U.S. Gasoline Prices and Consumption in International Context

Gasoline prices are spiking up toward $4 per gallon, so it\’s a useful time to review prices over the last couple of decades and some international comparisons. Here\’s a figure I generated using the ever-helpful FRED (Federal Reserve Economic Data) website maintained by the St. Louis Fed showing gasoline prices since 1990.

The overall pattern here is fairly clear. Gasoline prices were fairly flat through the 1990s at between about $1 and $1.50 per gallon. Starting around 2000, gasoline prices start rising. There\’s a lot of volatility in the pattern, and in particular, gasoline prices drop off when demand for gasoline falls during recessionary periods (as shown by the shaded areas in the figure). But the overall pattern of rising gasoline prices from about 2000 up through 2008 is pretty clear. Gasoline prices are now headed back toward their level before the recession-induced fall in prices in 2008.

Most supply-and-demand explanations of gasoline markets emphasize that supply often adjusts fairly slowly. The process of searching for and discovering oil, and then drilling, transporting, refining, wholesaling and retailing it, takes many economic interconnections. Thus, when  demand falls in a recession, the production process of oil doesn\’t drop off sharply–instead, prices fall. At other times, however, a disruption in this chain of supply can create a drop in the quantity that would otherwise have been available later in the process, and so prices rise.

The overall pattern of rising prices through most of the 2000s is usually attributed to the growth of demand for oil outstripping the growth of supply–where much of the rising demand for oil comes from rapidly growing economies like China, India, and Brazil. From this perspective, it seems utterly unsurprising that the price of gasoline has rebounded back near the peaks it reached earlier in 2008.

Although I think most Americans have a general idea that gasoline is often taxed more highly in other countries than it is here, the magnitude of these taxes isn\’t always well-known. Here\’s a table from Christopher R. Knittel\’s article, \”Reducing Petroleum Consumption from Transportation,\” in the Winter 2012 issue of my own Journal of Economic Perspectives, comparing gasoline taxes across countries.

The United States taxes gasoline at about 49 cents to the gallon, counting both federal taxes and the average of state taxes. By the time you get to the bottom of the list, you see that countries like the United Kingdom, Germany and Netherlands have gasoline taxes about eight times as high at roughly $4/gallon. Population densities and living patterns are different in the United States than  in these other countries, and I wouldn\’t advocate raising taxes to those levels.  On the other side, it\’s hard to believe that phasing in an increase in U.S. gasoline taxes to Canadian levels of 96 cents per gallon would be an unsustainable blow to the U.S. .economy, perhaps with a substantial of the money earmarked for offsetting income tax cuts and part earmarked for long-term deficit reduction. There are a variety of environmental and geopolitical reason why it might be reasonable policy for the U.S. to put some price disincentives in place for petroleum use.

Here\’s one more figure from Knittel. The horizontal axis of the graph shows the price of gasoline in each country, taxes included. The vertical axis shows the quantity of gasoline used for transportation in each country, measured in gallons per year per capita. This is part of the considerable body of evidence suggesting that when energy prices are higher, people and firms find ways to conserve.

Many Americans do truly hate the idea of higher energy taxes, so I don\’t expect this kind of proposal to make any political progress. Instead, Americans like to pretend that by setting technology standards to require more fuel efficient cars over time, the country can conserve energy without facing a cost. I explained in a post last week, \”Are the New Auto Fuel Economy Standards For Real?\” why this less flexible approach actually imposes higher costs as a way of encouraging energy conservation.

The Great Gatsby Curve

The current chairman of the Council of Economic Advisers, Alan Krueger, has called it the Great Gatsby curve. (Full disclosure: Alan was editor of my own Journal of Economic Perspectives, and thus my direct boss, from 1996-2002.) Here is the curve, from the 2012 Economic Report of the President:

The horizontal axis of the diagram is a measure of economic inequality called the Gini coefficient. For a detailed explanation of how it is calculated, see my earlier here. For present purposes, suffice it to say that this scale runs on a scale where 0 is perfect equality, where all people have the same income, and 1 is perfect inequality, where one person has all the income. Using data for 1985, countries like the United States and Spain have high levels of income inequality, while Nordic countries like Sweden, Finland, Norway, and Denmark have relatively low levels.

The vertical axis of the diagram is labelled the \”intergenerational earnings elasticity.\” This is a way of saying how how much the incomes of individuals are correlated with those of their parents. Here\’s the explanation from the Economic Report of the President:

 \”Family (or individual) incomes in one generation are also highly correlated with family (or individual) incomes in the next generation. In other words, the children of parents who are poor are more likely than
the children of well-off parents to be poor when they grow up. A common measure of mobility across generations is the intergenerational elasticity (IGE) of earnings or income, which is defined as the percentage difference in a child’s income associated with a 1 percent difference in the parent’s
income. … Studies based on U.S. data … suggest that plausible estimates of the average IGE between fathers and sons are between 0.4 and 0.6. An IGE of 0.4 means that if one father earned 20 percent more
than another over their lifetime, the first father’s son on average would earn 8 percent more than the second father’s son; an IGE of 0.6 means that the first father’s son would earn 12 percent more on average than the second father’s son. That is, the higher the IGE is, the lower economic mobility is between the generations.\”

Thus, the basic message of the Great Gatsby curve is that when a country has a higher level of income inequality at a point in time (the Gini coefficient on the horizontal axis), that country will also tend to experience less intergenerational mobility (that is, the correlation of income between one generation and the next will tend to be higher, on the vertical axis).

A first obvious question about this relationship is whether it is determined by some quirk in measurement: for example, would using different countries, or a different year, or different measures of inequality alter the relationship greatly? The Economic Report answers that question: \”As other research has shown, the finding of a positive relationship between IGE and inequality … is robust to alternative choices of countries, intergenerational mobility measures, and year in which income inequality is
measured …\”

Indeed, for economist who study this literature, the finding that the U.S. economy has less intergenerational mobility than many other high-income countries isn\’t even much of a surprise. For example, Gary Solon was listing evidence on this point in my own Journal of Economic Perspectives back in the Summer 2002 issue in his article, \”Cross-Country Differences in Intergenerational Earnings Mobility.\” That issue also includes three other articles with theories and evidence on intergenerational mobility.

Bhashkar Mazumder of the Chicago Fed offers an overview of the path of intergenerational mobility over time in the United States. He writes: \”After staying relatively stable for several decades, intergenerational
mobility appears to have declined sharply at some point between 1980 and 1990, a period in which both income inequality and the economic returns to education rose sharply. … There is fairly consistent evidence that intergenerational mobility has stayed roughly constant since 1990 but remains below the rates of mobility experienced from 1950 to 1980.\”

Of course, income inequality has been high and growing in the United States since the 1985 data shown on the graph above. The clear implication is that the intergenerational earnings elasticity will continue to grow as well. In a January 2012 speech on these issues, Alan Krueger ventured a projection:
\”While we will not know for sure whether, and how much, income mobility across generations has been
exacerbated by the rise in inequality in the U.S. until today’s children have grown up and completed their careers, we can use the Great Gatsby Curve to make a rough forecast. … The IGE for the U.S. is predicted to rise from .47 to .56. In other words, the persistence in the advantages and disadvantages of income passed from parents to the children is predicted to rise by about a quarter for the next generation as a result of the rise in inequality that the U.S. has seen in the last 25 years.\”

The most common theoretical mechanism hypothesized for this connection between current inequality and less intergenerational mobility is the education system. Gary Solon did much of the early modelling on this issue: here\’s a description of that work from Mazumder:

\”Economic models have emphasized the importance of parental investment in children’s human capital as one of the key mechanisms behind the intergenerational transmission of labor market earnings. One such model developed by Solon points to at least two important factors that could cause intergenerational
mobility to change over time: changes in the labor market returns to education and changes in the public provision of human capital. In periods where the returns to schooling are rising, the payoff to a given level of parental investment in children’s human capital will be larger, causing differences between families to persist longer and leading to a decline in intergenerational mobility. In contrast, during periods where public access to schooling becomes more widely available, then one might expect the intergenerational association to decline and mobility to rise.\”

In short, when the returns to human capital are especially high, inequality will be higher. In this situation, those with income will invest more in the education of their children, using education as a way to pass on their own economic position. Indeed, Mazumder also points to some evidence that \”the difference
in test scores by family income has grown by 30% to 40% for children born in 2001 relative to those born in 1976.\”

As a solution, it\’s easy to say that we\’re all in favor of expanding education for those at the bottom of the income scale, but if that is indeed true, it\’s fair to say that we as a society have been doing a lousy job of accomplishing that goal over the last few decades. Indeed, we\’ve been doing a lousy enough job as to make one wonder if a general broad rise in overall education levels–as opposed to better schools for their child or their town–really is a shared goal for many Americans. Work by Nobel laureate James Heckman and various co-authors has argued that the U.S. high school graduation rate, when consistently measured over time, peaked in the 1960s and has declined since then.

It\’s easy to say that \”we\’re all in favor\” of mobility between generations, but of course, in practice, many of us aren\’t. After all, the highest level of intergenerational mobility would mean zero correlation between incomes of parents and children. I earn an above-average income, and I invest time and energy and money make location choices so that my children will greater human capital and earn above-average incomes, too. Thus, I must admit that I do not favor completely free mobility of incomes. I\’m sure I\’m not alone. Divide the income distribution into fifths, and think about parents in the top fifth. How many of them would like to live in an economy where their children have an equal chance of ending up in any of the other fifths of the income distribution? (Megan McArdle makes this point with nice force in a blog post here.)

Those who would like an overview of some of the recent more technical debates over the Great Gatsby curve might usefully begin with this post by Miles Corak, an economist at the University of Ottawa who was one of the first to draw the curve.

Putting a Value on State Parks

In the latest issue of Resources magazine, from Resources for the Future, Juha Siikamäki inquires into \”State Parks: Assessing Their Benefits.\”

\”Each year, more than 700 million visits are made to America’s 6,600 state parks. … Using conventional economic approaches to estimate the value of recreation time combined with relatively conservative assumptions, the estimated an annual contribution of the state park system is around $14 billion. That value is considerably larger than the annual operation and management costs of state parks.\”

Siikamäki\’s approach goes like this. Start with estimates of how people use their time. Combining data from a number of time use surveys over time provides this overall pattern for hours of nature recreation per person.

This data on time use can be broken down to the state level. Siikamäki then also created a data base on how state parks have changed over time. \”Between 1975 and 2007, about 3,000 new parks totaling about 2 million acres were established in the United States, increasing the total area of the state park system by nearly one-quarter.\” It\’s then possible to try to determine the relationship between how changes in state parks affect the how nature recreation time changes in a certain state–using statistical methods to try to hold constant other possible confounding factors.

The Resources article is a highly readable overview of this work. Those who want the gory details need to turn to Siikamäki\’s more technical article in article in the Proceedings of the National Academy of Sciences, August 23, 2011, \”Contributions of the US state park system to nature recreation.\” Here\’s the result of the calculation:

 \”This expansion of the state parks is estimated to contribute about 9 percent of all current time use for nature recreation. Overall in the United States, this equals annually about 600 million additional hours of nature recreation, or about 2.7 hours of nature recreation per capita. … Valuing recreation time monetarily requires determining the opportunity cost of time. To illustrate the potential magnitude of recreation’s time value, I used a conventional and commonly adopted approach where recreation time is valued at one-third the wage rate. … Extrapolating from the above results, I estimate about 33 percent of current time use for nature recreation can be attributed to the U.S. state park system. This equals annually about 9.7 hours of nature recreation per capita, or about 2.2 billion hours of nature recreation in total in the United States. The estimated time value of nature recreation generated by the entire U.S. state park system is about $14 billion annually (about $62 per person annually, on average).\”

Of course, these results, like all statistical results, need to be handled with care. Even if state parks encourage considerable recreation on average, it is surely still true that some state parks have bigger payoffs while others have smaller payoffs. It could be that states where the citizens had a high demand for nature recreation are also the states  that are more likely to add to the state park system–and perhaps the quantity of nature activities would have risen in those states even without the expansion of the state parks. Even if the state parks had not been expanded, people would have done something with their time, so the value of the state parks should be the marginal increase over that alternative use–an inevitably tricky task.

On the other side, by measuring the benefits of state parks purely in terms of recreation benefits leaves out other benefits and thus underestimates total social benefits from state parks.  Siikamäki concludes: \”Nature recreation represents only a partial assessment of the full range of ecosystem services produced by natural areas. Examples of other potentially relevant ecosystem services include carbon sequestration and storage through biological processes, contributions to surface and groundwater services, and benefits from preserving endangered and threatened species. A full assessment of ecosystem services from state parks should consider these nonrecreation contributions, yielding an even more comprehensive—and presumably larger—estimate of the value of America’s state park system.\”

Economics (Almost) Never Sleeps

Catherine Rampell at Economix, the economics blog at the New York Times, reports on  \”America’s 10 Most Sleep-Deprived Jobs.\” She writes that Sleepy’s, the mattress chain \” hired researchers to analyze data from the National Health Interview Survey to determine which occupations, on average, produce workers who sleep the least and the most. The jobs with the most sleep-deprived work forces are below, starting with the most sleep-deprived at the top:\”

Most Sleep-Deprived
6h57m Home Health Aides
7h Lawyer
7h1m Police Officers
7h2m Physicians, Paramedics
7h3m Economists
7h3m Social Workers
7h3m Computer Programmers
7h5m Financial Analysts
7h7m Plant Operators
7h8m Secretaries

My own take is that the sleeplessness of economists is a fact begging for an unsubstantiated and unproveable hypothesis.

Does a miserable economy cause economists to sleep less, as they internalize the pain of others? This seems implausible, because it would require that economists care about others.

Is economics the kind of field that tends to attract those who have trouble sleeping? Perhaps only those who have physical trouble in sleeping can make it through the economics curriculum, while normal sleepers will perpetually be dozing off through the required classes.

Is economics a field that attracts hypercompetitive people who can\’t sleep because they fear that, somewhere, some other economist might be getting ahead of them? This would also help explain why economists have a tendency to believe that all other economic actors are hypercompetitive, too–they are just projecting their own personalities.

Perhaps the lack of sleep helps to explain why economists have such a difficult time perceiving the reality around them, and thus why their advice is sometimes so weirdly out-of-synch with the actual economy. 

And of course, one possible response is: \”Who cares why economists are sleeping less? As long as economists are suffering in some way, the sun will shine just a little brighter today.\”  

Further hypotheses are solicited. Send suggestions to .

Government Workers: It\’s Not the Wages, It\’s the Benefits

On average, government worker are paid more than private-sector workers, at both the federal level and at the state and local level. But the comparison is not apples-to-apples. On average, government workers have much higher levels of education and experience.  When adjusting for levels of education, it turns out that average wages are very similar for government and private-sector workers. The real advantage that government workers have in their compensation is that they receive noticeably better benefits–especially in their pensions and health benefits after retirement.

The most recent article of my own Journal of Economic Perspectives has an article by Maury Gittleman and Brooks Pierce called \”Compensation for State and Local Government Workers.\”   In January, the
Congressional Budget Office published \”Comparing the Compensation of Federal and Private-Sector Employees.\”  Here,  I\’ll first summarize some of the main evidence from these studies, and then list some of the main reasons why studies that compare pay of government and private-sector workers can reach such different results.

Numbers of government workers in context

Here\’s the CBO summarizing patterns in total government employment in recent decades (footnotes and references to figures omitted): 

\”For the past 30 years, the number of civilians employed by the federal government has hovered around 2 million people. During that period, federal employees have accounted for a declining share of the total U.S. workforce, because employment by the private sector and by other levels of government has grown along with the economy. In 1980, when about 79 million people worked in the private sector and 13 million worked for state or local governments, federal employees made up 2.3 percent of the workforce. By 2010, private-sector employment had reached 111 million and employment by state and local governments had reached 20 million.\”

Higher Education and Skill Levels for Government Employees

Here are some illustrations of the education differences between government and private-sector workers. From Gittleman and Pierce, here\’s a table showing average pay and education levels for state government employees,  local government employees, and private-sector employees. For example, 39% of private-sector workers have only a high school education, or less education than that. Among state government employees, only 18% have a high school education or less. Conversely, about 10% of private-sector workers have a post-graduate degree, compared with 29% of state government workers.

Here\’s some evidence from the CBO, making the same point  about federal employees. In their data sample, 41% of private sector workers have a high school degree or less, compared with 20% of federal employees. Conversely, 10% of private sector worker have a post-graduate degree, compared with 21%  of federal employees.

Similar Pay, Dissimilar Benefits

When comparing pay for state and local government employees, Gittleman and Pierce write:

\”Government workers are much more likely to be offered health insurance and retirement plans, and are more likely to enroll in  such plans if offered. In addition, public sector plan structures tend to offer more
comprehensive coverage. Public sector health plans tend to require lower employee contributions and have higher employer premiums, and are more likely to come bundled with supplemental dental, vision, or prescription drug plan components. … [T]he costs per hour worked for the various benefits collected are
much greater in the public sector (about $14) than in the private sector (around $8). Spending on health insurance in the government ($4.30 at the state level and $4.56 at the local level) is more than double that in the private sector ($2.14), while expenditures on retirement and savings are more than triple ($3.18 and $3.37 versus $1.00). … Paid leave is also more generous in government, more than double the private sector level in state government and more than 50 percent higher in local government.\”

Overall, Gittleman and Pierce conclude: \”After controlling for skill differences and incorporating employer costs for benefits packages, we find that, on average, public sector workers in state government
have compensation costs 3–10 percent greater than those for workers in the private sector, while in local government the gap is 10–19 percent.\”

In comparing the wages, benefits, and total compensation of federal workers, the CBO report finds:

\”Overall, the federal government paid 2 percent more in total wages than it would have if average wages had been comparable with those in the private sector, after accounting for certain observable characteristics of workers. …  On average for workers at all levels of education, the cost of hourly benefits was 48 percent higher for federal civilian employees than for private-sector employees
with certain similar observable characteristics … The most important factor contributing to differences
between the two sectors in the costs of benefits is the defined-benefit pension plan that is available to most federal employees. … Overall, the federal government paid 16 percent more in total compensation than it would have if average compensation had been comparable with that in the private sector, after accounting for certain observable characteristics of workers.\”

Why do comparisons of pay for government and private-sector workers reach varying conclusions?

1) Some comparisons don\’t adjust for education or skill level of the workers, which means that the comparison will inevitably find that government-sector workers are paid much more on average. But such comparisons are silly. It\’s a bit like saying that–surprise!–those with a college degree earn more than those without a college degree.

2) Some comparisons look only at wages and skip benefit. Such comparisons leave out a main advantage for government workers, and will tend to find that they are paid about as much as private sector workers.

3) Employees in larger firms tend to be paid more than employees in smaller firms. There are various theories for why this pattern holds true. Perhaps large employers do a better job of screening employees to get those with higher productivity. Perhaps in a large firm there is space for a more specialized division of labor, which leads to more productivity and higher pay for workers in those organizations. Perhaps in large organizations, pay becomes a little more detached from productivity, and workers can claim a larger share of the cash flow running through the organization. Ultimately, the question here is whether a worker who moved between the government and the private sector has a type of skill and expertise that would also lead to higher pay in the private sector–or not. If you adjust for size of employer, then it will look as if government employees should be paid more–because they work for a large employer. If you don\’t make such an adjustment, then pay for government workers will look relatively higher. The CBO study, for example, found that if one adjusts for size of employer (and education), federal employees get wages that are 2% above private sector workers, but if you don\’t adjust for size of employer, then federal employees get wages 9% above those of private sector workers.

 4) A larger share of public-sector workers are unionized, and we know that unionized workers are paid more than other workers with equivalent skills. Again, the essential question here is whether a being unionized represents a skill set that the worker would take with them into private-sector employment, or not. I think it\’s more plausible to say that being unionized isn\’t a a portable \”skill set.\” If a study adjust for unionization, it will tend to find that government workers deserve to be paid more.

5) One problem in comparing government and private sector jobs is that the jobs themselves can be so different. For example, think of jobs in the education sector: Private sector jobs in this area tend to be either with preschool children or with college students and adults, while public-sector jobs in this area tend to be with K-12 students. Conversely, most jobs in sales or manufacturing are in the private sector, with very few in the public sector. If the researcher tries to adjust for the exact kind of job, comparing public and private-sector workers become difficult or even impossible. But if the researcher doesn\’t adjust in some way for the sector of the economy, you end up comparing workers who are in potentially quite different industries. An in-between approach here is to adjust for broad sectors–like \”education\” or \”services\”–but not to try to adjust for highly specific job categories.

6) Pay scales are more compressed in government. As emphasized in the CBO study, workers with lower levels of skill are on average paid more in government work than in the private sector, but worker with higher levels of skill are on average paid less. An overall comparison between all government and all private-sector workers will miss this distinction.

7) Job are more than wages and benefits. For example, government jobs in the Great Recession and its aftermath have tended to be more secure than private-sector jobs, in the sense of a lower chance of being laid off and a lower chance of pay cuts. Jobs have other characteristics, too. Certain jobs pose greater health risks, like mining and manufacturing in the private sector, or police and firefighters in the civilian public sector. I\’m not aware of studies that make a serious effort to value and adjust for these kinds of factors.

In short, when looking at a study comparing government and private-sector pay, run down this checklist of
seven points and it will tell you something about whether the study is likely to be leaning in one direction or another.

For-Profit Higher Education

It has been common for some years for politicians and educators to vow that America will greatly increase the proportion of students attending college. For example, in a speech to Congress on February 24, 2009, President Obama said: \”I ask every American to commit to at least one year or more of higher education or career training.  This can be community college or a four-year school; vocational training or an apprenticeship.  But whatever the training may be, every American will need to get more than a high school diploma.  And dropping out of high school is no longer an option.  It’s not just quitting on yourself, it’s quitting on your country – and this country needs and values the talents of every American.  That is why we will provide the support necessary for you to complete college and meet a new goal:  by 2020, America will once again have the highest proportion of college graduates in the world.\”

But how will the United States structure and pay for this expanded college attendance? For example, one policy approach would be to plan for dramatic expansion of enrollment in existing state colleges and universities, but with very tight state budgets, this isn\’t happening to any great extent. Instead, the answer that seems to be evolving, without ever really being enunciated and debated, is that the federal government will finance a dramatic expansion of higher education through an expansion of student loans, and because of limits on the number of slots at existing public colleges and universities, many students will take those loans to the for-profit higher education sector. In the Winter 2012 issue of my own Journal of Economic Perspectives, freely available on-line courtesy of the American Economic Association, Deming, David J., Claudia Goldin, and Lawrence F. Katz discuss the tradeoffs of this choice in \”The For-Profit Postsecondary School Sector: Nimble Critters or Agile Predators?\”

As the authors point out, the time since 2000 is \”a period when enrollment in the for-profit sector tripled while enrollment for the rest of higher education increased by just 22 percent. The solid dark line shows
that the fraction of fall enrollments accounted for by the for-profits increased from 4.3 percent in 2000 to 10.7 percent in 2009.\” They point out that \”al
most 90 percent of the increase in for-profit enrollments during the last decade occurred because of the expansion of for-profit chains,\” where a \”chain\” is defined as an institution that operates across states or has more than five branches within a state.\” 

Along with the flexibility to expand enrollments, for-profit higher education has shown considerable flexibility in teaching groups not well-served by traditional higher education. \”African Americans
account for 13 percent of all students in higher education, but they are 22 percent of those in the for-profit sector. Hispanics are 11.5 percent of all students but are 15 percent of those in the for-profit sector. Women are 65 percent of those in the for-profit sector. For-profit students are older: about 65 percent are 25 years and older, whereas just 31 percent of those at four-year public colleges are, and 40 percent of those at two-year colleges are.\” In addition, for-profits are typically non-selective institutions, requiring only a high school diploma or a GED certificate.

For-profit institutions also have been quite flexible in providing the kinds of career-oriented classes that many students want: \”For-profit programs typically are not meant to prepare students to continue to another form of higher education, as is the case with most community colleges. Rather, the for-profits almost always offer training for a vocation or trade…. Although 5 percent of all BAs are granted by for-profit institutions, 12 percent of all BAs in business, management, and marketing are. Other large for-profit  BA programs are in communications (52 percent of all BAs in communications are granted by for-profits), computer and information sciences (27 percent), and personal and culinary services (42 percent). … Among AA degrees just two program groups—business, management, and marketing, and the health professions—account for 52 percent of all degrees. In the BA group, the business program produces almost 50 percent of the total. Among certificates granted in the Title IV for-profit sector, health professions and personal and culinary services account for 78 percent of certificate completers.\”

Of course, there is controversy over for-profit higher education. The big firms that dominate the sector are, well, for-profit, and they tend to pay their executives well and their faculty not-so-well. A high proportion of students at for-profit institutions are financing their studies with debt, and if they don\’t complete the degree–which can be a big problem at some for-profit institutions–the students are still on the hook for that debt. Total student debt now exceeds the total amount of credit card debt, and will soon top $1 trillion. In their well-balanced essay, Deming, Goldin, and Katz discuss these issues.

But to repeat my earlier point, we have apparently made a social decision that a combination of student loans and for-profit institutions is the primary method by which the United States will raise college admissions. I would like to see a competitive response to the for-profits from public-sector non-profit higher education. I\’d love to see the public sector aggressively increasing non-selective enrollments, offering on-line classes and flexible meeting times for nontraditional college students, using technology and nontenured lecturers aggressively to hold down costs, and expanding certificate and degree programs with a focus on what is demanded in the market. This kind of institutional change is undoubtedly difficult.  But with a few local exceptions, the public higher education sector is reacting too much much like Kodak when that company was first confronted with low-cost competition for film and then with the change to digital photography–and the firm was too slow to adapt. 

I know that for-profit higher education has its warts and flaws. But so far, the not-for-profit higher education sector has not shown that it is serious about being flexible or entrepreneurial in way that can meet the goal of expanding college enrollment.


Same Income, Varying Taxes: ERP #4

This is the fourth of four posts based on figures from the 2012 Economic Report of the President. For the first post and an overview, start here.

Amid the complexity and confusion of the U.S. income tax code, it\’s quite possible for people with similar levels of income to pay widely varying level of tax. For illustration, consider the table. The rows of the table divide up the U.S. income distribution into fifths, or quintiles. The last row shows results for the top 1% of the income distribution.  For each quintile–and for the top 1%–the columns of the table then tell about the distribution of taxes for that group.

For example, if one looks at the distribution of average tax rates for the bottom quintile, households at the 10th percentile of that distribution have a federal tax rate of -13.7% (that is, they receive refundable tax credits from the government). In the bottom quintile of the income distribution, those at the median pay 5.4% of income in federal taxes. (These calculations include income taxes and payroll taxes.)

Or look at the top 1%. Given the distribution of federal taxes for that group, the household at the 10th percentile of tax payments for this group pays 8.7% of income in federal taxes (presumably due to substantial tax-free investments, or perhaps to carrying forward losses from a previous tax year that count against income in this year). However, a household in the top 1% of the income distribution and the 90th percentile of the tax distribution for this group pays an average federal tax rate of 34.6%.

At least for me, there is something of a tendency when looking at tables like this one to feel as if some of those with high income are paying too little, and some of those with low incomes are paying too much. And maybe that quick reaction is correct. But the tax code has so many rules and provisions and exceptions and situations, that it\’s s also possible that if I knew the actual details of some of these taxpayers, the outcome would seem fairly reasonable to me.

The broader point here is that when a tax code becomes enormously complex and lengthy, it is also going to allow the possibility of considerable variation in taxes paid even for those with similar incomes. Even if all the individual provisions of such a tax code are defensible (an enormous \”if\”!), the tax code as a whole is likely to end up appearing arbitrary and unfair.

Job Market Churn is Slowing: ERP #3

This is the third of four posts based on figures from the 2012 Economic Report of the President. For the first post and an overview, start here.

The U.S. job market has long been famous for its \”churn\” — that is, the simultaneously large inflows and outflows out of jobs which suggest a fluid and adjustable labor market. Thus, it\’s disturbing to observe a long-term trend toward less churn in the U.S. labor market. Here\’s a figure using the Business Dynamics Statistics from the Bureau of Labor Statistics:

Here\’s commentary from the Economic Report of the President: \”The rates of both gross gains and gross losses have been declining over time. Whereas, on average, 18.2 percent of private-sector jobs in the 1980s were newly created positions in startups or expanding firms, gross job gains fell to 16.8 percent of total private-sector employment in the 1990s and to 15.8 percent between 2000 and 2009 (Figure 6-3). Similarly, gross job losses were slightly more than 16.2 percent of overall private-sector employment in the 1980s but fell to 14.9 percent in the 1990s and then remained largely the same between 2000
and 2009. These secular declines also are apparent when one focuses more narrowly on startups.\”

Here\’s a similar pattern from another source: quarterly data from the Business Employment Dynamics (BED) survey.

What explains this drop in job churn over time, and is it a cause for concern? The report says (citations omitted): \”Now that researchers have documented the long-term secular slowdown in job gains and losses, the underlying reasons for the slowdown and its implications for the future of the U.S. economy are fast becoming the subject of an active debate. One possible reason for the slowdown in job reallocation is the aging of the population. Older workers may be less likely to become entrepreneurs, and research has documented a positive correlation between worker age and job tenure.\”

An aging workforce probably is part of the explanation. But one also wonders if there isn\’t another dynamic at work: for a variety of reasons, it may be getting harder to start up a business in the United States, and harder to be an employer. In turn, workers perceive fewer outside opportunities, and become more likely to stick with their present job. Or perhaps the U.S. labor market is becoming less fluid and adjustable in other ways.

Why Wasn\’t the Risk of a Housing Price Decline Taken Into Account? ERP #2

This is the second of four posts based on figures from the 2012 Economic Report of the President. For an overview and the first post, start here.

When I give talks about the causes of the recession, people often shake their heads in disbelief at the thought that few investors were taking the risk of a housing price decline into account. I think this disbelief is a case of 20:20 hindsight. Investors didn\’t take the risk of a national housing price decline into account  because they hadn\’t seen anything like it before. Here\’s a figure showing comparing the housing price declines nationwide during the Great Depression,  and then comparisons with more local housing price declines in Boston in 1989 and in California in 1990. Sure, investors knew that housing prices could nosedive in a local market, and some were even braced for the possibility of a modest housing price decline nationwide. But for the country as a whole, predicting in 2005 or 2006 that national housing prices would drop much farther and faster than during the Great Depression would have been a prediction outside all historical experience. I admire the clairvoyance of the few who truly saw it coming, but I can\’t reasonably blame those who didn\’t.

The evidence does offer some hints that the decline in U.S. housing prices may be just about over. For example, one measure of a price bubble is to look at the ratio of housing prices to rents. When this ratio rises sharply, then it may be a signal that prices are getting out of line. But that ratio has now fallen back to pre-crisis levels. Similarly, the ratio of mortgage value per home-owning household has trended up over time, as the economy has grown. During the housing price bubble, that trend launched like a rocket, but now it has been flat for a few years, and is not too far out of line with the longer-term trend.

At the most basic level, the national average of actual housing prices does seem to have levelled out since early 2009. Indeed, futures markets that were predicting a continued drop in housing prices as of January 2009 have seen housing prices hold up better than expected at that time.

The Relatively Mild U.S. Financial Recession: ERP #1

I always enjoy looking through the annual Economic Report of the President, but I confess that I impose a couple of rules. I focus almost entirely on the figures and tables, and how they are discussed in the text. I ignore all economic projections for the future, and all comments about specific policies of the current administration. At least for me, this approach is useful in stripping away the politics, and focusing instead on some vivid facts and analysis. I\’ll offer four posts today using figures from the 2012 ERP:

  1. The Relatively Mild U.S. Financial Recession
  2. Why Wasn\’t the Risk of a Housing Price Decline Taken Into Account?
  3. Job Market Churning is Slowing
  4. Same Income, Varying Taxes

The Great Recession has been brutally deep, and the aftereffects seem likely to persist for at least five years after it officially ended in June 2009 (by the dating of the National  Bureau of Economic Research). But in the context of financial recessions in other countries, the U.S. experience actually doesn\’t look so bad. Here\’s a table comparing the behavior of real GDP across 14 recessions associated with financial crises. The average peak-to-trough decline is a drop of 10.2%; in the U.S., the decline was 5.1%. The average length of these recessions was 6.6 quarters; in the U.S., peak-to-trough was 6 quarters.

The rise in U.S. unemployment rates has been similar to that in other financial crisis in this comparison group, but believe it or not, somewhat less prolonged. The next table shows the rising U.S. unemployment rate over time from the business cycle peak compared with the average of the other countries in the comparison group. The figure after that shows a country-by-country comparison of the total rise in the unemployment rate.

Even the pattern of the U.S. economic recovery, sluggish as it has been, has basically followed the time profile of the 14 comparison countries.

Sometimes people talk about the depth of the Great Recession as if it really couldn\’t have been any worse–as if the very depth of the recession and the sustained proves that macroeconomic policy to counter the recession was necessarily ineffective. The conclusion does not necessarily follow, of course. To me, these comparisons offer some (admittedly impressionistic) evidence that the monetary policy steps taken by the federal government–the huge budget deficits on the fiscal side, along with  the near-zero federal funds interest rates and quantitative easing on the monetary side–did have beneficial effects. The Great Recession and its aftermath have been gruesome, but without the aggressive fiscal and monetary policy response, it could have been even worse.