Here\’s the puzzle. Outflows of international capital from emerging markets around the world played a key role in causing financial shocks and steep recessions all over the globe in the late 1990s, including the east Asian financial crisis affecting countries like Korea, Thailand, and Indonesia in 1997-98; Latin American countries like Brazil (1999) and Argentina (2001); along with an assortment of other places like Ukraine (1998) and Turkey (2000). But even larger outflows of international capital from emerging markets have been occurring in the last few years, with much less dire economic consequences. What changed? The World Economic Outlook published by the IMF in April 2016 devotes a chapter to this subject: \”Chapter 2: Understanding the Slowdown in Capital Flows to Emerging Markets.\”
Here\’s a figure that sets the stage by showing net capital inflows to emerging market economies since 1980. You can see the drop in capital inflows in the late 1990s, surrounded by various crises. The more recent drop was accompanied by some crises during the worse of the global recession of 2008 and its immediate aftermath, but not much since then. (The recent external financial crises in this data are Ukraine in 2014 and Albania in 2015.)
What changed? In the late 1990s, the destructive economic dynamic sometimes evolved like this. Banks and large companies in a country like Thailand would borrow in US dollars. They would convert those US dollars to the local currency–say, Thai baht–and then lend and spend that currency in Thailand. This process of borrowing in US dollars and lending in Thai baht seemed fairly safek because government policy had been to keep exchange rates fixed (or close to it) over time. But when international capital inflows went into reverse, exchange rates declined. As a result, the big banks and companies that had borrowed in US dollars and loaned in Thai baht could not repay those US dollar loans. The government had often in some way guaranteed the stability of the banking system, but didn\’t hold much in the way of US dollar reserves, so the government finances ended up in trouble, too.
In the last five years, many elements of this interaction have changed, at least in part because all the players learned from the experiences of the late 1990s. Here are some examples from the IMF report:
A rising share of the original international capital inflows aren\’t in the form of borrowed money and debt, but instead are in the form of stock market investments or foreign direct investment. These other kinds of investments are more flexible: an inability to repay debt causes legal consequences and even bankruptcy, but a drop in the price of stock market investments means only a loss in asset values.
Many of the big players emerging markets no longer need to borrow almost exclusively in US dollars; instead, they can now do a lot of borrowing in their own currency. As a result, they aren\’t exposed to the risk of exchange rate shifts. Here\’s a figure showing the rising ability of government and nongovernment borrowers in emerging markets to borrow in their own currency.
Many of the key emerging market no longer fix their exchange rate. What used to happen back in the 1980s and 1990s was that governments would claim to have a fixed exchange rate, which actually was a situation where the exchange rate was fixed for a time and then took a huge jump. Ongoing exchange rate adjustments mean that the players in the global economy are more likely to take the risks of exchange rate shifts into account, and the adjustments can be more gradual.
Many of the key emerging markets have built up substantial US dollar foreign reserves. Thus, if there is a sharp decline in capital inflows or an actual outflow, they can soften the effect of this change–at least for a time–by drawing down these foreign reserves.
The IMF report mentions some other factors, as well. But the central point is a bit of good news for the global economy: As emerging market economies are playing a larger role in global economic output, they are also becoming more integrated into the global financial system in more flexible ways. As a result, the cycles of inflows and outflows of international capital that caused severe disruptions and financial crises back in the 1980s and 1990s have had less power to do so in the last five years.
It\’s common to hear proposals that the US should adopt a \”cap-and-trade\” system for reducing climate emissions. Indeed, back in 2009 the House of Representatives passed the American Clean Energy and Security Act, the so-called \”Waxman-Markey\” act, which would have implemented such a law, but the legislation died in the US Senate without ever being brought to a vote. In the meantime, the European Union has now had a cap-and-trade policy in place for 10 years. How well is it working?
The Winter 2016 issue of the Review of Environmental Economics and Policy has a three-paper symposium on the subject of \”The EU Emissions Trading System: Research Findings and Needs.\” (REEP is not freely available on-line, but many readers will have access through library subscriptions.) The three papers are:
A. Denny Ellerman, Claudio Marcantonini, and Aleksandar Zaklan, \”The European Union Emissions Trading System: Ten Years and Counting (pp. 89-107),
Beat Hintermann, Sonja Peterson, and Wilfried Rickels, \”Price and Market Behavior in Phase II of the EU ETS: A Review of the Literature (pp. 108-128)
Ralf Martin, Mirabelle Muûls, and Ulrich J. Wagner, \”The Impact of the European Union Emissions Trading Scheme on Regulated Firms: What Is the Evidence after Ten Years\”\’ (pp. 129-148)
The paper by Ellerman, Marcantonini, and Zaklan offers an overview of the EU carbon trading market, while the other papers drill down into more specific issues. Ellerman et al. describe the EU Emissions Trading System (ETS) in this way (footnotes and citations omitted):
The EU ETS is a classic cap-and-trade system. As of 2014, the EU ETS covered approximately 13,500 stationary installations in the electric utility andmajor industrial sectors and all domestic airline emissions in the EU’s twenty-eight member states, plus three members of the closely associated European Economic Area: Norway, Iceland, and Liechtenstein. Approximately two billion tons of carbon dioxide (CO2) and some other greenhouse gases (GHGs) are included in the system, together accounting for about 4 percent of global GHG emissions in 2014. Aside from its sheer size in terms of geographic scope, number of included sources, and value of allowances, another distinguishing feature of the EU ETS is its implementation through a multinational framework, namely the EU, rather than through the action of a single state or national government, as assumed in most theory and as has been the case for most other cap-and-trade systems.
They discuss a variety of the nuts-and-bolts details of the system. For example, should the permits to emit carbon be given to existing firms, or auctioned? Economic theory tends to favor auctioning, but the horse-trading of politics tends to favor giving the permits away, which is mainly what happened. How will the total carbon emissions over time be set? Will EU emitters be allowed to pay for steps that would reduce carbon emissions elsewhere in the world, and then use reductions to offset part of any required reduction in their own direct carbon emissions?
I won\’t try to describe the ins-and-outs of the EU system in this blog post. It\’s gone through three \”phases\” and a bunch of other rule changes during its single decade of existence. But two graphs give a sense of its main themes–and the difficulties in evaluating it performance. The first graph shows carbon emissions in the EU while the carbon trading system has been in effect.
Emissions are clearly down. However, it\’s not easy to separate out the effects of the emissions trading system from other policies that would have an effect of reduce carbon emissions, including other environmental regulations and taxes, efforts at energy conservation, subsidies for non-carbon forms of energy, and the like. In fact, a look at the price of carbon in the ETS suggests that it might not be having much of a role.
Notice that the price of allowances during \”phase I\” of the system fell all the way to zero: in other words, the allowed emissions of carbon were considerably above what was actually being emitted, so there was no additional cost for emitting. During phases II and III, the cost of emitting carbon has been at around €5 per ton of emissions, which is a lot lower than the price of about €30 per ton that is often recommended for making a realistic and useful dent in carbon emissions over time. To be blunt about it, the price data suggests that perhaps the EU ETS hasn\’t had much effect in reducing emissions, and may not have much effect looking forward.
Should the low price for carbon emissions be interpreted as a success story for an emissions trading system? After all, emissions are indeed down. Or should it be interpreted as a failure for an emissions trading system, and perhaps a sign that political pressures have led to a system where it has little effect? After all, emissions may be falling for other reasons and the current price of €5 just isn\’t very high. Ellerman, Marcantonini, and Zaklan describe the resulting debates in this way:
The great surprise of the second phase of the EU ETS was that, as phase III started in 2013, the price paid to emit carbon was less than €5, not the €30 or more that had been indicated by 2013 futures prices in 2008 and that was generally expected at that time. This development has created a lively debate about the future of the EU ETS and its role in climate policy. This debate can be summarized as being between those who view the current, much-lower-than-expected price as indicating serious flaws in the EU ETS and those who argue that the low price shows that the system is working exactly as it should given all that has happened since 2008 (i.e., reduced expectations for economic growth in the Eurozone, increased electricity generation from renewable sources, the significant use of offsets), including the possibility that abatement may be cheaper than initially expected. Fundamentally, this debate reflects differing views of the objectives of climate policy itself: whether the objective is solely to reduce GHG emissions or also (and perhaps principally) to transform the European energy system. Although no one is suggesting that emissions have exceeded the cap, or that they will do so, current prices do not seem likely to lead to the kind of technological transformation that would greatly reduce Europe’s reliance on fossil fuels.
The other papers in the symposium make a case that the EU ETS policy should be regarded more as a partial success than as a partial failure. For example, Hintermann, Peterson, and Rickels write:
Although the EU ETS has been criticized from an environmental perspective because of its rather low carbon price signal, we believe that the policy has actually performed quite well from an economic point of view. It introduced a single price for emissions, which were previously a free public “bad,” and it correctly reflected the substantial oversupply of allowances in both phase I and phase II through a significant price drop. Moreover, the nonzero price toward the end of phase II, despite a nonbinding cap for the phase, reflected expectations of a cap on overall emissions that is binding in the long term, given the opportunity to bank allowances. …
As is currently being discussed in the EU, the low allowance price could be counteracted through the use of new mechanisms such as price floors or strategic allowance reserves. However, a more direct (and environmentally beneficial) approach would be to tighten the cap, for example, by adjusting the rate at which it is decreased after 2020; because of banking, this should affect the price even today. We would argue that the fact that allowance prices turned out to be lower than anticipated (and thus EU climate policy was cheaper than expected) should actually be interpreted as good news rather than a problem. After all, the main economic argument in favor of an emission allowance market is that it delivers a particular emissions goal at least cost.
Martin, Muûls, and Wagner focus on the specific sectors–energy and industry–that were directly regulated by the cap-and-trade arrangements under the ETS. They argue that there is little evidence the emissions trading system hurt these industries, and some evidence that it did accelerate their reduction in emissions and stimulate their innovation in cleaner-energy alternatives.
It seems to me that the best case one can make for the EU ETS after its first decade is along the lines of \”it\’s a start.\” Sure, the prices are very low, but they aren\’t zero. Ellerman et al. emphasize that the ETS is set up in a way that over the long-run, it will become a binding constraint forcing carbon emissions to decline. They write:
Absent a decision by the EU to abandon the program, which would require a super-majority, the EU ETS will march on with a continually declining cap, which, under all likely scenarios, will create continuing scarcity, thus virtually guaranteeing that a carbon price will be a permanent feature of the European economic landscape.
Right now, the political pressures to change the rules in such a way as to allow a lower carbon price are quite muted. It will be interesting to see how the political pressures play out a few years down the road when the carbon constraint in the ETS start to push the price of the allowances higher, up to €30 per ton or perhaps considerably more.
On the surface, it\’s easy to sketch what a \”good job\” means: having a job in the first place, along with good pay and access to benefits like health insurance. But that quick description is far from adequate, for several interrelated reasons. When most of us think about a \”good job,\” we have more than the paycheck in mind. Jobs can vary a lot in working conditions and predictability of hours. Jobs also vary according to whether the job offers a chance to develop useful skills and a chance for a career path over time. In turn, the extent to which a worker develops skills at a given job will affect whether that worker worker is a replaceable cog who can expect only minimal pay increases over time, or whether the worker will be in a position to get pay raises–or have options to be a leading candidate for jobs with other employers.
A majority of Americans do not consider themselves to be \”engaged\” with their jobs. According to Gallup polling: \”The percentage of U.S. workers in 2015 who Gallup considered engaged in their jobs averaged 32%. The majority (50.8%) of employees were \”not engaged,\” while another 17.2% were \”actively disengaged.\” … Employee engagement entered a rather static state in 2015 and has not experienced large year-over-year improvements in Gallup\’s 15-year history of measuring and tracking the metric. Employee engagement has consistently averaged less than 33%.\”
What makes a \”good job\” or an engaging job? The classic research on this seems to come from the Job Characteristics Theory put forward by Greg R. Oldham and J. Richard Hackman back in a series of papers written in the the 1970s: for an overview, a useful starting point is their 1980 book Work Redesign. Here, I\’ll focus on their 2010 article in the Journal of Organizational Behavior summarizing some findings from this line of research over time, \”Not what it was and not what it will be: The future of job design research\” (31: pp. 463–479).
Oldham and Hackman point out that from the time when Adam Smith described making pins and back in the eighteenth century up through when Frederick W. Taylor led a wave of industrial engineers doing time-and-motions studies of workplace activities in the early 20th century, and up through the assembly line as viewed by companies like General Motors and Ford, the concept of job design focused on the division of labor. In my own view, the job design efforts of this period tended to view workers as robots that carried out a specified set of physical tasks, and the problem was how to make those worker-robots more effective.
Whatever the merits of this view for its place and time, it has clearly become outdated in the last half-century or so. Even in assembly-line work, companies like Toyota that cross-trained workers for a variety of different jobs, including on-the-spot quality control, developed much higher productivity than their US counterparts. And for the swelling numbers of service-related and information-related jobs, the idea of an extreme division of labor, micro-managed at every stage, often seemed somewhere between irrelevant and counterproductive. When worker motivation matters, the question of how to design a \”good job\” has a different focus.
By the 1960s, Frederick Herzberg is arguing that jobs often need to be enriched, rather than simplified. In the 1970s, Oldham and Hackman develop their Job Characteristics Theory, which they describe in the 2010 article like this:
We eventually settled on five ‘‘core’’ job characteristics: Skill variety (i.e., the degree to which the job requires a variety of different activities in carrying out the work, involving the use of a number of different skills and talents of the person), task identity (i.e., the degree to which the job requires doing a whole and identifiable piece of work from beginning to end), task significance (i.e., the degree to which the job has a substantial impact on the lives of other people, whether those people are in the immediate organization or the world at large), autonomy (i.e., the degree to which the job provides substantial freedom, independence, and discretion to the individual in scheduling the work and in determining the procedures to be used in carrying it out), and job-based feedback (i.e., the degree to which carrying out the work activities required by the job provides the individual with direct and clear information about the effectiveness of his or her performance).
Each of the first three of these characteristics, we proposed, would contribute to the experienced meaningfulness of the work. Having autonomy would contribute to jobholders felt responsibility for work outcomes. And built-in feedback, of course, would provide direct knowledge of the results of the work. When these three psychological states were present—that is, when jobholders experienced the work to be meaningful, felt personally responsible for outcomes, and had knowledge of the results of their work—they would become internally motivated to perform well. And, just as importantly, they would not be able to give themselves a psychological pat on the back for performing well if the work were devoid of meaning, or if they were merely following someone else’s required procedures, or if doing the work generated no information about how well they were performing.
Of course, not everyone at all stages of life is looking for a job that is wrapped up with a high degree of motivation. At some times and places, all people want is a steady paycheck. Thus, Oldham and Hackman added two sets of distinctions between people:
So we incorporated two individual differences into our model—growth need strength (i.e., the degree to which an individual values opportunities for personal growth and development at work) and job-relevant knowledge and skill. Absent the former, a jobholder would not seek or respond to the internal ‘‘kick’’ that comes from succeeding on a challenging task, and without the latter the jobholder would experience more failure than success, never a motivating state of affairs.
There has been a considerable amount of follow-up work on this approach: for an overview, interested readers might begin with the other essays in the same 2010 issue of the Journal of Organizational Behavior that contains the Oldham-Hackman essay. Their overview of this work emphasizes a number of ways in which the typical job has evolved during the last 40 years. They describe the change in this way:
It is true that many specific, well-defined jobs continue to exist in contemporary organizations. But we presently are in the midst of what we believe are fundamental changes in the relationships among people, the work they do, and the organizations for which they do it. Now individuals may telecommute rather than come to the office or plant every morning. They may be responsible for balancing among several different activities and responsibilities, none of which is defined as their main job. They may work in temporary teams whose membership shifts as work requirements change. They may be independent contractors, managing simultaneously temporary or semi-permanent relationships with multiple enterprises. They may serve on a project team whose other members come from different organizations—suppliers, clients or organizational partners. They may be required to market their services within their own organizations, with no single boss, no home organizational unit, and no assurance of long-term employment. Even managers are not immune to the changes. For example, they may be members of a leadership team that is responsible for a large number of organizational activities rather than occupy a well-defined role as the sole leader of any one unit or function.
In their essay, Oldham and Hackman run through a number of ways in which jobs have evolved in ways that they did not expect or undervalued back in the 1970s. For example, they argue that the opportunities for enrichment in front-line jobs is larger than they expected, that they undervalued the social aspects of jobs, that they didn\’t anticipate the \”job crafting\” phenomenon in which jobs are shaped by workers and employers rather than being firmly specified. They point out that although working in teams has become a phenomenon, employers and workers are not always clear on the different kinds of teams that are possible: for example, \”surgical teams\” led by one person with support; \”co-acting teams\” in which people act individually, but have little need to interact face-to-face; \”face-to-face teams\” that meet regularly as a group to combine expertise; \”distributed teams\” that can draw on a very wide level of expertise when needed, but don\’t have a lot of interdependence or a need to meet with great regularity; and even \”sand dune\” teams that are constantly remaking and re-forming themselves with changing memberships and management.
When you start thinking about \”good jobs\” in these broader terms, the challenge of creating good jobs for a 21st century economy becomes more complex. A good job has what economists have called an element of \”gift exchange,\” which means that a motivated worker stands ready to offer some extra effort and energy beyond the bare minimum, while a motivated employer stands ready to offer their workers at all skill levels some extra pay, training, and support beyond the bare minimum. A good job has a degree of stability and predictability in the present, along with prospects for growth of skills and corresponding pay raises in the future. We want good jobs to be available at all skill levels, so that there is a pathway in the job market for those with little experience or skill to work their way up. But in the current economy, the average time spent at a given job is declining and on-the-job training is in decline.
I certainly don\’t expect that we will ever reach a future in which jobs will be all about deep internal fulfillment, with a few giggles and some comradeship tossed in. As my wife and I remind each other when one of us has an especially tough day at the office, there\’s a reason they call it \”work,\” which is closely related to the reason that you get paid for doing it.
But with the unemployment rate now under 5%, the main issue in the workforce isn\’t a raw lack of jobs–as it was in the depths of the Great Recession–but instead is about how to encourage the economy to develop more good jobs. I don\’t have a well-designed agenda to offer here. But what\’s needed goes well beyond our standard public arguments about whether firms should be required to offer certain minimum levels of wages and benefits.
Here\’s an oldie-but-a-goodie that I\’m sure some readers have already seen over the years, a satirical piece about the extremely high death rates of the grandmothers of college students during exam period. Mike Adams write about \”The Dead Grandmother/Exam Syndrome\” in the November/December 1999 issue of the Annals of Improbable Research.
In true social-science fashion, Adams first provides background, then establishes the facts, discusses lines of causality, then proposes a solution.
Background
\”In my travels I found that a similar phenomenon is known in other countries. In England it is called the “Graveyard Grannies” problem, in France the “Chere Grand’mere,” while in Bulgaria it is inexplicably known as “The Toadstool Waxing Plan” (I may have had some problems here with the translation. Since the revolution this may have changed anyway.) Although the problem may be international in scope it is here in the USA that it reaches its culmination, so it is only fitting that the first warnings originate here also. The basic problem can be stated very simply: A student’s grandmother is far more likely to die suddenly just before the student takes an exam, than at any other time of year.\”
Facts
\”For over twenty years I have collected data on this supposed relationship … [W]hen no exam is imminent the family death rate per 100 students (FDR) is low and is not related to the student’s grade in the class. The effect of an upcoming exam is unambiguous. The mean FDR jumps from 0.054 with no exam, to 0.574 with a mid-term, and to 1.042 with a final, representing increases of 10-fold and 19-fold, respectively. … [T]he changes are strongly grade dependent … Overall, a student who is failing a class and has a final coming up is more than 50 times more likely to lose a family member than is an A student not facing any exams.\”
Of course, the averages cannot capture the extreme cases, like one member of the baseball team \”who tragically lost at least one grandmother every semester for four years.\”
Causality
\”Only one conclusion can be drawn from these data. Family members literally worry themselves to death over the outcome of their relatives’ performance on each exam. Naturally, the worse the student’s record is, and the more important the exam, the more the family worries; and it is the ensuing tension that presumably causes premature death. Since such behavior is most likely to result in high blood pressure, leading to stroke and heart attacks, this would also explain why these deaths seem to occur so suddenly, with no warning and usually immediately prior to the exam. It might also explain the disproportionate number of grandmothers in the victim pool, since they are more likely to be susceptible to strokes. This explanation, however, does not explain why grandfathers are seldom affected, and clearly there are other factors involved that have not been identified. Nonetheless, there is considerable comfort to be had in realizing that these results indicate that the American family is obviously still close-knit and deeply concerned about the welfare of individual members, perhaps too much so.\”
Solutions
Adams evaluates the merits of three different solutions to saving the grandmothers: 1) Stop giving exams. 2) Allow only orphans to enroll at universities. 3) Have students lie to their families.
Those who want more detail on this health scourge are encouraged to check Adams\’s paper. It has actual tables and figures, so it must be true.
As a starting point, here\’s basic data on corporate profits divided by GDP for the period since World War II. The red line on top is profits before tax; the blue line at the bottom is profits after tax. The recent rise in profits is clear. But it\’s also interesting to note that the 1980s and 1990s were a period of relatively low corporate profits, while profits were higher from the 1950s through the 1970s.
There are a bunch of different ways to adjust profits to get a more nuanced number, but the same basic pattern over time tends to show through of higher profits from the 1950s to the 1970s, lower profits in the 1980s and 1990s, and generally higher profits in the 2000s–with a downward blip in profits during the Great Recession. Here are a few thoughts about this pattern.
1) It\’s common for those pointing to high profits to assert that they are closely linked to higher levels of income inequality. From a long-run perspective, the connection isn\’t at all obvious. After all, inequality was much lower back in the 1950s, 1960s, and 1970s. The rise in inequality started in the 1970s, but corporate profits drop to lower levels in the 1980s and the 1990s.
2) As the figure shows, the gap between before-tax and after-tax profits was larger back in the 1950s, 1960s, and 1970s. Here\’s a figure showing that corporate taxes have become relatively smaller as a share of GDP over time. But much of the drop in corporate tax revenues as a share of the economy happened back from the 1950s through the 1970s, when corporate profits were fairly high. The recent rise in corporate profits since about 2000 is apparent both in pre-tax and in post-tax corporate profits. It\’s not a creation of the corporate tax system.
3) There\’s a tendency in public discourse to treat \”profits\” as essentially a synonym for \”loot and plunder.\” For economists, profits are instead a signal conveying information. The problem lies in interpreting that information! Ideally, high profits are a signal that what is being produced by the firm is highly valued by consumers, and so it\’s a good time for firms to invest, expand output, hire more workers, and give raises to existing workers. Indeed, high profits provide the finance to help those steps along. High profits in the 1950s and 1960s, for example, were accompanied by (mostly) low unemployment and solid expansions of jobs and wages.
4) In contrast, the recent wave of high profits, especially since the Great Recession, don\’t seem to be combining with high investment, strong expansions in output and wages, and so on. There\’s some controversy on this point. For example, it may be that what we measure as \”investment\” in the US economy is conceptually outdated, because 21st century firms may not be increasing investment in machinery and equipment, but they are instead investing in intangible capabilities to provide new services in ways that conventional statistics don\’t capture. Unemployment rates have fallen more slowly than hoped, but they are now below 5%. Wages haven\’t risen as hoped, but there are some preliminary signs that they may be starting to do so.
5) In one way or another, profits do eventually flow back to the rest of the economy, but the mechanisms through which this happens have changed over time. For example, the high-profit companies of the 1950s and 1960s also tended to pay high rates of dividends to shareholders. Now, high-profit companies are more likely to use profits to engage in share buy-backs.
7) Like so many economic issues, the meaning of high corporate profits will be clarified over the next year or two with the arrival of additional data. If the next few years see growth in investment and wages, together with a sag in profits, and perhaps a wave of money flowing back to investors as part of share buy-backs and merger and acquisition deals, then these last few years will look like a transitional period after the Great Recession. But if profits continue to remain high, then other explanations become more likely. Some of the higher profits may be due to weakened compeitition between producers. A related theory is that many of the high-profit companies are technology companies where startups can be risky and have high costs, but when a company succeeds, it has built a community of appreciative users in such a way that the profits can be extraordinary and long-lasting.
Where I live in Minnesota, the short days of December have less than 9 hours of daylight, with sunrise around 7:50 am and sunset around 4:40 pm. In contrast, the long days of June have about 15 1/2 hours of daylight, with sunrise around 5:30 am and sunset around 9:00 pm. But of course, those summer times for sunrise and sunset use Daylight Savings Time. If we didn\’t spring the clocks forward in March, the summertime in Minnesota would feature a 4:30 am sunrise and an 8:00 sundown.
If I was a stronger and more flexible person, there would be no need for Daylight Savings Time. I would just rise with the summertime sun at 4:30 and take advantage of those extra daytime hours. But I don\’t synchronize my day to the sunlight. Instead, like most people, I have daily schedules that involve getting up at roughly same time most days. For me, this is the strongest case for Daylight Savings Time: it shifts an hour of daylight that would otherwise occur when I\’m asleep to a time of day at a time of year when I can enjoy it. For those who live closer to the equator, where the seasonal variation in length of day is less, I presume that Daylight Savings Time matters less. But for those of us in northern climates, long summer evenings are a nice counterbalance to those dismal winter days when you drive to work before sunrise and drive home from work after sunset.
However, discussions about the merits of Daylight Savings Time aren\’t usually focused on sweet summertime evenings. For example, the US Department of Transportation website lists three practical reasons for Daylight Savings time and the longer summer evenings: saves energy, reduces traffic deaths, and reduces crime. Austin C. Smith reviews the evidence on these claims before presenting his own research in \”Spring Forward at Your Own Risk: Daylight Saving Time and Fatal Vehicle Crashes,\” which appears in the April 2016 issue of the American Economic Journal: Applied Economics 8:2, 65–91). (The AEJ: Applied isn\’t freely available on-line, but many readers will have access through library subscriptions. Full disclosure: This journal is published by the American Economic Association, which also publishes the Journal of Economic Perspectives where I work as Managing Editor.)
It\’s long been argued that Daylight Savings Time provides modest but real energy savings, but Smith cites some recent evidence that leans the other way. A standard method in empirical economics in recent years is to look for \”natural experiments,\” which are situations where Daylight Saving Time was or was not imposed in a way that offers a chance for some comparisons. Thus, Smith writes:
\”Kellogg and Wolff (2008) use a natural experiment in Australia where DST was extended in some states to accommodate the Sydney Olympics. They find that while DST reduce energy demand in the evening, it increases demand in the morning with no significant net effect. Kotchen and Grant (2011) make use of a quasi-experiment in Indiana where some Southern Indiana counties did not practice DST until 2006. Their work suggests that DST could actually increase residential energy use, as increased heating and cooling use more than offset the savings from reduced lighting use.\”
(For those who would like specific citations for these papers:
Kellogg, Ryan, and Hendrik Wolff. 2008. “Daylight time and energy: Evidence from an Australian experiment.” Journal of Environmental Economics and Management 56 (3): 207–20.
Kotchen, Matthew J., and Laura E. Grant. 2011. “Does daylight saving time save energy? Evidence from a natural experiment in Indiana.” Review of Economics and Statistics 93 (4): 1172–85.)
Smith\’s main focus is on how Daylight Savings Time affects traffic fatalities. Smith looks at the data on all US vehicle crashes that involve a fatality from 2002-2011. He uses two main comparisons: 1) he looks at days around the shift from Standard Time to DST each year, looking for a \”discontinuity\” or a jump in the rate of fatalities when the change happens; and 2) he compares dates that were covered by DST in some years but not in other years–because the exact date of the shift varies from year to year. He argues that sleep disruption in the spring transition to DST imposes significant costs:
\”DST impacts practicing populations through two primary mechanisms. First, it creates a short-term disruption in sleeping patterns following the spring transition. Using the American Time Use Survey, Barnes and Wagner (2009) find that Americans sleep 40 minutes less on the night of the spring transition, but they do not sleep a significant amount more on the night of the fall transition despite the extra hour. Second, DST creates darker mornings and lighter evenings than would be observed under Standard Time. … In both specifications I find a 5–6.5 percent increase in fatal crashes immediately following the spring transition. Conversely, I find no impact following the fall transition when no significant shock to sleep quantity occurs. …This suggests that the spring transition into DST is responsible for over 30 deaths annually …The total costs of DST due to sleep deprivation could be orders of magnitude larger when worker productivity is considered …\”
In passing, Smith also mentions a recent studies about effects of Daylight Savings Time on crime. The December 2015 issue of the Review of Economics and Statistics includes \”Under the Cover of Darkness: How Ambient Light Influences Criminal Activity,\” by Jennifer L. Doleac and Nicholas J. Sanders (97: 5, pp. 1093-1103). They find that cases of robbery drop by 7% in the weeks right after Daylight Savings Time begins.
Smith\’s article is also full of \”did-you-know\” tidbits about Daylight Savings Time:
Did you know that about 1.5 billion people around the world practice some form of Daylight Savings Time? Of course, this means that about 5.5 billion people around the world, presumably those who live closer to the equator, don\’t use it.
Did you know that farmers tend to oppose Daylight Savings Time? \”DST is often mistakenly believed to be an agricultural policy. In reality, farmers are generally against the practice of DST because it requires them to work for an extra hour in the morning, partially in darkness, to coordinate with the timing of markets …\”
Did you know that the specific idea for Daylight Savings Time dates back to 1895, when \”the formal procedure was proposed by George Vernon Hudson, an entomologist who wanted more light in the evenings to pursue his passion of collecting insects …\”
I\’m a sleep-lover, and I disruption to sleep patterns is something I feel in the center of my being. My personal experience with evening insects is pretty much limited to catching lightning bugs and slapping mosquitoes. But I\’m with George Vernon Hudson in liking long summer evenings.
There\’s no systematic data collected on the distribution of college and university grades. Instead, such data is collected by individual researchers. Perhaps the largest and most prominent data on college grades over time, now with current data from over 400 schools with a combined enrollment of more than four million undergraduate students is from Stuart Rojstaczer and Christopher Healy. I wrote about the previous update of their data back in August 2014. They now have a substantial update of the data available at http://www.gradeinflation.com.
Their overall finding is that during the 30 years from 1983 to 2013, average grades for undergraduates at four-year college have risen from about 2.85 to 3.15 on a 4.0-point scale–that is, the average used to be halfway between a B- (2.7) and a B (3.0), and it\’s now halfway between a B (3.0) and a B+ (3.3).
Along the way, A\’s became the most common grade back in the mid-1990s. The prevalence of grades of C and D slumped back in the 1960s, and have continued to slide since then. More recently, B\’s have been declining, too.
I\’ve commented on the grade inflation phenomenon before, but perhaps a quick recap here is useful. I view grades as a mechanism for communicating information, and grade inflation makes that mechanism less useful–with consequences both inside academia and out.
For example, grade inflation is not equal across academic departments; it has been most extreme in the humanities and softer social sciences, and mildest in the sciences and the harder social sciences (including economics). Thus, one result of this differential grade inflation across majors is that a lot of freshmen and sophomores are systematically being told by their grades that they are worse at science than at other potential majors. The Journal of Economic Perspectives (where I work as Managing Editor) carried an article on this connection way back in the Winter 1991 issue: Richard Sabot, and John Wakeman-Linn on \”Grade Inflation and Course Choice.\” (pp. 159-170). For an overview some of the additional evidence here, see \”Grade Inflation and Choice of Major\” (November 14, 2011). In turn, when grade inflation influences the courses that students choose, it also influences the shape of colleges and universities–like which kinds of departments get additional resources or faculty hires
Another concern within higher education is that in many classes, the range of potential grades for a more-or-less average student has narrowed, which means that an extra expenditure of effort can raise grades only modestly. With grade inflation, an average student is likely to perceive that they can get the typical 3.0 or 3.3 without much effort. So the potential upside from working hard is at most a 3.7 or a 4.0.
Grade inflation also makes grades a less useful form of information when students start sending out their transcripts to employers and graduate programs. As a result, the feedback that grades provide to the skills and future prospects of students has diminished, while other forms of information about student skills become more important. For example, employers and grad schools will give more weight to achievement or accreditation tests, when these are available, rather than to grades. Internships and personal recommendations become more important, although these alternative forms of information about student quality depend on networks that will typically be more available to students at certain colleges and universities with more resources and smaller class sizes.
As the data at the top suggests, efforts to limit grade inflation have not been especially successful. In \”Grade Inflation: Evidence from Two Policies\” (August 6, 2014), I wrote about a couple of efforts to reduce grade inflation. Wellesley College enacted a policy that the average grade in lower-level courses shouldn\’t exceed 3.3, which was somewhat successful at reducing the gap between high-grading and low-grading department. Cornell University, took a different tack, by deciding to publish student grades along with median grades for each course, so that it would be possible to compare how the student looked relative to the median. This plan seemed to worsen grade inflation, as students learned more about which courses were higher-grading and headed for those classes. For the Wellesley study, see Kristin F. Butcher, Patrick J. McEwan, and Akila Weerapana on \”The Effects of an Anti-Grade-Inflation Policy at Wellesley College,\” in the Summer 2014 issue of the JEP. For the Cornell study, see Talia Bar, Vrinda Kadiyali, and Asaf Zussman on \”Grade Information and Grade Inflation: The Cornell Experiment,\” in the Summer 2009 issue of the JEP.
Asking politicians to spending money to reduce the risk of a future problems can be problematic. After all, it\’s hard to claim political credit for avoiding something and causing it not to happen. But in the case of planning ahead to reduce the risks and costs of pandemics, the case for advance planning seems especially strong. The Commission on a Global Health Risk Framework for the Future spells out the issues in its report, The Neglected Dimension of Global Security: A Framework to Counter Infectious Disease Crises, which is available here with free registration from the National Academies Press. This Commission was sponsored by a coalition of philanthropic and government groups. In included 17 members from 12 countries, who also got reactions from an oversight group and invited comments at public meetings. It was chaired by Peter Sands, who used to be the CEO of Standard Chartered, and is now a Senior Fellow at teh Mossavar-Rahmani Center for Business and Government at Harvard Kennedy School, with Oyewale Tomori, President of the Nigerian Academy of Science, serving as vice-chair.
A very quick summary of the report would be that it suggests spending $4.5 billion per year to build up the world\’s response system to pandemics. It offers estimates that the costs of pandemics could average $60 billion per year in the next century.
Here\’s a description of costs (citations and footnotes omitted):
The World Bank has estimated the economic impact of a severe pandemic (that is, one on the scale of the influenza pandemic of 1918–1919) at nearly 5 percent of global gross domestic product (GDP), or roughly $3 trillion. Some might see this as an exaggeration, but it could also be an underestimate. Aggregate cumulative GDP losses for Guinea, Sierra Leone, and Liberia in 2014 and 2015 are estimated to amount to more than 10 percent of GDP. This huge cost is the result of an epidemic that, for all its horror, infected only about 0.2 percent of the population of Liberia, roughly 0.25 percent of the population of Sierra Leone, and less than 0.05 percent of the population of Guinea, with 11,287 total deaths. The Commission’s own scenario modeling, based on the World Bank parameters, suggests that during the 21st century global pandemics could cost in excess of $6 trillion, with an expected loss of more than $60 billion per year.
Indeed, the economic impact of infectious diseases appears to be increasing as greater human and economic connectedness—whether through transnational supply chains, increased travel, or ubiquitous access to communication technologies and media—fuel contagion, both of the virus itself and of fear. Most of the economic impact of pandemics stems not from mortality but from behavioral change, as people seek to avoid infection. This behavioral change is driven by fear, which in turn is driven by a potent mix of awareness and ignorance. … The experience of SARS is instructive: viewed from the perspective of overall mortality, SARS infected “only” 8,000 people and killed less than 800. Yet the economic cost of SARS has been estimated at more than $40 billion. At the peak of SARS, Hong Kong saw a 66 percent reduction in airport arrivals and a 50 percent reduction in cinema admissions. …
We should not become fixated on the probability of a “once-in-a-100-years” pandemic of the 1918–1919 influenza pandemic of severity. Much less virulent pandemics can still cause significant loss of life and economic impact. The influenza pandemics of 1958 and 1968, while far less deadly than the one in 1918–1919, are estimated to have cost 3.1 percent and 0.7 percent of global GDP, respectively. Potential pandemics, that is outbreaks or epidemics that could become pandemics if not effectively contained, can also have enormous impact. Ebola, an epidemic that looked as if might have the potential to become a pandemic, has killed more than 11,000 people and cost more than $2 billion. While there is a high degree of uncertainty, the commission’s own modeling suggests that we are more likely than not to see at least one pandemic over the next 100 years, and there is at least a 20 percent chance of seeing 4 or more … .
What\’s the proposed solution? The report offers lots of detail, but the broad three-point plan is national action, global cooperation, and focused R&D:
Against this, we propose incremental spending of about $4.5 billion per year—a fraction of what we spend on other risks to humankind. …
Robust public health infrastructure and capabilities are the foundation of resilient health systems and the first line of defense against infectious disease outbreaks that could become pandemics. Yet far too many countries have failed to build the necessary capabilities and infrastructure. Even by their own internal assessments, 67 percent of World Health Organization (WHO) member states fail to meet the requirements of the 2005 International Health Regulations (IHR); objective external evaluations would almost certainly reveal even lower rates of compliance. …
Although reinforcing the first line of defense at the country level is the foundation of a more effective global framework for countering the threat of infectious diseases, strengthening international coordination and capabilities is the next most vital component. Pandemics know no borders, so international cooperation is essential. Global health security is a global public good requiring collective action. … The Commission believes that an empowered WHO must take the lead in the global system to identify, prevent, and respond to potential pandemics. There is no realistic alternative. However, we believe that the WHO must make significant changes in order to play this role effectively. It needs more capability and more resources, and it must demonstrate more leadership. …
This means accelerating R&D in a coordinated manner across the whole range of relevant medical products, including vaccines, therapeutics, diagnostic tools, personal protective equipment, and instruments. To ensure that incremental R&D has maximum impact in strengthening defenses against infectious diseases, we propose that the WHO galvanize the creation of a Pandemic Product Development Committee (PPDC) to mobilize, prioritize, allocate, and oversee R&D resources relating to infectious diseases with pandemic potential.
The report also points out that spending in these areas is likely to have substantial benefits even if a pandemic does not occur. \”Moreover, the risks of spending too much or too little are asymmetric. Even if we have overestimated the risks of potential pandemics, money invested to mitigate them will still be money well spent. Most of the investments we recommend will help achieve other high-priority health goals, such as countering antimicrobial resistance and containing endemic diseases like tuberculosis and malaria. Yet if we spend too little, we open the door to a disaster of terrifying magnitude.\”
I would probably quibble with some of the details of the recommendations. For example, I think the report may underestimate the difficulties of having the World Health Organization take a leading role in this effort, and a different institutional framework might be needed. But that said, the case for acting to limit pandemics seems ironclad. As an example of the potential gains, the report points to the example of Uganda, which has managed to deal with multiple outbreaks of Ebola in the last 15 years:
Before the current West African Ebola outbreak, Uganda was the site of the largest Ebola outbreak in history, with 425 reported cases in 2000. Yet the outcome of this outbreak was distinctly more positive, because Uganda had in place an operational national health policy and strategic plan, an essential health services package that included disease surveillance and control, and a decentralized health delivery system. After 2000, Uganda’s leadership realized that, despite the successful containment of the outbreak, a focus on strengthening surveillance and response capacities at each level of the national system would greatly improve the country’s ability to respond to future threats. Uganda has since suffered four additional Ebola outbreaks, as well as one outbreak of Marburg hemorrhagic fever. However, due to its new approach, Uganda was able to markedly improve its detection and response to these public health emergencies.
All too often, we are most willing to invest in disaster prevention right after a severe disaster has occurred, right after an outbreak of disease or famine or natural disaster, when memories are still fresh. It wold be nice if the pandemics we have already suffered, as well as cautionary stories of SARS, Ebola, the Zika virus and others could lead to actions before the next pandemic looms.
To separate the effects of the ACA’s [Affordable Care Act\’s] coverage provisions from those broader estimates, CBO and JCT [Joint Committee on Taxation] compared their current projections with estimates of what would have occurred if the ACA had never been enacted. In 2016, those provisions are estimated to reduce the number of uninsured people by 22 million and to result in a net cost to the federal government of $110 billion. … Those estimates address only the insurance coverage provisions of the ACA, which do not generate all of the law’s budgetary effects. Many other provisions—such as various tax provisions that increase revenues and reductions in Medicare payments to hospitals, to other providers of care, and to private insurance plans delivering Medicare’s benefits—are, on net, expected to reduce budget deficits.
Dividing the $110 billion in additional spending by 22 million more people with health insurance works out to about $5,000 per person. For comparison, although the comparison should be taken only as rough and not as apples-to-apples, Medicaid spending is about $5,800 per enrollee. There\’s never been any secret that if the US was willing to spend an extra $100 billion or more, it could subsidize health insurance for a lot more people.
The CBO report offers an overview of health insurance coverage in the US, along with federal subsidies. Here\’s part of a figure from the report showing US health insurance coverage by categories. Most of those under-65 have employment-based coverage, but you can see the estimates for Medicaid and other programs. The CBO prediction is that there will be 27-28 million Americans without health insurance through 2026.
Here\’s part of a table from the CBO report showing federal subsidies for health insurance coverage. The two main categories in which the Patient Protection and Affordable Care Act of 2010 raised subsidies for health insurance are $64 billion for expanding Medicaid coverage, and $43 billion in subsidies for those with lower income levels to purchase insurance though the \”marketplaces\” (which seems to be the new name for what have often been called the \”exchanges).
2) Overall, I\’m personally in favor of spending an extra $110 billion to provide health insurance coverage for 22 million more people. Sure, there\’s part of me that wonders if some of those people might have preferred getting health insurance that was more bare-bones and cheaper, and instead getting some of that $5,000 per person subsidy in the form of income that could have been spent in other ways. But that political choice wasn\’t available.
3) The main issue for me isn\’t the extra $110 billion in spending, but rather how that additional spending was designed and implemented, and how it interacts with the health insurance and health care markets as a whole. If the fundamental goal of the act was to spend and extra $110 billion and subsidize insurance for 22 million more Americans, the law could have been a lot simpler and less invasive.
4) In particular, it\’s worth noting that the cost of the tax exclusion for employer-provided health insurance–that is, the provision in the US tax code that the value of health insurance from your employer isn\’t counted as income on which tax is owed–was $266 billion in 2016. The CBO report forecasts that this tax exclusion will reduce tax revenues by $460 billion by 2026. At the risk of grievously oversimplifying a vast literature on how to control health care costs, I\’ll note that as long as employer-provided health insurance is an untaxed fringe benefit worth hundreds of billions of dollars, it really shouldn\’t be a big surprise that health care spending remains so high and rising. In addition, the fringe benefit is of course worth the most to those with higher income levels, who are more likely to have health insurance through their employers, more likely to have that health insurance be fairly generous, and more likely to be in higher income tax brackets. Finding a way to trim back the tax exclusion of employer-provided health insurance by about half–with an emphasis on reducing the subsidy to those with higher income levels–could provide the revenues to subsidize health insurance for all remaining Americans who continue to lack it.
As I\’ve thought about the reasons behind the sharp rise in inequality of compensation at the top 1% of the income distribution during the last 25 years or so, I keep returning to the rise of executive stock options. In turn, the widespread granting of stock options was fueled in part by a 1993 law which will forever exemplify the Law of Unintended Consequences. But although stock options helped generate a huge one-time jump in inequality of compensation, they now seem to have a diminishing role as a form of executive compensation.
As background for this theory, it\’s useful to review a few main facts and patterns about executive compensation and income inequality. For starters, here\’s a figure showing a rise in executive compensation as a multiple of the salary of a typical worker (taken from a January 2016 Credit Suisse report on trends in corporate governance). The multiple rises somewhat from the mid-1970s up through the early 1990s, but then rather abruptly takes off and fluctuates at a higher level after that point.
For a longer-term view going back to the 1940s, here\’s a figure showing the historical change in median pay levels of top executives at large US companies from Carola Frydman and Raven E. Saks in their article \”Executive Compensation: A New View from a Long-Term Perspective, 1936-2005,\” which appeared in the Review of Financial Studies (23: 5, May 2010, pp. 2099-2138).
From the 1930s up through about 1980, most executive pay was in the form of salary-plus-bonus. But in the 1980s, long-term pay and stock options began to play a much larger role. Clearly, much of the rise in executive salaries can be traced to new categories of executive compensation that were relatively small a few decades ago: \”long-term pay\” and stock options.
These rises in executive pay have a very similar timing to the rise in income inequality at the highest levels. Here are a couple of illustrative figures about inequality at the top income levels, based on tax return data, from \”Striking it Richer: The Evolution of Top Incomes in the United States (Updated with 2014 preliminary estimates),\” by Emmanuel Saez in a working paper dated June 25, 2015. First, this figure shows the share of total income received by the top 1%, the top 1%-5%, and the top 5%-10%. Notice that while there\’s a rise in the share of total income received by all three groups over time, the rise for the top 1% is by far the largest–and of course, the top 1% also by definition has fewer people than the other two groups. Also, while the increase for the top 1% dates back to the 1970s, there\’s an especially sharp for the share of income received by the top 1% in the early to mid-1990s. Since then, the share going to the top 1% is volatile, but doesn\’t show much upward trend.
And here\’s a figure showing the share of total income received at the very top, by the .01%–in 2014, for example, this group had more than 9.75 million in income. Again, there\’s an increase for this group in the 1980s, but the really large jump comes in the 1990s. Again, there is volatility since the late 1990s, but not much of an upward trend.
So what happened back in the early 1990s that would have caused executive compensation and the use of stock options to take off? A common explanation traces the causes back to the 1992 election when Bill Clinton made high executive pay a campaign issue. In 1993, a law was passed placing a $1 million cap on salaries for a number of top corporate executives. However, the cap was only about salaries, not about pay that was in some way linked to performance. In response to this law, there was a large-scale shift to paying top executives with stock options. The stock market more-or-less tripled in value during the five years from late 1994 to late 1999, and so those who had stock options did very well indeed. Christopher Cox, who had been a congressman back in 1993 but then had become chairman of the Securities and Exchange Commission, testified before Congress in 2006:
\”[O]ne of the most significant reasons that non-salary forms of compensation have ballooned since the early 1990s is the $1 million legislative cap on salaries for certain top public company executives that was added to the Internal Revenue Code in 1993. As a Member of Congress at the time, I well remember that the stated purpose was to control the rate of growth in CEO pay. With complete hindsight, we can now all agree that this purpose was not achieved. Indeed, this tax law change deserves pride of place in the Museum of Unintended Consequences.\”
Just to be clear, I\’m not arguing that stock options for top executives is the only factor affecting inequality of compensation. I suspect that what economists call skill-biased technical change–that is, the way in which information technology allowed some of those with high skills to add enormously to their productivity–also made a difference. The rise of globalization greatly increased the opportunities for some folks with certain skills, even as it diminished opportunities for others. But if the focus is on the rise in incomes at the very top, this change mirrors very closely in time the rise in stock options. In addition, my guess is that when the pay of top executives skyrocketed in the 1990s, it reset expectations about it was \”reasonable\” to pay top employees in many settings, including at law firms, financial firms, and even in top academic jobs. And remember, the widespread rise of stock options largely arose out of an attempt to pass a law that would limit CEO pay!
The obvious argument for stock options, for many years now, has been that they created a link between executive pay and corporate shareholders. There\’s a good argument for incentive pay for top executives, so that they are willing to take tough decisions when needed and not just sit around on their paychecks. But the particular kind of incentives provided by stock options often was not well targeted. In the statistical literature on baseball players, there is a concept of a \”replacement player\”–that is, an average or \”replacement\” player that any team can get at any time. Baseball statheads then calculate VORP, or \”value over replacement player.\” In a similar spirit, just running an average company and having average results doesn\’t seem as if it deserves special bonuses. High performance occurs when an executive performs better than a replacement of average quality–for example, if the firm is outperforming competitors, regardless of whether the overall market is up or down.
In this sense, stock options were often poorly designed to create a link with stock market performance. For some companies, handing out stock options apparently felt like paying with free money. Executives made money with stock options when the market as a whole went up in the 1990s, even if their company just went up less than average for the market or for their industry. There were concerns that stock options can encourage excessive risk-taking–for example, in the financial sector—because they offered a big upside for executives who did well, but no downside losses for those who did poorly. There were concerns that stock options encouraged steps to juice up the stock price–say, through having a company buy back its own stock or through empire-building mergers and acquisitions–rather than focusing on growing the company for the future. There was a scandal back in 2006 (when Cox was testifying before Congress) about how companies backdated\” options–that is, they falsely claimed that stock options had been granted to executives in the past, thus allowing the executives to cash in on increases in the stock price since that time. The amount of compensation actually being received by executives through stock options was often fairly opaque, at least to those outside the executive suites.
Whether or not you buy my argument about why the use of stock options became so widespread and my skepticism about their design, it\’s interesting to note that they seem to be in decline. Here\’s some evidence from \”Measuring CEO Compensation,\” a March 2016 \”Economic Brief\” written by Arantxa Jarque and David A. Price of the Federal Reserve Bank of Richmond. The green bars shows the share of large firms using stock options, but not grants of restricted stock. (\”Restricted\” stock means that it is not actually given to the executive certain targets are met, which can include an executive staying with a company for a certain time, or the company meeting certain financial or product development targets.) The purple bars show the rising share of companies using only restricted stock, and not stock options, while the red bars show companies using both. The trend is pretty clear: stock options have become much less dominant.
As Jarque and Price write:
In the 2000s, the data also show a marked shift from stock options to restricted stock grants or a combination of the two; this timing is consistent with firms reacting to policy changes unfavorable to options during that period. Among these changes were a provision of the Sarbanes-Oxley Act of 2002 requiring faster disclosure of option grants and the adoption in 2006 of accounting standards that mandated the treatment of option grants as expenses.
Just to reiterate the essence of their final sentence, stock options were popular when disclosure could be slower and the company didn\’t need to treat such payments as expenses (!). When those factors changed, apparently other methods of aligning the incentives of executives and shareholders, like grants of restricted stock linked to specific performance targets, became attractive.
If this theory about a strong connection from the widespread rise of stock options in the 1990s to the rise in income inequality at the very top contains some measure of truth, then a few insights follow. The especially sharp rise in income inequality at the top should be a more-or-less one-time event. As noted above, the rise in executive pay and in share of incomes going to the top 1% or .01% jumped in the 1990s, and while it has fluctuated since then, the overall trend doesn\’t seem to be up since the late 1990s. Moreover, this shift to greater inequality at the very top seems unlikely to be repeated. There\’s a shift away from stock options toward restricted stock; moreover, the stock market doesn\’t seem likely to triple in the next five years, as it did from late 1994 through late 1990s. Finally, there\’s probably a lesson in the fact that when executive pay was highly visible to outsiders, in the form of salary plus cash bonus, compensation for top executives didn\’t rise much, but as the form of compensation became more opaque with stock options and grants of restricted stock that were often based on a number of nonpublic underlying conditions, executive pay rose substantially.
