Conversable Economist

International tourism is an industry that now involves more than one billion travellers per year and more than $1 trillion per year in total spending. Welcoming more international visitors to spend their vacation dollars in the U.S. is both a plausible way of putting a dent in the U.S. trade deficit and a potential growth industry for new jobs. But international tourism is also an industry where America doesn\’t really try to compete; indeed, it actively hinders international tourists through its visa requirements.  Robert A. Lawson, Saurav Roychoudhury, and Ryan Murphy consider \”The Economic Gains from Eliminating U.S. Travel Visas\” in a Cato Institute Economic Development Bulletin (February 9, 2014).  Here\’s a realistic if hypothetical scenario to set the stage:

\”Suppose a reasonably affluent Brazilian family was interested in visiting Disney World in Florida. First they must fill out the DS-160 online application. Then they must pay a $160 application fee per visa and perform two separate interviews, one of which requires invasive questions and fingerprinting. The interviews typically must take place at an American embassy or consulate, of which there are only four locations in all of Brazil–a country as big as the continental United States–meaning that many of the Brazilian applicants will have to travel for the interview. While visas may take only 10 days to process, delays are common, and the United States government recommends not making travel plans until receiving the visa. To make matters even more uncertain, consular officials can stop the process at any moment and deny the family a visa without reason. The Brazilian family could go through that entire lengthy, expensive, and uncertain process or they could go to Disneyland Paris, France, without getting a visa at all. Unsurprisingly, many Brazilian families choose to go to Disneyland in France over the United States.\”

By their estimates, removing visa requirements completely could triple the number of international tourists in the United States. \”Eliminating all travel visas to the United States could increase tourism by 45–67 million visitors annually, corresponding to an additional $90–123 billion in tourist spending.\”

Of course, there are two main concerns about international tourists: they may be using the tourist visa as a way to immigrate to the U.S., or they may be a terrorist risk.  Lawson, Roychoudhury, and Murphy suggest the possibility of phasing in the removal of travel visas for countries where these issues seem less likely to be important. After all, the U.S. already has a Visa Waiver Program under which people from 37 countries can visit the U.S. for up to 90 days without a visa. They write:

\”The United States could phase in tourist visa reciprocity with nations that do not have a history of sending many unauthorized immigrants or that do not present security threats. Tourists from Malaysia, Botswana, Mongolia, Uruguay, and Georgia–nations that do not require Americans to obtain visas before visiting–could be allowed to enter without a visa to begin with, phasing in other nations depending on the success of those liberalizations. If the American authorities grow confident in their ability to limit visa overstays or the possibility of unauthorized immigration is greatly reduced, reciprocity could eventually be phased in with Mexico, Central American countries, and Caribbean nations as well.\”

Americans need to stop thinking about international tourism as only something where Americans spend money abroad, and start thinking about it as an economic opportunity, too. In a globalizing world economy, the countries that make an effort to be at the crossroads of that economy will have particular advantages.

I found especially thought-provoking Billig\’s argument early in the book about how the necessity for continual publications is relatively recent innovation in academic life, and how it has altered the incentives for quantity and quality of academic writing.  Here are a few of Billig\’s thoughts (citations omitted):

\”In the late 1960s, only a minority of those working in American four-year higher educational colleges tended to publish regularly; today over sixty per cent do … In 1969 only half of American academics in universities had published during the previous two years; by the late 1990s, the figure had risen to two-thirds, with even higher proportions in the research universities. The number of prolific publishers is increasing. In American universities the proportion of faculty, who had published five or more publications in the previous two years, exploded from a quarter in 1987 to nearly two-thirds by 1998, with the rise in the natural and social sciences particularly noticeable …

\”Experienced academics know that teaming up with other academics can be a means to increasing their collective output and thereby the total number of papers of which they can be credited as an author. In a field such as economics,  jointly written papers were rare before the 1970s but now they are commonplace. Journal editors, as well as those who have studied academic publishing, recognize the phenomenon of `salami slicing\’. Academic authors will cut their research findings thinly, so that they can maximize the number of publications they can obtain from a single piece of research. …

So, we produce our papers, as if on a relentless production line. We cannot wait for inspiration; we must maintain our output. To do our jobs successfully, we need to acquire a fundamental academic skill that the scholars of old generally did not possess; modern academics must be able to keep writing and publishing even when they have nothing to say. ….

As professional academics, we must extract the small nuggets of material relevant to our our interests from the mass of stuff that is being produced. Finding what we need to read necessarily means overlooking so much else. The more that is published in our discipline, the more there is to ignore. In consequence, the sheer volume of published material will be narrowing, not widening, horizons, containing us within ever smaller, less varied sub-worlds. It is important to remember that no one designed this system. There was not a moment in history when a group of powerful figures sat down in secret around a table and said: `Let us create a situation where academics have to read narrowly and to write at speed; that will stop them making trouble.\’ No secret meeting planned all this. But this is where we are now.\”

Over time, productivity growth determines the rise in a society\’s standard of living. I often find myself talking to people who are skeptical of economic growth for a variety of reasons, so let me specify that by productivity growth, I mean health-increasing, education-improving, job-creating, wage-gaining, pollution-reducing, energy-saving growth. More broadly, the nice thing about the problems of economic growth is that you can afford to do something about all your other social desires, because a bigger pie creates room for both higher government spending and lower tax rates.  Chapter 5 of the In the 2014 Economic Report of the President, released last week by President Obama\’s Council of Economic Advisers, tells the story of U.S. productivity growth in recent decades.

To put some intuitive meat the bones of the productivity idea, the discussion starts with a basic example of productivity for an Iowa corn farmer.

\”In 1870, a family farmer planting corn in Iowa would have expected to grow 35 bushels an acre. Today, that settler’s descendant can grow nearly 180 bushels an acre and uses sophisticated equipment to work many times the acreage of his or her forbearer. Because of higher yields and the use of time-saving machinery, the quantity of corn produced by an hour of farm labor has risen from an estimated 0.64 bushel in 1870 to more than 60 bushels in 2013. This 90-fold increase in labor productivity—that is, bushels of corn (real output) an hour—corresponds to an annual rate of increase of 3.2 percent compounded over 143 years. In 1870, a bushel of corn sold for approximately $0.80, about two days of earnings for a typical manufacturing worker; today, that bushel sells for approximately $4.30, or 12 minutes worth of average earnings.

This extraordinary increase in corn output, fall in the real price of corn, and the resulting improvement in physical well-being, did not come about because we are stronger, harder-working, or tougher today than the early settlers who first plowed the prairies. Rather, through a combination of invention, more advanced equipment, and better education, the Iowa farmer today uses more productive strains of corn and sophisticated farming methods to get more output an acre. … Technological advances such as corn hybridization, fertilizer technology, disease resistance, and mechanical planting and harvesting have resulted from decades of research and development.\”

In the picture, a typical American worker had more than four times the output per hour than a worker in 1948. As the table shows, about 10% of the gain can be traced to higher education levels and about 38% of the gain to workers that are working with capital investments of greater value. But the majority of the change is growth in multifactor producitivity: that is, innovations big and small that make it possible for a given worker with a given amount of capital to produce more.

The U.S. productivity challenge can be seen in the statistics of the last few decades. U.S. productivity growth was healthy and high in the 1950s and 1960s, plummeted from the early 1970s up to the mid-1990s, and has rebounded somewhat since then.

The reasons for the productivity slowdown around 1970 not fully understood. The report lists some of the likely candidates: energy price shocks that made a lot of energy-guzzling capital investment nearly obsolete; a relatively less-experienced labor force as a result of the baby boom generation entering the labor force and the widespread entry of women into the (paid) labor force; and a slowdown after the boost that productivity had received from World War II innovations like jet engines and synthetic rubber, as well as the completion of the interstate highway system in the 1950s. The bounceback of productivity since the mid-1990s is typically traced to information and communications technology, both making it and finding ways to use it. There is a considerable controversy about whether future productivity growth is likely to be faster or slower. But given that economists failed to predict either the productivity slowdown of the 1970s (and still don\’t fully understand it) or the productivity surge of the 1990s, I am not filled with optimism about our ability to foretell future productivity trends.

Sometimes people look at the vertical axis on these productivity graphs and wonder what all the fuss is about. Does the fall from 1.8% to 0.4% matter all that much? Aren\’t they both really small? But remember that the growth rate of productivity is an annual rate that shapes how much the overall economy grows. Say that from 1974 to 1995 the productivity growth rate had been 1% per year faster. After 22 years, with the growth rate compounding, the U.S. economy would have been about 25% larger. If the U.S. GDP was 25% larger in 2014, it would be $21.5 trillion instead of $17.2 trillion.

Policy-makers spend an inordinate amount of time trying to fine-tune the outcomes of the market system: for example, consider the recent arguments over raising the minimum wage, raising pay for those on federal contracts, changing how overtime compensation is calculated, or the top tax rate for those with high incomes. Given the rise in inequality in recent decades, I feel some sympathy with the impetus behind policies that seek to slice the pie differently–although I\’m sometimes more skeptical about the actual policies proposed. But 20 or 30 years in the future, what will really matter in the U.S. economy is whether annual rates of productivity growth have on average been, say, 1% higher per year.

The agenda for productivity growth is a broad one, and it would include improving education and job training for American workers; tax and regulatory conditions to support business investment; innovation clusters that mix government, higher education, and the private sector; and sensible enforcement of intellectual property law. But here, I\’ll add a few words about research and development spending, which is often at that growth in innovative ideas that are a primary reason for rises in productivity over. The Council of Economic Advisers writes:

\”Investments in R&D often have “spillover” effects; that is, a part of the returns to the investment accrue to parties other than the investor. As a result, investments that are worth making for society at large might not be profitable for any one firm, leaving aggregate R&D investment below the socially optimal level (for example, Nelson 1959). This tendency toward underinvestment creates a role for research that is performed or funded by the government as well as by nonprofit organizations such as universities. These positive spillovers can be particularly large for basic scientific research. Discoveries made through basic research are often of great social value because of their broad applicability, but are of little value to any individual private firm, which would likely have few, if any, profitable applications for them. The empirical analyses of Jones and Williams (1998) and Bloom et al. (2012) suggest that the optimal level of R&D investment is two to four times the actual level.\”

In other words, it\’s been clear to economists for a long time that society probably underinvests in R&D. Indeed, some of the biggest cliches of the last few decades is that we are moving to a \”knowledge economy\” or an \”information economy.\” We should be thinking about doubling our levels of R&D spending, just for starters. But here\’s what U.S. R&D spending as a share of GDP looks like: a boost related to aerospace R&D in the late 1950s and into the 1960s, which drops off, and basically flat since around 1980.

How best to increase R&D spending is a worthy subject: Direct government spending on R&D? Matching grants from government to universities or corporations? Tax breaks for corporate R&D? Helping collaborative R&D efforts across industry and across public-private lines? Whether we should be increase R&D is a settled question, and the answer is \”yes.\”

Finally, here\’s an article from the New York Times last weekend on how the U.S. research establishment is depending more and more on private-sector and non-profit funding. The graph above includes all R&D spending–government, private-sector, nonprofit–not just government. Nonprofit private foundations can do some extremely productive work, and I\’m all for them. But they are currently filling in the gaps for research programs that lack other support, not causing  total R&D spending to rise.

The great difficulty with lifetime financial choices is that you only get to do them once. With lots of choices in  a market, like buying dinner or buying clothes, the choices are made and the consequences are experienced in a fairly short time. Mistakes are fairly small-scale. If you don\’t like the clothes or the restaurant, go somewhere else next time. Indeed, one of the ways that competitive market forces work to encourage value and quality is through this process of repeated (or not!) purchases. But in a single lifetime, you get to try out precisely one set of lifetime financial choices. If at age 50 or 60 or 70 or 80 you wish that you had done something different earlier in life, you can\’t go  back to your 20s and 30s and 40s and live it over again.

When I talk about \”financial literacy\” to make these choices sensibly, I don\’t mean anything too sophisticated–just the basics to get by. For example, consider a person who can\’t answer the following three questions, which are examples given by Annamaria Lusardi and Olivia S. Mitchell in \”The Economic Importance of Financial Literacy: Theory and Evidence,\” published in the March 2014 issues of the Journal of Economic Literature. (Full disclosure: The JEL is published by the American Economic Association, which also publishes the Journal of Economic Perspectives, where I work as Managing Editor.) The JEL isn\’t freely available on-line, but many in academia at least should have access through a library subscription. Here\’s your three question financial literacy quiz:

• Suppose you had $100 in a savings account and the interest rate was 2 percent per year. After 5 years, how much do you think you would have in the account if you left the money to grow: [more than $102; exactly $102; less than $102; do not know; refuse to answer.]
• Imagine that the interest rate on your savings account was 1 percent per year and inflation was 2 percent per year. After 1 year, would you be able to buy: [more than, exactly the same as, or less than today with the money in this account; do not know; refuse to answer.]
• Do you think that the following statement is true or false? “Buying a single company stock usually provides a safer return than a stock mutual fund.” [true; false; do not know; refuse to answer.]

Remember, these questions are multiple choice, and you don\’t need to really understand the subject in any depth to make a plausible guess at the correct answers. These three questions were included as part of the Health and Retirement Survey in 2004, which is a nationally representative sample of Americans age 50 and over. Apparently, about one-third of Americans are able to answer all three of these questions correctly.

As Lusardi and Mitchell point out, many other surveys similar findings, and the young often do worse than their elders. However, it seems that most Americans are actually pretty optimistic about their financial literacy. They write (citations and references to tables omitted): \”Even though actual financial literacy levels are low, respondents are generally rather confident of their financial knowledge and, overall, they tend to overestimate how much they know. For instance, in the 2009
U.S. Financial Capability Study, 70 percent of respondents gave themselves score of 4 or higher (out of 7), but only 30 percent of the sample could answer the factual questions correctly …\”

Of course, a lack of financial literacy has many costs. People don\’t save enough, so that they become more vulnerable if their car breaks down, or someone in the family gets sick, or loses a job.  They are also vulnerable to costly financial decisions. Instead of having a bank account, they end up paying high fees through pawn shops and payday loans. They often pay high credit card fees. They end up in costly arrangements when buying cars or appliances or houses, and when interest rates fall (as in the last few years), they fail to refinance their mortgage or other loans. They end up poor in retirement.

Regulators have in the past tended to respond to these issues by requiring more and more disclosure, but adding more fine print is not the superhighway to financial literacy. The harder challenge is to specify a smaller number of clear choices, with sensible default options that will work for most of those who choose note to make a choice. People have different needs and desires, so this isn\’t easy. On the other hand, people who function in 21st century America need to deal with health care choices, consumer electronics, software, map-reading, insurance, and lot of other issues. Most of them can manage the basics of financial literacy, too. But they need to learn it relatively young, because knowing when you\’re 60 what you should have done when you were 25 is not useful.

Many U.S. states have at least some elements of personal finance in their high school curriculum requirements, but it\’s not clear how well the lessons are being communicated, either to high school students or to adults interested in learning more. As Lusardi and Mitchell write: \”Much work remains to be done. Very importantly, there has been no carefully-crafted cost–benefit analysis indicating which sorts of financial education programs are most appropriate, and least
expensive, for which kinds of people.\”

The issue of income inequality is international. The IMF Fiscal Affairs Department provides an overview in an IMF Policy Paper \”Fiscal Policy and Income Inequality,\” published January 23, 2014.

As a starting point, consider inequality across the world by region, as shown in Figure 1. The measure of inequality here is the Gini coefficient, a measure of inequality which ranges from zero where everyone has the same income to 1 when one person has all the income. The measure of income here is \”disposable income,\” which means that it is income after taxes and after transfers of income, but it does not include \”in-kind\” transfers like the provision of food stamps or Medicaid in the United States. The number in parentheses shows the number of countries in each group.

As the figure shows, inequality has been rising in advanced economies, even after the redistributive effects of government tax and spending programs are taken into effect. But it\’s also interesting to note that in these groupings, the amount of income inequality has been and remains much higher in other regions of the world. The IMF writes:

\”Between 1990 and 2010, the Gini for disposable income has increased in nearly all advanced and emerging European economies. Over one-third of advanced economies and half of emerging Europe experienced increases in their Ginis exceeding 3 percentage points, with most of the increases in emerging Europe occurring between 1990 and 1995 during the early years of their transition to market-based systems. Inequality also rose in most economies in Asia and the Pacific and in Middle East and North Africa. While average inequality fell in sub-Saharan Africa over this period, it still rose by more than 3 percentage points in more than one-fourth of these economies. Inequality also increased in over one-third of the economies in Latin America, although on average there was a slight decline. However, since 2000 there has been a substantial decline in the Gini in nearly all countries in this region. … \”More striking than changes in inequality within regions are the persistent differences across regions. For instance, between 1990 and 2010, average inequality in each region changed by less than 3¼ percentage points. In contrast, average inequality in the two most unequal regions
(sub-Saharan Africa and Latin America) remained 12 percentage points higher than the two most equal regions (emerging Europe and advanced economies).\” 

The long-term patterns of inequality at the very top of the income distribution vary as well.  For one group of countries–including the US, Canada, the UK, China, and India–the share of gross income going to the top 1% fell through much of the 1950s and 1960s, but has now risen back to levels similar to the 1920s and 1930s. However, in another group of countries–France, Germany, Japan, Sweden–the share of gross income going to the top 1% declined, but then has pretty much flattened out.

As the IMF report points out, \”a large proportion of the differences in regional average disposable income inequalities can be explained by differences in fiscal policies, especially in the levels and composition of taxes and spending.\” As a starting point, here\’s a figure based on public opinion polls showing public support for redistribution. The horizontal axis shows support for redistribution in the late 1990s and the vertical axis shows support in the late 2000s. If a country is right on the black line, that means that polling data showed the same support for redistribution in the late 2000s as in the late 1990s. The USA, for example, is quite close to the black line. But most countries are above the line, showing that public support for redistribution increased.

Just to be clear, the points here are based on a combination of surveys. The IMF report explains:

\”These surveys, which include the World Value Surveys (WVS), Regional Barometers, and International Social Surveys, ask citizens whether they favor more or less redistribution. In the WVS, respondents are asked to indicate, on a scale from 1 to 10, whether “incomes should be made more equal” (1) or whether the country “needs larger income differences as incentive” (10). For our purposes, we divide these responses in two categories: answers 1 to 5 indicate that the respondents prefer more redistribution, and answers 6 to 10 indicate preference for less redistribution. A similar approach is applied to other surveys to find the share of the population that supports more redistribution. The evidence indicates that public support for redistributive policies has grown in recent decades. Between the late-1990s and the late-2000s, public support for redistribution increased in almost 70 percent of the advanced and developing economies surveyed. For instance, support increased substantially in Finland, Germany, and Sweden, and also in China and India … Support for redistribution grew more in countries where inequality increased and, more recently, in advanced economies where the crisis hit hardest. For instance, public support between the late-1990s and the late-2000s grew by more than 30 percentage points in China, Finland, Germany and several Eastern European countries, where the income Gini increased by over 20 percent. At the same time, support declined in countries where the Gini decreased, including in Bulgaria, Mexico, Peru, and Ukraine.\”

The IMF calculates how much redistribution is actually happening through tax and spending policies: that is, how much is the Gini coefficient reduced by the tax and transfer policies enacted by government. Here\’s a measure for the advanced economies, where the Gini based on market incomes would average .43, but the Gini based on disposable after-tax after-transfer income is .29.

As the figure shows, the U.S. does less redistribution than other high-income countries. But the figure also helps to illustrate a perhaps less-known point: the lower level of U.S. redistribution is more on the spending side than on the tax side. Many European countries collect a lot of their tax revenues through value-added taxes or energy taxes, which work like sales taxes in collecting a higher share of income from those who have lower incomes, and who consume a higher share of their income. Indeed, the amount of redistribution that the U.S. does through taxes hasn\’t changed much in the last couple of decades, but the amount of redistribution that it does through transfer spending programs has declined substantially, in part because the big entitlement spending programs like Social Security and Medicare are not especially aimed at the poor. The report has much more to say about the design of tax and transfer programs around the world.

Teen birthrates in the United States have been falling for two decades–and falling at a faster rate in the last few years. Melissa S. Kearney and Phillip B. Levine explore possible reasons why in \”Teen Births Are Falling: What’s Going On?\” written as as March 2014 Policy Brief for the Economics Studies group at the Brookings Institution. Here\’s the trend:

To be sure, the U.S. teen birthrate remains well above that of most other high-income countries, where, as Kearney and Levine point out, the teen birthrate is usually in the range of 5-10 births per 1,000 women aged 15-19. Still, the teen birth rate in the U.S. has fallen by half in the last couple of decades. What might be the underlying causes?

There are three possibilities: teens having sex less often, teens who are having sex using contraception more often, and a higher number of abortions. The abortion rate among teens has not risen in a way that would explain the fall in teen births, so Kearney and Levine focus on the first two causes. They sum up their overall perspective in this way (citations omitted for readability):

\”To some extent, it is appropriate to consider teen childbearing to be the result of “non-decisions;” some teens are sufficiently ambivalent about becoming pregnant that they do not commit themselves to taking precautions against such an outcome. To illustrate this point, half of teens who report having an unintended pregnancy were not using contraception at the time of conception. This way of thinking about the issue allows for individual error and randomness in the process, but
ultimately considers that individuals – even teens – respond to the environment around them and make choices that either increase or decrease the likelihood of becoming a teen parent. Indeed, the data suggest as much, with teen childbearing rates rising and falling with environmental factors in systematic ways.\”

In ongoing research, they look at a number of these different environmental factors at the state level: different kinds of state sex education programs, from abstinence to contraceptive education; expansions of Medicaid that cover contraception or post-partum care for broader income groups; welfare payments; state abortion rules like waiting times or parental consent rules; child support enforcement; state unemployment rates, and more. These conditions will vary across states, and they are enacted at different times in different states. So you can do a statistical test to see how much of the variation across states in teen birthrates can be explained by these factors. The answer is \”very little.\” They write: \”We found that declining welfare benefit levels and expanded access to family planning services for lower income women through the Medicaid program were the only two
policies to have had a discernible effect. However, their effect is limited: we calculate that these two policies together account for only 12 percent of the reduction in teen childbearing between 1991 and 2008. Our analysis yields no evidence suggesting that other policies had a significant role in the decline.\”

Thus, if state-level differences are not the main factor, the next place to look is in broader economic or social patterns across states. In addition, these need to be factors that apply through both good and bad economic times over the last couple of decades. Indeed, although the U.S. has the highest rate of teen births across high-income countries, the rate of teen births has been falling in most countries, which suggests that at least some of the causes are broader than U.S. policies or socioeconomic conditions.

Kearney and Levine point to a few factors that have probably hastened the decline in the U.S. teen birth rate in recent years: in particular, the popularity of the TV shows 16 and Pregnant and Teen Mom, as well as the overall pattern that teen birth rates tend to be lower when unemployment is higher. But in terms of explaining the long-term trend, and the broader trend across countries, they readily admit that the evidence in not yet conclusive, but end up focusing on two factors:

\”We speculate that there are two likely candidate explanations: (1) access to improved contraceptive technologies, most notably long-acting reversible contraception (LARCs) such as implants and intrauterine devices (IUDs) and (2) increased educational attainment along with better labor market prospects for young women. … The policy challenge that we believe offers the greatest potential is to address the needs of those young women who are not committed to avoiding a pregnancy. These are teens whose views are characterized by ambivalence. For them, the issue is more about finding ways to make them want to avoid a teen birth. …  Simply put, increased aspirations and expanded opportunities for young women have the potential to extend the downward trend in teen childbearing.\”

For those interested in this topic, and especially in unravelling the difficult questions of whether teen pregnancy causes poor economic outcomes or poor economic outcomes lead to more teen pregnancy, and why teen pregnancy rates vary across countries and U.S. regions, I recommend an article by Kearney and Levine in the Melissa S. Kearney and Phillip B. Levine tackle these questions in\”Why is the Teen Birth Rate in the United States So High and Why Does It Matter?\” which appears in the Spring 2012 issue the Journal of Economic Perspectives. (Full disclosure: I\’ve been Managing Editor of the JEP since 1987, and so am predisposed to believe that all article in the journal are well-exposited and of considerable interest.)

The March 2014 issue of the Journal of Medical Ethics has a symposium on the issues of whether people should be allowed to sell a kidney. The lead article by Simon Rippon, \”Imposing options on people in poverty: the harm of a live donor organ market,\” is freely available on-line, but you need a subscription to read the comments.

Rippon aims to tackle head-on the claim, popular among economists, that offering people an additional option–in this case to sell a kidney–must make the people better off, because they don\’t need to choose the option, but if they wish to do so, they can. He clears the ground by saying: \”I know of no good reason for believing that there is anything intrinsically wrong with buying or selling

\”This means that even if you have no possessions to sell and cannot find a job, nobody can reasonably criticise you for, say, failing to sell a kidney to pay your rent. If a free market in organs was permitted and became widespread, then it is reasonable to assume that your organs would soon enough become economic resources like any other, in the context of the market. Selling your organs would become something that is simply expected of you as and when financial need arises. … 

We should ask questions such as the following: Would those in poverty be eligible for bankruptcy protection, or for public assistance, if they have an organ that they choose not to sell? Could they be legally forced to sell an organ to pay taxes, paternity bills or rent? How would society view someone who asks for charitable assistance to meet her basic needs, if she could easily sell a healthy ‘excess’ organ to meet them? … Wherever there is great value in not being put under social or legal pressure to sell something as a result of economic forces, we should think carefully about whether it is right to permit a market and to thereby impose the option on everyone to sell it.\”

The recovery of the U.S. economy since the end of the Great Recession in June 2009 has been sluggish and weak–and still much better than in most high-income countries. Here a figure from the 2014 Economic Report of the President, released earlier this week.

The figure shows Real GDP per Working Age Population. Real GDP means that it is measuring national economic output adjusted for inflation. By looking at \”working age population,\” it is adjusting for size of population but not (in a direct way) for level of unemployment. The horizontal axis measures quarters that have passed since the start of the recession. The vertical axis set the measure of output for each country equal to 100 at that time, so that you can easily compare the patterns across countries since that time. A few lessons jump out at me.

1) The U.S. and Germany are the only two of the 12 countries shown that have recovered back to the level of output/working-age population from before the Great Recession.

2) It\’s natural for Americans to focus on the problems of the U.S. economy, but by comparison, the U.S. economy is looking pretty good. The euro crisis isn\’t in the headlines right now, and I sometimes read that the crisis is past us. But look at the output/population level in Greece or in Italy, still sinking. The euro-area unemployment rate is up around 12%, and is at 25% in Spain and Greece. Germany, thanks to flexibility of its labor market institutions and benefits from the euro zone, has been doing well, too.

3) Ukraine was added to this graph at what I suspect was the last minute. You can see the shock that hit Ukraine\’s economy back in 2008, and how slow it has been to recover.

4) International comparisons are always a bit tricky. After all, the U.S. has been less affected by the euro crisis than countries of the European Union. Nonetheless, the basic fact is that the U.S. economy is leading the way in this comparison group, which suggests that U.S. economic policy in the aftermath of the Great Recession did something right. To put it another way, critics of the U.S. fiscal and monetary policies in the aftermath of the Great Recession need to explain why, if the policies were so bad, the outcome has been comparatively so good.

The basic student experience in many schools is quite similar to what it was a half-century ago. Te school day is divided into periods, each period is a subject, each subject has a teacher, and it all happens in a building that has been there for decades. Nowadays there\’s some additional technology mixed in. But perhaps, for at least some schools, a bigger shake-up is called for? Caroline Hoxby offers some thoughts in \”The Global Achievement Gap,\” published in the journal Defining Ideas from the Hoover Institution. In  my own reading, her essay suggests to me three potentially useful ways of shaking up public schools.

1) More extensive use of information technology.

Hoxby\’s example here is the \”Rocketship\” schools that operate in Santa Clara, California–that is, in the middle of Silicon Valley. She writes:

The Rocketship schools are hybrid schools that serve students who are largely poor and Hispanic or black. They attain some of the highest scores for students from such backgrounds among California schools. Their students spend part of each day in a \”learning lab\” in which they work on computers. The schools also use computer-based technology for curricular enrichment, diagnosis, and tracking progress. (Although the Rocketship schools are charter schools and largely admit students via lottery, they have not yet been evaluated using lottery-based methods. Thus, some of their high performance may be due to motivated or able students\’ self-selecting into them. However, what really interests us here is their financial model.)

The Rocketship schools have current per-pupil expenditures equal to 79 percent of that of traditional public schools in their county: $7,492 for Rocketship and $9,463 for the other schools. How do they manage this? First, their ratio of pupils to classroom teachers is 30.5 while the traditional public schools\’ is 21.6. Thus, Rocketship schools need only two teachers for every three teachers whom the traditional public schools need. According to their accounts, this entire reduction is attained by means of computers being used for mundane instruction and practice of skills. Second, Rocketship schools spend a much lower share of their budget on the wages and salaries of non-teachers: 12.7 percent as opposed to 32.6 percent. This is largely because they have approximately one non-teaching staff member for every three such people at traditional public schools. The schools’ explanation is that they have less need for administrators and support staff because technology performs many of the tracking and paperwork tasks that such people perform in traditional public schools.

Another benefit of integrating information technology is that it allows 

\”One might wonder how it is possible that US public schools could, within their current budgets, pay teachers in a manner that is so competitive with private sector rewards. The main explanation is that although high value-added teachers are currently underpaid, low value-added teachers who have high seniority, master\’s degrees, and other paper credentials are systemically overpaid relative to their alternative jobs. They have no incentive to leave teaching, therefore. They also have no incentive to improve their value-added. Low value-added teachers absorb so much of the total compensation budget that little is left for high value-added starting teachers, who are not only underpaid if they do teach but who tend to leave teaching as a result.\” 

For economists, why people vote has  long been a puzzle. After all, why go to the time and trouble of turning up at the polls for any big election, when the probability that your vote will decide the election is essentially zero? In Chapter 20 my Principles of Economics textbook on \”Public Choice\” (which I commend to the attention of college teachers out there), I sum up the argument this way: 

\”In a 1957 work, An Economic Theory of Democracy, the economist Anthony Downs stated the problem this way: “It seems probable that for a great many citizens in a democracy, rational behavior excludes any investment whatever in political information per se. No matter how significant a difference between parties is revealed to the rational citizen by his free information, or how uncertain he is about which party to support, he realizes that his vote has almost no chance of influencing the outcome. . . . He will not even utilize all the free information available, since assimilating it takes time.” In his classic 1948 novel Walden II, the psychologist B. F. Skinner puts the issue even more succinctly via one of his characters, who states: “The chance that one man’s vote will decide the issue in a national election . . . is less than the chance that he will be killed on his way to the polls.”

Indeed, one of the arguments for compulsory voting  is that otherwise, not enough people will bother. The arguments for why people vote quickly seem to invoke social motivations: that is, people vote because they feel part of a broader society, and participating in that society seems like a social norm that is worthwhile to them. But finding a way to confirm this feeling, rather than to assert its existence, and to measure its intensity has been elusive. 

Stefano DellaVigna, John A. List, Ulrike Malmendier, and Gautam Rao offer a deeply interesting experiment along these lines in \”Voting to Tell Others,\” which is available as NBER Working Paper #19832 (January 2014), but they have also written a nice readable overview for the Vox website here. Along with what the study has to say about voting, it also offers an interesting and hands-on method for  doing social science.

The authors mix together two sorts of data. One set of data they create themselves by interviewing people in some Chicago suburbs about whether they voted. However, some of the people received a flyer on their doorknob in advance. Some of the flyers said that a someone would come to do a five-minute survey. Other flyers said that it would be a five-minute survey \”on your voter participation in the 2010 Congressional election.\” Some of the flyers also promised to pay $10 for participating in the survey, and some said that the survey would take 10 rather than 5 minutes. Thus, the first set of data is how many people come to the door with and without the flyers, with longer and shorter times, with a promise of monetary payment and without. But the second big source of data is that the researchers had already accessed the voting rolls, so they actually already knew whether people had voted. Thus, they could compare the answers people gave, and whether people were more likely to respond to the survey, according to whether they had actually voted.

With this study design in in place, they draw several conclusions:

Finding 1: Voters do not feel pride from saying they voted, but non-voters do feel shame …  In fact, voting households are slightly less likely to answer the door and do the survey when they are informed about the turnout question. However, non-voters sort out significantly, decreasing their survey participation by 20%. … We find that the effect of reducing payment by $10 is comparable to the sorting response of non-voters to the election flyer. In other words, non-voters appear to dislike being asked whether they voted as much as they dislike being paid $10 less for completing the survey. … 

Finding 2: Non-voters lie and claim they voted half the time, while voters tell the truth … We find that voters tell the truth and say they voted 90% of the time, while non-voters lie and claim to have voted 46% of the time.

This kind of research clearly doesn\’t fit the stereotype of the economist sitting in an office, downloading electronic data to a spreadsheet. Instead, these researchers hired \”many\” undergraduate students to distribute the flyers, and 50 people to carry out the surveys, thus accumulating a dataset of over 13,000 households. Because of the pre-planned and random variation across the different households, with and without flyers before the survey, and with different information on the flyers, there is compelling reason to believe that they are capturing something real about how people think about voting.

Of course, one may raise concerns that the 2010 Congressional elections in in Illinois were a special case in some way, and the result might not generalize elsewhere. Those who raise such objections now have a template for the follow-up research they should to address those concerns.