knowledge of relative rank and status would be disrupted, which would make it more difficult to coordinate commands throughout the organization. Even if the organization and its consultants were to beg the employees to think of promotions as simple matching, people wouldn’t accept it—we are incorrigible social animals in this regard.

The status concordance theory of employee compensation can explain why professionals seem very committed to having ‘paid vacation’ and other forms ‘paid leave.’ ‘Paid leave’ is of course a fiction in the sense that a job that pays $100,000 with two weeks of paid leave per year is identical to a job that pays $104,000 from which one takes two weeks of unpaid vacation per year. (Indeed, according to decision theory, the paid-leave job above is strictly inferior, since the unpaid leave job contract additionally gives the employee more options, beyond the option to get the exact same package as the paid-leave contract.)We are all smart enough to realize this consciously, but we all seem to enjoy our “paid leave” anyways. Why is this? To the extent that people see their compensation not as a reward/incentive for work, but as a recognition of their standing, then taking unpaid leave strikes them as an insult to their standing in the organization—a loss of rights and recognition—rather than as, say, a choice that any human being with a life outside of work should enjoy making from time to time. “To think, that they would reduce my salary, just for taking a vacation, which is a reasonable thing for me to do, my right after all I’ve given this organization!” So, we tend to prefer having our leave rights described as ‘paid leave’ and having the costs essentially amortized in our salaries over the remaining weeks—having money and choices taken away, a thing which conventional economic theory sees as self-contradiction—rather than face economic tradeoffs could make us feel status disconcordance.

The status concordance theory can explain why we don’t see interesting job packages that reflect tradeoffs that meet the diverse preferences of different people, or, in other words, compensating differentials within job tracks. In my experience, most corporate lawyers in the world will report that they work too many hours and earn more money than they need. But corporate law firms mostly don’t offer career tracks with both lower pay and shorter hours, because doing so would introduce status discordance. If associates exit law school as equals, then, upon being split in career tracks, one track would resent the superior pay or the superior hours of the other.

The status concordance theory can explain business-class ticket prices. Most business travelers would not pay first-class ticket prices out of their own pockets, and the tax advantage of business expenses can’t account for a difference so large. So there should be a profitable trade to be made between business travelers and their firms. The status concordance theory provides an explanation: If businesses used a rational comping scheme for business travel, most of the business travelers would themselves choose to fly coach, but then, at that point, they would feel status discordance, feeling that their seat in coach did not properly recognize and reflect their status within their organization. So, we once again seem to prefer to have money and choice taken away from us (contrary to classical decision theory) to avoid having to face status-discordance. (By the way, I thank business- and first-class travelers for their charity in subsidizing flights for everybody else, allowing this doctoral student to travel the world for amazingly cheap prices in coach! You and your firms are martyrs.)

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A theory of startups:

For a long time, I’ve been looking for a theory of startups. We seem to talk about startups constantly these days—they are at times the object of uncritical worship and at other times the object of cheap ridicule. But whatever we think of the startups that are in the news, a question that has always bothered me is, why is it even meaningful to talk about startups per se? Whatever activities we associate with startups—good or bad—why can’t those same business activities—the actual things that actually happen, rather than the our verbal description of the firm doing them—happen in bigger, established firms? Why does it make sense for people to say ‘I want to work for a startup’ instead of saying ‘I want to do a job that involves doing X’? Strictly speaking, a startup is just a legal form at a point in time—a newish standalone business entity. There is no necessary tie between being newish and standalone and doing any particular activities, or not doing them. So, why is it meaningful to talk about the activities, prospects, or characteristics of startups per se?

I propose that status concordance in employee compensation can provide a theoretically-grounded explanation for why startups per se might be meaningfully different from other firms, and capable of different activities, in particular the extreme growth and innovation for which they are usually lauded and promoted. I make three assumptions: (1) status concordance matters, (2) people look to the members of their legally-defined organizations  as their peer groups, and (3) organizations are reluctant to fire employees. With these three assumptions, it follows that startups can give high-powered incentives and scope of authority to young employees, that they would not be able to give them while part of a larger, older organization. And these high-powered incentives and scope to experiment and make mistakes are required for radical growth and innovation. So it is economically efficient for startups to be a thing—for radical growth and innovation activities to be housed inside newish standalone firms.

An important fact about startups, and the radical innovations and growth which they ideally aspire to achieve, is that they are usually largely made up of young people. Why is this? I see several candidate explanations. One factor might be that people seem to be at their most ambitious, aggressive, risk-seeking, and creative, at least along some important dimensions, in their youths. Another factor might be that young people are better at certain kinds of innovation because their minds are more adapted to the current state of technology. Another factor might just be that young people have more free time and energy, before they have kids. Whatever the reasons, the takeaway is simple: Startup activities are often driven by young people, who, by virtue of their youth, would be ranked lower in the status hierarchy of a more established firm.

Another important fact about startups is that they are doing risky business: developing new products is an activity whose modal profits are negative, but whose top-quantile returns are extremely high. A final important fact is that startups are in fast-moving businesses: time is of greater essence when racing for share in a network economy, than it is when debating whether or not to change the packaging of an established CPG brand, for example. These two facts have some important implications: First, startups need to have control systems in which the employees have scope to quickly make decisions which could go wrong, which have potential downsides. Second, startups need to give their employees equity incentives to motivate them and make them willing to take risks, against the long-odds they are facing.

When you combine these facts with the status concordance theory, it’s seems that older established firms could run into trouble when trying to develop startup-like activities in-house. Basically, archetypal startups are doing activities where you need to give young twenty-somethings a lot of scope to make some potentially bad decisions, while offering them equity incentives that could potentially make them extremely wealthy. In an older, more established organization, the scope of control, mistakes (both potential and realized), and potential riches of aggressive, cocky newcomer employees would be offensive and status-discordant to many of the more senior, established employees. Established employees would find it nearly impossible to have startup-like compensation packages and scope of control in one (younger) part of the organization, and established-firm-like compensation packages in the remainder. So this constraint on compensation packages within an organization stops more established firms from optimally incentivizing radical growth and innovation activities.This provides one reason why it might make sense that radical growth and innovation activities must often be housed in new, upstart firms.

Oliver Hart’s economic theory of the firm

On Monday, two economists, Bengt Holmstrom of MIT and Oliver Hart of Harvard, were awarded the Nobel Prize in economics, for their contributions to the area that economists describe as ‘contract theory.’ I suspect that this Nobel will be particularly difficult for non-economists to fully appreciate. Usually, macroeconomics and financial economics are the fields of econ that make the front page of the Wall Street Journal, and capture the public’s attention. Plus, contract theory can often be abstract and technical—using game theory and probability to address questions that most people would not think to ask. So I wanted to write a brief post about Oliver Hart—as I’ve been a student of his and been deeply influenced by him—and his theory of the firm, and then talk about some recent high-profile news events that we might apply his theory to. Of all economic theories of the firm that I have encountered, Hart’s gives the most coherent and persuasive economic theory of ownership, control, and the boundaries of firms. But it seems like there are lots of transfers of control that are hard to rationalize with this theory, and, I suspect, any model of financial and economic rationality. So I’ll wrap up this post by asking how much we can expect of economic theory in explaining the world.

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First, what do we mean by ‘theory of the firm’? Basically, a theory of the firm is a theory of why certain economic activities take place within the command hierarchy of a firm, rather than via arms-length market transactions. When our cars break down, most of us take our cars to local mechanics, pay them for a single service, and then drive home. But most firms have internal IT departments to fix computers and resolve other IT problems. Why should this be the case? Why couldn’t companies just hire computer-repair services from an external IT firm—or external IT contractors—piecemeal? Why do firms ‘own’ so many diverse functions in-house—IT, marketing, human resources, R&D, in-house, instead of outsourcing and buying services piecemeal, just as we do for most goods and services in ordinary life, for groceries and haircuts? Economic theory is not satisfied with the claim that it’s cheaper for firms to do these things in-house, rather than go to the market, as that just punts on the question of why it’s cheaper—why should it be more efficient?

So, a comprehensive theory of the firm should explain the full scope of firm ownership decisions—why it owns this tool rather than renting it or requiring its employees to provide the tool, why it has an in-house IT division rather than outsourcing, etc. On a more concrete level it should be able to explain concrete changes in the firm boundaries and asset ownership—why did firm X acquire firm Y instead of just having a contracting relationship?

Oliver Hart’s major theory of the firm revolves around three major concepts: (1) ownership as residual control rights, (2) non-contractible contingencies/ ‘incomplete contracts’, and (3) non-verifiable relationship-specific investments. Once we define what we mean by these concepts, it will be straightforward to understand his theory of the firm.

First, Hart defines ownership as residual control rights. Given that I can contract to use an asset that you own in any number of ways, all that your ownership really means is that you control the use of the asset in any situation or circumstance that we have not contracted around—hence ownership means residual control rights. Ownership is just who has a say where contracts pass over in silence.

Second, Hart assumes—and there’s a lot of deep, theoretical debate in contract theory over this assumption—that there are certain contingencies (that is, possibly future events) that it is impossible to write contracts around, whether because it is impossible to foresee them or impossible to legally specify them, or simply too costly to try. In other words, contracts can’t specify everything that must be done in every situation that matters to two different parties. As a result, ownership matters—in those non-contracted-for situations, the party that has ownership rights (residual control rights) gets its way. An example of a contingency that it might be hard for firms to contract around might be subtle changes in consumer tastes or the company’s marketing strategy: A car-maker contracting with a supplier that makes its auto bodies will want the auto-body maker to adapt each year’s bodies to that year’s fashions and tastes. But it might be hard to specify in a contract how fashions and tastes might change, how we would formally identify those changes, and how much the auto-body maker can be expected to make costly retailorings of its manufacturing process to satisfy those demands.

Now with these first two parts of the theory, alert readers might think we already have a theory of the firm: There are certain future contingencies that we cannot contract around, and so economic parties will demand ownership—residual control rights—to protect their interests in these situations. Concretely: The car manufacturer will buy the auto-body maker to directly control the production of the auto-bodies, based off of its knowledge of changing consumer tastes and demands. But this doesn’t totally satisfy economic theorists. After all, two contracting parties could just agree that, if one of these non-contractible contingencies takes place, they can renegotiate at that point. The car manufacturer and auto-body maker could just write a new contract each year, once they’ve gotten new information about consumer tastes that year. It turns out that, with only the first two components of our theory, it would actually be more efficient to do things that way—renegotiate at each contingency. So, to use the preferred economic language, this doesn’t quite explain why ownership matters ex ante—the parties could just renegotiate/re-contract ex post.

So Hart introduces a third, critical component to his theory: In the real world, parties often have to make unobservable relationship-specific investments in complementary assets—that is, investments that only pay off fully if the two parties continue their economic relationship. For example, the auto-body maker might invest in retooling its machines so that it is especially good at making bodies that are specifically tailored to the manufacturer’s chassises; just as the manufacturer might make chassises that work particularly well with the auto-body maker’s bodies. Relationship-specific investments can be good, efficient, and important, but expose parties that make relationship-specific investments to “hold up” risk. In a supplier-customer relationship without relationship-specific investments, hold-up isn’t a problem: If a supplier produces a commodity product, and its usual customer tries to ‘hold it up’ by demanding generous price concessions, the producer of the commodity product can just go sell to another buyer in a competitive market. But once parties have made relationship-specific investments, they no longer have this luxury: Given that other auto manufacturers might use different chassises (or just be located further away), the auto-body maker cannot easily sell to them.

So now we can put all three elements together: In some economic relationships, efficiency requires the parties to make relationship-specific investments. But each party will be wary of making such relationship-specific investments if they fear that, in future non-contractible contingencies, the other party will try to hold them up. So, the parties don’t fully invest in the relationship-specific investments and complementary assets ex ante, which is inefficient. But when complementary assets are owned together—by one economic agent with all residual control rights—this fear is not relevant, and the owner can fully invest in making the assets compatible, yielding all the efficiency. 

To make it concrete: When the auto body maker and the car manufacturer are housed separately, each will be wary of investing in tailoring their machines and processes to make compatible chassises and auto bodies, since such co-dependence could expose each of them to hold-up. By integrating under common ownership, prospective hold-up problems disappear and the owning firm can fully invest in making the assets compatible.  (This abstract example I’ve developed is based loosely off of the famous case of Fisher Body and General Motors.)

The short—but technical—way of summarizing this is as follows: Assets are commonly owned in firms in order to mitigate hold-up problems in non-contractible contingencies that would prevent separate contracting parties from efficiently investing in relationship-specific complementary assets.

In practice, there are various forces that push against integration, that can make integration costly even when there might be the potential for relationship-specific investments in complementary assets. Managers may not have the omniscience to run ever-more complex firms. Incentive problems may become worse and worse as more divisions and functions within a firm become ever more removed from the firm’s bottom-line. But the Oliver Hart’s theory is about the basic underlying economic forces that pull assets together, under common ownership, inside firms, and why, at the most basic theoretical level, integrated firms make sense and are so pervasive.

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Oliver Hart’s theory of the firm is the most coherent and persuasive I have encountered. But it is very much an economic theory of the firm—it explains what firm boundaries make sense and why, given people who are behaving rationally toward financial ends. Is such an economic theory complete? Readers might object that many of the acquisitions that we’ve read about in recent years are hard to account for with this theory. When CEOs issue press releases explaining their M&A activity decisions they rarely reference non-contractible contingencies and unobservable relationship-specific investments.

For example,can this theory account for why Twitter should be acquired by anybody, or by SalesForce in particular? Or why Yahoo was acquired by Verizon? In the case of Twitter, the idea—as far as one can discern—is that because Twitter has not Grown (where Growing is defined as growing as fast as Facebook), it needs a Strategy and should find a buyer. The Twitter go-shop process does not seem to be motivated by expected synergies, relationship-specific investments, actions that Twitter cannot take as a standalone company, or anything else that economic reasoning would tell us invites an acquisition per se. It seems to be driven by human narrative reasoning: Twitter’s stock price has gone down and so we need to Do Something Bold, such as selling to another company so that we can have narrative resolution on the Story of Twitter.

The business press is replete with examples of companies making acquisition decisions that have no coherent economic logic, but which are very easily explained by managers’ vanity, failure to understand certain financial identities, fixation on ‘growth’ even when it is inorganic and thus not meaningful, narrative reasoning, and etc. It seems hard to avoid the conclusion that a large fraction of M&A activity and thus changes in firm scope and control is explained by, in two words, human folly. But economic journals like to publish models of rational economic behavior and empirical tests of those theories. This means that an empirical paper that finds some theoretically-motivated relationship—say, between observability of relationship-specific investments and integration—will be published and make it into the literature and the official understanding of the firm that econ and business-school PhDs learn and internalize. And the large fraction of the residual in that regression that is explained by simple human folly won’t make it into the official theory. One is unlikely to publish a paper whose thesis is, “Managers often grope along in darkness and ignorance, as evidenced by their own statements, and a significant portion of M&A activity is explained by this fact alone.”

None of this is a criticism of Hart’s theory per se—just an explanation of why there is a disconnect between the sophisticated theories that academics win Nobel Prizes for and the kinds of things we read in the business press every day about M&A. But I think that Hart’s theory is extremely useful for two different things:

1. First, it is useful as a normative theory (rather than a purely descriptive one), of how agents should behave. This should be useful for consultants and managers who actually want to do what is in the interest of a company’s stakeholders. Hart’s theory shows why integrated ownership can add value for everybody. If it is impossible to articulate why the goals of an acquisition cannot be achieve through arms-length contracting, or to express the logic of the acquisition in terms of important relationship-specific investments in complementary assets, then the acquisition should not be undertaken.
2. Second, it should descriptively explain firm boundaries and integration decisions in the special circumstances in which we can expect the economic rationality assumption to hold. These assumptions would hold when either (a.) agents are smart enough to reason through the optimal solution to their contracting problems and are actually motivated by financial goals, or (b.) competitive selection pressures are strong enough to eliminate suboptimal firms and allow optimal contracting relationships to be imitated and replicated, even when the human beings involved in these contracts aren’t smart enough to know what’s going on.

The selection argument operates over a fairly long horizon. As such, Hart’s theory of the firm perhaps best explains firm integration decisions that run so deep that we take them for granted and don’t even notice them. In other words, perhaps it is best at explaining the basic patterns of how business units are held together—which assets are co-owned and what activities tend to be paired together—but not necessarily why corporations and conglomerates buy and sell those business units. And that could be its true genius, that it explains the arrangements we take for granted—the co-owned assets that never, ever get separated and sold off—and not the ownership arrangements that are spun off, traded, and acquired, and thus make the front page of the WSJ.

Is a rising stock market a good thing?

The answer is, “usually, yes.” But the reasons why are somewhat subtle.

Some of my friends have been sharing this article by Jeff Sommer in the NYT; the article points out how well the stock market has done under the current President’s tenure. The article focuses on the Down Jones Industrial Average, a dinosaur relic of the past for measuring the stock performance (the index tracks an arbitrary and small number of companies and uses an absurd weighting scheme). But the more logical (and popular among economists) measure of stock market performance, the S&P500, has done incredibly well—up 163% since Obama’s inauguration, according to Yahoo Finance data. People like to look at how the stock market has performed under various presidents, at least partly because they think it is a measure of how well they have done on economic policy. People also like to look at how the market reacts during closely contested elections: If one party or the other unexpectedly wins the presidency or control of the House or Senate, the stock market’s reaction the next day is seen by some people as a measure of the market’s perception of the economic competence of the two parties.

In this post, I want to use just the most basic financial theory identities to show how to think through the question of when and why a rising stock market is a good thing. As I referenced above, the bottom line is that it generally is a good thing, but the reasons why are, I think, slightly more subtle than may be assumed by those who use the stock market to score political points. By exploring what, precisely, the stock market’s value represents, and why that matters, we can learn about finance and the economy, and also have more intelligent conversations about evaluating policy makers.

 

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The fundamental identity of finance:

When people buy stocks, they do so in the hope of turning their spare cash today into more cash in the future. So, when we buy a stock, we’re paying for the future cash flows from that stock. Some of those cash flows could come from payouts from the company—in the form of dividends and share repurchases. And some of those could come from reselling the asset/stock to other investors (yielding a return from ‘capital appreciation’). But those other investors to whom we resell the stock will, in turn, also be hoping to profit via dividends, buybacks, and capital appreciation. All capital appreciation has to come from some other market participant being willing to pay more for the stock in the future, ad infinitum. What this means is that, even though capital appreciation is an important part of the gains that any investor can expect to make in her own lifetime, for the market as a whole, we can think of the stock valuations and prices as a function just of dividends and repurchases.*

For simplicity, let us from now on just use ‘dividends’ in place of ‘dividends and repurchases.’ Since the market values stocks for their expected future cash flows—which we are now calling ‘dividends’—it makes sense to write the price using the following simple identity:

Price = [Expected dividends] / [Some discount rate]

I am making an abuse of notation here.** But the basic concept is there in this simple notation: Price today reflects expectations for future dividends, discounted by some amount. This is an identity. It is true by virtue of how we are defining the terms: Whatever the market’s expectation of future dividends, there must be some discount rate at which those future expected dividends are being discounted that can rationalize why the market is trading the asset at the current Price.

So that’s just an identity—what can it tell us? Well, it tells us that significant*** changes in the value of stocks can come from one of two sources: Changes in expectations for future dividends and changes in discount rates. Let’s look at each of these in turn.

 

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Dividends:

Dividends are just cash that firms can choose to pay out to shareholders. Legally speaking, shareholders are ‘residual claimants’ of the firm, meaning that they are entitled to be paid after the firm has met its obligations to pay contracting parties such as suppliers, debtholders, etc. This means that, to a rough approximation, the money that the firm can pay out to shareholders is determined by its profits. Empirically, dividends tend to reflect a moving average of firms’ profits over time. Profits that are not paid out to shareholders can be reinvested inside the firm. If the company’s internal reinvestments have the same rate of return as the company’s discount rate—and in economic equilibrium, they should be approximately equal, on average—then these internal reinvestments are equally valuable to shareholders as the cash payout would be. So, assuming that equality, short-term ‘payout policy’ (the choice of what fraction of profits to pay as dividends vs. reinvest) has no effect on the share value.

What does this mean? It means that, to a close approximation, we can use profits and dividends interchangeably in thinking about firm valuation. Practically speaking, the things that increase firm profits are things that increase dividends. It also means that we can change our exact identity above to an approximate identity:

Price ≈ [Expected profits] / [Some discount rate]

(Indeed, you may already know that “fundamental value” investors and analysts typically use some accounting measure of profits (such as EBITDA) or free cash flows, to value firms, rather than explicitly modeling their future dividend flows. The tight theoretical and empirical link between profits and dividends is the reason why they can do this.)

So, all that said, what are the implications? The bottom line is that one reason why stock prices increase is that expectations for future profits increase.

Is it a good thing when that happens? The answer is, I think, mostly yes. Usually, if market participants expect firm profits as a whole to grow, it’s because they’ve become more optimistic about consumer spending—and the things that tend to drive consumer spending, employment and GDP, tend to correlate with better outcomes in life for people as a whole.

But there could be some special circumstances when increased corporate profitability could be a bad thing. Suppose that some new policy were adopted that protected incumbent firms from competition by innovative startups. Since S&P500 firms are, by definition, large firms, expectations for their future profitability would, in this thought experiment, increase. The value of the S&P500 would increase, even as consumers would be hurt, and the value of privately-held and small-cap startups would decrease. Or, suppose that some new law were passed that greatly extended various patent protections. Assuming that S&P500 firms are net suppliers of patents, their profits would benefit, while the effects on consumers and the economy as a whole would be more ambiguous. Thus, if we used the value of the S&P500 as our summary statistic of economic well-being, we would be misled. In some policy circles, people draw a distinction between being “pro-business” and being “pro-market,” and this thought experiment captures one of the ways in which there can be a difference. Various types of policies could benefit certain corporations’ profits while being bad for the economy as a whole.

So the bottom line is that increases in the value of the stock market that are driven by what economists call “cash flow news” are usually, but not always, indicative of good news for the economy as a whole. It turns out that news about macro variables that will affect consumer spending (which tends to affect all firms in all industries) tend to swamp news about, say, legislation that will protect one industry or another from competition, etc. So most changes in expectations for corporate profitability reflect good news. But it’s worth remembering that this doesn’t always have to be the case.

 

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Discount rates:

Discount rates capture the fact that, even if I expect some stock to pay me $100, on average, next year, I’m not willing to pay $100 for it today. There are two reasons for this: First, even if I expect it to pay $100, there’s some uncertainty—some probability that it could pay more or less—and most of us are risk averse and thus willing to pay less than the average payoff. Second, it has traditionally been asserted (though the era of negative interest rates may be casting doubt on this) that there is a time value of money, such that even riskless future cash flows are discounted in the present. For the purposes of this question—since risk-free interest rates have been low and stable for the past 8 years—the first factor is most important. Let’s leave aside the time value of money for now.

What will determine by how much I discount a risky payoff of $100? Necessarily, the two things that will determine that are (1) the riskiness of the payoff, i.e., how widely dispersed are the possible outcomes are around my expectation (e.g., does it pay $50 vs. $150 with probability .5 each, or does it pay $0 vs. $200 with probability .5 each?), and (2) my attitudes towards that risk, how risk-averse or risk-seeking I am.

So what this means is that the other major source of changes in the value of the stock market is changes in discount rates, driven by changes in perceptions of riskiness as well as attitudes towards risk.

The prevailing consensus in modern finance is that most major aggregate (that is, market-wide) changes in the value of stocks are driven by ‘discount rate news’ rather than ‘cash flow news’—that is, changes in perceptions and attitudes towards risk. (Note that discount rate means the same thing as [required] rate of return, expected return, etc. All these terms can be used interchangeably, but I think that ‘discount rate’ is the most intuitive in the context of valuation.)

Is it a good thing, per se, when discount rates decrease—i.e., when perceptions of risk and aversion to risk decrease?

I actually think this is a tough philosophical question. Normatively, how can we say what our preferences and attitudes towards risk should be? Moreover, is it even possible to say how we should perceive the amount of risk that there is? Presumably, in judging changes in perceived riskiness, we would want to separate true riskiness from inaccurate perceptions of riskiness. Perhaps we think it is good when true riskiness decreases, and good when an inaccurately high perception of riskiness decreases to a correct perception—but that it is not good when the perception of riskiness becomes inaccurately low. But how do we make such a distinction between the truth and the perception? Indeed, in a deterministic world, it’s unclear what it even means to talk about the true riskiness!

If we could make such a distinction, between true riskiness and perceived riskiness, then it would seem that decreases in discount rates driven by decreases in true riskiness were a good thing. If the future path of GDP, consumer spending, and thus corporate profits, all become more reliable, and less risky, that would be desirable. But if discount rates decrease, we can never know if the economy truly became less risky, or the market fallaciously perceives it as less risky. In the end, if the economy continues to do well, low discount rates will be proclaimed, ex post, to have been justified; if not, then the previous market  high will be proclaimed, ex post, to have been an obvious bubble. But we can never know with certainty ex ante.

When the current president took office in 2009, the U.S. was still amid a major and largely unprecedented financial crisis. The low stock market valuations at the time likely reflected general macroeconomic pessimism—expectations that corporate profits might be low for some time—but also, more significantly, very high discount rates, reflecting uncertainty (perceptions of riskiness) and risk aversion. There could be a mix of institutional reasons (e.g., interlocking financial constraints) and psychological reasons for it, but the current academic finance literature is in agreement that discount rates/expected returns/required rates of return tend to be very high during recessions. It’s no surprise when the stock market bounces back from a recession low. The value of the stock market goes so low in recessions precisely because those are the time periods in which investors are most sensitive to downside risks—and that very fact, in turn, makes the stock market cheap, and thus likely to bounce back.

So the performance of the stock market over the past 8 years would seem to reflect two separate periods: First, a resolution of the extreme uncertainty of the financial crisis, which allowed discount rates to go from being very high to moderate. Most people would say that the smooth resolution of the financial crisis and its fear and uncertainty was a good thing. And second, the period of the last several years, in which decreased perceptions of and aversion to riskiness (themselves, in turn, influenced by monetary policy) allowed discount rates to go from being moderate to being very, very low. Are these very low discount rates a good thing?

We don’t know, and we won’t know, until it’s too late.  🙂

 

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Conclusion:

Significant*** changes in the value of stocks are driven by changes in (i.) expectations for corporate profits and (ii.) discount rates. Increases in expectations for corporate profitability usually, but not always, reflect good economic news. Decreases in discount rates could reflect a desirable decrease in fear and uncertainty, but might also reflect fallacious overconfidence and risk tolerance. To find out whether today’s very low discount rates are a good thing, you’ll just have to wait and see.

 

 

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* Somewhat technically, for any positive discount rate, the discounting of the ‘terminal value’ of the asset will asymptote to zero as time increases.

** In reality, since dividends are paid out over many future periods, and since discount rates can vary between periods, I should really have t-subscripts, and an infinite summand symbol. Also, depending on what notation you prefer, you can write the discount rate as the thing you multiply cash flows by (something like .94), or as the thing you divide them by (something like 1.05). We also have flexibility with whether to write the divisor as [discount rate] or as [1 + discount rate]. My goal is to focus on putting the high-level concepts in English, so my apologies if I irritate some precise readers, or those who have been previously exposed to one notation or the other.

***Technically, where I write ‘significant,’ it should be ‘unexpected,’ to reflect the fact that, in the theoretical absence of news, the stock market would still be expected to increase by its expected rate of return.

Nash, Equilibrium, and the Logic of Social Order

[Two caveats before beginning: First, I have no familiarity with, and nothing to say about, Nash’s major intellectual contributions outside of game theory. Second, this post is a verbal reflection on the big ideas that a smart, non-technical person could take away from Nash—so there will many elisions, glosses, and small technical abuses in this piece.]

John Nash made extraordinary contributions to game theory, which has, in turn, become the foundational toolkit for understanding human social behavior. My hope in this post is to convey an appreciation for the depth and importance of these contributions and their utility in our intellectual toolkits.

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First, what do we mean by game theory? The most down-to-earth way to define what social scientists mean by a ‘game’ is that a game is a situation where several people have goals and want to take actions to achieve those goals, but each individual’s ability to achieve their goals depends on the actions the other people take. (In the preferred jargon, a game is a situation in which ‘players’ choose ‘strategies’ to maximize their ‘payoffs,’ and each player’s payoff is in turn determined by the ‘cross-product’ or ‘profile’ of all players’ strategies.) As you can see, this an extremely general concept that encompasses basically all of human social interaction and that’s why game theory is a foundational concept for most socials sciences now.

So, to make the definition more concrete: If I’m, say, playing at a fully mechanical, random slot machine at a casino, and I know the probability of winning the jackpot, then my decision about whether and how to play is not (under this definition) a game—instead, I’m just optimizing against a purely random, mechanical process that takes no account of my thinking at all. But if I’m, say, hoping to negotiate with a prospective employer for the right to take unpaid vacation time, then I’m playing a game, in which I have to think about her goals and subsequent actions conditional on the assumptions she’ll make about my likely productivity and fit with the firm conditional on the things I ask for during the interview and negotiations process, etc.

What do we expect to happen in these situations? Very simply, we expect that people will do the best they can conditional on the choices the others are making. And that, in short, is a Nash equilibrium, which is arguably the most important concept in game theory. The concept is actually very simple: A particular outcome in a game is a Nash equilibrium if every individual is doing the best they can to achieve their goals given what everybody else is doing. (In the preferred jargon I referenced above: A strategy profile is a Nash equilibrium if each player’s strategy is his own best response to the others’ strategies.)

In general, we would expect that in ‘games’ (or, more broadly, strategic situations) that we observe in real life, the agents are probably in a Nash equilibrium because, if they weren’t, then, by definition, at least one person would do well to change their behavior. The way I think about this is that any possible outcome of the game that is not a Nash equilibrium is self-refuting or at least self-correcting: We assumed that people were trying to achieve some goals, but if the outcome of some social situation is not an NE, that means that at least one person was not making the choice they wanted to make.

This may seem like a fairly trivial, obvious idea, and so alert readers may be wondering why Nash equilibrium is considered such an important, foundational concept. The way I think about this is that using the concept of a NE allows us to understand human social interactions by immediately understanding and characterizing the outcome of a social process, without having to worry about the extremely messy and complicated path that the social system will take to get to that outcome. An easy way to think about this is with a sort of pedantic example from high-school physics:

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Suppose that we had a solid glass tube with two halves separated by a glass panel; and suppose that one half of the tube were filled with air at atmospheric pressure and the other half were a vacuum. What would happen if the glass panel were suddenly removed?

Hopefully, the answer to this question is obvious: Air molecules would rush into the half that had been a vacuum and pressure would become evenly distributed throughout the tube. If you were so inclined, you make even further predictions, such as that at any given time there should be approximately as many molecules on the left side of the tube as on the right, that the two halves should be approximately even temperatures. In short, the new, conjoined tube will induce a new equilibrium.

The interesting question to ask yourself is why do you feel confident making this prediction? After all, when I was a child, I thought that we could only answer this question by appealing to more foundational mechanics, i.e., starting with the physics of individual air molecules, estimating the individual positions and trajectories of the air molecules before the glass panel was removed and then modeling what their trajectories would be after its removal and then writing down what their positions and velocities would be, and then (finally!) using those positions and velocities to calculate the pressure and temperature throughout….

And while in theory this might be a rigorous way to truly understand this physics problem, in practice, it is just far, far too complex—we can’t observe the positions of so many molecules with enough precision, we don’t have the computational power to model each one’s trajectory—and we already know we can skip over the precise mechanics of how individual molecules bounce around and still know the answer to what the end result will be. We know that the contained chamber must be in equilibrium for the tautological reason that if it were not in equilibrium, it would keep changing until it were. If the air in one section of the chamber were higher pressure than the air in another, then the high-pressure air would expand into the low-pressure section, decreasing its own pressure and increasing the other’s until equilibrium was reached. And etc.

Moreover, the fact that the outcome will be an equilibrium is probably most of what we need to know in practice, and allows us to say many more things to characterize and describe what’s in the chamber.

So, in short, there are lots of questions in hard sciences that we don’t answer by going, as we might expect, causally ‘upstream’, to some more basic science, in order to trace the path of how some process will unfold—quite the contrary, we ignore the path and the upstream sciences and their implied mechanics altogether, and immediately leap straight to the outcome knowing simply that it must be equilibrium.

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The thing that a lot of people don’t realize is that this is exactly how economics proceeds in understanding social processes. (People don’t realize this—I didn’t realize this at first—because the typical econ class introduces you to such a dizzying array of new notation, jargon, and unrealistic modeling assumptions that the student typically doesn’t have the mental space to ask the fundamental question of why we are we doing things this way?)

When I took my high-school science sequence, I saw biology being built on bio-chemistry, bio-chemistry built on chemistry, and chemistry built on physics. My assumption was that when I got to college and started studying “social sciences,” this construction project would continue, and neurology would be built on biology, psychology built on neurology, and economics built on psychology. So I was pretty surprised when I walked into my first economics and saw, instead, a completely self-contained lecture, with the professor simply starting with the abstract construct of a ‘utility function’ and then building to an ‘equilibrium solution,’ with none of the upstream sciences involved at all.

But as fashionable as it is to beat up on economics, there’s a great deal of—sometimes subtle, usually not explicitly argued—reason in this “axiomatic” approach, in which we devote our attention to things like giving very abstract, general descriptions of what people’s goals might be (as in their utility functions) and then characterizing what kind of equilibria could result among such people depending on what kind of game they’re playing, rather than tracing out individuals’ “paths.” The reason is that we humans are even more complicated than the air molecules in the physics problem above, and so the task of describing our social behavior via a mechanistic approach—of using ‘upstream’ sciences to describe the path each and every one of us would take—is completely hopeless.

(Some readers might imagine that “behavioral economics” is taking this approach, of rebuilding economics on models of actual human behaviors, rather than via the axiomatic approach above. But my understanding is that behavioral econoimcs has mostly added asterisks to particular applied economic models and some of their restrictive assumption, but has not replaced or supplanted equilibrium as the overarching approach to characterizing the outcomes of social processes.)

Instead, just as in the physics question above, economics can give us a great deal of insight by ignoring the individual molecules’/people and their current positions, and going up a level of abstraction, and noting that the final outcome must be an equilibrium, and there are many important and useful things we can know and say about the equilibrium per se. For example, in macroeconomics, we can’t really keep track of what all of America’s 300 million citizens are up to and actually feeling on a daily basis, but we can use an equilibrium notion and some general assumptions to about people’s preferences to figure out some of what must be true.

A concrete example of this is to think about the question: How should I invest my money? A lot of people seem to think that in order to invest your money, you should read up on firms and pay attention to their debt levels and stuff and make up your mind about whether it’s a good or bad company. But if we simply assume that the world is roughly in equilibrium we have a different way of looking at this problem: If everybody is doing the best they can do, no investor would want to sell me a stock if (s)he could get a better price by selling it to someone else, and so my counterparty’s willingness to sell to me at price $x means that nobody in the whole rest of the market thinks that stock is a incredible bargain at price $x. In other words, I should never, ever expect to be able to buy a stock at a bargain. A world in which I could buy a stock at a big bargain would be self-refuting, self-correcting, and not in equilibrium. As such, unless I have some private information advantage, I should just hold (levered) index funds.

That paragraph may seem pedantic to people who are already well-versed in finance, but this is often a very surprising gestalt shift for those who are not, and so I’ll emphasize it again. Brilliant and well-educated professionals outside of the social sciences—doctors, engineers, computer scientists—in my experience often have trouble wrapping their mind around this, because they are used to working with objects that they can objectively evaluate on the merits of the object per se. But finance is different, because the critical property of interest—the price of the asset relative to its future returns—is not a fixed object, but is itself the product of a social game. In an engineering context, a car’s specifications are objective features, and if I want to know how fast the car can go, I should look at them. But in a financial market, a stock’s price is itself the equilibrium output of a social process, and so I already know the answer to the question ‘what is this stock likely to return?’ without knowing any objective facts about the underlying company at all. The answer is: ‘the market rate, adjusted for its risk.’ I can answer this question without knowing anything about the stock’s debt, market share, CEO, etc., just by knowing the nature of the game I’m playing and short-cutting directly to its equilibrium.

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So that’s how I think about equilibrium. The major contributions of John Nash to this, in my understanding, were that, first, he developed the notion of Nash equilibrium, which is the appropriate equilibrium concept for human social systems (since its just about individuals doing what they most prefer—whatever that is—conditional on others’ actions) and showed its depth and generality. And second, he did a lot of the important technical groundwork in proving some surprising mathematical things about Nash equilibria in games. Specifically (and most famously), he showed that there is at least one NE for any finite game, that is, any game with a finite number of players and a finite number of possible choices.

One example of a finite game—a finite number of players with a finite number of choices, whose decisions will then determine how well everyone does—is human life. Like—sorry to be cheesy—there are only 7 billion of us who have only so many options, and so it’s mathematically demonstrable there’s a Nash equilibrium that must be an outcome to the game we’re all playing. (That doesn’t necessarily mean we can know enough about individuals’ preferences to accurately model this game in practice.) More generally, the fact that Nash equilibria always exist for any realistic social setting means that it can reasonably be called the unified framework for understanding human social behaviors and its consequences.

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So on a deep level, that’s why Nash and Nash Equilibria matter, from my perspective. This blog post does not describe the fun little games—the prisoner’s dilemma, matching pennies, etc.—because describing these games requires describing some technical assumptions about game structure that would confuse matters. Instead, I want to keep this post on the level of appreciating the generality and flexibility of game theory.

Game theory provides a general unified framework for thinking about how individuals’ actions aggregate into social outcomes. The framework, too, is surprisingly general: A lot of people think that game theory’s language of ‘payoffs’ and ‘utility functions,’ etc., entails an assumption that people don’t care about others, are materialistic, or have unrealistically ‘rational’ preferences, but this is just not true. The game theory and economic equilibrium frameworks are certainly general and flexible enough to accommodate actual human beings’ preferences in these regards. The machinery of game theory can show how some surprising results about: how individually rational behavior can aggregate into collectively horrible behavior (e.g., prisoner’s dilemmas/externalities); how individually selfish behavior could aggregate into collectively wonderful outcomes (general equilibrium with complete information); how we humans can end up in situations where we sink enormous amounts of money, time, etc., sending signals about the kind of people we are, via education, luxury good purchases, etc., to differentiate ourselves from others, and how everyone can find this wasteful state of affairs to be their own best response (e.g., information economics, separating equilibria, signaling models, screening models); and how we humans don’t think about public policy and finance in the right way, because we’re used to engineering-style thinking (e.g., most of instinctively love the idea of legally requiring firms to do some Unambiguosly Good thing for their employees, without considering how that requirement will affect their proclivity to hire new employees in the first place, etc.).

There’s a good argument to be made that Nash equilibrium should not be the exclusive basis of theorizing in the social sciences. But there is a good reason it’s become the main one.

What do business-school accounting professors do?

A little over a year ago, I decided that my career goal was to become a business-school professor. I’ve been lucky enough to be admitted to several great business-school doctoral programs, and, this past week, I’ve been traveling to visit some of the schools. One common theme in my conversations with my fellow admits and the current grad students is that we have trouble explaining to outsiders what our research interests are and why they count as a part of a business-school PhD in subfields like marketing, or accounting, or management. Like many fields, we have our own private semantics, and we’re not always so good at translating it for outsiders. This is hardly unique to business schools: Anymore, some dissertations in economics might strike outsiders as looking like straight mathematics, and many dissertations in political science are what regular people might identify as economics or game theory. So I thought I’d use what I learned and write a quick blog post about what business-school professors do, with a particular focus on what business-school accounting professors do, for the sake of curious and confused Googlers.  

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Most business school faculty and their associated doctoral programs are organized into several units, which might include Management, Organizational Behavior, Accounting, Strategy, Finance, Marketing, and maybe some others. But these names could give outsiders the wrong impression of what the faculty inside these units actually do. ‘Marketing’ professors and journals don’t typically study, say, whether 30-second or 60-second TV spots are more effective. Instead, they publish rigorous social science about human behavior and psychology that is, typically, more abstractly related to or adjacent to the things that firms’ marketing employees actually do–or sometimes, they publish on topics that are relevant to the academic debates and literatures those papers have generated. As such, all of the following might be broadly categorized as marketing research:  the microeconomic theory of ‘optimal auctions’ (how to design auctions such that bidders reveal their true prices—one application would be stopping oligopolistic government contractors from implicitly colluding); the psychological bases of trust and attachment (one application of which might be how learning how preferences and ideas ‘diffuse’ through populations); or even the neurological bases of attentiveness (which might have applications for education as much as for TV advertisements).

Similarly, ‘management’ professors wouldn’t typically study, e.g., how to schedule staff hours at a local retailer, but might study regional economics and why firms tend to cluster in certain geographies. And ‘organizational behavior’ professors don’t just study social psychology within the firm, but might also look at families, the military, or digital communities like online forums, or even computer models of evolving group behaviors. Even ‘finance’ tends to be broader and more abstract than outsiders expect. In other words, most of these fields are broader than you would likely expect, and can be thought of, I think, as subfields of economics (or in the case of organizational behavior and certain parts of management and strategy, subfields of psychology), that are related to, but not totally constrained by, the associated real-world business functions.

Now, some may read that criticize business academe for being impractical, but the counterargument is that the private sector already gives private-sector researchers very strong incentives to research the very immediately practical questions, and so academe can add value by stepping back to more abstract questions, to shore up the clarity, precision, empirical rigor, and theoretical basis of our ideas. The continued, outsized demand for expensive executive education courses, and business-school professors’ consulting fees, are evidence that business practitioners see some benefit in the perspective that this brings.

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Let me go into more detail about the unit that I know the most about: What are the things that people in the ‘accounting’ units at business schools do? Well, to adapt a joke about economics, accounting research is what accounting researchers do, and accounting researchers are people who do accounting research. But one way of thinking about what counts as ‘accounting research’ in academe is that ‘accounting research’ is the subfield of economics that deals with the ‘accounting’ and ‘accountability’ functions within firms, but doesn’t limit itself to the actual process of bookkeeping. (Just as marketing deals with topics adjacent to sales an advertisement, but doesn’t limit itself to studying TV commercials, etc.)

‘Accounting’ refers to the financial information that firms produce (the legally required financial accounting in quarterly reports, as well as the managerial accounting used to make decisions internally, as well as more informal disclosures such as investor presentations and earnings calls). As such, some describe accounting research as a subfield of information economics. Research in this area includes the following: (A) The game theory of how firms decide what information to disclose given their conflicting goals of (i.) giving investors enough credible information so that they can get financing on good terms, (ii.) keeping trade and strategic secrets away from prospective competitors, and (iii.) not losing access to capital due to overreactions to short-term negative news—a complicated optimization problem. (B) The relationship between firms’ earnings numbers and their asset (stock and debt) valuations. (C) Assessing the performance of doctors in hospitals (given that it would be naïve to simply measure their patients’ outcomes, as this would reward doctors for choosing patients in less-dire straights). (D) How analysts assess municipalities’ finances and, thus, how city governments become cash constrained. (E) Corporate finance, e.g., how firms can issue more equity to raise cash for investments, without thereby signaling to investors that their shares are overvalued. All of these topics could be considered accounting in a broad sense because they deal with information and performance measurement.

‘Accountability’ refers to the allocation of decision and control rights within the firm, as well as how the individuals/groups who have been allocated those responsibilities are subsequently assessed and rewarded (‘held accountable’). Research in this area includes the following: (A) Corporate governance—everything about how the owners (shareholders) of firms control the management—including the role and effects of activist investors and the characteristics of successful directors. (B) Executive compensation and pay/incentive packages more broadly. (C) Mergers and acquisitions, which are fundamentally just changes in control/accountability. (D) White collar crime and corporate scandals. and (E) Corporate finance, e.g., how debt holders and equity owners fight over the riskiness of the firm’s capital structure, or how private-equity owners use debt-financing as a way to ‘discipline’ their businesses into running tight ships. All of these topics fall broadly within theoretical questions of accountability and control.

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So, what is the value-add of business-schools’ accounting research? What does it have that isn’t already being done in regular college economics departments? Well, I actually think there’s a different answer for every individual topic I listed above, but let me focus on one of the biggest questions in accounting research, and the topic that launched the field—financial valuation. Now, from the perspective of basic financial theory, a financial asset (like a stock) is a vehicle for transforming cash today into cash tomorrow. Therefore, valuing a financial asset (that is, deciding how much cash today it is worth) is simply a question of projecting how much cash it will return to you in the future, and discounting each future cash flow by a number that translates that future money into today’s terms—that is, the discount rate rate—and then adding them all up. You can think of that discount rate as consisting of two parts:  The first is driven by how much we humans prefer money today to money a year from now, or, alternatively, as the rate of return of completely risk-free alternative investments such as Treasuries. Second, given that the world is uncertain, you also have to think about the probability distributions of those future cash flows, as well as how worried you are about losing how much of your wealth—that is, risk and risk preferences. So financial theory says that only three things matter in valuing assets—and thus, by extension, in setting prices, which are the basis of everything else in the economy—(i.) cash, (ii.) the risk-free rate, and (iii.) risk.

Given this, under one view, firms’ accounting numbers, as opposed to actual realized cash flows, ought to be irrelevant. This is because audited accounting financial statements (such as those that you see in companies’ annual reports) hinge on artificial, man-made, abstract concepts, including accruals, amortization and depreciation, rather than purely reporting actual cash flows. E.g., historically, under U.S. GAAP, you may have had to depreciate the expense of a building even if it was in fine condition and located in an area that had become more popular such that it’s true value had only increased. GAAP earnings incorporate these fake expenses that don’t actually exist; thus, they are deceptive about what actually matters, namely cash. Under this view, while accounting information might have had a legal function, in preventing managers from deceiving the public, it did not have an economic/financial function in setting prices and valuations and efficiently allocating capital.

The paper that launched the field of academic accounting research, An Empirical Evaluation of Accounting Income Numbers (Ball and Brown 1968), however, found just the opposite, that accounting numbers drove market valuations. And a wealth of research since then has found the same, that the ‘artificial’ accounting numbers are relevant to understanding firms’ financial value.

Now, I do not–before I have even started my doctoral program–wish to dare to try to summarize the whole field of accounting research or do a systematic literature review. But let me try to convey my sense of the major takeaways, of why, exactly, this might be the case. Now, nobody doubts that cash flows are what really matters–the fundamental identity of finance, that present value equals discounted future cash flows, still holds. But accounting numbers might help us get at those cash flows better, through their indirect path.

Let me draw a parallel to heuristics in the evolutionary use of the term. We could metaphorically think of our genes as fundamentally ‘wanting’ to survive and reproduce, given that survival and reproduction are what have selected and passed down these genes over billions of years. But that doesn’t mean that the genes that influence our brains tell us “survive and reproduce,” and then let us figure out the rest. Instead, our genes give us a set of desires which happen to have maximized our chances of survival and reproduction in our evolutionary history, but which we do not read as such. In other words, they achieve their goal obliquely. These desires are heuristic goals in that they are not the goal itself (from our genes’ perspectives), but rather are rules-of-thumb that tended to produce evolutionary ‘success’ better than orienting us toward the goal itself would.

In the same vein, every investor’s goal in buying a financial asset is to transform cash today into cash tomorrow, but s/he may be more likely to achieve that goal by focusing on accounting-numbers heuristics, rather than by trying to make a complicated and uncertain cash-flow projection. This is arguably the case because accounting standards have been produced by a historical, evolutionary process, of small adjustments and changes being made as-needed, at the suggestion of experienced practitioners. As such, accounting standards embody a lot of historical intelligence that’s hard to reproduce through just looking directly at cash flows. In this vein, accounting numbers do not represent the truth about a firm, but, rather, the best simplification of the truth that we imperfect humans can work with.

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To be clear, I haven’t come close to summarizing the breadth of the field. I’ve only described a few questions I’ve gotten the flavor of, to give a sense of the breadth and abstraction of the field, to others.

There are a few other things that I think are attractive about working as a business-school academic, particularly in accounting. First, today’s accounting academics get great training in economic theory and empirical methods, but they’re also rewarded for having institutional knowledge, about things like corporate law, contracts, the internal mechanics of firms and their transactions, and the things that go into the numbers that we statistically analyze. A pure economist and an accounting academic could both prove the Modigliani-Miller theorem (that equity and debt financing are equally costly to firms in equilibrium absent tax biases), but the accounting academic may be required to have more knowledge about how, say, how interest payments are accounted for in tax law, and how these things affect financing decision in reality. Second, business-school professors tend to engage with experienced students and real-world practitioners, through MBA, executive education, and consulting. As such, they tend to be a little bit closer to the ‘practice’ end, along the spectrum from pure theory to pure practice. They’re at a point in that spectrum that I like and one that, I think, produces valuable insight and knowledge. (But t his is just my preference, and I do respect my pure-economist friends who have a preference for more abstraction and pure equilibrium theory.)

So the TL;DR version of this blog post is that business-school professors do some of the most exciting and interesting social-science research around today, while still being able to engage with the real world and enjoy very strong career options. I think it’s wise for young scholars to consider doing their doctoral work through a business school.

The proper scope of the firm

One of the most interesting topics in econ/business/finance is the question of the proper scope of the firm. That is, what functions (like IT or human resources or logistics or industrial design), stages in the value chain (like retail, manufacturing, or raw materials sourcing), and businesses/product lines (like a textile manufacture considering shoe-making or a grocer considering an in-store medical clinic), does it make sense for a firm to own as part of its own internal corporate structure, and which ones should it contract out to the rest of the market? I find this question so fascinating for three main reasons: (1) It takes us back to really fundamental, basic economic questions like, ‘When are markets efficient, vs. when are there market failures such that a hierarchical command structure is better?’ (2) It’s relevant to every M&A deal we read about in the news and the value of the companies we all invest in, and managers sometimes use clearly fallacious reasoning to justify costly decisions to expand their companies’ scope; and (3) The business/econ theory of scope of the firm yields a lot of insights on the proper scope of other institutions, including those for whom profit is not the main desideratum. So in this post, I’ll talk through my understanding of the proper scope of the firm, in the hopes that some readers will learn from me and others will improve my understanding in the comments.

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It’s often said, particularly by those with a capitalist disposition, that the major insight of economics is that decentralized, competitive markets yield better outcomes than centralized controls. Markets, this line of reasoning goes, aggregate the distributed knowledge and comparative advantages of widely dispersed individuals and give each actor strong, direct incentives to meet the needs (as signaled through prices) of the others. Centralized command economies fail because human beings (who give the commands to the command economy) cannot aggregate information as well as a market-clearing price could, and, in a large hierarchical system like a bureaucracy, every individual is distant from the consequences of his/her own actions and so lacks urgency and strong incentives. That’s the argument. And while on a political/social level this may be true, it clearly cannot be true on the microeconomic level of the firm. After all, a corporation is, internally, a centralized command economy that does many different things that theoretically could be contracted via an open, competitive market. The continued existence of actual firms — as opposed to flexible market arrangements among contract CEOs and freelance legal and HR departments, with intellectual properties and factory facilities constantly trading to the highest bidder like a stock — is evidence that command structures are better at this level.

What do I mean? Well, let’s start with an example that might seem silly: Why did Henry Ford own a factory with an assembly line full of workers who had long-term contracts to build Model T’s? Why didn’t Ford instead just go into a public square with his patented Model T design and blueprints and announce that he would buy 2,000 Model T’s at the end of the month from whoever offered the lowest price? After all, classical economic theory sees all markets as working like this — constant auctions between individuals seeking the best deal at that moment. Since Ford owned the rare, unique asset, the intellectual property on the design of the Model T, and since unskilled labor is a ‘commodity,’ economics would suggest that Ford would still earn all the profits from the sale of the Model T through this competitive auction process. So why did Ford Motors own a factory with regular workers (as opposed to just earning rents on its design and contracting the building out to craftsmen)? Well, an obvious reason is that the most efficient way to build a Model T was along an assembly line, which required an enormous capital investment and cooperation among a large number of individuals. 30 people working one day on this assembly line could produce many more Model Ts than one worker could 30 days. That is, a Model T factory had enormous economies of scale as compared to individual craftsmen building Model T’s. Clearly, the benefits to be gained from this economy of scale were greater than the costs of substituting a command hierarchy for a market (costs like workers having weaker incentives and less sensitivity to price changes). So given that, why didn’t Ford outsource the manufacture of Model T’s to another company with a factory? (This is a less ridiculous question — today, after all, many major industrials outsource their manufacturing to companies like Flextronics.) There are a couple of justifications I can think of: Since automobiles were a new, nascent technology at the time, there probably wasn’t a competitive market of potential outsourcers; thus, if Ford hired an outsourcer, it could have exploited its position, claiming that new complications and cost overruns justified ever-higher prices, and Ford would have no alternative but to accept. Also, since automobiles were a nascent industry, there was probably still a lot of “learning by doing,” and Ford could use its experience assembling the Model T in-house to develop its next profitable innovation.

If I’ve belabored this, it’s to illustrate that often some firm scope seems laughably, obviously necessary, but when we dig deeper it’s actually challenging to articulate why. In the perfectly competitive market of Econ 101, in which every individual is constantly auctioning her skills and assets to the highest bidder, there’s zero advantage to owning an asset or hiring an employee long-term per se, as opposed to licensing and renting them. The price of any asset or resource, in this competitive market, is equal to the time-discounted value of the profits it would generate. So by buying an asset (and asset here is used to include resources like mines, entire companies and business units, and intellectual properties), a firm isn’t doing itself any favors unless it can add value to that asset to make it worth more internally than it is in the rest of the market. Fundamentally, firm scope has to be justified by market failure, or, to be more precise, a market failure that has costs that are greater than the costs associated with a control hierarchy. So I ask again, why do we see the level of integration and firm scope that we do see in the world? Why don’t firms hire temp CEOs for specific tasks on short-term bases? Why did Facebook buy WhatsApp instead of doing a joint venture? Why do firms have R&D divisions — why don’t they just buy or license intellectual properties as needed directly from external labs and research scientists? Why would a retailer clean or own its own building? Why are universities in the real-estate business, owning their own student housing? Etc.

Well, obviously there are many reasons. Here’s my preliminary list of some market failures that explain the firm scope we typically see in the real world:

1. Negotiated, written contracts are costly and time-consuming and cannot fully capture everything a firm needs: This is the most basic reason for corporate scope. For example, imagine you are a firm that sells hand-woven baskets made in India. Hand-weaving baskets is not capital intensive, so theoretically, you could just continuously buy from independent basket-weavers on an as-needed basis. But calling up the weavers for each new project and writing a new contract would be costly; and, particularly for a firm hoping to develop a brand, ensuring that the independent weavers all meet quality standards, or fighting over payments on baskets that do not meet standards, etc., would also be costly. In this situation, it could be more efficient to take the weavers in-house, to a single factory floor, where the weavers are managed continuously, where hours can be planned well in advance to plan inventory to match demand, and where consistent quality can be ensured in the process. These benefits would outweigh the probable costs of paying the weavers for downtime, renting space, and reducing the weavers’ own individual incentives. A lot of firm employment relationships are arguably analogous to this. Firms don’t temporarily hire their CEOs for particular tasks or services, giving the job to whoever asks the lowest salary, because no contract could specify everything a CEO is supposed to do (CEO’s valuable actions are most unobservable); instead, CEOs are given long term contracts and lots of stock ownership of the firm and its profits.
2. Economies of scale: This is another pretty basic reason for business scope, already discussed in the Ford example above. (Some would make a distinction between ‘scale’, as size specifically, and ‘scope’ as the range of businesses a corporate entity operates in, but I’m including scale as a subset of scope.) Economies of scale can explain why company-owned factories beat market arrangements among artisanal craftsmen. And they can also, perhaps, give advantages to conglomerates like Maersk (a single corporate entity that owns many relatively distinct lines of business that operate separately for the most part). Maersk “shares” a few key functions across its businesses, including bulk purchases. Because suppliers will offer discounts on higher-volume orders, Maersk can make its otherwise pretty distinct business units better off by making single bulk purchases of oil and other commodities as a single unit, on behalf of the whole.
3. Monopoly/oligopoly exploitation: A classic example of this is the steel-making industry, which requires two distinct processes: metal heating and then setting the hot metal to make steel. Could these two processes be done by separate firms? Probably not. Given that transporting hot metal is costly and dangerous, the two firms would have to co-locate to make this arrangement efficient. And once they had co-located, each would effectively be a monopolist of the other’s business. The metal-heater could demand a pay raise whenever the steel-maker faced new demand, and the steel-maker would have no realistic alternative (and vice versa). As such, separate ownership, and the chance to opportunistically renegotiate contracts, could lead to market failure here. And this fear has meant that there has usually been integration in this business and similar spaces (e.g., coal mines and co-located power plants). (As a side note, interestingly, it’s often claimed that concern over oligopolistic exploitation varies across cultures and this can explain some differences in industrial structure. For example, it’s believed that Japan’s business world is characterized by more cooperative, long-term arrangements among firms and their suppliers and so this particular kind of integration isn’t as ubiquitous in Japan.)
4. Capital markets failures: This is a broad term that can encompass a number of different things. (a) Managers may believe, correctly or incorrectly, that external investors cannot identify good investment opportunities for the firm as well as they can and that, as a result, the capital markets will not always give them the financing they need for their growth strategies. In this case, a firm could add value by expanding in scope to be able to achieve an ‘internal capital market’ — i.e., getting to the point where it can plow cash from one business into investments in another, instead of relying on the external capital markets to finance its internal investments. Conglomerates often justify their existence using this ‘internal capital market’ argument, but many investors and academics are skeptical. (b) A business can increase its value by buying another business (or another asset more generally) that is very simply underpriced. For example, a company in an esoteric, niche market may be able to identify the value of a new competitor before the capital markets see its value and price it correctly; a company that buys up this new, underpriced firm adds to its value, but essentially does so as a stock picker. (c) Investors may have too-limited time horizons: For example, an independent research lab that yielded important new insights every two decades or so might not be sufficiently supported as a standalone corporate entity by “short-term focused” capital markets. Thus, firms with long horizons (such as drug makers) tend to bring R&D in-house, and standalone, publicly-traded research labs are not (to my knowledge) common.
5. “Synergy”: This widely-ridiculed term just means that the value of several distinct things together is greater than the sum of the values of those things separately. In business terms, this would have to mean that Company A is worth $100 million and Company B is worth $100 million, but if they were packaged together under one ownership, A-B-Corp would be worth $220 million or so. How can business entities be worth more together than they are separately? A pretty mundane example of synergy would be this: Each individual corporation has to file a number of mundane legal disclosures every year, so when two companies combine they halve the total number of these legal documents and the associated legal costs. A more interesting example of synergy is this: Disney can use the movie studio that it owns to feature Disney characters, which then gets more kids hooked on the Disney universe and drives up demand for other Disney products. A more abstract example of synergy would be this: Since the process of manufacturing new technologies — the trials and errors and failures, etc. — often yields new insights, creators and owners of intellectual properties who are “forward-integrated” into the manufacturing of the associated technologies are more likely to generate new and better intellectual properties. Thus, in this case, keeping the creative R&D work and the manufacturing/implementation work packaged together in one firm (and even one physical location) can be more valuable than compartmentalizing the creatives/innovators vs. the manufacturers in separate firms and stages. A marginal example of synergy is this: Merging companies will often say things like, ‘we have a a great distribution network and they have an innovative new product, so we can use our distribution to market their product.’ It’s not clear that’s really synergy, since the one company could have just used the other’s via a joint venture or something.
6. Monopoly power/customer exploitation: This one probably needs the least explanation. If I’m one of fifty lemonade stands on the block, I’m a “price taker.” If I buy out all the other lemonade stands, I can raise prices above the competitive market rate and claw back some of the value that consumers would have gotten in a competitive market.

So I hope this outline helps explain the most ubiquitous examples of firm scope. But clearly there is a limit here. There must be a reason why conglomerates have gone out of favor, why the Soviet Union failed — there must be a point at which marginal increases in the scope of a command economy do worse than a competitive market. Indeed, in actual practice, most researchers and savvy investors think that firms have a bias toward going too far — on average, acquiring firms’ stock prices decline immediately after the acquisition is announced. Investors think that managers tend to overpay for acquisitions and cannot realize the value they expect from the acquisition. Why is this? Well, partly it must reflect the fact that our capital markets are working decently well and not obviously mispricing too many firms. (Indeed, if acquisitions usually clearly, unambiguously improved the value of firms, then that would mean that acquiring firms were getting a steal, which would reflect poorly on our capital markets.) And partly it reflects the fact that increases in scope bring their own costs, as referenced above. In a conglomerate-style corporation, the Vice President of one of the internal business will be partly compensated with options that depend on the performance of the conglomerate stock as a whole; thus she will have weaker incentives than she would as CEO of a standalone company. Vertically integrated firms where, e.g., the manufacturing division has to buy from the raw-materials division, can miss out on the information that is communicated by price changes in a competitive market. On the whole, economic theory would predict that rational firms would tend to grow right up to the size where the marginal costs of increased scope begin to surpass the marginal benefits.

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So given all that theory, what are some applications? What most interests me is the fallacious arguments that managers often give to justify acquisitions. I’ll give a couple of examples:

1. “Diversification and risk”: Managers (of, say, acquiring Company A) sometimes claim that by acquiring unrelated businesses (of, say, eaten Company E) with uncorrelated earnings, they can smooth their own earnings, and thus reduce their risk.  Doing so obviously should reduce stock price volatility, but it doesn’t actually add value for shareholders, for a very simple reasons: Shareholders of company A could just as easily buy shares of company E themselves and achieve reduced risk through diversification on their own.
2. “We’re moving to the higher-margin stage of the value chain”: Hardware firms sometimes justify their acquisitions of software firms by noting that software is now the higher-margin stage of the technology business. But this justification is fallacious, or at least incomplete, for a simple reason: The owners of software firms know that they have high margins (and profits) and thus, like anyone else, shouldn’t sell out for a price that doesn’t reflect the time-discounted profits they expect to earn. So high-margin businesses have high value and they accordingly have high prices and so there’s no free lunch in buying into a high-margin industry. Now, there could be other good reasons for acquiring these higher margin businesses; for example, if the capital-markets undervaluing them or there is some ‘synergy’. But buying a high-margin business isn’t a free lunch per se.

Rather, to justify an acquisition, a firm has to pass at least these four tests (some of these “tests” are borrowed from Prof. David Collis of Harvard Business School):

1. The acquirer has to be able to add value to the acquired entity, to make it better off. This added value has to be greater than the acquisition premium, obviously.
2. The acquired business unit should be worth more inside the firm than in any other possible ownership structure. Otherwise, the acquiring firm can best profit by selling the unit to the most valuable ownership.
3. There is no market-based way to realize the value of the acquisition — i.e., flexible market contracts and joint ventures will not realize the same value.
4. The benefits to the acquisition have to outweigh the costs of expanded scope, in terms of internal coordination and information problems and individual incentives/motivation.

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Ever since I got interested in corporate scope, I’ve been trying to apply the theory to understanding all of the institutions around me. It’s fun and sometimes I feel like I see a lot of surprising logic and illogic. One institution I debate about is the University. For example, why do universities own housing and also own cool facilities like rock-climbing gyms and heavily subsidize these facilities? Why can’t college students just rent their own apartments like other twenty-somethings, and pay for time at private rock-climbing gyms? Why do some business schools, after charging admits very high up-front tuition, then pay to send those MBAs abroad for ‘immersive experiences’? Why can’t the MBAs pay lower tuition and buy their own flights abroad? What is the ‘synergy’ that justifies packaging all these things together?

One hypothesis I have is that the University is sort of like the managers who think they’re smarter than the capital market and can improve on it with an ‘internal capital market’: The University is an institution that has a particularly paternalistic (and I really don’t necessarily mean that in a bad way) attitude towards its ‘customers’. The University may believe that the external capital market tends to underinvest in human capital and that it can add value through an internal capital allocation process that nudges students to try new things like rock-climbing, going abroad, living in comfortable housing in close proximity with peers, etc. That is, the University charges a high upfront fee to let you in in the first place, but, once you’re inside, all these cool experiences are heavily subsidized so that even the financially-anxious student will try things that the University thinks are worth spending money on, but that cash-constrained young people might normally eschew.

This is abstract, though, and in practice I think universities should consider unbundling many of their products. I’m curious if readers have other examples of surprisingly intelligent or stupid scope in firms or non-profit institutions.

The Innovative University, by Clayton Christensen and Henry Eyring

As part of a broader research project, I recently read Clayton Christensen’s and Henry Eyring’s The Innovative University: Changing the DNA of Higher Education from the Inside Out. There is a temptation to be snobbish about books that have the overused ‘innovative’ in the title, so I started reading with a skeptical mindset. But I found the book to be immensely informative and thoughtful and so I wanted to share what I learned. I’m going to summarize the three main main strands of thought that I pulled from the book: (1) A history of American universities, particularly how accredited universities today are bound to what the authors call a ‘Harvard model’ of what a university should be, a model that came to be for specific historical reasons and that does not serve all of us well today; (2) An application of the theory of ‘disruptive innovation’ (the term here being properly used by its originator) to the higher education market; and (3) Case studies and ideas on how digital technologies can improve the delivery and price of higher education. Then I’ll close with a small criticism and my heterodox take on the big market failure in higher education today.

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(1) One major bias or barrier to really innovative higher education reform is that the people who accredit and run universities, the people who hire college graduates, the intellectuals who shape the conversation around higher education, and our legislators are almost all graduates of relatively elite tier universities. They have thus been acculturated into thinking that that is the way that a university must be; they have a self-serving bias in thinking that that is what equips you to be a good employee/leader/citizen; and they have no exposure to people who have different needs and expectations for higher education. The authors of and the leaders profiled in The Innovative University are mostly people who have been at one time Harvard faculty. But they make great efforts to control for this bias by (i.) revisiting in detail the history of American universities to understand why they came to be that way and (ii.) studying today’s ‘down-market’, non-selective universities and their students.

What are some things we learn when we study universities this way? First, you learn that a lot of things that we take for granted have really arbitrary historical origins. For example, why do we have summer break at four-year colleges in the U.S.? Is it because students had to go work on the farm in the summer? Not so. In fact, summer breaks can be traced to the first couple decades of Harvard’s existence, when instructors found that the couple-dozen students at the college at the time, some as young as 14 years old, were more likely to break out into fist-fights while studying ancient Greek during the hot, malarial months. Are there nonetheless good reasons for a long summer break today?  Maybe. Arguably this model works very well for Harvard, whose professors need dedicated time for valuable independent research, whose students can secure stimulating summer internships and research opportunities from their freshman years, and whose brand name allows it to rent out its dorms and lecture halls for lucrative summer schools and summer camps. But summer breaks may be a huge waste at other, ‘down-market’ universities, whose students’ feasible internships will not offer as much stimulation and advancement as classes would, whose professors’ research is arguably less valuable than their instruction, whose students are far more likely to get frustrated with the time required to get a degree and drop out, and whose empty facilities are a significant strain on their operating budgets.

Or take, for another example, the assumption that university professors must serve dual roles as teachers and researchers. This can be traced to the early 1700s, and the influence of Isaac Greenwood, Harvard’s first chair of mathematics and natural philosophy, who learned of Newton’s new Laws on a trip to London, and led a push to get Harvard faculty to use the lab equipment necessary to demonstrate these laws to Harvard undergraduates. At the time, it made sense to have instructors doing basic research, to ensure that they didn’t get basic things like ‘does a moving object lose speed if no counteracting force is applied to it?’ wrong, and because scientific knowledge was at a point where undergraduates could be taught the latest insights. But now that cutting-edge research in physics is not accessible to freshmen, it makes less sense to allocate the tasks of cutting-edge research and freshman instruction to the same group of people; in fact, it’s conceivable that today’s experts may be immersed in their specialties to an extent that disables them from communicating the basics to outsiders. Again, the dual role of the professor-as-researcher-and-instructor may still be defensible at Harvard, where professors can pull their own weight in research grants, where many students want to move onto graduate-level original research themselves. But it doesn’t make much sense for down-market universities to be inflexibly committed to this duality. Also, the early research focus ultimately evolved into today’s ‘publish or perish’ — universities are now in the puzzling situation of simultaneously (a) claiming that they are doing their best to improve undergraduate instruction and (b) making frequent publication their professors’ near-exclusive career incentive, giving almost no incentive for good instruction.

A large number of university features that we take for granted trace to the Harvard presidency of Charles Eliot in the late 19th and early 20th century. Eliot gave the Harvard “Faculty of Arts and Sciences responsibility for all college-level instruction.” Prior to this, high-school students could apply directly to Harvard College, Harvard Law School or Harvard Medical School. Now, you need a bachelor’s to apply to the latter two. Eliot coupled this move with an attempt to reduce the undergraduate curriculum from four to three years — but this was vetoed by the 1907 financial crisis, which made Harvard FAS unwilling to forego 25% of their undergraduate tuition. Requiring 7 years of very expensive education to become a general practitioner makes little sense today and is a serious financial burden on our health-care system.  Eliot initiated a move toward a system of lifetime tenure and great faculty autonomy, partly to attract scholars in a time of under-supply and low social tolerance for many ideas. Again (sorry for repetition) the situation may be different today, particularly at down-market universities. Eliot emphasized breadth, aiming to attract the world’s leading scholars in all subjects, and requiring Harvard undergraduates to begin their studies by fulfilling broad distributional requirements. Today’s down-market universities, though, could benefit from product differentiation (“we don’t serve Slavic studies here”; “we do chemical engineering, they do mechanical; apply/transfer accordingly”) and putting technical specialization up front in the curriculum (i.e., arranging the curriculum so that if a student drops out after year 1, s/he already has a few technical certificates, rather than putting the technical certificates in year 4, and the distribution requirements in year 1). Eliot found (to his disappointment) that the college’s football team was a key to raising donations from alumni, and invested in its development and league-memberships accordingly; today’s universities would do better with less emphasis on athletics. Eliot placed a ‘German-style’ research university (PhD programs) ‘on top’ of the ‘English style’ liberal arts college; he and his successor began the dual requirement of distributional requirements and a specialization in a major. While this gave students the advantage of taking graduate-level courses when they preferred and combining breadth with specialization, it also pulled the undergraduate curriculum to become preparation for PhD level research and increased the number of courses required for graduation.

All these taken-for-granted characteristics of the university and more came to be for historical reasons. They’ve since been solidified by replication (i.e., people who found new universities model them on the ones they graduated from) and accreditation and college-rankings standards. After WWII, as veterans began using their GI bills to go to college, the U.S. government empowered established universities to have a sort of ‘peer review’ process in accrediting the new universities that sprung up to serve them. Today, regional accreditors are frequently criticized on the grounds that they emphasize the colleges’ inputs over their outputs (i.e., research facilities and faculty credentials over student employment and measurable learning progress). In 1967, the Carnegie foundation created a simple taxonomy of different types of higher-ed institutions according to their emphasis on research and doctoral programs, intending the classification system to be used for its own charitable purposes. But the Carnegie Commissions’ taxonomy quickly became seen as a normative, hierarchical ranking system, with colleges desperately seeking to “climb the Carnegie ladder” and proudly announcing each new step. We all know about the problems with the U.S. News and World report ranking system, which incentivize schools to compete with luxurious student amenities and otherwise game the system. The U.S. News rankings don’t just put pressure on colleges to make irrational decisions, they also put pressure on students and parents — a student who would prefer to attend a college with lower tuition and fewer luxurious amenities (and hence a lower ranking) will know that his/her prospective employers will rate the value of that university’s degree according to the U.S. News rankings.

So, you get the gist here:  There are a lot of historical features of the ‘Harvard model’ that are not serving today’s down-market institutions and students, but which are not frequently questioned and are actively solidified by the Carnegie ladder, regional accreditors, and the college-rankings system. The book brings home the contrast between the needs of more typical college students and the bounds of the ‘Harvard model’ by following Kim Clark, who unexpectedly stepped down as Dean of Harvard Business School in 2005 to move to the unheard-of BYU-Idaho (formerly Ricks College). There, Clark has made humanitarian efforts to reach out to all high-school graduates, to women (often Mormons) who felt they should drop out of college to become mothers, and to ‘at risk’ students who might not be able to complete a full bachelor’s curriculum, but whom Kim hoped to equip with technical certificates and employability along the way.

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(2) The term ‘disruptive innovation’ gets ridiculed a lot for its overuse, but the original meaning of the term actually captures a really important phenomenon. The idea is like this: One day, an innovative new product, like the computer, arrives on the scene. Because it’s new and innovative, it’s expensive, and it gets sold to businesses, governments, and the wealthy. A lot of different businesses compete to sell computers to these clients. They try to differentiate themselves and outdo their competitors by offering ever faster speeds  and ever-more widgets and functionalities, what Christensen calls “sustaining innovations.” The computer (the product) gets better and better and higher-functioning and more expensive. But then one day, someone thinks, “Who actually needs all this speed and all these widgets? Why don’t we just offer a super-stripped down computer with the bare minimum functions and sell it to regular people on the cheap?” The big established players don’t like the idea of making a low-quality product and don’t think it could ever work. So this “disruptive innovation” usually comes from a new company, not one of the established ones; the disruptive innovation first wins consumers at the low end of the market with simple low prices, but then also eventually wins the high end of the market, once the simplicity and low cost of the innovation are enough to compensate high-end users for slightly fewer widgets and whistles. The disruption of the mainframe and minicomputer industries by Macs and PCs is a classic example, but Christensen says this is a common product life-cycle.

Does this sound like something that could happen to higher education? Christensen and Eyring answer with a qualified ‘sort of.’ The evolution of the university over the past century is certainly an example of sustaining innovations going beyond consumers’ needs: Too many universities have too many departments, too many indoor rock gyms and athletic teams, and too little student-oriented faculty. There’s now widespread attention to the problem of high costs. So, Christensen and Eyring think there’s a real opportunity for universities to do well by serving ordinary students in a more cost-effective and stripped down manner. But they think that traditional universities’ ability to pass on “wisdom” from established scholars, to facilitate face-to-face interaction among peers, and to produce original research — what Christensen and Eyring call “discovery, meaning, and mentoring” — are unique.  These are things that cannot be replicated, they argue, outside the traditional university and so we won’t see any massive disruption by for-profit and online providers (more on that later).

Instead, they hope for incremental, cost-lowering changes within universities. This depends on a conceptual rethinking and a bunch of specific changes. The conceptual rethinking is that we should stop seeing the higher-ed space as a ladder, with every university competing to climb to the top rung with Harvard. Instead, we should think of the higher education space as a ‘landscape,’ with universities differentiating on their core advantages, attracting particular kinds of students with niche offerings, and competing on price as well as on rankings. Christensen and Eyring highlight some colleges that are trying to become cheaper and more stripped-down, praising BYU-Idaho, under Kim Clark, for cutting athletic teams, reducing the number of majors, and optimizing the logistics of building use in order to move from a two-year community college to a four-year bachelor’s-granting college without increasing annual costs. They also note that if we use cost-per-degree-granted as our primary metric, the number one way most colleges could improve would be to increase their graduation rates and decrease the number of students who stay on for a fifth or sixth year. To this end, they advocate some basic structural changes like a ‘modularized’ curriculum. The idea is that, right now, a lot of students who take a fifth or sixth year to graduate do so because they switched majors at some point and were unable to apply their former major’s classes for credit in their new major. Universities could instead start grouping classes into modules, any of which could be considered a component of a couple of different majors. So, for example, a ‘quantitative methods’ module, including calculus, linear algebra, statistics and/or computational statistics, could be ‘stuck on’ to any social science, science, or engineering BA. A ‘business basics’ module that included accounting and finance could be ‘stuck on’ to both an economics and a healthcare management BA, etc. If students’ interests or career goals change, they could then switch through a variety of majors without losing too much progress toward graduation.

They also suggest that there’s an opportunity for universities to change their professors’ career incentives. For example, a university might offer multiple tenure tracks — professors would be rewarded not just for their esoteric original research, but also for outstanding teaching, course development, textbook writing, integration of insights from others’ original research, and even publication for general audiences that improve non-expert access to fields. They also suggest rethinking tenure. Now, to be in favor of ‘rethinking tenure’ is not to be in favor of ‘firing professors at whim, particularly for having unpopular opinions.’ (If anything, up-or-out tenure may only increase political censorship in the academy, as faculty committees will vote down professors with unpopular views, while more practical-minded administrators would have been happy to have the professor stay on and continue teaching.) Most professions and institutions build up long-term relationships of mutual respect with their employees that prevent abusive and unfair dismissals and there’s no reason academe can’t be the same way. Rethinking tenure could improve the teaching productivity of junior faculty, who would feel less anxiety and pressure to publish prolifically, and also improve the productivity of senior faculty, who would feel less apathetic.

Finally, they suggest that brick-and-mortar universities can survive in the digital future by differentiating themselves from low-cost for-profit, online alternatives by emphasizing a commitment to moral instruction and mentoring (more on this below). Altogether, then, they list twelve “recommended alterations” for universities. They represented these as a table, with a column of “Traditional University Traits” and a column of “Recommended Alterations.” Since it’s the main takeaway of the book, I’ll represent them here, with a list in which each “Traditional University Trait” will be separated by an arrow (“–>”) from its “Recommended Alterations,” below:

• Face-to-face instruction—>Mix of face-to-face and online learning;
• Rational/secular orientation—>Increased attention to values;
• Comprehensive specialization, departmentalization, and faculty self-governance—>Interdepartmental faculty collaboration and heavyweight innovation teams;
• Long summer recess—>Year-round operation;
• Graduate schools atop the college—>Strong graduate programs only, and institutional focus on mentoring students, especially undergraduates;
• Private fundraising—>Funds used primarily in support of students, especially need-based aid;
• Competitive athletics—>Greater relative emphasis on student activities;
• Curricular distribution (general education) and concentration (major)—>Cross-disciplinary, integrated GE and modular, customizable majors, with technical certificates and associate’s degrees nested within bachelor’s degrees;
• Academic honors—>increased emphasis on student competence vis-à-vis learning outcomes;
• Externally funded research—>undergraduate student involvement in research;
• Up-or-out tenure, with faculty rank and salary distinctions—>Hiring with intent to train or retain, Customized scholarships and employment contracts, Minimized rank and salary distinctions consistent with a student-mentoring emphasis;
• Admissions selectivity—>Expansion of capacity, (for example, via online learning and year-round operation) to limit the need for selectivity.”

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(3) The really big talked-about development in higher education today is the rise of MOOCs. There’s an argument to be made that all this excitement is just noise: Universities have made efforts to provide low-cost distance education online in the past, and it didn’t upend the higher-education market then; completion rates have always been very low in distance education courses. But in recent years there have been major improvements in internet connectivity, download times, and online course platforms, which could provide the basis for modestly effective but super-low cost delivery of higher education, through MOOCs and others. Christensen and Eyring are cautiously optimistic about these changes and the rise of for-profit online universities as well, but they stop short of all-out disruptive-tech-boosterism. They do not expect that students will soon take classes from Coursera for free and get their BAs and MBAs for a few hundred dollars in course registration and testing fees plus the cost of rent and an internet connection. Instead, top-tier universities will continue to provide in-person instruction (and people will continue to compete desperately and pay anything to access them), while second-tier universities will incorporate MOOCs for ‘flipped classrooms’ and similar uses. As they write,

The most powerful mechanism of cost reduction is online learning. All but the most prestigious institutions will effectively have to create a second, virtual university within the traditional university, as BYU-Idaho and SNHU (Southern New Hampshire University) have done. The online courses, as well as the adjunct faculty who teach them, should be tightly integrated with their on-campus counterparts; this is an important point of potential differentiation from fully online degree programs. To ensure quality, universities may also decide to limit online class sizes or pay instructors more than the market rate. Even with such quality enhancements, online courses will allow traditional universities not only to save instructional costs but also to admit more students without increasing their investment in physical facilities and full-time faculties.

It’s hard to predict how online courses will be used in a decade. But the authors highlight some incremental changes being made now, which they recommend to other universities. At BYU-Idaho, for example, online courses have been particularly useful in allowing women who dropped out when they became mothers to finish their degrees. The school actually made it a requirement that all students take at least one online course, as a way of proactively developing their and the university’s comfort with the medium. They’ve found that online instruction is not best used to replace in-person classes, but, rather, for blended and ‘flipped’ courses. In flipped courses, students watch lectures online (sometimes lectures that are specifically tailored for the medium, e.g., including small computer-graded quizzes throughout); students go in to class in-person to work on problem sets, to talk over more advanced applications with the instructor, etc. And BYU-Idaho has also used its online courses toward its humanitarian goal of giving people in developing countries access to its courses and technical certificates.

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Here are some more thoughts and criticisms: First, I think most of my friends reading this blog post are already prepared to criticize me and these authors for advocating a pre-professional/vocational vision of the university. But we’re not. There’s zero inconsistency in maintaining two positions simultaneously: (1) that universities should pass on ethical and aesthetic learning, and facilitate students’ philosophical expansion, exploration, asking of intrinsically important questions, etc.; and (2) that universities should find ways to do so in a financially sustainable and reasonable way, and mid- and lower-market universities in particular should not yield 50% dropout rates, 6.5 year average graduation times among the graduating half, heavy student debt, and un- and under-employment of their graduates.

In fact, my main concern with The Innovative University is that, if anything, it puts too much faith in universities as providers of the ‘soft’ goods of mentoring and moral-character formation. At one point in the book, the authors observe that what they call “cognitive outcomes” (that is, measurable learning) for one particular online course are as good as cognitive outcomes for a similar course offered at a traditional university, but students pay more for the course at the traditional university. They therefore infer that this disparity proves that students are paying for value, and must be receiving moral instruction, wisdom, and mentoring in return. But there is of course a simpler, more pessimistic interpretation of this data: Employers value traditional universities more because they’re familiar and employers are skeptical of unfamiliar routes and so the students are paying a premium just to reassure prospective employers; they’re not necessarily paying that premium to truly get some pedagogical value for themselves. In other words, the evidence is consistent with higher-ed consumers being stuck in a “prisoner’s dilemma”: we all might prefer some low-cost, no-frills education, but as long as employers will give even a slight nod to students from traditional prestigious universities, we’ll all face immense pressure to choose the traditional one. I’m not prepared to say that Christensen and Eyring are incorrect that professors provide valuable mentoring and moral education. I more that their assertion could be used bolster beliefs in the irreplicability of in-person instruction and to resist calls for experimentation and change. For example, suppose there was a person who was very good at self-directed learning and got a broad liberal arts education in college in a curriculum that covered nearly all of the most significant works in moral philosophy and social thought. Should this person be required to spend two years and $140,000 moving away and receiving “meaning and mentoring” from business-school professors in order to, say, get an MBA to get promoted up from the analyst level in a consultancy, rather than spending a year or two of self-directed learning tearing through some edX and Coursera courses and textbooks to get really hard technical skills in computational statistics, financial valuation, accounting, and optimal pricing theory, etc.? While many students will still be happy to go the traditional MBA route, I think we should also find a way to properly credential self-directed learners, particularly in an era in which so much work is self-directed and unstructured. I hope education entrepreneurs will seize the opportunity to develop “competency-based” credentialing for these self-directed learners. And faculty members should recognize they have a bias when they tell accreditors, legislators, and prospective students, “No, really, you need to separate from your spouse, move cities, and receive our wisdom in person”; those of us who benefit from academe as it currently works should listen closely to those who currently see it as a barrier to their goals.

So I wish that the book had done more to highlight and promote bigger, more fundamental changes in higher education that could be facilitated by new digital technologies — particularly, any of the nascent efforts to establish certification for self-directed learners who are taking advantage of online courses, both in the U.S. and abroad. But my sense is that Christensen and Eyring did not focus on these because the evidence suggests that the users of these open-access online courses have so far been a relatively privileged, college-educated set. Christensen and Eyring think it’s a humanitarian priority to focus on less privileged students, at universities that graduate only fractions of their entering classes. The problems and frustrations of those students, and the benefits that would accrue to society if we solved them, make mine seem utterly trivial.

Finally, a theoretical question and an attendant concern: We often hear that higher education today is a ‘bubble’, but there’s a problem with this claim. If higher education is a bubble, what’s the market failure that’s to blame? After all, when people choose to pay lots of money for iPhones, we generally assume they’re rational, informed consumers paying more to get more; when some price is irrationally high, we can usually blame some monopoly or cartel or psychological bias. So what could the market failure be in higher education? This is a big question, but I’ll offer one comparison that occurred to me: Emergency rooms are a well-known market failure. The problem in an emergency room is that your life, which is the condition of your enjoyment of everything that is valuable to you, is immediately at risk, and so you can’t really shop around and ask all the emergency rooms in town to quote you a price. The hospital knows it can charge any price to the emergency-room patient, and this is why we rely on a mix of (i.) medical professional ethics, (ii.) government price controls, and (iii.) collective bargaining via insurers, to control costs here. In a similar way, in a country that aspires to meritocracy, we have made  university affiliations one of the main determinants of social status and we do not shop for a bargain when it comes to social status — humans will pay almost anything to move up the hierarchy. That’s why there’s little real competition on price in higher education–there’s no university that advertises itself as “85% as good as Harvard, at 60% of the cost” and even if there were, few who had the chance to go to Harvard would go to it. Harvard could cut out most of its in-person instruction, tell its undergraduates to take many of their courses through Coursera, and triple its tuition, and I predict that demand for entrance to the university would barely fall, because one of the college’s biggest sources of value to students is as a gate-keeper of social status. Status is virtually priceless–like your life in the emergency room, it’s the condition of so much else you hope to enjoy in life–and that’s the market failure here. There’s no competitive pressure on elite universities to control costs because status is priceless. Elite universities can charge anything they like, and as long as elite universities set the pace for the universities that imitate them, the market won’t control tuition costs. The market won’t, on its own, value self-directed learning through online classes as much as it values degrees from status-conferring, gate-keeping institutions; the market won’t pressure law schools to adopt a two-year curriculum, as President Obama has advocated; the market will put zero pressure on Yale and Harvard to lower their tuition prices. The market won’t protect us consumers here, because we’ll keep paying anything to place our kids a little higher in the social hierarchy. So, instead, it’s incumbent upon university leaders to make an ethical choice to control their costs and restrain the university arms race, even when it is against the interests of their faculty and employees.

Intellectual Property

One major policy domain of which I have a limited understanding is intellectual property law and policy. So I wanted to write a post to talk through my understanding of intellectual property and invite you, readers, to correct and improve me in the comments. In the first part of the post, I’ll try to lay out broad ideas about intellectual property; in the second, I’ll try to apply those ideas to some current controversies.

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Property: In the modern world, at least since the fall of the Berlin wall, most of us believe that private property is important and deserving of protection. There’s both a deontological, ethical argument and a consequentialist, economic argument for why. The deontological argument hearkens back to John Locke, who famously argued in his Second Treatise that people initially assumed property rights to the land by ‘mixing their labor’ with it; the original landlords, he imagined, were those who put their selves into their land by founding, taming, and tilling it, making that land a kind of extension of their selves; the right to private property was therefore an extension of self-ownership. Modern intellectual heirs to Locke (including those who identify as Nozickians) would argue by extension that when I freely contract with others, offering them my talents and hard work in return for cash compensation which I use to purchase assets or commodities, then I have earned and deserved those assets, and so taking those things from me would be a violation of my self and a denial of my desert. The economic argument for property rights it that people will not build and invest in valuable assets unless they feel assured that they will continue to control those assets and, hence, be able to use them to their profit. Countries that don’t credibly guarantee to protect private property discourage investment and scare their own citizens into investing all their assets abroad, hurting their growth and prosperity. (See Argentina.)

Property, Intellectual: Intellectual property  — typically defined as property that is a work or creation ‘of the mind’ or the ‘result of creativity’ — is similar but different from regular physical property. It’s arguably similar in that (1) the things I create with my mind are a kind of extension of my self, and so it would be a violation for someone to claim my work as their own or appropriate my work for profit without my consent and (2) people and companies will not invest in new ideas, research, creations, and brands unless they can be assured that they will gain compensating benefits for those investments. Since in a competitive market you cannot gain any profit from a thing that everybody else has access to, recognizing exclusive intellectual property rights is thought to be an ideal way to incentivize research and innovation. But intellectual property is different, crucially, from physical property in that it is abstract and hence non-rivalrous — that is, someone can copy my algorithm or song or blog post without taking it from me. If someone takes my physical asset, like my land, I can no longer enjoy and use it; if they copy my song or algorithm or blog post, I still can.

What principles should we use in granting intellectual property rights? I would argue that it’s better to think about property rights primarily through the consequentialist, economic lens, rather than the deontological, natural-rights-based lens. Philosophically, it’s hard to parse the boundaries of individual desert: I largely ‘owe’ my ability to produce creative work to the parents who fed me and read to me as a child, to the public institutions that educated me, and to the political system and culture that were the basis for it all. More practically, even the most Lockean stalwarts would caveat their understanding of property-as-natural right when the consequences are great enough: Suppose a brilliant scientist had discovered and patented a cure for all cancers, but refused to sell or license the patent out of a Kaczynski-esque hatred of technological modernity; in the face of the potential to save millions of lives, would we really have an obligation to ‘respect’ this scientist’s ‘natural right’ to his discovery? For another thought experiment: If our ideas are extensions of ourselves, and thus our inviolable natural rights, then shouldn’t, e.g., a policy wonk or mayor who comes up with an innovative policy solution for managing mass-transit or Medicaid logistics be able to patent that method and prevent other municipalities from adopting it? If the creative inventions of our minds are our natural rights, why would we grant patents for, e.g., efficient computer algorithms for managing data, but not for efficient ‘social algorithms’ like those imagined policies? Finally, if intellectual property is a natural right, then how would we justify ever letting patents expire? In short, I think the property-as-natural-right argument doesn’t withstand philosophical scrutiny; we should instead think of intellectual property rights as constructed social tools, artificial legal rights that we as a society assign in the interest of promoting our shared prosperity and felicity.

The basic economics of intellectual property: If we accept the argument above, then we should think about intellectual property rights as economists do, as a tool to maximize social utility. To that end, we want to both (1) give people incentives to produce innovative and creative works in the first place and (2) maximize ordinary consumers’ ability to access and enjoy those goods. These two goals are obviously in tension: If you increase patent protections from 10 year to 15 years, then you give firms even stronger incentives to invest aggressively in research and development (because they’ll be able to command monopoly prices on the innovation for longer), but you’ll also increase by 5 years the length of time that consumers have to wait to enjoy the good at cheap, competitive prices. If you decrease patent protections from 10 years to 5 years, you’ll halve the time consumers have to wait for competitive prices on goods, but you might decrease risky and innovative R&D, as companies fear that they’ll find it hard to make a killing in that time. The economic debate centers on finding the social optimum, given this tradeoff.

As I’ve read up on intellectual property I’ve found that there’s basically a consensus among intellectuals and experts I respect about three very broad things: (1) The basic economic theory — that we generally need some IP protections to give incentives to creators, and the debatable question is how to optimize the tradeoff between giving creators these incentives and giving consumers earlier and more access — is sound; (2) But in its actual legal implementation, there are a lot of problems and abuses in our current IP-law system — our IP system is subject to abuse by extortionate ‘patent trolls,’ we grant patents for small, incremental changes to technologies that may not constitute truly creative breakthroughs, etc.; and (3) Our intellectual property legal protections are probably too strong overall. Item number three here is actually what one would predict given the theory of public choice. Intellectual property law lobbying is a classic example of “distributed costs and concentrated benefits.” Individual firms and patent owners get very big, very obvious benefits from legislative extensions of the protections on their intellectual properties and they lobby accordingly; we individual consumers get hurt by these in delayed access, higher product costs and health-insurance premiums, etc., but because these costs are diffuse and sometimes invisible, we don’t put appropriate pressure on our legislators to stop them. Thus our democracy produces laws whose aggregate costs outweigh their benefits.

There’s also a compelling heterodox viewpoint that our IP laws are radically too strong, and that we should radically weaken all of our IP protections and completely eliminate many of them. But in the rest of this post, I want to first touch on a potpourri of IP issues, using the consensus ideas, and then finish up by touching on the heterodox idea a little more.

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Types of IP: First, let’s distinguish among types of intellectual property. The least controversial type is trademarks. Protecting trademarks simply amounts to preventing vendors from lying about who they are to consumers; this makes it easier for us find what we want from sources we trust. Very few people are against the indefinite extension and protection of trademarks. Industrial design rights basically amount to the same thing. Copyrights protect creative, artistic works, allowing their authors to control their use, replication, and distribution. Individual copyrights extend to 70 years after their authors’ deaths; corporate copyrights last until 120 years after their creation. It seems very hard to justify these extremely long copyright lengths. Personally, I find it hard to motivate myself with the prospect of the financial returns my blog posts will generate 1 year after my death, much less 70 years thereafter. Patents protect inventions and discoveries and allow their holders to control their use and sale for 20 years after the initial filing date (in the U.S.). While 20 years of patent protection doesn’t seem outrageous when compared to the length of copyright protection, it certainly seems like a long time for those hoping to access life-saving drugs at a competitive cost, or an energy company hoping to use some patented chemical in prototyping a new super-efficient battery, or non-Amazon e-commerce sites hoping to implement one-click shopping. In other words, it’s still an urgent question, are we offering too-strong patent protections?

Industry variance: In thinking about patents, we need to distinguish among industries. There’s no reason in principle to think that the ideal patent regime would be the same across all lines of business. Judge Richard A. Posner has argued that the pharmaceutical industry is a classic example of one that does require patent protection, due to its high, up-front R&D costs and uncertain payoffs, but that most other industries “would do fine” without patents. The I.T. industry in particular seems to be characterized by lots of lawsuits over patents held on ergonomic quick-fixes that seem more like part of the companies’ marketing than their R&D. Do we really think that Apple would not have developed the swipe function on the iPhone without the promise of patent protection? Or Amazon and its one-click-shopping option, for that matter? According to this table, all industries outside of pharmaceuticals and chemicals think the overwhelming majority of their patents would have been developed and implemented absent patent protection.

Patent trolls: These companies, which allegedly buy up dubious and less-than-innovative patents in order to shake down unsuspecting businesses with legal threats (usually coming formally from shell companies) are back in the news. In recent years companies using certain scanners and producing podcasts, for example, have received demands for cash from companies holding patents on ideas that only vaguely prefigured podcasts and contemporary scanners. People in the tech industry overwhelmingly say that they feel that innovation is being stalled by tech firms’ constant legal anxiousness that they’ll be found in violation of some esoteric, vague patent. Part of the problem is that the overstretched and understaffed U.S. patent office has granted a lot of vague patents that it probably should not have. The President is currently proposing new rules that would require that patent-holders be disclosed in patent arbitration cases; this would, at least, expose and hopefully shame the most blatant patent trolls. A more general idea for mitigating patent trolling is that we should be able to patent only implementations, not purely abstract ideas.

Music today (back to copyrights): The music industry today is an instructive case. As we all know, it’s very easy to download and torrent music for free online and so young people generally do not pay for the copyrighted music they listen to. And yet it’s commonly observed that musicians are doing better than ever before today. How’s that? The radically expanded access to music that we consumers are all now enjoying, and the ease with which we can share and recommend our friends, has whetted our collective interest in musicians and we now pay more to see more live shows than ever before. What musicians have lost in CD sales they’ve largely made up in ticket revenues. I suspect that in the future, the authorities will largely grow to accept a world characterized by (1) not-for-profit illegal downloading of media; (2) for-profit ventures like Spotify that stream music for users for small fees or advertisements and pay relatively small per-play fees to creators; and (3) pop music and movie producers that know they have to be extra spectacular to draw people into concert venues and theaters, and indie bands that learn how to cultivate voluntarily supportive cult followings. More generally, the fact that musicians have flourished despite the effective erosion of their copyrights, thanks to second-order effects of music’s increasing availability, strengthens the case for reconsidering intellectual property rights in other domains as well.

Financing medical innovation through public prizes: Pharmaceutical patents are possibly the most controversial domain of patents, first for the obvious reason that denying or charging prohibitively high prices for necessary medicine horrifies us, and second because many people see pharmaceutical companies as patenting a lot of not-so-innovative incremental changes to extant drugs, and then pushing these patented drugs, which they can sell at monopoly prices, on insurers, doctors, and consumers, driving up costs for all of us, without providing true innovation or benefits. (Now, notably, I think it’s silly to blame patent rights per se  or corporate greed here — the root problem (if I may pause to grind my ax) is the total lack of individual incentives in our insane health care system. If the medical market were more cost sensitive at every level, and we consumers were rewarded for our choices to reduce our costs, then we would simply choose to use less expensive, unpatented drugs, unless the more expensive, patented ones offered compensating benefits.) But given that my preferred healthcare policies are not likely to be implemented, how else could we mitigate this problem of wasteful pharmaceutical investment and innovation? One clever idea would be to stop granting new pharmaceutical patents and instead begin offering public prizes. I.e., the government would offer $5 billion for whichever company could first produce a drug that met some well-defined criteria in improving our treatment of AIDS/Alzheimer’s in XYZ ways. Theoretically, this would stop pharmaceutical companies from overinvesting in small, incremental pharmaceutical innovations and encourage them to focus on our most pressing health needs, as defined by smart public authorities. Once the government had awarded the prize to the victorious pharmaceutical company, any company in the world would have the right to vend it, and so its price would quickly be driven down to its marginal cost of production, immediately widening its availability. This is a clever idea, but it certainly has some problems: As a public-sector entity, such a prize-granting agency would face political pressures to focus on politically popular cures, and underinvest in less salient ones; with no ‘bottom-line,’ its revolving-door bureaucrats might overpay pharmaceutical companies generally, just as, today, government contractors are seen as overpaid; there would be huge liability issues and public outrages when prize-winning drugs turned out to have mild side effects or tradeoffs or cause 3 people 5 sleepless nights, which might also drive such a public entity to be way too conservative in awarding prizes and publicly offering drugs. I’m not sure whether our current system or this proposal is more imperfect.

Intellectual property abroad: Enforcing U.S. patents and trademarks abroad, particularly in China, India, and Africa, is a legally and morally tricky issue. Legally, sovereign nations are sovereign within their boundaries, and so U.S. patents qua U.S. patents simply don’t apply outside of the U.S. — we can only persuade and, sometimes, pressure these government through trade retaliation to adopt and enforce their own laws protecting U.S.-based IP. Morally, there’s an argument to be made that that developed-world creators’ primary markets will always be in rich, developed nations. If developed-world consumers produce strong enough incentives for innovation, then there’s a strong humanitarian argument for letting it slide when poor countries violate IP laws and use our innovations very cheaply to save lives and develop their lagging domestic economies. At the same time, we can also understand the distress American consumers feel when they find that drugs that were developed in U.S. labs and are prohibitively expensive in the U.S. are cheap and over the counter in India. And since China, India, and Africa contain most of the people in the world, as they develop economically, they’ll become increasingly important factors in firms’ incentives to innovate, and so at some point it’ll be key for them to get more serious about intellectual property. 

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The radical argument: Some smart, legit folks argue that we should go a lot further than I’ve advocated here in radically weakening all, and completely abolishing much, intellectual property protection. Proponents of this viewpoint point to the fashion industry: There, new clothing designs enjoy no patent protections (because clothing, due to its utilitarian function, does not constitute art that can be copyrighted) and yet we still see plenty of innovation. Perhaps we would see the same in other industries if we abolished their IP protections: firms would arguably continue to invest in R&D and innovation, even absent patent protections, seeking the financial rewards of ‘brand value’ in being the first and the best to implement their innovation. In addition, absent protections, there would be more technologies and ideas in the public domain, which would give us all more resources to draw upon in producing new innovations. A software engineer would have a somewhat smaller financial incentive to make any new software innovation, but she would have a lot more ideas and software engineers to draw on in producing new ideas. So it’s plausible that abolishing patents here could produce more innovation in the aggregate. 

On the whole, then, these heterodox thinkers argue, we’d be better off with much, much weaker IP protection. I’m not sure this argument is right, particularly for firms in industries with very large up-front R&D costs, like pharmaceuticals and alternative energy. I also worry that once firms couldn’t enjoy monopoly rights to their patents, they would respond by aggressively and permanently guarding the secrecy of their innovations, which wouldn’t be great for human progress in the long run. But I think the example of the still-innovative fashion industry, and the surprisingly still-successful music industry should both push us to think very boldly about more narrowly circumscribing intellectual-property rights. 

Some thoughts on higher education

After healthcare, the biggest, growing expense that is dragging on every middle-class American’s well-being right now is probably the cost of higher education. Full tuition and expenses at top colleges in the U.S. is famously surpassing $60,000 a year. Newly-minted college graduates are taking five to six figures of debt into an economy with extremely high youth unemployment, in which a college degree is no longer a guarantee of a stable middle-class existence. New J.D.s are famously graduating from law school with six-figure debt loads and declining job prospects. American medicine is facing a shortage of general practitioners, at least partly because a lot of young M.D.s can’t bear the expense and work of medical school and internships if they’ll be condemned to a life making only (!) $300,000 a year, as non-specialists. These have a lot of serious, second-order, distributed costs that we don’t always think about: economically indebted young people are more risk-averse, less confident, more prone to depression and anxiety; the ever-growing costs of labor in services that employ credentialed professionals get passed on to all of us when we use their services; less savings ends up invested in other useful places in the economy; a kid whose parents grew up working class, but who are now middle-class and ineligible for financial aid, might choose to go to attend a state school instead of a prestigious Ivy League university, meaning that high college costs drag on social mobility even given generous financial-aid packages. But one cost that sticks out to me is that I think parents should be allowed to have a little fun and live large once their kids have graduated form high school. And many parents who fund their children’s educations are spending all of their savings — money which they could have put to a lot of other fun and worthy uses.

So it’s a big deal. What’s driving these rising costs? Economists who research this talk about a bunch of different things. First, since the 1970s, the “skills premium” in American wages has increased — that is, the differential between college-graduates’ and high-school graduates’ has grown. This, in turn, is explained by the fact that the U.S. has continued transitioning from a manufacturing-based economy to a services-based economy driven by information and knowledge. So as the financial returns to college education have increased, the purchase price that colleges can demand has naturally increased as well (particularly given that available spots at elite colleges have not kept pace with population growth). But colleges are non-profit — so where has all this extra money gone? One major rising cost is faculty salaries, and this has to do with a nifty economic concept called Baumol’s cost disease — since technology and globalization have increased the productivity of highly-educated professionals in other fields, such as law and finance, academe has had to raise its faculty salaries in order to compete with those industries for the highly educated, even though faculty productivity has not increased. Then, there are a lot of other assorted sources of growing costs: increases in administrative and non-faculty university staff (including yours truly!); all the indoor rock-climbing gyms and exorbitant athletic facilities and other frivolities designed to lure high-school seniors who do not know what money is.

These high costs and frivolities may be tolerable in a time of affluence. But since the recent recession, people have become increasingly upset. A spate of books have been written questioning whether college is still worth it. (For the record, in terms of financial returns, strictly, there’s no question that college is still ‘worth it’, in that the college wage-premium easily repays the cost of college, though there is a legitimate debate about the source of this advantage, i.e., whether it comes from real ‘value-add’ to graduates or mere signaling). In the startup community, it’s increasingly fashionable to advocate “hacking” your education, outside of prestigious brick-and-mortar universities.

Normatively, it’s very important to look for policies and innovations that can decrease the cost of providing higher education. Descriptively, colleges may face a much less compliant clientele unless they lower their prices (already, law-school applications have fallen of sharply). How could this happen? As in any other industry, decreases in costs will have to come from competition and technological advance. The major technological change that could impact higher education is the internet in general, especially Massive Online Open Courses (MOOCs), such as those being offered by edX and Coursera. The best argument for universities experimenting with employing MOOCs is that college costs are currently so unacceptably high that we should be open to almost any experiments to help control higher-education costs. But in the rest of this post, I want to consider MOOCs, and argue that they’re not just a valid experiment, but they’re likely to be a part of the right answer as well.

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What is the value of higher education? It might be most helpful to partition higher education into two parts. Part 1 is higher education’s instrumental value — i.e., it’s practical, it’s skill-acquisition, it’s relevant to jobs, it’s giving people abilities that will match them up with what the market is demanding. Part 2 is about education’s intrinsic value — i.e., finding yourself, inhabiting unusual and novel perspectives on life, learning to better understand and empathize with others, asking question that are just worth asking for their own sake, etc.. We probably get more of Part 1 in STEM classes and lab work. We probably get more of Part 2 in English and philosophy classes and in the conversations we have with our fellow bright young collegians. Now, this taxonomy is imperfect. It’s likely that things like “communication skills” and “teamwork” and “leadership” — all skills that employers look for — are things that we develop in late-night conversations and philosophy papers and extracurriculars. It’s also the case that computer science, cognitive science, and physics all are intrinsically meaningful and beautiful as well, and can even expand our curiosity and empathy. But this imperfect schema might help our thinking a bit as we move forward.

In particular, I think there’s little controversy that MOOCs could be extremely useful in at least contributing to the provision of Part 1 of higher education. Indeed, MOOCs might be able to take over the majority of the work for many classes in this category. This past year, I took an introductory computer science course in my free time and never once attended the lecture in person. I sometimes watched a live feed of the lectures from my office — I usually watched them after the fact. But it wasn’t clear to me why the professor was still lecturing in person — few people attended class in person anyways, and  he’s been giving the same intro course for many years now. Tellingly, when a Monday class was cancelled due to the Boston marathon bombing, the professor simply had us watch his lecture from the previous year. In these courses, I also didn’t get much individual attention from my overworked, grad-student Teaching Assistants. I benefited more from online fora where I could exchange questions and tips with other students. And my problem sets probably could have been graded by a computer instead of these TAs — professors can easily write programs that, in a few seconds, throw thousands of different potential inputs into a program to make sure that the programs output the correct answer.

So I think it’s a no-brainer that universities should broadcast and offer credit for MOOC-based intro CS courses and other similar introductory STEM courses. For intro chem and bio classes, universities would likely employ mixed model, where students would watch lectures online, but attend lab in person. This would free professors up from intro teaching duties that they generally don’t enjoy. And by allowing students to choose from a variety of MOOC courses to use toward their college credit, students can be matched up with professors whose teaching styles fit them best, whatever university they’re situated at. This choice could also (once professors receive compensation for the MOOC use of their courses) bring competitive pressures to bear on professors’ teaching efforts.

For more advanced classes across the STEM category, I imagine mixed models would prevail. For a higher level course on, e.g., the theory of efficient algorithms, professors might want students to watch some lectures, write some programs, and master some content via MOOC-style recorded content, and automatically-graded problem sets, but the professor might want the students to then attend some seminar discussions on the much trickier theoretical stuff. Or a university might offer calculus, linear algebra, differential equations, real analysis, and mathematical logic, as MOOCs, while expecting math majors to attend seminars on the later, pure math theory courses in the curriculum, in person.

But the coolest thing about MOOCs is how they might provide more freedom and flexibility to people in seeking necessary job credentials. If you were, say, a successful engineer in Pakistan, but you moved your family to the U.S. (out of fear of religious persecution, or a desire to provide a brighter future for your grandkids), your lack of U.S.-based academic credentials might prevent you from landing a job in the U.S. that could fully employ your talents. Or if you’re a 25-year old mother stuck in a mid-level job, you might feel that your kids’ existence will preclude you from going back to school for a law degree or a CS masters degree. If these people could attend classes online at night, and get credit for their actual knowledge, however they attained it, and then get matched to jobs that are appropriate for their talent levels, that would our economy a lot more fair and efficient.

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Can MOOCs also change the provision of Part 2 of higher education? I have a couple of thoughts about this. First,  “asking deep, meaningful, philosophical questions for their own sake” sounds really nice — and it’s something I sincerely believe in in the abstract — but it’s probably not of much interest to the vast majority of people and is probably, in fact, a luxury that disproportionately appeals to that class of people who write about ideas and run universities for a living. The idea that a good education should not concern itself with utility is a luxury of those who will never need to really worry about unemployment.

Second, it’s hard to say how MOOCs will contribute to Part 2 of higher education, because it’s really hard to define what exactly Part 2 is, and how we measure it in the first place. We say that the liberal arts should make us more empathetic people and open our minds. So what do we make of the value of the liberal arts education of a recent cultural studies BA who gives no money to charity, spends no time interacting with people who lack his cultural markers and affiliations, and is completely intellectually incurious about non-Marxist veins of economic thought and aggressive towards those who are? Did this person fail at his liberal-arts education in the same way that, say, a computer science major who couldn’t build an app did?

Third, every other Yale College graduate I talk to says the same thing, that the most meaningful aspect of their time at Yale was their constant conversations with each other — i.e., the philosophy and political theory that happened outside of the classroom. Right now, people tend to have these excellent transformative experiences at college. But in principle, it’s not clear why that has to be the case — and it’s also not clear how much of Yale’s $200,000 tuition expenses are necessary to facilitate those experiences.

So how will MOOCs transform Part 2 of education? The conventional wisdom is that they’ll only slightly change it, as part of a blended model — i.e., that  students may watch recorded lectures from great teachers, will still attending seminars in person and having their essays graded by people. But I think it would be interesting to see how far we could pushing using digital technologies for Part 2. Professor Gregory Nagy, a professor of Greek at Harvard, has made a compelling case that automated multiple-choice grading in Humanities courses can be useful, when well-designed:

A little later, Nagy read me some questions that the team had devised for CB22x’s first multiple-choice test: “ ‘What is the will of Zeus?’ It says, ‘a) To send the souls of heroes to Hades’ ”—Nagy rippled into laughter—“ ‘b) To cause the Iliad,’ and ‘c) To cause the Trojan War.’ I love this. The best answer is ‘b) To cause the Iliad’—Zeus’ will encompasses the whole of the poem through to its end, or telos.”

He went on, “And then—this is where people really read into the text!—‘Why will Achilles sit the war out in his shelter?’ Because ‘a) He has hurt feelings,’ ‘b) He is angry at Agamemnon,’ and ‘c) A goddess advised him to do so.’ No one will get this.”

The answer is c). In Nagy’s “brick-and-mortar” class, students write essays. But multiple-choice questions are almost as good as essays, Nagy said, because they spot-check participants’ deeper comprehension of the text. The online testing mechanism explains the right response when students miss an answer. And it lets them see the reasoning behind the correct choice when they’re right. “Even in a multiple-choice or a yes-and-no situation, you can actually induce learners to read out of the text, not into the text,” Nagy explained

But there’s another possibility. Everything I’ve discussed so far has centered on simply complementing or replacing some of the features of current universities, within the structure of universities as they exist today. But the most truly “disruptive” proposal for online education is currently coming from the Minerva Project. The Minerva Project intends to have a highly-selective admissions process (it aims to get ‘Ivy-League quality students’) and then house them at different dormitories, on a rotating basis, over the four years of their education. Meanwhile, they’ll watch recorded lectures from top scholars online (meaning–the top scholars only need to be involved in the production of course material once), while they’ll interact with, and be graded by, newly-minted PhDs who are currently out of jobs. Minerva claims that by cutting out the expenses of university infrastructure, athletic fields, etc., it will be able to charge half the tuition of most top-tier universities today. And by housing elite students together, they’ll maintain the benefits of late-night dorm-room conversations, etc.. By moving them around the world, from Paris to Sao Paulo, etc., every few months, they’ll make them more cosmopolitan citizens of the world.

Will it work? It’s not clear. But we need to try.

Inflation basics [Econ for poets]

I recently had a conversation with a smart acquaintance about monetary policy, and we discussed the new Bank of Japan’s governors’ promises to push for higher inflation in the country. I tried to argue that we had good reasons to believe that such an inflationary policy could boost the real economy, while my friend argued against me. But eventually, I realized that the friend and I were doing a bad job articulating what, exactly, drives inflation, and this was a drag on our conversation. I suspect that there are a lot of us who know how to use all the words we see associated with inflation in magazines (“money supply,” “loose monetary policy,” “inflation expectations,” etc. etc.), who may even remember a mathematical formula from Intro Macro (MV = PQ), but who, when we dig a little deeper, have to admit we don’t have a clear grasp on what’s going on. So I thought I could do the blog world a favor by writing a very back-to-basic post (in English words) on what inflation is exactly and how it happens.

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What is inflation? It is a rise in the prices of goods and services. What causes inflation? Most people would say that  inflation is driven by an increase in the amount of currency or money in the economy — the “money supply.” The intuition here is that if an economy produces the exact same amount of goods in year 1 as in year 2, but there is twice as much money in circulation in year 2, then prices will have to double in order to sort of “soak up” the extra money. I think that’s the implicit metaphor most of us have for how it works: The monetary price of real goods is determined by the amount of money in circulation relative to the amount of real goods; and inflation (and deflation) is driven by increases (and decreases) in the money supply. Now, the interesting thing about this is that it is mostly true in practice but not entirely true in theory. To get a much better grasp  on this, we need to go back to very basic theory, to make sure we’re clear on things, and then we need to clarify exactly what we mean by the “money supply.”

Who sets prices? Theory: In a market economy, everybody sets prices. That is, the price of anything in a market economy is the price at which sellers choose to sell their goods, provided that they can find buyers. So any full explanation of inflation has to answer the question: Why, exactly, did sellers choose to raise their prices and why did buyers go along with it? So let’s start with an incredibly simple model: Adam and Barbara are stranded on a desert island and they have their own economy. Adam grows peaches on his peach tree; every day, he harvests a bushel, eats a peach for himself, and sells the rest to Barbara; Barbara then eats a peach, turns the rest into peach juice, drinks some of it, and sells the rest back to Adam; Adam drinks some of the peach juice and uses the rest to water/fertilize the soil of his peach tree. One day, a $10 bill falls from the sky. Adam and Barbara decide to use this for their transactions: First, Barbara gives Adam the $10 bill in exchange for his peaches; then Adam gives Barbara the $10 back for her peach juice.

Now, suppose that two more $10 bill falls from the sky, one into Adam’s hand and another into Barbara’s. What will happen? Will prices triple? Well, that’s up to Adam and Barbara. They might just decide to save their new $10 bills and continue trading one day’s worth of peaches and one day’s worth of juice for $10, every single day — the only thing that would have changed from before would be their “savings.” But it also is possible that prices could increase. Maybe one day Adam gets greedy for dollar bills, and decides to demand $20 from Barbara for his peaches — he knows she has the money, and since he’s her only supplier, she has to consent. At that point, since Barbara now expects she’ll have to pay $20 for future supplies of peaches, she’ll start charging $20 for a day’s worth of peach juice in order to maintain her living standard. So suddenly prices double, just like that. And it’s also possible — this is the really interesting part — that prices could more than triple. Perhaps Adam gets really greedy and starts to charge $40 for his peaches — more than all the currency in the economy — and Barbara responds by charging $40 for her peach juice as well. One way this could work is that, first Barbara buys half a day’s supply of peaches for $20, makes half a day’s supply of peach juice and sells it for $20, and then uses that $20 to buy the next half-day’s supply, etc. Another way they could do this would be to use the magic of credit —  Adam or Barbara hands over $20 for the full amount of peaches/peach juice and also a promise to pay another $20 that night. At the end of the day, after their two transactions, each is $20 in debt to the other, but each earned $20 in cash from that day’s transaction, so they simply swap $20 to settle up.

Now, notably, this simple model is not a good a good one, because it leaves out (1) the reason money is useful and influences our behavior in the first place, namely that is completely fungible and usable across a broad array of transactions that would otherwise be complicated by barter and (2) competition, which is the major thing that stabilizes prices in the first place. But the point of this model has been to get us beyond our implicit metaphor that prices have to “soak up” the supply of money. Adam and Barbara — the market — are in charge of the prices they set, and they do so according to their own purposes. They could randomly double or halve their prices at their whims. And what’s true for Adam and Barbara is also theoretically true for all of us. If every single person in the world were to wake up in the morning and decide to double the prices they pay and charge for absolutely everything (including doubling, e.g. the amount of credit they demand from and extend from others), then this could work without a hitch — every numerical representation of the value of every good would change, and nothing else would.

The above is just a verbal expression of the familiar “Equation of Exchange” that we see in Econ 101, MV = PQ. In this equation, P represents the price level and Q represents the total quantity of real goods sold — multiplied together, PQ thus simply represents the nominal value of all real goods sold in a given time period. So in the second iteration of our fictional desert-island economy above (where Adam and Barbara were each charging $20), PQ = $40 per day. What about the other side of the equation? M represents the supply of money (a total of $20 in that part of the thought experiment). And V is stands for velocity of money, or the number of times any given unit of that money changes hands in a transaction, per time period; in our thought experiment, since $40 worth of goods changed hands a day, and the amount of money was only $30, then the velocity of money was 1.333 transactions per day (($40 of transactions/day) / $30). If you think carefully about this, you can see that MV = PQ is an axiomatic mathematical identity: The total monetary value of all transactions taking place in a given period of time must necessarily be equal to the amount of money there is times the number of times the average unit of money changed hands in a transaction. If prices suddenly double, while everything else stays the same, it must necessarily be the case that money is changing hands twice as fast, doubling V.

So let’s now think about some of the things that happened in our thought experiment, in terms of this identity, PQ = MV. At first, there was $10 in the economy, and $20 worth of purchases, because the $10 bill changed hands twice a day. So PQ = $20 and MV = 2 * $10. It balances! Then $20 fell from the sky. In one scenario, Adam and Barbara didn’t change their prices, so PQ still was equal to $20. Since M was was now equal to $30, V must have fallen to 2/3rd. In other words, since they were still just doing the same transactions, at the same dollar value, even though there were two new $10 bills hanging around, the ‘velocity’ of any given $10 bill was now 1/3rd of what it had previously been — only 2 $10 bills changed hands per day, even though there were 3 of them in the economy. In the scenario after that, both Adam and Barbara raised prices to $40, meaning that PQ was now equal to $80. Because M was equal to $30, V was necessarily 8/3 transactions per day — that is, the average $10 bill changed hands more than twice, because of how Adam and Barbara transacted four times per day.

So going forward, let’s keep in mind this main theoretical takeaway: The only fundamental constraint on prices is the mathematical identity that PQ = MV. So, if the money supply, M, say doubles, that could cause prices to double, but it’s also possible that the extra money could get “soaked up” by a lower velocity of money, i.e., people choosing, for whatever reason, to hold on to any given dollar in their hands for longer before spending it (and it’s also possible that we could see a little bit of each, or that velocity could surprisingly increase, leading to more than double inflation, etc., etc., etc.)

What influences prices? Practice: In theory, the only certainty about the price level is the identity that MV = PQ — the velocity of money could double one day, and halve the next, making prices double and halve in turn. But in practice, things are much different. First, we don’t, in practice, all just wake up in the morning and all collectively decide to double or halve the velocity of money. If I own a shop and I double my prices one day, my competitors probably won’t, and so all my customers will leave me and buy from them. If I suddenly halve my prices, I’ll run out of goods real quick and won’t make a profit. So, because most firms (hopefully!) face real and prospective competitors and don’t like selling things at a loss, the velocity of money, V, doesn’t just randomly, wildly oscillate on its own. This means that if both the quantity of real goods an economy is producing, Q, and the money supply, M, are held relatively constant, then we won’t usually see wild fluctuations in the price level, P.

And second, in practice, changes in the supply of money do not usually get entirely absorbed/cancelled out by changes in the velocity of money. Just think about it: If you suddenly had an extra $100,000 would you hide it all under your mattress? Maybe you would hide some of it (you would probably save much — but these savings would be someone else’s credit, which we’ll get to later), but probably you would increase your spending at least somewhat. And if all of us suddenly got an extra $100,000 we would all probably start to spend a bit more. Since our increased spending would amount to an increase in nominal demand for goods, we would expect prices to rise. So the Econ 101 explanation here is that increases in money lead to an increase in nominal demand, which causes nominal prices to rise. If you prefer narrative to graphical style thinking, think of it this way: if we helicopter-dropped an extra $100,000 into everyone’s bedroom, workers would demand higher pay to work overtime (since they already have such great savings), people would take vacations and bid up the price of spots at restaurants and on airplanes, everyone would be willing to pay more for houses, bidding up prices, etc., etc. But people also would hold onto or save much of that $100,000, meaning that velocity of any given dollar would slow down at first, and so the extra money supply wouldn’t be immediately ploughed into higher prices. So usually the price level should correlate and moves with the money supply, but not immediately in a perfect, linear 1-to-1 relationship.

What is money? In the first few iterations of the desert-island thought experiment, “money” basically means “paper currency.” But in the modern world, most of what we call “money” is actually just debits and credits in bank accounts. For example, if you have accumulated $10,000 in cash at work, and you put that into a checking account, you still have $10,000 in “money” (because you can withdraw at any time) even though your bank is not keeping those $10,000 locked away in a vault. Your bank likely lent most of those $10,000 in cash out to somebody else, and so now there is $19,000+ in “money” resulting from your deposit, even though there was only $10,000 in cash. Indeed, if the person who got that loan from the bank spends her $9,000 to hire somebody a job, and that hiree then saves his $9,000, and the bank then loans out those $9,000 in cash to somebody else, then there is now $28,000 in money. As we can see, in the modern world, “money” is very different from “currency,” and so economists have very categories for measuring the money supply. “M0” refers to actual physical currency in circulation; “MB” (the Monetary Base) refers to currency in circulation, currency stored in bank vaults, and Federal Reserve credits to banks (see below); “M1” refers to currency, bank deposits, and traveler’s checks; “M2” includes savings accounts and money-market accounts as well; “M3” includes all those and a few other savings/investment vehicles. As you can see, M0 through M3 are ordered according to their relative liquidity — M0 is just actual cash, which is completely liquid, and M3 includes things that might take a bit more time for you to withdraw — savings accounts and money-market funds. Money, in the modern world, exists on a spectrum of liquidity. Indeed, it’s arguable that ‘money’ in these traditional categories is too conservatively defined. If you have $10,000 invested in an index ETF, and you can exit the ETF at any moment, you might think of those $10,000 as your money, but the Federal Reserve, at least when it pays attention only to M0-M3, would not.

So how does the Federal Reserve control the money supply? It doesn’t do so by “printing money,” as Fed-skeptics often put it — it’s even more aerie than that! The Fed actually mostly influences the money supply just by entering credits and debits into its and other banks’ digital balance sheets.  Suppose a bank has $100 in deposits from savers like you and me, and it has loaned those $100 to General Electric. At this point, there are $200 ($100 in deposits, and $100 in cash on hand for GE). But now, the Federal Reserve can buy GE’s debt obligation from the bank; the bank thus gets $100 (or whatever the market purchase price of the loan was) in cash credit from the Federal Reserve, which it can then loan out to another company, like Ford. So now there’s $300 of money in the economy ($100 for GE and Ford each and $100 for the banks’ original depositors), with the extra $100 having been created simply by the Fed crediting another bank’s account.

In reality, due to ‘fractional reserve banking,’ each purchase of X that the Federal Reserve makes creates much more than X new money, because banks often lend to other banks, or banks’ loanees deposit some of their loans in other banks, etc. So the Federal Reserve can have a large impact on the money supply simply by purchasing banks’ assets — by giving these banks fresh money, it allows them to lend more money to other people/banks who will lend to other people/banks who will lend again, creating new money at each iteration.

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I hope this is all the basic background one needs to understand the talk about inflation that we see in the business press. But I want to quickly touch on some implications:

1. This reason all this theory is important is that it explains why Federal Reserve policy is controversial and debatable. If there were a simple, linear relationship between the money supply and the price level, there would be no controversy — we could easily and uncontroversially predict inflation by quantifying the money supply. But Fed policy right now is controversial, for some, because we can’t actually be sure how changes in the money supply will affect inflation over the long run. It’s theoretically conceivable that a central bank could increase the money supply while observing very little inflation, because people largely hide their new money under their mattresses, only to see that 5 years later, everyone suddenly starts spending their mattress-savings, sending prices skyrocketing. The complex psychological factors that influence the velocity of money, including self-fulfilling expectations about inflation (see below), mean that there is always some uncertainty about what the consequences of the Fed’s actions will be. For the record, I’m not very worried about the prospect of very high inflation. The market’s expectations for future inflation are priced into price difference between TIPS (Treasury Inflation Protected Securities) and regular, non-inflation protected Treasuries. And TIPS continue to show low inflation expectations. If I were smarter than the market, I should probably be a billionaire right now. People who are very certain that high inflation is coming should put their money where their mouths are, by putting most of their savings in inflation-protected securities.

2. Expectations for inflation are largely self-fulfilling: If you expect wage rates to rise 10% next year, you might try to lure a new hire with a contract at a 8% premium (relative to current wages), to lock her in at a price that will be a 2% savings relative to what you expect for the future. If you expect prices for your supplies to rise next year, you might raise prices on your merchandise right now, in order to earn enough cash to afford those higher-priced supplies. If you think your competitors are raising their prices right now, then you know you can raise your prices without losing customers. Etc., etc., etc.. The fact that inflation is a sort of self-creating phenomenon, ultimately based on everyone’s best guess about what everyone else thinks about what everyone else thinks about how much prices will rise in the future, is one thing that sometimes makes it hard to control. Most episodes of hyperinflation ultimately originate from governments printing massive amounts of new money — but from there, inflation radically outpaces the printing presses, as everyone keeps raising prices in response to everyone else’s price hikes in a downward spiral. More, one of the most effective ways for the Fed to control inflation is for the Fed chairman to literally make statements — in words — about future inflation. If the Fed says, “we are committed to ensuring that inflation is 3% next year,” the average company will have a good reason to raise prices by 3%.

3. Most mainstream economists believe that moderately higher-than-usual inflation can help boost an economy out of a recession. There are at least four mechanisms through which inflation can benefit a recessionary economy:

          (i) If you own a company and you expect prices to be 8% higher next year, all else equal that fact will make you more inclined to purchase more merchandise now, while prices are still lower. You also might ramp up your production and investment right now, so you’ll be well-position to meet that high nominal demand.  This boost can help an economy get out of the recessionary downward spiral in which low demand and low production begets more low demand and low production.

          (ii)  Most of us think about our salaries in nominal terms. Most of us do not like to take paycuts. However, during a recession, individual workers’ productivity decreases (i.e., if I’m a car salesman, I’m worth more to my company during a time when lots of people want to buy cars). The problem is that if workers’ contribution to companies’ bottom lines decreases, but workers’ salaries stay the same, then firms will hire less and fire more, and/or become less competitive. Inflation allows firms to lower their employees’ real wages, without needing to lower their nominal wages. Economists think this is a good thing — the alternative to lower real wages during a recession is mass unemployment and bankruptcy.

          (iii) Inflating a currency typically devalues it relative to other world currencies. If we make the dollar worth less relative to the Brazilian real, then Brazilians will be able to more easily afford to buy American goods. This should help America’s exporters, which is another thing that can help drag a country out of a recessionary downward spiral. (The flip side of this, of course, is that it will be more expensive for Americans to import things from Brazil — so policymakers have to think carefully through the full industrial implications of a devalued currency).

          (iv) Inflating a currency benefits debtors (at the expense of creditors). If I owe my very wealthy landlord $1 million next year, but prices rise 15% in the interim, then the “real” value of my obligation to my landlord will only be some $850,000. If I as a middle-class consumer am more likely to spend extra money than my ultra-wealthy landlord, then this inflation-driven decrease in my debt/increase in my wealth (and decrease in my landlord’s wealth) will mean greater net demand in the economy. Again, this short-term boost to demand can help jolt an economy out of a downward spiral. You often hear that the problem we’re facing in the U.S. is that, after the financial crisis, everybody tried to “de-leverage” (that is, reduce their debt obligations) at the same time, which led to a “demand shortfall.” (This is often called the “paradox of thrift” — saving more money is good for any individual, but when everybody does it at the same time, it can cause a recession). Inflation can make it easier to reduce our debt obligations, thus weakening the demand shortfall problem that comes with deleveraging.

On the flip side, most mainstream economists believe that in non-recession times, relatively low, stable inflation is good. This is because it’s easier for people to enter into short-term and long-term economic contracts when they can have relatively certain expectation about what things will cost and be worth in the future.