Year: 2014

The old 1951 movie \”The Man in the White Suit,\” starring Alec Guinness, is both an entertaining adventure/comedy and a meditation on technology and planned obsolescence. The Alec Guinness character invents a wonderful new fabric that will never get dirty and never wear out. He sees a future where ordinary people will save money on clothes and cleaning expenses. People marvel at the invention at first, but soon everyone is against him: the textile and clothing companies fear his cloth will put them out of business, the workers in those companies fear losing their jobs, and those who do the washing fear losing work, too. Near the end of the movie, one character notes wryly that markets won\’t function if the products work too well. He says: “What do you think happened to all the other things? The razor blade that doesn’t get blunt? The car that runs on water with a pinch of something else?”

It\’s harder to come up with clear-cut real-world example of where companies sought to reduce the quality of a product in order to boost sales. After all, in real-world markets there should usually be a mixture of lower-quality, lower-price products and higher-quality, higher-price products, and what people want to buy will have a substantial effect on what gets produced. But in the October 2014 issue of IEEE Spectrum, Markus Krajewski tells the story of \”The Great Lightbulb Conspiracy: The Phoebus cartel engineered a shorter-lived lightbulb and gave birth to planned obsolescence.\”

The lightbulb conspiracy refers to the Convention for the Development and Progress of the International Incandescent Electric Lamp. It was signed in 1924 by the world\’s major light bulb manufacturers, including Germany’s Osram, the Netherlands’ Philips, France’s Compagnie des Lampes, Hungary’s Tungsram, the United Kingdom’s Associated Electrical Industries, and Japan’s Tokyo Electric. As Krajewski explains: \”The U.S. company GE, one of the prime movers behind the group’s formation, was itself not a member. Instead it was represented by its British subsidiary, International General Electric, and by the Overseas Group, which consisted of its subsidiaries in Brazil, China, and Mexico. Over the next decade or so, GE would acquire significant stakes in all the member companies that it did not already own. … [T]he group founded the Phoebus cartel, a supervisory body that would carve up the worldwide incandescent lightbulb market, with each national and regional zone assigned its own manufacturers and production quotas. It was the first cartel in history to enjoy a truly global reach.\”

Of course, cartels were widespread in the early decades of the 20th century, as the legal concept of antitrust enforcement was just getting established (which is surely why GE kept its American-based fingerprints off the Phoebus cartel). But even today, international antitrust is just now becoming a hot topic.

What makes the Phoebus cartel especially interesting is not its its standard cartel behavior in seeking to fix prices and quantities for sale, to assure higher prices. It\’s the effort of the cartel to shape the technological development of the light bulb, and in particular, to make light bulbs that would reliably burn out after about 1,000 hours–thus assuring additional future sales. Krajewski writes:

How exactly did the cartel pull off this engineering feat? It wasn’t just a matter of making an inferior or sloppy product; anybody could have done that. But to create one that reliably failed after an agreed-upon 1,000 hours took some doing over a number of years. The household lightbulb in 1924 was already technologically sophisticated: The light yield was considerable; the burning time was easily 2,500 hours or more. By striving for something less, the cartel would systematically reverse decades of progress. …
[W]e found meticulous correspondence between the cartel’s factories and laboratories, which were researching how to modify the filament and other measures to shorten the life span of their bulbs. The cartel took its business of shortening the lifetime of bulbs every bit as seriously as earlier researchers had approached their job of lengthening it. Each factory bound by the cartel agreement—and there were hundreds, including GE’s numerous licensees throughout the world—had to regularly send samples of its bulbs to a central testing laboratory in Switzerland. There, the bulbs were thoroughly vetted against cartel standards. If any factory submitted bulbs lasting longer or shorter than the regulated life span for its type, the factory was obliged to pay a fine.

Much of the research on shortening the expectancy of light bulbs focused on the materials and shapes used for the filament. One project at GE, for example, set out to reduce the life expectancy of flashlight bulbs, so that the bulb would need to be changed roughly each time the batteries were changed. At one point, some cartel member tried to sneak in some longer-lasting bulbs that would also require higher voltage. But the cartel snapped back.

After the Phoebus development department’s customary report of voltage statistics revealed such product “enhancements,” Anton Philips, head of Philips, complained to an executive at International General Electric: “This, you will agree with me, is a very dangerous practice and is having a most detrimental influence on the total turnover of the Phoebus Parties…. After the very strenuous efforts we made to emerge from a period of long life lamps, it is of the greatest importance that we do not sink back into the same mire by paying no attention to voltages and supplying lamps that will have a very prolonged life.”

A regular bank gets deposits from customers, and then loans out the money to borrowers. But what happens if the loans aren\’t repaid? Since the 1930s, the U.S. banking system (and the banking system of most other high-income countries) have relied on a two-pronged method of ensuring stability in the banking system: 1) deposit insurance means that the overwhelming majority of bank depositors don\’t need to worry that their money will be lost; and 2) bank regulation stops banks from taking unreasonably large risks that could lead to the loss of deposits. On the whole, this approach worked fairly well for more than  half-century. But the financial and economic crisis of 2007-2009 revealed a large and growing loophole in these arrangements: the existence of \”shadow banks.\”

 A \”shadow bank\” is any financial institution that gets funds from customers and then in some way lends the money to borrowers. However, a shadow bank doesn\’t have deposit insurance. And while the shadow bank often faces some regulation, it typically falls well short of the detailed level of risk regulation that real banks face. In this post in May, I tried to explain how shadow banking works in more detail. Many of the financial institutions at the heart of the financial crisis were \”shadow banks.\” For example, Reserve Primary Fund was a large money-market fund that had received money from depositors and had invested some of that money in debt issued by Lehman Brothers. When Lehman went broke, investors began to pull money out of Reserve Primary Fund–and indeed, about $300 billion flowed out of money market mutual funds that money–until the Federal Reserve and the Treasury Department stepped in with guarantees and emergency loan assistance. In turn, investment banks like Lehman Brothers were not standard commercial banks either, but they were relying on continual inflows of short-term borrowing (similar to deposits at a standard bank) and lending out and investing the funds. When their investments turned bad, their ability to receive short-term borrowing dried up at the same time, and they no longer had capital to function.

Five years past the end of the Great Recession, how vulnerable is the U.S. and the world economy to instability from shadow banking? One worrisome dynamic is that the more tightly actual banks are regulated, the more the financial industry comes up with other \”shadow banking\” institutions for making loans. The IMF devotes a chapter in its October 2014 Global Financial Stability Report to \”Shadow Banking Around the Globe: How Large, and How Risky?\” From the summary:

Although shadow banking takes vastly different forms across and within countries, some of the key drivers behind its growth are common to all: a tightening of banking regulation and ample liquidity conditions, as well as demand from institutional investors, tend to foster nonbanking activities. The current financial environment in advanced economies remains conducive to further growth in shadow banking. Many indications there point to the migration of some activities—such as lending to firms—from traditional banks to the nonbank sector. Shadow banking can play a beneficial role as a complement to traditional banking by expanding access to credit or by supporting market liquidity, maturity transformation, and risk sharing. It often, however, comes with banklike risks, as seen during the 2007–08 global financial crisis. Although data limitations prevent a comprehensive assessment, the U.S. shadow banking system appears to contribute most to domestic systemic risk; its contribution is much less pronounced in the euro area and the United Kingdom.

Along with money market mutual funds, the shadow banking sector includes hedge funds, non-bank finance companies and nonbank mortgage  originators, broker-dealers, investment funds, real estate investment trusts, and the \”structured finance\” sector that includes asset-backed commercial paper, collateralized debt obligations, residential mortgage-backed securities, and structured investment vehicles. Many pension funds and insurance companies now do some direct lending of their funds to businesses. As one example of a financial innovation facilitated by banks, but ultimately where the funds are held outside banks, I posted about the leveraged loans sector a few days ago. These many sectors each have their own characteristics and pose their own risks, and it\’s an oversimplification to lump them together. That said, here\’s how the assets in shadow banking compare with conventional bank assets in various countries and areas. The U.S. ranks so highly, in part, because its financial system is less dominated by banks than is the financial system of many countries in the EU and elsewhere. Still the difference is striking.

The IMF makes an effort to sort through the details of all the different shadow banking sectors and to evaluate the risks involved. The IMF notes:

So far, the (imperfectly) measurable contribution of shadow banking to systemic risk in the financial system is substantial in the United States but remains modest in the United Kingdom and the euro area. In the United States, the risk contributions of shadow banking activities have been rising, but remain slightly below precrisis levels. …  In the United States, shadow banking accounts for at least a third of total systemic risk, (measured as extreme losses to the financial system that occur with a very low probability), similar to that of banks. In the euro area and the United Kingdom, their contribution to systemic risk is much smaller relative to the risks arising from their banking system. This largely reflects the fact that the latter are still more bank-based financial systems.

It is discomforting to me to read that for the U.S., shadow banking risks are \”slightly below precrisis levels.\” In general, the policy approach here is clear enough. As the IMF notes: \”Overall, the continued expansion of finance outside the regulatory perimeter calls for a more encompassing
approach to regulation and supervision that combines a focus on both activities and entities and places greater emphasis on systemic risk and improved transparency.\”

The price of necessities hits us all in a vulnerable spot. If the price of airfares to New Zealand rises, it doesn\’t affect my life–except that my dream vacation to New Zealand looks a little less possible. But if the price of food and gasoline rise, I notice it immediately, and it cuts into the family budget for entertainment and other pleasant activities. In an Economic Commentary written for the Federal Reserve Bank of Cleveland (October 6, 2014), LaVaughn M. Henry looks at \”Income Inequality and Income-Class Consumption Patterns.\”  By his measure, those with higher incomes can (unsurprisingly) spend a far smaller share of their income on necessities as compared to luxuries. However, all income groups are spending a lower share of their income on necessities than they did several decades ago.

Henry looks at data from the Consumer Expenditure Survey, which divides up what people buy into various categories. He then classifies some of the categories as more likely to be disproportionately \”necessities\” and others as disproportionately \”luxuries.\” for example, necessities include food at home, rent, utilities, health care, education, gasoline, and household supplies. Luxuries include food away from home, entertainment, household furnishings, \”other lodging,\” and others. His complete list appears at the bottom of the post. This division is clearly rough and ready, but as Henry explains: \”A specific type of good or service is classified as a luxury if more of it is consumed, on a percentage basis, as real income levels increase (that is, going from lower to higher income quintiles). Similarly, a specific good or service is classified as a necessity if it accounts for a smaller percentage of consumption as real income levels increase.\”

Back in 1984, household spending was more-or-less evenly divided between necessities and luxuries. Luxuries then rose as high as 58% of annual spending before the Great Recession hit, and have now fallen back to 56% of annual spending. Here\’s the pattern:

What about if we look across income groups? The following five graphs show the share of spending on luxuries with the blue line, and on necessities with the red line, across the five quintiles of the income distribution (that is, dividing the income distribution into five parts with equal numbers of households in each).  The share of income spent on  luxuries is much higher for the highest-income group. while the share of income spent on necessities is much higher for the lowest-income group. Of course, this is why people in lower income groups are so vulnerable to a rise in the price of necessities. But it\’s also intriguing to note that since 1984, the share of income spent on luxuries is rising for each income group, and the share of income spent on necessities is falling for each income group.

Many people, including me, have a tendency to feel that their hard-earned money should be spent on something fun, rather than having too much of it go to boring necessities like food and gas. One reason the pinch of the Great Recession has felt so severe, I think, is that people have been used to a world where over time they were able to spend more on luxuries. But that long-term trend halted during the Great Recession, and has not yet resumed.

Finally, here is Henry\’s overall list of consumption categories, categories by luxuries, necessities, and indeterminate.

Table 1. Average Share of Total Real Consumption, 1984-2012

In the aftermath of the Great Recession, we all learned to beware complex lending structures, which can crumble like a house of cards if repayments don\’t happen on time. A central ingredient in the financial crisis from 2007-9 were \”collateratized debt obligations,\” which were essentially a way of putting a group of subprime mortgage loans into a financial security, structured in a way that the credit rating agencies would rate a large portion of their value as safe. Financial regulators and the Federal Reserve didn\’t pay enough attention to the dangers of this financial legerdemain.

Now yellow warning lights should be blinking in the area of \”leveraged loans,\” which can be defined as \”a large, variable-rate loan originated by a group of banks (sometimes called a syndicate) for a corporate borrower who is perceived to be riskier than most.\”  Alex Musatov and William Watts lay out the issues in \”Despite Cautionary Guidance, Leveraged Loans Reach New Highs,\” in the September 2014 Economic Letter published by the Federal Reserve Bank of Dallas.

The issuance of leveraged loans spiked just before the financial crisis of 2007-9, then collapsed in 2008, but has now rebounded to new highs.

The basic idea of a leveraged loan is that because of the size of the loan and the risk posed by the borrowing firm, no individual bank wants to lend the money. However, a group of banks get together as a syndicate to organize the loan. \”The banks retain portions of the loan on their own books, but the majority of it is packaged for other investors—typically finance companies, insurance companies and hedge funds.\” A leveraged loan can be organized in several ways, as Musatov and Watts explain:

Specific lending arrangements reflect the size of the loan and riskiness of the borrower. In an underwritten deal, the syndicate issues the full amount of the loan and then tries to sell portions to outside investors. Underwritten deals are generally the most attractive loans to borrowers because they ensure that the entire amount of needed capital is raised; the lead bank gets higher fees for the risk of holding the debt while looking for investors. A “club deal,” used for smaller loans,involves several banks raising the money within the group while splitting the fees charged to the borrower. Finally, in “best effort” syndication, the arrangers of the loan underwrite less than its entire value and attempt to raise the remainder in the credit market. This type of syndication is generally used for
the riskiest borrowers or the most complex loan agreements.

Of course, there\’s nothing wrong or underhanded about leveraged loans. It\’s just one of the ways in which modern finance works. It\’s not easy for firms with with a less-solid credit record to borrow, and this is one of the ways it can happen. Of course, because such firms pose greater risks, they also need to pay a higher interest rate. But if the syndicates are making too too many of these loans, while taking the fees and then selling the loans along to investors who are eager for a higher return, then there a danger that a bubble is rising in this market.

In March 2013, as as Musatov and Watts note, financial regulators began to express concerns about the leveraged loan market: \”[T]he Office of the Comptroller of the Currency (OCC), Federal Deposit Insurance Corp. (FDIC) and Board of Governors of the Federal Reserve System (FRS) issued “Interagency Guidance on Leveraged Lending” in March 2013, outlining principles of safeand-
sound leveraged lending activities …\” What are some of the danger signs in this kind of market?

One signal is that the firms that are borrowing in the market sign a \”covenant\” contract, in which they make various promises about the total amount that the borrower will borrow, the value of short-term assets on hand that can easily be sold, limits on long-term investments, and so on. However, more and more leveraged loans are using \”covenant-lite\” approaches, where these rules are loosened–thus making the loan a riskier one.

While covenant-lite loans are becoming more popular, the additional interest rate charged to the borrowing firms–to account for their higher risk–has been coming down. The red line shows how much the interest rate \”spread\” on leveraged loans, above the baseline rate on U.S. Treasury borrowing, has been sagging over time. The green line shows the default rate on such loans, which has been rising over time. In short, the risks of such  borrowing seem to be rising while the extra interest rate charged to such borrowers to compensate for the risks is falling.

As noted earlier, financial regulators are keeping an eye on the leveraged loan market. As Janet Yellen testified before Congress in July 2014:

The Committee recognizes that low interest rates may provide incentives for some investors to \”reach for yield,\” and those actions could increase vulnerabilities in the financial system to adverse events. While prices of real estate, equities, and corporate bonds have risen appreciably and valuation metrics have increased, they remain generally in line with historical norms. In some sectors, such as lower-rated corporate debt, valuations appear stretched and issuance has been brisk. Accordingly, we are closely monitoring developments in the leveraged loan market and are working to enhance the effectiveness of our supervisory guidance.

What ultimately concerns me is not the specifics of the leveraged loan market by itself, but the thought that there are likely to be similar niche markets out there, invisible to most of us in their day-to-day operations, but with some potential to melt down in a way that could cause broader financial and economic distress.

The prospect of an infrastructure push is seductive. Economic and job growth has been sluggish. Interest rates and thus borrowing costs remain relatively low. At least some kinds of infrastructure might help to boost long-term growth. Thus, the October 2014 World Economic Outlook from the IMF includes a chapter on \”Is It Time for an Infrastructure Push? The Macroeconomic Effects of Public Investment.\” The IMF writes:

[I]ncreased public infrastructure investment raises output in both the short and long term, particularly during periods of economic slack and when investment efficiency is high. This suggests that in countries with infrastructure needs, the time is right for an infrastructure push: borrowing costs are low and demand is weak in advanced economies, and there are infrastructure bottlenecks in many emerging market and developing economies. Debt-financed projects could have large output effects without increasing the debt-to-GDP ratio, if clearly identified infrastructure needs are met through efficient investment.

Like so many statements by economists, this may seem straightforward, but it is actually hedged with qualifiers. For example, the first sentence refers to the positive outcomes arising \”when investment efficiency is high,\” and the closing line states \”if clearly identified infrastructure needs are met through efficient investment.\” In the middle, there is a reference to \”infrastructure bottlenecks in many emerging market and developing economies,\” but this sentence carefully does not claim that infrastructure bottlenecks are a first-order problem in advanced economies.

I take from this that the case for an infrastructure push is especially strong right now in those \”many emerging and developing countries.\” Here\’s a figure showing current levels of electricity, roads, and phone lines by region. But of course, infrastructure would also include water and sewage, airports and seaports, rail, wireless connections, natural gas and oil pipelines, and more.

Japan offers a mildly cautionary tale for advance economies on the limits of infrastucture investment.

What about for the advanced economies? The IMF chapter goes through a variety of calculations that attempt to separate out the specific effect of a boost in public infrastructure spending. The report notes (footnotes and references to figures omitted):

The macroeconomic effects of public investment shocks are very different across economic regimes. During periods of low growth, a public investment spending shock increases the level of output by about 1½ percent in the same year and by 3 percent in the medium term, but during periods of high growth the long-term effect is not statistically significantly different from zero. Public investment shocks also bring about a reduction in the public-debt-to-GDP ratio during periods of low growth because of the much bigger boost in output.

What about infrastructure in the United States? Here\’s a figure from the ever-useful FRED website run by the St. Louis Fed showing total public construction spending in the U.S. In rough terms, about one-third of this is highways and streets and another one-tenth is other transportation, one-quarter is education-related construction, about one-sixth is sewage and water. Other categories include power, public safety, and conservation and development. I\’m not surprised to see a boost in infrastructure spending during the Great Recession; after all, that was part of the \”economic stimulus\” package that passed in 2009. But I had not realized that public construction spending had actually been rising fairly briskly since about 2005, well before the recession hit.

As someone who lives in Minnesota, I favor more infrastructure spending. After all, about seven years ago a major bridge in Minneapolis collapsed during rush hour. After the brutal Minnesota winter, the potholes on the roads are large enough to swallow dogs, and sometimes appliances. But like a lot of economists, I have two concerns about how to focus and direct a push for more infrastructure, so that it means more a nice shiny bridge-to-nowhere in every Congressional district.

1) There\’s always a tension between civil engineers and economists. The engineers often look at every infrastructure limitation and see a building project that ought to happen. Economists often look at the same problem and see ways that  the existing infrastructure might be used more effectively. For example, instead of just automatically trying to build more roads, water-mains, electrical capacity, and the like, how about looking for ways to conserve on the need for using this infrastructure. Many economist favor finding ways to charge more at peak usage times as a way of spreading the use of infrastructure over a wider time period each day.

2)  I have a hard time believing that U.S. economic prosperity in the 21st century is going to be built on concrete and asphalt. As I said, I\’m all for fixing bridges and potholes, updating the municipal water pipes, and the like.  But what about infrastructure for the 21st century? Some of this infrastructure may be funded directly by the government, but most of it will require a fairly high level of government support and cooperation if it is going to happen. For example, as we repair current highways and bridges, how about starting to build the capacity for smart highways and self-driving cars?  What about a smart electricity grid, both to facilitate the use of decentralized renewable energy sources and to implement higher prices for large users at peak times? The U.S. needs to update its rail-freight system, which could move large numbers of trucks off the highways–thus reducing congestion and saving on road repair costs. The U.S. needs to update its network of oil and gas pipelines.  When the IMF talks about \”clearly identifiable needs\” and \”efficient investment,\” these seem to me some of the main U.S. infrastructure issues, although the list could doubtless be lengthened.

When talking about how infrastructure spending could boost a sluggish economy, the case of Japan often comes up. After all, didn\’t Japan boost infrastructure spending in the 1990s in an attempt to boost economic growth, but with little effect? The IMF report notes that the patterns of what happened in Japan are more complex:

It is true that Japan briskly increased public investment in the early 1990s, but the increase was unwound after just a few years to finance higher social security spending for a rapidly aging population. In particular, after the bursting of the bubble economy in the early 1990s, the government increased public investment spending by 1½ percent of GDP, with such spending reaching a peak of 8.6 percent in 1996. After that, the ratio of public investment to GDP steadily declined, picking up only recently in the aftermath of the global financial crisis, the 2011 earthquake, and the start of Abenomics. In the 20 years after 1992, the last year in which Japan recorded a fiscal surplus, social spending increased by 10.6 percent of GDP, and public investment declined by 2.3 percent of GDP.

Consumer energy efficiency programs (often funded by utilities) now cost about $5 billion per year, and most of the money goes to subsidies for consumers to purchase energy-efficient appliances.  Of course, there are also subsidies for purchasing certain kinds of fuel-efficient cars. Are these subsidies for consumers a cost-effective way of encouraging the purchase of energy-efficient appliances?

A couple of recent papers from Resources for the Future tackle this question in different ways.  Sébastien Houde and Joseph E. Aldy argue that the subsidies for consumers to purchase energy-efficient appliances are not a very cost-effective approach to encouraging energy conservation in \”Belt and Suspenders and More: The Incremental Impact of Energy Efficiency Subsidies in the
Presence of Existing Policy  (Discussion Paper 14-34, September 2014). A readable overview of their  results in the RFF blog is here.

However, in the most recent issue of Resources magazine from RFF, Richard Newell and Juha Siikamäki investigate, \”Can Product Labels Nudge Energy Efficient Behavior?\” The working paper offering the detailed analysis behind the article is available here. They find experimental evidence that what specific information is presented on the label of energy-efficient appliances can make a large difference in consumer perceptions. Let\’s take a quick look at these results.

The analysis of the cost-effectiveness of subsidies for energy-efficient appliances turns on dividing appliance purchasers into three categories: 1) some people are just going to buy the less efficient appliance, which often costs less up front; 2) some people are just going to buy the more energy-efficient appliances, either because of the longer-term cost savings from lower energy use or  because they want to do so; and 3) some people are \”switchers,\” who would have bought the less energy-efficient appliance, but because of the subsidy, switch over to the more energy-efficient appliance.

Of course, those who would have bought an energy-efficient appliance even without a subsidy are likely to favor the subsidies. For them, it feels like free money and a reward for virtuous activity. But from an energy conservation point of view, subsidies going to this group are all cost and no benefit–because these people would have bought the energy-efficient appliance anyway. The only energy conservation benefit comes from those who actually switch as a result of the subsidy.

Houde and Aldy take a statistical look at data from the State Energy Efficient Appliance Rebate Program, which was part of the 2009 American Recovery and Reinvestment Act. Basically, the federal government provided money, and then states had lots of flexibility in how to create such programs–which means its possible to do comparisons when the program existed and when it didn\’t, and also to look at comparisons across states. They find:

We estimate that the ratio of “switchers” (individuals who switch from a non–Energy Star to an Energy Star–rated appliance as a result of the rebate) to “freeriders” (individuals claiming rebates who would have purchased an Energy Star-rated appliance even in the absence of the rebate program) is 1:10, 1:12, and 3:8, for refrigerators, clothes washers, and dishwashers, respectively. As a result, the cost per kilowatt-hour saved is on the order of about $0.25 to $1.50, depending on assumptions and appliance category. The low end of this range is four times the average cost-effectiveness of utility-sponsored energy efficiency programs. 

In short, giving consumers a rebate for purchasing energy-efficient appliances isn\’t a cost-effective way to reduce energy use, because too much of the money goes to those who would have bought the energy efficient appliance anyway.

Newell and Siikamäki look at the labels on energy efficiency labels on water heaters. Here\’s the current standard EnergyGuide label:

They they experiment with presenting less information, and presenting different information. They survey a group of about 1,200 households who were randomly offered different labels and prices for water heaters. For economists, the issue here is the extent to which people are willing to take long-term costs in energy savings into account when they think about purchasing an appliance. You can find specific details in the articles, but basically, the standard label did a pretty good job: on average, those who saw the label also perceived the long-run energy savings accurately.

Perhaps not surprisingly, of the various elements on the label, the basic information on yearly operating cost had the biggest effect. However, if the policy goal was to encourage even further energy conservation, Newell and Siikamäki offer a couple of options that make people pay greater attention to the energy savings: for example, one approach is to add the EnergyStar logo and label to the standard information. Another approach, commonly used in the European Union, is to offer a colorful label that shows a range of \”grades\” for energy efficiency, and where this appliance stands in the range.

It\’s important to remember that the Newell and Siikamäki results are based on surveys of consumers, not on actual purchase decisions, so some further research is needed here. Still, the existing evidence strongly suggests that if the goal is greater energy efficiency for consumer appliances, the useful policy tools are setting minimum standards for energy efficiency and requiring labeling about energy efficiency that will catch the eye of potential buyers, while paying rebates to buyers of such appliances is money that could be better spent in other ways.

Across the high-income countries of the world, about one student in eight will have repeated a grade before reaching age 15. Does it do any good? The OECD assembles some of the evidence in \”Are disadvantaged students more likely to repeat grades?\” published in PISA in Focus (September 2014).
There\’s also a readable overview at the OECD blog here.

For starters, here are some basic statistics about the amount of grade repetition across countries for the OECD countries. Some European countries which stand out with especially high rates of grade repetion include Belgium, Netherland, Portugal and Spain. The U.S. is roughly at the average for OECD countries. A number of other countries including Korea, Sweden, and the United Kingdom hold back students at less than half the average rates.

ashfdksd
The report also collects data on grade repetition for a number of other countries. What jumps out at me in particular is the prevalence of grade repetition in many Latin American countries, where the share of students who have repeated a grade is often over one-third.

Looking across these different national experiences, what is the evidence that holding students back is an effective approach? After all, there are  a number of other ways to assist students performing below grade level, including tutoring, remedial classes, working with families, and classed that are \”tracked\” according to academic performance. The OECD writes:

In practice, however, grade repetition has not shown clear benefits for the students who were held back or for school systems as a whole. And grade repetition is a costly way of handling underachievement: retained students are more likely to drop out, or to stay longer in the school system and spend less time in the labour force. As a result, some countries that had used grade repetition extensively have rejected that policy in favour of more intensive early support for struggling students. Among the 13 countries and economies that had grade repetition rates of more than 20% in 2003, these rates dropped by an average of 3.5 percentage points by 2012.

Moreover, the choice of which students are held back and which students get alternative forms of help seems to be heavily influences by socioeconomic factors about the family of the student. Here\’s a figure showing how often students in the bottom 20% of a measure of socioeconomic status are held back a grade–after adjusting for any differences in math, reading and science test scores. (The dark green bars mean that the difference is statistically significant.) The report notes: \”In Portugal and Spain, for instance, when comparing a group of disadvantaged students to an equally proficient group of advantaged students, there are three times more repeaters for every non-repeater in the disadvantaged group than in the advantaged group. On average across OECD countries, disadvantaged students are 1.5 times more likely to repeat a grade than advantaged students who perform at the same level.\”

Of course, none of this rules out holding back a few students, some of the time. But every time a decision is made to hold back the student, that student will then be surrounded by peers who are younger, and when everyone else his or her age is leaving school, that held-back student will have completed less school than others of the same age. Holding back students should both be more of a last resort, and also a choice made on a more equitable basis, in many countries. The OECD sums up this way:

The bottom line: Grade repetition may not only be ineffective in helping low-achieving students overcome their difficulties at school, but may also reinforce socio-economic inequities. Providing extra teaching time for students who fall behind, adapting teaching to their needs so that they can catch up with their peers, and targeting these efforts where they are most needed is a much better way of supporting students with learning difficulties or behavioural problems.

About 1.2 billion people around the world have a consumption level of less than $1.25 per day, and 2.4 billion have a consumption level of less than $2 per day, according to the World Bank. One standard policy prescription has been to try improve the standard of living for this group through foreign aid. Indeed, the higher-income nations of the world gave $134.9 billion in official development assistance in 2013, according to the OECD.

One can argue that foreign aid should be higher. The OECD some years ago set a target that high-income countries should try to give 0,7% of GDP in foreign aid, but few countries meet that target, and the average (as a share of GDP) is about half that amount.

But a bigger problem for foreign aid is suggested by long division: Take $134.9 billion in aid and divide it by 2.4 billion people consuming less than $2 per day, and it works out to about $56 per person. Even if effectively administered and invested, that amount of aid isn\’t going to budge the needle on global poverty by very much.

Thus, it\’s natural to ask what high-income countries might do, other than tweaking their foreign aid budgets, to help the world\’s poor. A committee in the UK House of Commons is apparently seeking to compile a policy agenda along these lines. Owen Barder and Theodore Talbot of the Center for Global Development drew up a memo for the House of Commons committee. The memo is here; a blog post about the issue at the CGD website is here. Here\’s a sampling of their policy proposals to help the world\’s poor that go beyond the foreign aid budget (with many citations omitted for readability).

Reducing trade barriers

\”Laborde et al. (2013) study the possible impact of the on-going WTO Doha Round
negotiations and find real income gains to low- and lower middle- income countries
of between £28.5 billion to £37.6 billion a year just from lower tariff barriers in rich
countries. … [The US] Congress signed the African Growth and Opportunity Act
(AGOA) into law in May 2000. Frazer and van Biesebroeck find a resulting increase
in exports from eligible African countries of around £299 million a year.\”

Facilitating private investment, especially for infrastructure

\”Data from 2007 shows that twenty-five of the forty-four countries in sub-Saharan Africa were experiencing crippling power shortages. Power cuts reduce annual growth rates of the worst hit African economies by over 2%. Transport is also a serious problem. … [T]he annual funding shortfall for low- and lower middle-income African countries is estimated at nearly £27 billion per year to overcome the current infrastructure gap within a 10-year period. For developing South Asia, Andrés et al. (2013) estimate a £1.4 trillion dollar infrastructure gap over the next decade. … Tackling illicit financial flows (IFFs) could help governments in poor countries meet more of their own needs. These flows include tax evasion (like firms underreporting export values to lower their tax bills), theft of public assets and related corruption, the laundering of the proceeds of crime (like drug sales), and a range of market and regulatory abuses under cover of anonymity (like hidden connections between politicians regulating an industry and the industry itself). Illicit flows, by their nature, are difficult to measure, but all studies put total costs in the billions annually. According to one estimate, twenty Sub-Saharan African lost an estimated 10% or more of their cumulative GDP produced between 1980 and 2009 to these outflows.

Migration 

\”About 60% of global income inequality can be explained simply by which country people live in: one of the most effective ways to raise incomes of poor people would be to allow more people to choose what country to work or reside in (even temporarily). …  Research on the US labour market by the Center for Global Development (CGD) shows that workers from Paraguay or Turkey, for example, could triple their monthly wages, while workers from poorer countries like Cambodia or Ghana could earn nine times more purely by working in the United States. By contrast, there is no aid-funded project that would raise a workers income from £60 to £540 per month. Furthermore, migration, unlike aid, directly adds value to rich countries’ economies.\”

Protecting global environmental public goods

\”The fisheries sector of African countries was worth more than £10.6 billion in 2011, equivalent to over 6% of African agricultural GDP, and net fisheries exports from all developing countries reached £21.4 billion in 2012. However, two thirds of the North Atlantic fish stocks and 82% of Mediterranean stocks are overfished. Fisheries can be a renewable resource only if they are carefully managed. … Despite the catastrophic risks to fish stocks of overfishing, the EU continues to subsidise engine replacement for vessels larger than 24 meters while half of the EU’s distant-water fleet makes its own arrangement with third countries. Weak government capacity in developing countries increases the chance of fishing past sustainable yields.\”

More research and development and technology transfer

\”Tighter controls on intellectual property … are part of the reason that developing countries have not been able to close the gap on industrialised countries. Facilitating private investment is an important piece of this puzzle. Foreign firms that operate overseas increase the productivity of their suppliers and customers, train workers who can then migrate to other firms in the same sector with new skills, and demonstrate models that other firms can copy. Rich countries can also make the global pool of knowledge available to poor countries by targeted improvements in their intellectual property rights (IPR) regimes for developing countries.\”

Reducing the chance of war

\”Conflict and insecurity have appalling human costs. In addition they also have longer-run effects on economic growth by destroying productive capital and reducing the incentives for firms and households to invest. Collier (1999) estimates that countries in civil war experience a decline in growth of 2.2 percentage points, and other estimates are significantly higher. …  The UK requires an approved export permit for arms sales or exports of technologies, like cryptographic equipment, that have a dual civilian and military use. Despite this safeguard, a report by the Committees on Arms Export Controls (2013) found 3,375 arms export licenses worth nearly £12 billion to countries on the Foreign and Commonwealth Office’s (FCO) list of countries of human rights concern, including Iran, Russia, Sri, Lanka, Belarus and Zimbabwe. In the same period, the government rejected 148 applications (1% of approvals). …  Peacekeeping missions are a cost-effective contribution to promoting stability overseas.\”

Of course, people will differ on which options are likely to be have the biggest effects for the world\’s poor and which options are politically feasible in high-income countries. But if you think that alleviating global poverty is a worthwhile policy goal, some combination of the items on this list can have an effect that is a hefty multiple of what foreign aid is able to achieve.

In practical terms, Bitcoin is not all that important, at least not yet.  Sadat Karin and Nancy Condon offer some details in in \”Making Change: What Bitcoin Could Mean to the Payments Industry,\” in the May-August 2014 issue of EconSouth, published by the Federal Reserve Bank of Atlanta. They write: Any discussion of bitcoin must begin with the disclaimer that it really is a very small player in the payments system. … To put it in perspective, bitcoin averages about 60,000 transactions
a day, according to the consulting firm Deloitte. By comparison, Visa’s electronic payment processing network handles more than 150 million transactions a day from 2.1 billion credit cards and more than 2 million ATMs.\”

But Bitcoin has come to represent the possibility of an alternative way of thinking about money. In a conventional financial system, money is in bank accounts, and payments transfer money between accounts. To put it another way, the transaction relies on the fact that the bank can see what people have in their accounts. In a Bitcoin transaction, no third party can see what the buyer and seller have in their accounts; indeed, no third party can name the two parties that are making the transaction. People can buy and sell anonymously, without the interposition of a conventional currency or the control of a central bank. But through what magic of cryptography can such a system work? One of the best explanations I\’ve seen of how Bitcoin actually works in a nuts and bolts way is by Robleh Ali, John Barrdear, Roger Clews, and James Southgate, who have two articles in the Quarterly Bulletin of the Bank of England (2014, Q3) that offer a nice overview: \”Innovations in payment technologies and the emergence of digital currencies\” and \”The economics of digital currencies.\” Here\’s a step-by-step sense of how a Bitcoin transaction works, drawing from their essays.

Step 1: Two parties agree on a Bitcoin transaction. For simplicity, call the buyer Anne and the seller Bill.

Step 2: \”Anne creates a message with three basic elements: a reference to the previous transaction through which she acquired the bitcoins, the addresses to pay (including Bill’s) and the amount
to pay each one.\” The message can also include other conditions: for example, Anne may specify that she is willing to pay a small amount to the party that verifies the transaction–a step to be discussed further in a moment.

Step 3: \”Once the message has been created, Anne digitally signs it to prove that she controls the payer address.\” The concept of a \”digital signature\” gets deeper into theories of cryptography than I really understand. But at a basic level, Ann uses a \”private key\” to encode the transaction, and announces a \”public key\” that allows others to decode the transaction. But those who decode it cannot change the transaction, nor can they trace the transaction specifically to Anne. \”Bitcoin addresses are a version of the public key, which can be made widely available and published. Addresses and their
private keys are random strings of alphanumeric characters. An address is typically 34 characters long (for example 1FfmbHfnpaZjKFvyi1okTjJJusN455paPH), while a private key is typically 51 characters long. Each Bitcoin address is paired with a corresponding private key, which is kept secret by the owner of the address, and needed to sign transactions from — and, hence, prove ownership of — the address.\”

Step 4: \”Anne broadcasts the signed message to the network for verification.\” At this point, Anne has created an anonymous \”buy\” message, and the issue is  how to verify that the funds should indeed be transferred.

Stage 5: \”Miners gather Anne’s new transaction and combine it with others into new candidate ‘blocks’. They then compete to verify them in a way that other miners will accept.\” Let us postpone for a moment the notion of \”blocks\” and how the miners compete to verify the transactions, and just say that Claire is the miner who succeeds in verifying Anne\’s transaction. The transaction is then completed in one more step.

Stage 6: \”Clare is a miner and successful at verifying a block with Anne’s transaction in it, so she will receive both a reward of new bitcoins, as well as the transaction fee from Anne’s transaction. Clare broadcasts this result and other miners add the block to the end of their copies of the block chain and return to step 5. Bill receives the 1 bitcoin sent to him …\” Notice that Bill now has a Bitcoin in his account, which he could use to initiate a transaction of his own.

Clearly, the activities of these \”miners\” are at the center of how Bitcom works. The basic idea of Bitcoin is that if it is to function, \”all users agree on which transactions have actually happened and in which order.\” The block chain is the description of past transactions, built up one block of transactions at a time. But how can miners reach a consensus over what should be added to the block chain? Ali, Barrdear, Clews, and Southgate explain:

\”Establishing consensus is purposefully more difficult and requires each miner to demonstrate the investment of computing resources known as a ‘proof of work’. …  The proof of work scheme used by Bitcoin means that the time taken for a miner to successfully verify a block of transactions is random. But as new miners join the network, or existing miners invest in faster computers, the time taken for a successful verification can fall. In order to allow time for news of each success to pass across the entire network, the difficulty of the proof of work problem is periodically adjusted so that the average time between blocks remains broadly constant at ten minutes for Bitcoin, meaning that payments are not instantaneous.  …

The chain of blocks representing the greatest sum of work done is the accepted truth within the Bitcoin network (sometimes referred to as the ‘longest chain’). Whichever branch is received by the majority of the network will initially be selected. However the branch with the most computation resources should ultimately take the lead. This branch will be most likely to have a subsequent block built on top of it and is therefore more likely to eventually ‘win’ the race. Miners that were working off blocks in the ‘shorter’ branch (that is, the branch with less demonstrated work done) then have a significant incentive to switch to the longer branch, as any work they contribute to the shorter branch will never be accepted by the majority of the network. …

The rule that the chain with the greatest sum of work done wins is an important element in combating fraud in the Bitcoin network. Any attacker attempting to modify earlier blocks (so that bitcoins could be spent twice) would have to control enough computing power for them to both catch up with and then overtake the genuine block chain as the ‘longest’. … It therefore makes more sense for anyone capable of assembling the necessary computing power to contribute to the continuation of the system, rather than attacking it.

 This seems more-or-less clear, and the point that Bitcoin transactions are not instantaneous strikes me as especially interesting in our credit-card economy. But there are two big holes remaining in the explanation. What exactly is the work done by the miners? And how are the miners rewarded for doing it?

Here is how Ali, Barrdear, Clews, and Southgate describe the \”proof of work\” done by the miners:

The proof of work scheme used by Bitcoin makes use of a special algorithm called a ‘cryptographic hash function’, which takes any amount of information as an input and creates an output of a standard length (the ‘hash value’). The function is cryptographic because the hash value produced is different for any change in the input (even of a single character), and it is almost impossible to know in advance what hash value will be produced for a given input. For example, the hash function used by Bitcoin (called ‘SHA-256’) generates the following:

The Bitcoin protocol requires that miners combine three inputs and feed them into a SHA-256 hash function:

• A reference to the previous block.

• Details of their candidate block of transactions.

• A special number called a ‘nonce’.

If the hash value produced is below a certain threshold, the proof of work is complete. If it is not, the miner must try again with another value for the nonce. Because there is no way to tell what value of the nonce, when combined with the other two inputs, will produce a satisfactory hash value, miners are forced to simply cycle through nonce values in trial and error.

Outsiders can verify how much work it takes to get an acceptable hash value: that is, how many values of the nonce must be tried. Again, the one that took the most work is accepted as the basis for the block chain on which others will build.

Why do miners compete to do this calculation? They are rewarded by a combination of receiving a transaction payment specified by the original buyer, and also because the producer of the accepted block chain is directly paid by the issuance of new Bitcoins. \”The first blocks created 50 new bitcoins per block and the Bitcoin protocol calls for this reward to be halved every 210,000 blocks (roughly every four years). The current reward is 25 bitcoins per block, and this is likely to be reduced
to 12.5 bitcoins per block in 2017. The planned eventual total number of bitcoins is therefore 21 million, which will be mostly reached by 2040. There are currently a little over thirteen million bitcoins in circulation, distributed over perhaps one or two million users worldwide. … The Bitcoin protocol seeks to maintain a roughly constant time of ten minutes between each successfully verified block.\”

These incentives are powerful enough that the Bitcoin miners are continually updating the speed of their computers, to make it more likely that they will win more block chain competitions. Karin and Condon write: \”As the work to mine bitcoins has increased, so has the cost. No one seems
to have precisely pegged the cost of the electricity to run—and cool—the computers that solve the algorithms, but estimates run up to $15 million a day.\”

The discussions in these articles tackle many other issues. What are some pros and cons of anonymous money? What would happen if someone started a Bitcoin bank? Might some small country set up its own currency in a Bitcoin style, and seek to attract those who desire such a currency?  If law enforcement and governments wanted, could they find ways of tracking the flow of Bitcoins? What are the risks for fraud? What would competition between different Bitcoin-like currencies look like? If Bitcoin becomes more important, so will these kinds of questions.

But here\’s one final thought. The price of Bitcoins spiked in early 2013 and then even more in late 2013, and has since then fallen by about half. Watching this process casually, it seemed to me like evidence of grievous instability in this currency. Here\’s the pattern.

But it turns out that this is an interesting example where having the vertical axipresented as linear, rather than logarithmic, alters ones perceptions considerably. (A logarithmic graph rises in percentage terms. Thus, a continual percentage increase over time looks like a curved line on a linear graph, but like a straight line on a log graph.) Here\’s the price of Bitcoin on a log graph. It\’s still bumpy, but it now looks a lot more like a reasonably steady (if volatile) upward movement, not at crazy cycle of boom and bust.

Right now, people are experimenting with Bitcoin for a lot of reasons: pure novelty, anonymous transactions, getting some experience with this kind of transaction, and so on. But given that the ultimate supply of Bitcoins is fixed, their value will ultimately be determined by the demand for their use in transactions.

AOne child in five in the United States lives in a \”food insecure\” household. Craig Gundersen and James P. Ziliak lay out the evidence in \”Childhood Food Insecurity in the U.S.: Trends, Causes, and Policy Options,\”  a Fall 2014 Research Report written for The Future of Children. They begin (footnotes omitted):

In 2012, nearly 16 million U.S. children, or over one in five, lived in households that were food-insecure, which the U.S. Department of Agriculture defines as “a household-level economic and social condition of limited access to food.” Even when we control for the effects of other factors correlated with poverty, these children are more likely than others to face a host of health problems, including but not limited to anemia, lower nutrient intake, cognitive problems, higher levels of aggression and anxiety, poorer general health, poorer oral health, and a higher risk of being hospitalized, having asthma, having some birth defects, or experiencing behavioral problems.

The underlying data here comes from survey answers to the Current Population Survey, a nationally representative survey done each month by the U.S. Census Bureau. The survey includes a module about food and hunger in households.

Examples of questions include: “Did you or the other adults in your household ever cut the size of your meals or skip meals because there wasn’t enough money for food?”; “Did you ever cut the size of any of the children’s meals because there wasn’t enough money for food?”; and, the most severe item for households with children, “Did any of the children ever not eat for a whole day because there wasn’t enough money for food?” ….  Children are experiencing food insecurity if at least two of the eight child-centered questions are answered in the affirmative, and very low food security if five or more such questions are answered positively.

Unsurprisingly, families that are poor are more likely to experience food insecurity. But perhaps more surprisingly, the connection from poverty to food insecurity is by no means ironclad. After all, the U.S. spends over $100 billion on food-related programs for the poor, including food stamps, school lunches and breakfasts and others.  As the authors write:

 Clearly, the risk for child food insecurity drops quickly with income. But even at incomes two and three times the poverty level, food insecurity is quite high. Moreover, almost 60 percent of children in households close to the poverty line are in foodsecure
households. This suggests that income is only part of the story and that other factors also contribute to children’s food security.

As the authors dig into the data on children living in food-insecure households, the theme that keeps emerging is the quality of parenting the children receive. Here are snippets from the report, taken from a number of different studies.

[E]ven when income and other risk factors are accounted for, adult caregivers’ mental and physical health play a central role in children’s food security. … [M]others in food-secure poor households are in better physical and mental health and are less likely to report intimate-partner violence and substance use compared with mothers in food-insecure poor households. When the sample is restricted to those with incomes twice the poverty line and lower, food-insecure families are more likely to be headed by poorly educated single mothers and more likely to report maternal depression and substance abuse than are food-secure families with similar incomes. … [W]hen mothers are moderately to severely depressed, the risk of child and household food insecurity rises by 50 to 80 percent, … [D]rug use in the last 30 days—and heroin use in particular—is strongly associated with food insecurity among children. …

[A]fter controlling for economic and household characteristics, children living with a single parent or living with an unmarried parent in a more complex family (for example, one that includes a cohabiting partner or another adult such as a grandparent) have a greater risk of food insecurity than do children living in families where the parents are married. … [C]ompared with children cared for exclusively by their parents, low income preschoolers attending a child-care center had lower odds of both food insecurity in general and very low food security … [C]hildren of foreign-born mothers were three times as likely to experience very low food security as werechildren of U.S.-born mothers, even after controlling for other risk factors.  Children in households with an incarcerated parent constitute another vulnerable group. … 

The takeaway lesson, at least for me, is that food stamps and school lunches do help to reduce food insecurity, as do programs that provide income support to those with low incomes. But when the adults in a household are having trouble managing their own lives, children end up suffering. The answers here are straightforward to name, if not always easy to do, like finding ways to get food to children directly (perhaps by expanding school food programs to the summers and weekends) and to help parents in low-income households learn how to stretch their limited resources.  As I have argued before on this website, for many children, the parenting gap they experience may be limiting their development even from a very young age.