Year: 2016

The World Bank is apparently inaugurating what will be an annual report on the theme of \”Poverty and Shared Prosperity.\” The first report in the series, with the subtitle  \”Taking on Inequality,\” was released in early October. \”The report series will inform a global audience comprising development practitioners, policy makers, researchers, advocates, and citizens in general with the latest and most accurate estimates on trends in global poverty and shared prosperity.\” Here are some themes from the report that caught my ehe.

Global poverty, measured by the number of people living on $1.90 or less per day, has fallen dramatically in the last couple of decades. The blue line (right axis) shows the decline in the total number of the world\’s poor. The red line (left axis) shows the percentage of the world\’s population below the poverty line. The fall from 35% just 25 years ago in 1990 to about 10% at present is a dramatic improvement.

There are basically two ways that broad swaths of a population can be lifted out of poverty: broad economic growth and redistribution. It\’s worth remembering that the overwhelming majority of poverty reduction is due to economic growth–especially in China and India, but in other low-income countries around the world as well. About half of the world\’s poor live in countries of sub-Saharan Africa, while the nations of South Asia have another third of the world\’s poor, and not coincidentally, those are countries that have not experienced sustained economic growth.

However, as a result of economic growth, it has now become much more possible for even relatively low-income countries to undertake policies aimed at assisting the poor. A working paper by Chris Hoy and Andy Sumner at the Center for Global Development made this point in \”Gasoline, Guns, and Giveaways:Is there New Capacity forRedistribution to End Three Quarters of Global Poverty?\” (CDG Working Paper 433, August 2016). Hoy and Summer focus on countries with high levels of poverty, but that also subsidize fuel use and have higher military spending than their neighbors. They find that reallocating funds from fuel subsidies and military spending could address three-quarters of existing global poverty (in what follows, citations omitted):

We also consider the reallocation of two illustrative public “bads.” Specifically, regressive fossil-fuel subsidies which are an aspect of fiscal policy that is unequivocally pro-rich and what we have termed “surplus” military spending which we define as more guns than your neighbours meaning military spending above the regional lowest per capita spent. We appreciate that reducing military spending to this level may seem radical to some as no doubt would the reallocation of fossil fuel subsidies away from cheap petrol. However, our estimates of the impact of such changes in fiscal policy show what is at stake — the end of three quarters of global poverty — and our estimates are deliberately conservative for a number of reasons we outline. Our intention is not to annoy those who enjoy cheap petrol for example but to illustrate the resources now available nationally to governments and the implied opportunity costs in terms of poverty.

The report devoted a couple of chapters to policies for reducing poverty and inequality: \”[S]pecific interventions discussed are ECD [early childhood development], including breastfeeding; universal health care coverage; good-quality education; cash transfers, mostly conditional transfers; investments in rural infrastructure, specifically, rural roads and electrification; and income and consumption taxes. The selection means that other policy interventions with potential effects on inequality are not included in the assessment. This is not intended to deny the potential equalizing effects of these other interventions; the evidence of the equalizing effects is merely less compelling, is currently being collected, or a general consensus is absent on how to frame the policies to reduce inequality while reaching other objectives.\”

It\’s interesting to me that the highlighted policy choices mostly are about unconditional cash transfers, and little of the focus is on high marginal tax rates for those with high incomes. Instead, the policies here both offer near-term support to the poor and also can work as longer-term investments in productivity and economic growth.

The chapters of the report focused on inequality point out a theme that I\’ve mentioned before on this blog: inequality across the world as whole is falling, perhaps for the first time since the start of the industrial revolution in the early 19th century. But inequality within specific countries is rising. For example, economic growth in urban areas of China will tend to increase inequality within China, but reduce inequality from a global perspective. Thus, here\’s a picture of global inequality using the Gini coefficient. The break in the line occurs because there was a change how to compare the size of incomes across countries

I think greater inequality in high-income countries like the US is a legitimate cause for concern. But I worry less about greater inequality in low-income countries. Tumultuous economic growth tends to affect some areas more than others. The challenge is for governments in countries that have experienced strong but region-specific or industry-specific growth to make the investments in health, education, and infrastructure that can help the poor who have not benefited from that growth.

Douglas Clement has an \”Interview with David Autor\” in The Region, published by the Federal Reserve Bank of Minneapolis (September 7, 2016). The subheading give a sense of the scope of the conversation: \”MIT economist on tech, trade & job markets, how Chinese imports affect U.S. politics & family structure, and the Janus-faced gig economy.\” The interview is a lively and interesting read throughout, but here is a sampling of the comments that caught my eye.

On using Commuting Zones (CZs) to look at local employment effects of rising Chinese exports: 

\”The U.S. Department of Agriculture developed the CZ [commuting zone] concept. Basically, they are contiguous counties where most of the people live and work within the same county cluster and where the centroid of the county is commutable from the edges of the CZs. It was [David] Dorn who discovered them in his doctoral thesis work, in the sense that they were out there, but no one outside the Department of Agriculture had used them for economic research. Following Dorn’s lead, we started using them because we thought they had a lot of attractive properties—they’re a sort of “revealed preference” measure of local labor markets. They cover the entire mainland United States, and their boundaries can be drawn consistently over time (unlike metropolitan statistical areas, which are regularly redefined as populations shift). Now a lot of scholars are using them, which is great. …

The basic idea is simple: We see China’s share of U.S. manufacturing goods consumption rising rapidly in the 1990s and even more so in the 2000s. Is this due to changes in China’s competitive position—lower prices, higher quality—or is it due to shifts in U.S. consumer tastes or even due to declines in U.S. production capacity …
To make progress, we studied China’s exports to eight other high-income countries simultaneously in each of 392 goods categories (covering all of manufacturing). Our idea was that if Chinese exports to the United States are driven in part by falling costs and rising quality, then Chinese import penetration in other rich countries in precisely these same goods categories should rise in parallel. And this hypothesis is strongly confirmed by the data. The bivariate correlation between the rise in China’s market penetration at the product level in the United States and these eight other countries ranges from 0.55 to 0.96.

For our analysis of the impact of the China shock on U.S. labor markets, we use only the component of rising China—U.S. import penetration that is shared with these other countries—that is, we use the component that we can confidently attribute to China’s improved competitive position.

We take these predicted changes in import penetration into the United States by goods category, and then we project that down to these commuting zones, looking at the geographic structure of U.S. manufacturing employment. Manufacturing is always very geographically concentrated. When you’re talking about furniture, for example, you’re talking about Tennessee or the Carolinas; you’re not talking about 50 states making furniture. The same is true if you’re talking about toys or leather goods or textiles—they’re very localized.

So that was the strategy; we thought it was a good idea, and we didn’t have a strong prior about what we would find. We thought we would find contraction of import-competing manufacturing employment, and we did. That was not surprising, but what happens after that was an unknown.

We were quite startled by how slow and incomplete the adjustment process was and the fact that you didn’t see offsetting gains in employment in other sectors. You see people entering unemployment or exiting the labor force, and wages falling modestly, but much adjustment was on the employment margin, not the earnings margin.

That is another thing that differentiated what we were doing. Historically, trade economists have relied upon full employment models, where people may lose jobs but they don’t lose work per se because they are quickly reallocated across sectors. According to such models, you should expect markets to clear by wages falling. But, in fact, what tends to happen is that people lose employment, and wages don’t really change for those who stay in employment.

Similarly, if we were in full general equilibrium all the time, the commuting zone would be irrelevant as an outcome measure because markets would clear nationally. The local shock is geographically dissipated because there’s effectively a law of one price of skill. And if that law did not hold in the very short run, workers would move to areas with higher wages until wages were again equalized. But it turns out that not only are the trade shocks locally concentrated—due to the concentrated geography of manufacturing—they also primarily play out locally. Much of the pain of adjustment is borne at the point of impact. … At the level of commuting zones, looking at workers initially in the impacted industry, you just don’t see the kind of diffusion or reallocation that general equilibrium models suggest. It’s not that it doesn’t happen eventually, but it happens slowly and painfully.

How the polarization of Congress spread to polarization of the public

\”What’s really fascinating—something we were not aware of—is that while the polarization of Congress has been going on for 30 years, basically since Ronald Reagan took office, the polarization of the U.S. electorate is much more recent. It’s really just been in the last 10 years.

By “polarization,” I mean the clustering of beliefs along party lines. So, for example, it’s increasingly the case that your view on global warming is highly predictive of your view on Mexicans, is highly predictive of your view on how high or low taxes should be and whether people should have a right to open-carry weapons.

Those beliefs didn’t used to be as correlated. So people have more strongly held, more divergent views. They have much more negative views of the other party as well. There is rising disapproval of cross-party marriage: The idea that you would be upset if your kid married someone of the other party has risen. Pew has documented this phenomenon. This has coincided with the rise of the Tea Party, and it’s most pronounced after 2006.

We’re seeing this same phenomenon in the data that we’re using to look at the trade exposure. We don’t want to say that all political polarization is due to trade exposure; I’m sure it’s not. But the localized adverse economic impact of the China shock in the 2000s does appear to be a kind of unnoticed contributor. In fact, you can see the antecedents of the current divisive presidential race playing out in the House in the 2000s—and specifically, in the locations where manufacturing was most hard hit.

On the longer-term relationship between technology and jobs

\”It’s a very natural thing to think that if computers do more work, people do less work. But I think the answer is much more nuanced—and, of course, economists have recognized these nuances for centuries.

Computerization changes what type of work people do—that’s very clear; we see the occupational change going on. But the part that people miss is that displacement of a set of tasks or even entire job categories does not augur the end of work. In the last 200 years, technology has totally changed the work that we do. Most of the jobs we have didn’t really exist in any significant number 200 years ago. As a result, work is much better. It’s more interesting, it’s more productive, it’s safer and more rewarding.

My optimism on this topic comes in part from the fact that we’ve already gone through incredibly dramatic adjustments and have been largely made enormously better off for it. It’s not just because we’ve increased aggregate wealth, but more of us work in paid jobs now than 100 years ago. At the turn of the 20th century, most women worked in grueling unpaid employment in the household. Now the majority work in better jobs, for pay, in the formal labor market.

We’ve adjusted to the displacement of human labor by automation along at least three margins. One is that we’ve just created many new and interesting things to do. Think about software development or tourism or all kinds of travel and food and restaurants. We do all kinds of creative and interesting things we didn’t do before.

Two, more of us work, but we work fewer hours. People don’t work until the day they die. They work 40- and 50-hour weeks instead of 80-hour weeks. They work five days a week instead of seven. They take vacations. So they’ve spread the work in a way that’s constructive and leads to a better quality of life.

And the other thing, of course, is that as we get wealthier, our consumption demands rise, so we create a lot of work because we choose to consume rather than just taking it all in leisure. If a worker in 2015 wanted to have a 1915 level of income, he or she could work about 17 weeks a year. But most of us choose not to. We’d rather have a bigger house and a couple of cars and whatever else.

Full disclosure: Autor was the Editor of the Journal of Economic Perspectives from 2009-2014, and thus was my boss for six years.

The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel for 2016 has been awarded to Oliver Hart and Bengt Holmström \”for their contributions to contract theory.\” So what is contract theory, why does it matter, and what did Hart and Holmstrom do? The Nobel committee each year posts some background information about its choice, both a \”Popular Science Background: Contract Theory,\” and a more technical \”Scientific Background\” paper called \”Oliver Hart and Bengt Holmström: Contract Theory.\”

As the pedants among us never tire of pointing out, the so-called \”Nobel Prize in economics\” is not literally a \”Nobel prize.\” It was not established by the original bequest from Alfred Nobel, but instead was first given in 1969, with the prize money provided by a grant from Sweden\’s central bank as part of the 300th anniversary of the founding of the bank. Thus, the award is officially \”The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel.\” (Justin Fox gives a nice brief overview of the history here.) Although I am pedantic in many matters, this doesn\’t happen to be one of them, so I will continue following the conventional usage in calling it the \”Nobel prize in economics.\”

More interesting is that Friedrich Hayek the co-winner of the sixth Nobel prize in economics (with Gunnar Myrdal), spoke at the prize banquet in 1974 as to why the establishment of the prize was mistaken. Here\’s is Hayek\’s call to humility for economists from his speech at the Nobel banquet on December 10, 1974.

Your Majesty, Your Royal Highnesses, Ladies and Gentlemen,

Now that the Nobel Memorial Prize for economic science has been created, one can only be profoundly grateful for having been selected as one of its joint recipients, and the economists certainly have every reason for being grateful to the Swedish Riksbank for regarding their subject as worthy of this high honour.

Yet I must confess that if I had been consulted whether to establish a Nobel Prize in economics, I should have decidedly advised against it.

One reason was that I feared that such a prize, as I believe is true of the activities of some of the great scientific foundations, would tend to accentuate the swings of scientific fashion. This apprehension the selection committee has brilliantly refuted by awarding the prize to one whose views are as unfashionable as mine are.

I do not yet feel equally reassured concerning my second cause of apprehension. It is that the Nobel Prize confers on an individual an authority which in economics no man ought to possess.

This does not matter in the natural sciences. Here the influence exercised by an individual is chiefly an influence on his fellow experts; and they will soon cut him down to size if he exceeds his competence.

But the influence of the economist that mainly matters is an influence over laymen: politicians, journalists, civil servants and the public generally. There is no reason why a man who has made a distinctive contribution to economic science should be omnicompetent on all problems of society – as the press tends to treat him till in the end he may himself be persuaded to believe. One is even made to feel it a public duty to pronounce on problems to which one may not have devoted special attention.

I am not sure that it is desirable to strengthen the influence of a few individual economists by such a ceremonial and eye-catching recognition of achievements, perhaps of the distant past.

I am therefore almost inclined to suggest that you require from your laureates an oath of humility, a sort of hippocratic oath, never to exceed in public pronouncements the limits of their competence.

Or you ought at least, on confering the prize, remind the recipient of the sage counsel of one of the great men in our subject, Alfred Marshall, who wrote: \”Students of social science, must fear popular approval: Evil is with them when all men speak well of them\”.

Hayek is quoting from an comment from Marshall which appears in \”In Memoriam: Alfred Marshall,\” a speech given by A.C. Pigou  in 1924 and published as part of a Memorials of Alfred Marshall volume in 1925 (pp. 81-90). The fuller quotation attributed to Marshall (on p. 89) is:

The fundamental power granted by holding patent is to block others from making use of the invention, unless they pay you a licensing fee. Inevitably, this power looks pretty good when you are the patent-holder, and not so good when you are being sued for infringing on someone else\’s patent. Just to complicate matters, some companies that bring suit for patent infringement didn\’t actually do the inventing themselves, nor do these companies actually make a product. The neutral name for these firms are \”patent assertion entities.\” A less-neutral name, when some of these firms act in a way that seems to misuse patent law as a genteel method of extorting payments from other firms, is to call them \”patent trolls.\”

There is nothing illegal about buying patents, or enforcing patent rights by requiring a license fee. Indeed, it can be a useful service for a firm to collect a group of closely-related patents and then license all of those patents as a group, so that firms wishing to use those patents can negotiate with a single entity. Is it possible to divide up the \”patent assertion entities\” in some defensible way, to distinguish the trolls from the rest?

The Federal Trade Commission has the authority to collect confidential business information. \”[T]he FTC analyzed information from 22 Responding PAEs and over 2,500 of both their Affiliates and other related entities.\” The FTC describes it findings in an October 2016 study: Patent Assertion Entity Activity. The report runs well over 200 pages, including a review of existing research literature and the relevant court cases, together with past FTC thinking on this subject over the last decade or so. It you want to get up to speed on this topic, this report is the place to start.The FTC defines the subject of its study this way:

The term “patent assertion entity,” or PAE, as used by the Commission in this report and elsewhere, refers to a firm that primarily acquires patents and seeks to generate revenue by asserting them against accused infringers. As the term underscores, PAE business models focus on asserting patents that the firm has acquired from third parties, rather than obtained from the U.S. Patent and Trademark Office (USPTO) through prosecution. Patents are a PAE’s principal asset; a PAE does not manufacture, distribute, or sell products. Merely holding a patent, however, does not generate revenue for a PAE. Instead, the firm generates revenue by licensing that patent or, more rarely, by obtaining court-ordered damages in successful patent infringement litigation. Furthermore, a PAE generally initiates negotiations that may lead to a license by communicating a demand for payment to, or filing an infringement suit against, an accused infringer.

Basically, the FTC argues that the \”patent assertion entities\” can be divided fairly neatly into two \”two distinct PAE business models: Portfolio PAEs and Litigation PAEs.\” The FTC steers away from using the term \”patent trolls,\” which in this report mainly comes up in quotations from other articles buried in the footnotes. But \”litigation PAEs\” is the category that most people are thinking of when they refer to \”patent trolls.\” Here is how \”portfolio PAEs\” functioned:

\”Portfolio PAEs most closely resembled the licensing arms of manufacturing firms; they were highly capitalized and often raised money from investors that included both investment funds and manufacturing firms. Typically, these investors received a share of the Portfolio PAE’s future revenue and a license to the Portfolio PAE’s patents. …

\”Portfolio PAEs typically conducted business in the following manner. First, they acquired portfolios of patents. Portfolio PAEs frequently acquired patents from manufacturing firms by making large up-front payments to the owner. Some Portfolio PAEs acquired hundreds or thousands of patents in individual transactions, often purchasing these patents from manufacturing firms. Other Portfolio PAEs acquired smaller numbers of patents per transaction and aggregated them into larger portfolios. Regardless of acquisition model, Portfolio PAEs then organized acquired patents into one or more portfolios, each containing hundreds if not thousands of patents and offered these portfolios for licensing. …

\”Portfolio PAEs negotiated licenses covering large portfolios, often containing hundreds or thousands of patents, frequently without first suing the alleged infringer. The value of these licenses was typically in the millions of dollars. Although Portfolio PAEs accounted for only 9% of the reported licenses in the study, they generated 80% of the reported revenue, or approximately $3.2 billion.  …

In particular, notice that the investors in these \”portfolio PAEs\” are often companies, which the get access to the patents in the portfolio. Thus, these institutions can be viewed as ameliorating the \”patent thicket\” problem, where there are so many closely related and interlocking patents in some areas that it becomes difficult for innovators to function.

Litigation PAEs look different.

\”The Litigation PAE business model frequently employed one or more affiliate entities, usually set up as limited liability companies (LLCs), each created to acquire and assert a small portfolio of patents, without bundling or aggregating acquired patents into larger portfolios. … Regardless of whether they sent demand letters, Litigation PAEs almost always sued potential licensees in district court before beginning license negotiations.  … Litigation PAEs tended to be thinly capitalized. Many had between one and three individual owners, often with no other employees and no offices outside of their owners’ homes. In fact, several Litigation PAEs were simply individual entrepreneurs who relied entirely on outside attorneys and professionals to maintain records regarding their assertion activity. …

\”Litigation PAEs typically sued potential licensees and settled shortly afterward by entering into license agreements with defendants covering small portfolios, often containing fewer than ten patents.  The licenses typically yielded total royalties of less than $300,000.  … The American Intellectual Property Law Association (AIPLA), which periodically surveys the costs of patent litigation, recently reported that defending an NPE patent lawsuit through the end of discovery costs between $300,000 and $2.5 million, depending on the amount in controversy. By this estimate, 77% of Litigation PAEs’ settlements fell below a de facto benchmark for the nuisance cost of litigation. This suggests that discovery costs, and not the technological value of the patent, may set the benchmark for settlement value in Litigation PAE cases. … Given the relatively low dollar amounts of the licenses, the behavior of Litigation PAEs is consistent with nuisance litigation.

\”For each separate patent portfolio that they acquired, Litigation PAEs characteristically
created a new affiliate entity, which often held ten patents or less. They generally operated with little or no working capital and relied on agreements to share future revenue with patent sellers to fund their businesses. Litigation PAEs filed 96% of the cases in the study and accounted for 91% of the reported licenses, but only 20% of the reported revenue, or approximately $800 million.\”

The report also notes that this problem is really centered in the electronics and software industries. \”Of all the patents held by PAEs in the FTC’s study, 88% fell under the Computers & Communications or Other Electrical & Electronic technology categories, and more than 75% of the Study PAEs’ overall holdings were software-related patents.\”

The policy question of how to draw legal distinctions put the brakes on the patent trolls without unduly hindering legitimate protection of patent rights raises some tricky questions, but the report offers some general guidance:

The FTC recognizes that infringement litigation plays an important role in protecting patent rights, and that a robust judicial system promotes respect for the patent laws. Nuisance infringement litigation, however, can tax judicial resources and divert attention away from productive business behavior. With this balance in mind, the FTC proposes reforms to: 1) address discovery burden and cost asymmetries in PAE litigation; 2) provide the courts and defendants with more information about the plaintiffs that have filed infringement lawsuits; 3) streamline multiple cases brought against defendants on the same theories of infringement; and 4) provide sufficient notice of these infringement theories as courts continue to develop heightened pleading requirements for patent cases.

For a previous discussion of these issues, I recommend \”The New Patent Intermediaries: Platforms, Defensive Aggregators, and Super-Aggregators,\” by Andrei Hagiu and David B. Yoffie, which appeared in the Winter 2013 issue of the Journal of Economic Perspectives.

The venture capital industry is fairly well-known: they raise funds from investors, often pension funds or university endowments, to invest in start-up companies at an early stage, knowing that a most of those companies won\’t do very well, but hoping to make a good return when about one in ten of those companies hits it big. The National Venture Capital Association estimates that VC funds raised $28 billion in 2015, and have about $168 billion under management. This isn\’t a large amount in the context of an $18 trillion US economy, but the effects of VC firms in choosing and nurturing start-ups are much larger than the dollar value would suggest.

But behind or perhaps along-side of the VC firms are a more shadowy group known as \”angel investors.\” which may well be investing more money than their better-known VC cousins. Angel investors are not raising a fund from others; instead, they are investing their own money in small start-ups.  Not much is known about them. But Josh Lerner and Antoinette Schoar present some evidence in their report \”Rise of the Angel Investor: A Challenge to Public Policy,\” written for the Third Way think tank (September 23, 2016). They describe the subject this way:

Angel investors are high-net-worth individuals, often (but not exclusively) former entrepreneurs and corporate executives, who make private investments in start-up companies with their own money. While individual angel investors have a long history—for instance, Naomi Lamoreaux and co-authors highlight how Cleveland’s angel investors played a critical role in financing the early electricity and automotive industries—organized angel groups are a quite recent phenomenon. Beginning in the mid-1990s, angels began forming groups to collectively evaluate and invest in entrepreneurial ventures. …  

Angels typically invest at the seed funding stage, making them among the first equity investors in a company beyond its founders. … Angels invested a total of $24.6 billion in 2015 with an average deal size of $345,390, according to the Center for Venture Research. …  The Angel Capital Association (ACA) lists more than 300 U.S. groups in its database. The average ACA angel group in 2015 had 68 member angels and invested a total of nearly $2.5 million in 10.3 deals in 2007. At least between 10,000 and 15,000 angels are believed to belong to angel groups in the U.S. … 

The precise measurement of the total size of the angel investment market is difficult to ascertain due to the fact that most angel investments are made on an individual basis and thus typically are not subject to regulatory disclosure requirements. But estimates suggest that the total size of angel investment has long surpassed venture capital investment in the U.S. and increasingly in some other countries as well. For instance, survey estimates suggest the projected size of the total angel market in the U.S. grew from $17.6 billion in 2009 to $24.1 billion in 2014. The estimated capital
deployed by angel groups in Europe has almost doubled over the past five years, and in Canada, it almost tripled. Some estimates suggest that these investors are as important for high-potential start-up investments as venture capital firms. But despite their
rapid growth, we know very little about the role that angels play internationally and the type of firms in which they invest.

 As Lerner and Schoar describe them, angel investors are \”a growing form of start-up investing that is less formal than the VC market but more professional than receiving funding from friends and family.\”  Venture capitalists often have a few seats on a company\’s board of directors, but angel investors are more likely to be personal mentors to entrepreneurs who are starting a company and to play a fairly direct role in using their connections and experience to help the company grow. Their average investment in a company is fairly small, measured in  hundreds of thousands of dollars, not millions. Here\’s a description of the process for a typical angel group:

Angel groups follow mostly similar templates. Entrepreneurs typically begin the process by submitting to the group an application that may also include a copy of their business plan or executive summary. The firms, after an initial screening by the staff, are then invited to give a short presentation to a small group of members, followed by a question-and-answer session. Promising companies are then invited to present at a monthly meeting (often a breakfast or dinner). The presenting companies that generate the greatest interest then enter a due diligence review process by a smaller group of angel members, although the extent to which due diligence and screening leads or follows the formal presentation varies across groups. If all goes well, this process results in an investment one to three months after the presentation.

The authors describe some of their recent research on angel investors. For one study, they got detailed data on two groups of angel investors, so they could compare companies that just barely made the cut to receive funding with companies that just barely missed the cut–and thus firms whose prospects  looked quite similar–the firms that got funding were measurably (although not extremely) more successful over the next few years. For another study, they looked at \”the records of 13 angel investment groups based in 12 nations and with applicants for financing transactions from 21 nations,\” and again find that firms which just made the cut for funding do better over time. 

The health care costs that Americans pay out-of-pocket are rising–both in total amount, which is perhaps not a surprise, but also as a share of incomes, which is perhaps more disturbing. Ann Foster discusses the pattern in \”Household healthcare spending in 2014,\”  written as a \”Beyond the Numbers\” short essay for the US Bureau of Labor Statistics (August 2016, vol. 5, no. 13). She has lots of details of spending in particular areas, but here\’s an overall figure showing out-of-pocket spending by households as a total amount (left axis) and as share of total expenditures (right-hand axis).

Part of the reason for this rise is that more Americans have health care insurance with high deductibles: that is, the amount you pay out of pocket before the insurance kicks in. Here\’s some information from the most recent Kaiser Family Foundation 2016 Employer Health Benefits Survey.  The report notes:

\”[T]he share of covered workers in plans with a general annual deductible has increased significantly over time: from 55% in 2006, to 74% in 2011, to 83% in 2016, as have the average deductible amounts for covered workers in plans with deductibles: from $584 in 2006, to $991 in 2011, to $1,478 in 2016.\” 

Another simpler way to describe this information is just to look at what share of workers now have a deductible above a certain amount, like $1,000.  This share has been rising for firrms of all sizes, but especially for smaller firms.

I\’ll add that I\’m not automatically opposed to  higher out-of-pocket spending for certain kinds of health costs. One way of holding down the rise in  health care costs is for patients and health care providers to be more sensitive to the cost implications of their choices. Most kinds of insurance against certain costs or damages–auto insurance, homeowner\’s insurance, and so on–have some form of out-of-pocket cost sharing for this reason. In the big picture, being protected against the risk of health care costs in the tens of thousands of dollars, or more, is quite important, even if it means you aren\’t protected against annual health care costs in the range of a few hundred or even several thousand dollars.

But it\’s also wise to remember that the relatively modest rise in out-of-pocket health care costs above is a mixture of households with relatively little in such costs in most years, and other families that are consistently paying the full deductible–an amount which is rising fast–every year. High and rising deductibles will make a lot of people feel as if their health care doesn\’t offer them much benefit in a typical year.

US housing prices have recovered so that they are more-or-less back to the long-run trend that existed before the price bubble of the early 2000s. The total amount of equity that US households have in the form of housing has largely recovered too. Here, with the help of the FRED website run by the Federal Reserve Bank of St. Louis, is a quick overview of the recent roller coaster ride for US housing markets–which leads to the case for why state and local government should be tweaking their priorities to encourage more homebuilding.

Here\’s the bounceback in housing prices since about 2012. There are rises and falls over time, but the current value isn\’t too far from the trend over the last four decades.

The amount of equity that homeowners have in real estate peaked at about $13 trillion at the top of the housing bubble in 2006, then dropped by $7 trillion by 2009 (!), and since 2012 has rebounded back up to almost $13 trillion again.

Another perspective is to look at homeowners\’ equity in housing divided by GDP, which adjusts for changes in inflation and in the size of the real economy over time. With this adjutment, you can see that homeowner equity was mostly in the range of 50-70% of GDP for the second half the 20th century. The housing bubble pushed homeowner equity up to nearly 100% of GDP in 2006, and the bursting of the bubble dropped it to 40% 2009.

Yet another way to slice this data on homeowner\’s equity is to look at it relative to the total value of the real estate. For example, though the 1970s and into the early 1980s, it was common that about 70% of the total value of real estate was equity for homeowners–while the rest was presumably mortgage debt owed to lenders. But even with the rise in housing prices in the 1990s and early 2000s, the share of that value which was homeowner equity was falling, as homebuyers borrowed more aggressively. when the housing bubble burst and the value of homes dropped, the size of the accumulated borrowing remained. The share of housing value that was home equity dropped almost to 35%, which would have been half the level prevailing back in the 1970s and early 1980s. The share of real estate that is homeowner equity has now bounced back, but is still under 60%.

The movements in housign prices also affect home construction. Here\’s the pattern of new housing starts since the late 1950s. These figures are measured in units of housing starts–that is, not relative to the size of the US population, which was about 180 million back in 1960 compared with 320 million today. The data on housing starts is spiky, but the long run-up for the construction industry from about 1990-2005 is clear enough, as is the dramatic fall in construction after that to the lowest levels seen in this data. . There\’s been a bounceback, but in historical context (and given the larger US population and smaller family sizes), it seems rather modest.

The recent bounce-back in housing prices seems to me different from the rise during the bubble. During the housing bubble in the early 2000s, there was a large amount of building (as shown by housing starts), which was sitting vacant (as shown by the vacancy rate), and financed by borrowed money (as shown by the low level of homeowners\’ equity relative to real estate values at a time when prices were rising). The recent bounce-back in housing prices is happening at a time when construction levels remain relatively low, vacancy rates are at historically common levels, the total value of housing relative to GDP is at historically common levels.

Thus, my sense is that the bounce-back in housing prices isn\’t about a borrowing-driven boom in demand, but is more about limitations on housing supply. Those limitations are not typically a matter of federal policy, but are imposed by state and local governments, and by neighborhood activists and courts, whose efforts have the effect of discouraging construction and keeping housing prices higher than they would otherwise be. Jason Furman, the head of President Obama\’s Council of Economic Advisers since 2013, has forthrightly made this point. Last November, for example, he gave a talk called \”Barriers to Shared Growth: The Case of Land Use Regulation and Economic RentsRemarks,\” where he said: \”I will focus on how excessive or unnecessary land use or zoning regulations have consequences that go beyond the housing market to impede mobility and thus contribute to rising inequality and declining productivity growth.\”

Similarly, the 2016 Economic Report of the President, published last January by the CEA, had this to say (pp. 87-89):

\”Supply constraints provide a structural challenge in the housing market, particularly in high-mobility, economically vibrant cities. When housing supply is constrained, it has less room to expand when demand increases, leading to higher prices and lower affordability. Limits on new construction can, in turn, impede growth in local labor markets and restrain aggregate output growth. Some constraints on the supply of housing come from geography, while others are man-made. Constraints due to land-use regulations, such as minimum lot size requirements, height restrictions, and ordinances prohibiting multifamily housing, fall into the man-made category and thus could be amended to support more inclusive growth. While these regulations can sometimes serve legitimate purposes such as the protection of human health and safety and the prevention of environmental degradation, land-use regulations can also be used to protect vested interests in housing markets. …

\”In addition to housing affordability, these regulations have a range of impacts on the economy, more broadly. Reduced housing affordability—whether as an ancillary result of regulation or by design—prevents individuals from moving to high productivity areas. …  Ensuring that zoning and other constraints do not prevent housing supply from growing in high productivity areas will be an important objective of Federal as well as State and local policymakers.\”

Policymakers and economists have been saying for 10-15 years that China\’s economy needs to shift away from being driven by extraordinarily high levels of investment, together with growing exports, and instead shift to being driven by growth of China\’s own domestic consumption. Maybe it\’s actually starting to happen. Jun Nie and Andrew Palmer discuss some recent evidence in \”Consumer Spending in China: The Past and the Future,\” published in the Economic Review of the Federal Reserve Bank of Kansas City (Third Quarter 2016, pp. 25-49). They begin this way:

\”After steadily declining for nearly half a century, the share of consumer spending in China’s GDP has recently increased. Economists and policymakers widely agree that the share of consumer spending must increase for China to continue its economic development; sustaining growth primarily on exports and investment will become more difficult in the longer run. … Although the recent rise in the consumption share has allayed some concerns about slowing growth in China, it has also spurred discussion over whether this trend is sustainable and whether China will truly become a consumption-driven economy.\”

To put China\’s low consumption patterns in perspective, it\’s useful to remember that in the US, about 65% of GDP is usually accounted for by consumption. In China, consumption was only about half of GDP in 1970s and 1980s–and then the share dropped even lower, falling below 40% of GDP. What\’s happening here is that China\’s consumption was growing, but GDP was growing even faster, so the ratio of consumption/GDP was falling, right up until about 2010.

Nie and Palmer discuss the evidence from economic research on what caused China\’s consumption to fall so low, and whether the modest rise of the last few years seems likely to continue. They focus on a few factors that have been evolving over the decades: the age distribution and \”dependency ratios\” in China\’s population, the trend to urbanization, and China\’s housing boom since around 2000–which is about when the consumption/GDP ratio plummeted even lower. I\’d summarize their story this way.

The \”dependency ratio\” refers to what share of the population is either too young or too old to work, as opposed to being working age. The dependency ratio and consumption tend to rise and fall together. Thus, the dramatic fall in birthrates in China as a result of economic growth (and greater education and incomes for women) along with the one-child policy meant a lower dependency ratio. Basically, fewer children means less consumption spending on children, and more saving.

China has seen a dramatic rise in urbanization. As Nie and Palmer write: \”Over the past five decades, the share of China’s population living in urban areas has more than tripled, rising from 18 percent in 1960 to 56 percent in 2015.\” The common pattern is that people moving to urban areas in emergin economies increase both their production and their consumption, but they increase production by more, and so their rate of saving rises.

Nie and Palmer look at patterns of dependency ratios and urbanization across a \”sample of 24
countries including most Asian countries and large developing countries.\” Based on the common patterns, they find that China\’s fall in consumption/GDP ratio from 1970-2000 is almost completely explained by changes in its dependency ratio and urbanization. But the additional drop in consumption/GDP after 2000 is not explained by these patterns, and they instead attribute this fall to a shift in China\’s housing market. Here\’s their explanation (citations and references to charts omitted):

\”The large jump in the household saving rate from 2000 to 2010 is largely related to development in China’s housing market during this period. Before 1998, most Chinese families lived in government-provided houses; after economic reforms in 1998 removed this benefit, however, most Chinese families needed to buy their own homes. This change triggered rapid growth in the Chinese real estate sector, causing home prices to rise tremendously. Furthermore, as house prices started to increase quickly, housing became a popular investment for wealthy Chinese households, raising demand even further and exacerbating house price increases. Indeed, from 2000 to 2010, house prices
in China increased by about 161 percent. In addition to rapidly increasing prices, Chinese homebuyers faced large required down payments—typically 30–40 percent, but in some major cities as high as 50 percent. As a result, middle-class Chinese households were forced to save a disproportionately large share of their earnings to purchase a home. The saving didn’t end with the purchase of a home—the subsequent mortgage payments constituted additional saving as they increased the homeowners’ housing equity. As Rosenzweig and Zhang argue, this housing market dynamic helps explain the rising saving rate associated with rising housing prices from 1998 to 2010.

\”As the scramble to buy homes after the 1998 reform faded, so, too, did the desire to save for homes. Moreover, young people currently do not need to save as aggressively as the previous generation for home purchases because their parents and grandparents often help them buy a home. Due to the one-child policy, which was introduced in 1979, a typical young couple in China are the sole descendants of four parents and eight grandparents. In China, it is common for parents and grandparents to help their children by paying the high down payment or even paying for the entire house. Small family sizes under the one-child policy allow families to focus their resources rather than spreading them among multiple children or extended family members.

\”Large financial contributions from older generations are feasible for two additional reasons. First, after aggressively saving for several decades, many parents and grandparents are wealthy enough to afford this gift to the younger generation. Second, many households own multiple homes. Based on the 2014 China Household Finance Survey, one out of five urban households owns a second home, meaning that on average, a young couple’s parents and grandparents have one extra home between them in addition to their primary residences. Overall, less pressure for young Chinese couples to save helps explain why the Chinese saving rate has started to decline since 2010.\”

What do these factors imply for the future? China\’s old-age population is beginning to rise, and in October 2015 China\’s government announced that it was shifting to a \”two-child policy.\” China\’s dependency ratio seems set to rise, which should cause consumption to continue rising. Urbanization in China also seems likely to continue, which has tended to hold down consumption in China. The original huge boost in saving from the shift to private housing market has largely run its course (although whether the ongoing boom in China\’s housing prices is sustainable is different issue). Mixing this together and stirring a few times, Nie and Palmer suggest that China\’s consumption/GDP ratio will keep rising in the next few years, perhaps to between 45-50% by 2020–that is, to say, almost back to levels prevailing in the 1980s.

When economists and policymakers talk about \”rebalancing\” China\’s economy toward faster growth of domestic consumption, I think they have a bigger shift in mind. Nie and Palmer describe the changes in China\’s household spending this way:

\”[R]eal [household] spending on transportation and communication increased sevenfold over the last two decades compared with a threefold increase in overall household spending. Transportation and communication is a broad category that encompasses many high-end goods and services that have recently become available to middle-class Chinese households, such as smartphones, laptops, and air travel. Travel services in particular appear to be growing quickly: the number of Chinese outbound travelers has been growing at a double-digit pace for many years, and 2015 marked the fourth consecutive year of China as the world’s top tourism source market … [A]nother component of consumption, educational services, is also growing rapidly. Chinese families now are spending more resources on their child’s education both inside and outside the classroom. In addition to paying tuition both domestically and at foreign colleges and universities, Chinese families are increasingly paying for tutoring and other educational supplements for their children.\”

If China\’s government wishes to boost consumption, it could do more to encourage spending in areas like education and health care, as well as to support consumption and health services for its growing population of elderly.

In the long-ago days of the 20th century, it was difficult to find out about small or medium companies that were far away: hard to discover they existed, hard to get details about their products and pricing, hard to place an order, and especially if the firm was in another country, hard to pay for an order and track shipping. That\’s all becoming easier, which suggests that small and medium enterprises may be able to draw on wider markets, and not be so focused on local markets. Thus, the World Trade Organization in its World Trade Report 2016 focuses on the theme of \”Leveling the Playing Field for SMEs\”–that is, \”small and medium enterprises.\”

Much of the report focuses on practical issues affecting small and medium enterprises: connectedness, international trade rules, finance and others. Here, I\’ll just point to two patterns that I found intriguing. Here\’s a figure showing the share of exports and imports attributable to small and medium enterprises, which are defined as as employing 10-250 people (the blue bars), and also micro-enterprises (the gray dots), which are defined as employing 0-9 people.

Unsurprisingly, the developed economies where small and medium enterprises have the largest share of their trade tend to be smaller European economies, like Estonia, Cyprus, and Ireland. It\’s interesting that Italy, which is the fourth-largest economy in Europe, gets more than half its exports from micro, small and medium enterprises. It does jump out at me that the US economy is by far the lowest for small and medium enterprises as a share of its trade. Traditionally, small and medium US firms focused on the enormous US market.

The pattern is different if you look at not the share of exports from small and medium firms, but instead at the share of exporting firms that are small and medium firms. In the US, for example, the micro, small, and medium firms make up about 26-28% of the value of trade. But of the total number of US firms involved in international trade, micro, small, and medium firms make up more than 90%. Here\’s the figure:

It will be interesting to see how these patterns evolve over time. It seems as if the division of production across national borders into global value chains and the ability to export and import services, not just goods, should mean a larger role for small and medium enterprises in global trade. Or course, it will cause some of them to shift categories and turn into larger companies, as well.