(As regular readers know, my paying job–as opposed to my blogging hobby–the Managing Editor of the JEP. The American Economic Association has made all articles in JEP freely available, from the most recent issue back to the first. For example, you can check out the Fall 2017 issue here.)
Here\’s Sampson\’s basic description of the UK and its position in the international economy before Brexit. For me, it\’s one of those descriptions that doesn\’t use any weighted rhetoric, but nonetheless packs a punch.
\”The United Kingdom is a small open economy with a comparative advantage in services that relies heavily on trade with the European Union. In 2015, the UK’s trade openness, measured by the sum of its exports and imports relative to GDP, was 0.57, compared to 0.28 for the United States and 0.86 for Germany (World Bank 2017). The EU accounted for 44 percent of UK exports and 53 percent of its imports. Total UK–EU trade was 3.2 times larger than the UK’s trade with the United States, its second-largest trade partner. UK–EU trade is substantially more important to the United Kingdom than to the EU. Exports to the EU account for 12 percent of UK GDP, whereas imports from the EU account for only 3 percent of EU GDP. Services make up 40 percent of the UK’s exports to the EU, with “Financial services” and “Other business services,” which includes management consulting and legal services, together comprising half the total. Brexit will lead to a reduction in economic integration between the United Kingdom and its main trading partner.\”
A substantial reduction in trade will cause problems for the UK economy. Of course, the estimates will vary according to just what model is used, and Sampson runs through the main possibilities. He summarizes in this way:
\”The main conclusion of this literature is that Brexit will make the United Kingdom poorer than it would otherwise have been because it will lead to new barriers to trade and migration between the UK and the European Union. There is considerable uncertainty over how large the costs of Brexit will be, with plausible estimates ranging between 1 and 10 percent of UK per capita income. The costs will be lower if Britain stays in the European Single Market following Brexit. Empirical estimates that incorporate the effects of trade barriers on foreign direct investment and productivity find costs 2–3 times larger than estimates obtained from quantitative trade models that hold technologies fixed.\”
What will come next after Brexit isn\’t yet clear, and may well take years to negotiate. In the meantime, the main shift seems to be that the foreign exchange rate for the pound has fallen, while inflation has risen, which means that real inflation-adjusted wages have declined. This national wage cut has helped keep Britain\’s industries competitive on world markets, but it\’s obviously not a desirable long-run solution.
But in the longer run, as the UK struggles to decide what actually comes next after Brexit, Sampson makes a distinction worth considering: Is the opposition to Brexit about national identity and taking back control, even if it makes the country poorer, or is it about renegotiating trade agreements and other legislation to do more to address the economic stresses created by globalization and technology? He writes:
\”Support for Brexit came from a coalition of less-educated, older, less economically successful and more socially conservative voters who oppose immigration and feel left behind by modern life. Leaving the EU is not in the economic interest of most of these left-behind voters. However, there is currently insufficient evidence to determine whether the leave vote was primarily driven by national identity and the desire to “take back control” from the EU, or by voters scapegoating the EU for their economic and social struggles. The former implies a fundamental opposition to deep economic and political integration, even if such opposition brings economic costs, while the later suggests Brexit and other protectionist movements could be addressed by tackling the underlying reasons for voters’ discontent.\”
For me, one of the political economy lessons of Brexit is that relatively easy to get a majority against a specific unpopular element of the status quo, while leaving open the question of what happens next. It\’s a lot harder to get a majority in favor of a specific change. That problem gets even harder when it comes to international agreements, because while it\’s easy for UK politicians to make pronouncements on what agreements the UK would prefer, trade negotiators in the EU, the US, and the rest of the world have a say, too. Sampson discusses the main post-Brexit options, and I\’ve blogged about them in \”Brexit: Getting Concrete About Next Steps\” (August 2, 2016). While the process staggers along, this \”small open economy with a comparative advantage in services that relies heavily on trade with the European Union\” is adrift in uncertainty.
For me, one surprising insight from the report is that real wage growth–that is, wage growth adjusted for inflation–has actually not been particularly slow during the most recent upswing. The upper panel of this figure shows real wage growth since the early 1980s. The horizontal lines show the growth of wages after each recession. The real wage growth in the last few years is actually higher. The bottom panel shows nominal wage growth, with inflation included. By that measure, wage growth in recent years is lower than after the last few recessions. Thus, I suspect that one reason behind the perception of slow wage growth is that many people are focused on nominal rather than on real wages.
Government statistics offer a lot of ways of measuring wage growth. The graphs above are wage growth for \”real average hourly earnings for production and nonsupervisory workers,\” which is about 100 million of the 150 million workers.
An alternative and broader approach looks what is called the Employment Cost Index, which is based on a National Compensation Survey of employers. To adjust for inflation, I use the measure of inflation called the Personal Consumption Expenditures price index, which is the inflation just for the personal consumption part of the economy that is presumably most relevant to workers. I also use the version of this index that strips out jumps in energy and food prices. This is the measure of the inflation rate that the Federal Reserve actually focuses on.
Economists using these measures were pointing out a couple of years ago that real wages seemed to be on the rise. The blue line shows the annual change in wages and salaries for all civilian workers, using the ECI, while the redline shows the PCE measure of inflation. The gap between the two is the real gain in wages, which you can see started to emerge in 2015.
Not only has the recovery in US real wages been a bit higher than usual for the last few decades, and especially prominent in the last couple of years, but there is good reason to believe that the wage statistics since the Great Recession may be picking up a change in the composition of the workforce that tends to make wage growth look slower. Shambaugh, Nunn, Liu, and Nantz explain (citations and footnotes omitted):
\”In normal times, entrants to full-time employment have lower wages than those exiting, which tends to depress measured wage growth. During the Great Recession this effect diminished substantially when an unusual number of low-wage workers exited full-time employment and few were entering. After the Great Recession ended, the recovering economy began to pull workers back into full-time employment from part-time employment … and nonemployment, while higher-paid, older workers left the labor force. Wage growth in the middle and later parts of the recovery fell short of the growth experienced by continuously employed workers, reflecting both the retirements of relatively high-wage workers and the reentry of workers with relatively low wages. In 2017 the effect of this shifting composition of employment remains large, at more than 1.5 percentage points. If and when growth in full-time employment slows, we can expect this effect to diminish somewhat, providing a boost to measured wage growth.\”
The baby boomer generation is hitting retirement and leaving the labor force, as relatively highly-paid workers at the end of their careers. New workers entering the labor force, together with low-skilled workers being drawn back into the labor force, tend to have lower wages and salaries. This makes wage growth look low–but what\’s happening is in part a shift in types of workers.
One other fact from Shambaugh, Nunn, Liu, and Nantz is that wage growth has been strong at the bottom and the top of the wage distribution, but slower in the middle. This figure splits the wage distribution into five quintiles, and shows the wage growth for production and nonsupervisory workers in each.
Taking these factors together, the \”mystery\” of why wages haven\’t recovered more strongly since the end of the Great Recession appears to be resolved. However, a bigger mystery remains. Why have wages and salaries for production and nonsupervisory workers done so poorly not in the last few years, but over the last few decades?
There\’s a long list of potential reasons: slow productivity growth, rising inequality, dislocations from globalization and new technology, a slowdown in the rate of start-up firms, weakness of unions and collective bargaining, less geographic mobility by workers, and others. These factors have been discussed here before, and will be again, but not today. Shambaugh, Nunn, Liu, and Nantz provide some background figures and discussion of these longer-term factors, too.
The dramatic global convergence between rich and poor
\”There has been more convergence between poor people in poor countries and rich people in rich countries over the last generation than in any generation in human history. The dramatic way to say it is that between the time of Pericles and London in 1800, standards of living rose about 75 percent in 2,300 years. They called it the Industrial Revolution because for the first time in human history, standards of living were visibly and 2 meaningfully different at the end of a human lifespan than they had been at the beginning of a human lifespan, perhaps 50 percent higher during the Industrial Revolution. Fifty percent is the growth that has been achieved in a variety of six-year periods in China over the last generation and in many other countries, as well. And so if you look at material standards of living, we have seen more progress for more people and more catching up than ever before. That is not simply about things that are material and things that are reflected in GDP. … [I]f current trends continue, with significant effort from the global community, it is reasonable to hope that in 2035 the global child mortality rate will be lower than the US child mortality rate was when my children were born in 1990. That is a staggering human achievement. It is already the case that in large parts of China, life expectancy is greater than it is in large parts of the United States.\”
The marginal benefit of development aid is what is enabled, not what is funded
\”I remember as a young economist who was going to be the chief economist of the World Bank sitting and talking with Stan Fischer, who was my predecessor as the chief economist of the World Bank. And we were talking, and I was new to all this. I had never done anything in the official sector. And I said, \”Stan, I don\’t get it. If a country has five infrastructure projects and the World Bank can fund two of them, and the World Bank is going to cost-benefit analyze and the World Bank is going to do all its stuff, I would assume what the country does is show the World Bank its two best infrastructure projects, because that will be easiest, and if it gets money from the World Bank, then it does one more project, but what the World Bank is actually buying is not the project it is being shown, it is the marginal product that it is enabling. And so why do we make such a fuss of evaluating the particular quality of our projects?\” And Stan listened to me. And he looked at me. He\’s a very wise man. And he said, \”Larry, you know, it is really interesting. When I first got to the bank, I always asked questions like that.\” \”But now I\’ve been here for two years, and I don\’t ask questions like that. I just kind of think about the projects, because it is kind of too hard and too painful to ask questions like that.\”
Funds from the developing world governments and multilateral institutions have much less power
\”[O]ur money—and I mean by that our assistance and the assistance of the multilateral institutions in which we have great leverage—is much less significant than it once was. Perhaps the best way to convey that is with a story. In 1991, when I was new to all of this, I was working as the chief economist of the World Bank, and the first really important situation in which I had any visibility at all was the Indian financial crisis that took place in the summer of 1991. And at that point, India was near the brink. It was so near the brink that, at least as I recall the story, $1 billion of gold was with great secrecy put on a ship by the Indians to be transported to London, where it could be collateral for an emergency loan that would permit the Indian government to meet its payroll at the end of the month. And at that moment, the World Bank was in a position over the next year to lend India $3 billion in conjunction with its economic reform program. And the United States had an important role in shaping the World Bank\’s strategy. Well, that $3 billion was hugely important to the destiny of a sixth of humanity. Today, the World Bank would have the capacity to lend India in a year $6 billion or $7 billion. But India has $380 billion—$380 billion—in reserves dominantly invested in Treasury bills earning 1 percent. And India itself has a foreign aid budget of $5 billion or $6 billion. And so the relevance of the kind of flows that we are in a position to provide officially to major countries is simply not what it once was.\”
Protecting the world from pandemic flu vs. the salary of a college football coach
\”[T]he current WHO budget for pandemic flu is less than the salary of the University of Michigan\’s football coach—not to mention any number of people who work in hedge funds. And that seems manifestly inappropriate. And we do not yet have any settled consensus on how we are going to deal with global public goods and how that is going to be funded.\”
Many years ago I heard a story from a member of a committee of a midwestern university that was thinking about hiring a certain economist. The economist had an alternative offer from a southern California university that paid a couple of thousand dollars more in annual salary. The economist offered to come to the midwestern university if it would match this slightly higher salary . But the hiring committee declined to match . As the story was told to me, the hiring committee talked it over and felt: \”Spending a couple of thousand dollars more isn\’t actually the issue. The key fact cost of living is vastly higher in southern California. An economist who isn\’t able to recognize that fact–and thus who doesn\’t recognize that the lower salary actually buys a higher standard of living here in the midwest–isn\’t someone we want for our department.\”
Here are the US states color-coded according to per capita GDP. For example, you can see that California and New York are in the highest category. My suspicion is that states like Wyoming, Alaska, and North Dakota are in the top category because of their energy production.
And now here are the US states color-coded according to per capita GDP with an adjustment for Regional Price Parities: that is, it\’s a measure of income adjusted for what it actually costs to buy housing and other goods. With that change, California, New York, and Maryland are no longer in the top category. Hoever, a number of midwestern states like Kansas, Nebraska, South Dakota, and my own Minnesota move into the top category. A number of states in the mountain west and south that were in the lowest-income category when just looking at per capita GDP move up a category or two when the Regional Price Parities are taken into account.
When thinking about political and economic differences across states, these differences in income levels, housing prices, and other costs-of-living are something to take into account.
If you think if Medicare and Medicaid as examples of \”single payer\” health insurance plan, you are at best partially correct. Government health spending (including federal, state, and local) does accounts for about 46% of total US health care spending. However, a major and largely unremarked change is that government health care spending is being filtered through a system in which those receiving the government health insurance need to make choices between privately-run health insurance plans.
\”Currently, almost one-third of Medicare enrollees are in privately provided insurance plans for all of their medical spending, and another 43 percent of Medicare enrollees have standalone private drug plans through the Medicare Part D program. More than three-quarters of Medicaid enrollees are in private health insurance plans. Those receiving the subsidies made available under the Patient Protection and Affordable Care Act of 2010 do so through privately provided insurance plans that are reimbursed by the government.\”
Or here\’s a figure from Geruso and Layton. When you take into account the people choosing between Medicaid managed care plans, Medicare \”Advantage\” plans (as part of Medicare Part C), Medicare prescription drug benefits (as part of Medicare Part D), and people choosing between health insurance plans in the insurance \”marketplaces\” set up by the Patient Protection and Affordable Care Act of 2010, you have a total of nearly 100 million enrollees. Of course, if you\’re looking at choice in health insurance more broadly, many individual also have some choices in the the health insurance plans supported by their employers, too.
In all insurance markets, not just health insurance, choice can be a double-edged sword. On one side, choice lets people match up the characteristics of different health insurance care plans to their personal preferences and needs, which clearly can be positive. But health insurance providers here have mixed incentives: in this choice-based health insurance universe, they want to encourage people to choose their plans, but they also are trying not to attract disproportionate numbers people who are more likely to have high health care costs in the future. Health insurance plans have a very wide array of characteristics: not just the structure of deductibles, copayments, and annual caps, but also including limits on the breadth of a provider network and how costly (in terms of out-of-pocket costs) or difficult (in terms of paperwork and delay) it can be to go outside that network. Another limit can be on what types of care are covered in extreme health situations. With these difficulties in mind, a number of conventional problems arise.
Health insurance market will have a tendency to sort people into groups, where those who regard themselves as healthy at present will seek out health insurance that covers less and has a lower cost, while those who know that they are likely to have higher health-care costs will tend to seek out insurance that covers more but has a higher cost. As this dynamic emerges, so to a number of problems:
Insurance companies will have an incentive to structure their insurance plans with the idea of attracting the more-healthy consumers, while encouraging less health consumers to shop elsewhere, which is sometimes known as \”cream-skimming.\” Health insurance plans that would tend to be more attractive for the less healthy will tend to be packed full of out-of-pocket costs and restrictions on the network of service providers. At an extreme, health insurance plans suitable for those with high costs may become so costly or limited as to be essentially unavailable, which of course defeats the purpose of insurance altogether, which is sometimes known as \”death spiral\” for that market. Some of the people who signed up for lower-cost plans, either because they expected to be healthy or just because they focused on the low costs, will instead turn out to be unhealthy–and discover that their low-cost plan provided only limited coverage.
Of course, these are exactly the issues that have been playing out in the state-level insurance \”marketplaces\” set up under the Affordable Care Act. Economic analysis points out that these kinds of issues are endemic to choice-based insurance markets. These problems lead to a parade of policy interventions in health insurance markets, laid out by Geruso and Layton.
There are often rules for \”premium rating,\” which limits the price differences between insurance plans for different groups, or rules that insurance companies cannot reject an applicant outright, but must offer some kind of plan. These rules seek to avoid the problem that a consumer who is likely to have health care costs can\’t find an insurance policy at all, but given the many ways in which health insurance can be structured, the available policies can still look rather scanty.
The government can impose penalties for not purchasing health insurance, or subsidies for buying it. In practice, the state-level health insurance marketplaces do both of these.
\”Risk adjustment\” refers to the situation which a statistical formula is used to predict who is likely to have higher or lower health insurance costs–so that the government pays that amount to the insurance company. For example, in the Medicare Advantage program, where Medicare recipients can choose among private insurance plans rather than the government single-payer approach, the government needs to avoid a situation where the private health insurance firms just attract the healthier participants, and so it uses a risk adjustment formula. The evidence is that this risk adjustment is imperfect, in the sense that the higher payments for those expected-to-be-sick don\’t quite account for the higher costs, but it\’s better than not having it at all. Medicaid and the state-level insurance marketplaces have risk adjustment procedures, too.
Yet another policy is \”contract regulation,\” to require that insurance firms offer certain benefits. Of course, the question of what coverage is required, and the extent to which firms can require additional payments or limit the providers for certain kinds of coverage, remain controversial.
The bottom line here is that choice in health insurance markets unleashes both good and distressing dynamics. The good dynamic is people who can select the plan that they think best suits their immediate needs, and to some extent it focuses insurance companies on providing what people actually want. The distressing dynamic is that as people do this, the health insurance market for those who need more extensive health insurance will stagger for all the reasons given above. The available public policies that seek to address this issue–premium rating, penalties/subsidies to encourage buying insurance, risk adjustment, and contract regulations–all have understandable underlying purposes. But they add a great deal of complexity to an already messy market, and only partially address the underlying problems.
The ongoing US shift in how public health insurance is increasingly provided through private health insurance firms should influence the discussion over a \”single payer\” approach to health care.
Traditionally, the term \”single payer\” has referred to direct government payments to health care providers. In this sense, a true advocate of \”single payer\” in the traditional meaning cannot advocate \”Medicare for all,\” at least not as Medicare is currently constructed, because a large part of Medicare (both the choice section in Part C and the pharmaceutical benefits Part D) is no longer a single-payer system in the traditional meaning of the term. Similarly, an expansion of Medicaid is largely an expansion of government paying health care providers directly. A supporter of \”single payer\” should presumably oppose both the state-level insurance \”marketplaces,\” as well as the provision of private-sector health insurance.
Conversely, those who oppose \”single payer\” should contemplate whether their concerns about government control over health care are at ameliorated to some extent if the beneficiaries of those programs have a degree of choice across health insurance firms and health providers–albeit in regulated markets.
Here are volumes of mail-sent-per-adult for three categories that make up over 90 percent of the volume of what is delivered by the USPS: single-piece first class mail, first-class mail presorted, and marketing mail.
Single-piece first-class mail per adult started dropping in 1996, and has fallen by 70% since then.
First-class mail in the presorted category (which is more likely to be mailings sent by firms or government to consumers) continued to rise up until the Great Recession, but has declined by about one-third since then. .
Marketing mail dropped in the Great Recession, and is now down by more than one-quarter from 2007 levels, but its decline has been much smaller in recent years. As the report notes: \”Marketing Mail is also playing an increasingly prominent role in the Postal Service’s product portfolio. At approximately 80 billion pieces, Marketing Mail volume is higher than FCM-SP and FCM-Presort combined. In 2015, it made up about 52 percent of total mail volume.\”
In part, I find these patterns interesting as a reflection of how America communicates, and how the ease and convenience of web-based communication has affected the postal service.
But if the quantity of these core lines of the mail business are not falling as fast, while \”packages have become an increasingly prominent product for the Postal Service, with volume growing 68 percent to 5.2 billion pieces between 2009 and 2016,\” it becomes more feasible to think about how to restructure and right-size the Postal Service in a sensible way.
\”Peer-to-peer (P2P) lending came to the United States in 2006, when individual investors began lending directly to individual borrowers via online platforms. In the decade since, the industry has grown dramatically … Online lenders and policymakers have suggested that the P2P market offers unique benefits to consumers. Three benefits are often repeated and seem to have become widely accepted. First, P2P loans allow consumers to refinance expensive credit card debt. Second, P2P loans can help customers build their credit history and improve their credit scores. Finally, P2P proponents claim that P2P lending extends access to credit to those who are underserved by traditional banks.
\”But signs of problems in the P2P market are appearing. Defaults on P2P loans have been increasing at an alarming rate … We exploit a comprehensive set of credit bureau data to examine P2P borrowers, their credit behavior, and their credit scores. We find that, on average, borrowers do not use P2P loans to refinance preexisting loans, credit scores actually go down for years after P2P borrowing, and P2P loans do not go to the markets underserved by the traditional banking system. Overall, P2P loans resemble predatory loans in terms of the segment of the consumer market they serve and their impact on consumers’ finances. Given that P2P lenders are not regulated or supervised for antipredatory laws, lawmakers and regulators may need to revisit their position on online lending marketplaces.\”
The P2P sector is actually misnamed. As one might have predicted, it very quickly because a market where the supply of loans is not coming from individuals, but rather from institutions like \”hedge funds, banks, insurance companies, and asset managers.\” The amount loaned doubled from 2012 to 2016, and now exceeds $100 billion.
The authors have gained access to some useful data:
\”We use data from the TransUnion credit bureau, in which we observe about 90,000 distinct individuals who received their first P2P loan between 2007 and 2012. We also observe about 10 million individuals who did not receive P2P loans and whom we label non-P2P individuals. Using a statistical technique called propensity score matching, we identify non-P2P individuals who are financially similar to P2P individuals during the two years prior to the date on which P2P individuals obtained their P2P loan. We match individuals based on the location of their residence, their credit score, their total debt, their income, their number of delinquencies in the past two years, and whether or not they have a mortgage.\”
Thus, the authors can compare those who take out a P2P loan to a group with similar financial characteristics, and consider whether 1) they have been more successful in reducing their debt burden after a year or two (they haven\’t); 2) they have been more successful in building up their credit score (they haven\’t); and 3) they are a group that was less likely to have access to bank loans and other credit before (they aren\’t).
In a broader view, it\’s also troubling that each year, even though the economy has been experiencing a mild recovery, the P2P loans seem to be getting riskier. Here is the delinquency rate on P2P loans after one and two years. Each line shows the year in which the loan was made. The delinquency rates are rising over time.
It\’s useful to be clear on the potential policy problem here. I\’m not concerned about the institutions that make P2P loans: they are regulated by the Securities and Exchange Commission, and they can look after themselves. Lots of borrowers seem to be taking on a P2P loan thinking that it\’s a first step to paying down their existing debt, but for the group as a whole, this expectation isn\’t being met. If a financial market is in some danger of melting down in a way that could take a few million borrowers along with it–with all the stresses of wage garnishment, charging higher fees for missed payments, property liens, even bankruptcy–that\’s a public policy problem.
King\’s argument has both a broad conceptual message for the study of macroeconomics, which is that it is literally impossible to demonstrate with statistics that a certain macroeconomic model is \”true.\” After all, drawing statistical conclusions requires a decent sample size. But to get a sample size of, say, 20 or 30 recessions in a given economy would take a long time–perhaps several centuries–and it is not plausible that any macroeconomic model remains \”true\” over that length of time. As King puts it (footnotes omitted):
\”Let me give a simple example. It relates to my own experience when, as deputy governor of the Bank of England, I was asked to give evidence before the House of Commons Select Committee on Education and Employment on whether Britain should join the European Monetary Union. I was asked how we might know when the business cycle in the U.K. had converged with that on the Continent. I responded that given the typical length of the business cycle, and the need to have a minimum of 20 or 30 observations before one could draw statistically significant conclusions, it would be 200 years or more before we would know. And of course it would be absurd to claim that the stochastic process generating the relevant shocks had been stationary since the beginning of the Industrial Revolution. There was no basis for pretending that we could construct a probability distribution. As I concluded, `You will never be at a point where you can be confident that the cycles have genuinely converged; it is always going to be a matter of judgment.\’\”
In the current economic context, King takes aim at the macroeconomic perspective which argues that we had a pretty good model of the macroeconomy for the decades leading up to the Great Recession, but the model has broken down since then. The dashed line in the figure shows a trendline for growth of GDP per capita from 1960-2016. For the US economy, you can project that trendline backward to 1900: as I noted a few years ago, long-run US economic growth had a remarkable consistency from the late 19th century up through about 2010. However, the divergence from this long-run path in the aftermath of the Great Recession is quite noticeable. The trendline for the United Kingdom data doesn\’t project backward as well, but it does show a similar divergence from that trend in recent years.
Looking at the economy as represented in this figure, one might plausibly argue that the macroeconomy can be modeled by a fairly steady long-run trend, with some up-and-down fluctuations of recessions and recoveries around that trend. However, King suggests that this appearance is misleading. Instead, the world economy saw a dramatic shift starting in the mid-1990s that has continued since then, which can be seen in the pattern of real interest rates over time. King says:
\”From around the time when China and the members of the former Soviet Union entered the world trading system, long-term real interest rates have steadily declined to reach their present level of around zero. Such a fall over a long period is unprecedented. … [M]uch effort has been invested in the attempt to explain why the \”natural\” real rate of interest has fallen to zero or negative levels. But there is nothing natural about a negative real rate of interest. It is simpler to see Figure 3 as a disequilibrium phenomenon that cannot persist indefinitely.\”
In King\’s view, the world economy is still adjusting to this shift, which has a number of components. High savings rates in China and Germany have helped to drive down real interest rates. Moreover, we have moved into a world economy where some countries have seemingly perpetual trade surpluses while others have seemingly perpetual trade deficits. King writes:
\”Both the U.S. and U.K. had substantial current account deficits, amounting in aggregate to around $600 billion, and China and Germany had correspondingly large current account surpluses. All four economies need to move back to a balanced growth path. But far too little attention has been paid to the problems involved in doing that. With unemployment at low levels, the key problem with slower-than-expected growth is not insufficient aggregate demand but a long period away from the balanced path, reflecting the fact that relative prices are away from their steady-state levels. The result is that the shortfall of GDP per head relative to the pre-crisis trend path was over 15 percent in both the U.S. and U.K. at the end of last year. Policies which focus only on reducing the real interest rate miss the point; all the relevant relative prices need to change, too.\”
In short, King is offering an alternative diagnosis of our current slow-growth woes. In his view, the slow growth, it\’s not due to lingering hangover from the high debt burdens that preceded the Great Recession, nor is it due to a decline in technological opportunities, or to a shortfall in investment related to \”secular stagnation.\” Instead, King argues that what needs to happen is a shift in global prices in the sectors of tradeable and nontradeable goods.
I\’m adding King\’s explanation to my list of mental possibilities for what forces are underlying the slow productivity growth in the US economy. But in addition, it\’s worth adding a dose of King-size skepticism about economists who arrive at any macroeconomic situation with a given model fixed in their minds, rather than trying to figure out which model is most likely to apply in a given case. King notes:
\”Imagine that you had a problem in your kitchen, and summoned a plumber. You would hope that he might arrive with a large box of tools, examine carefully the nature of the problem, and select the appropriate tool to deal with it. Now imagine that when the plumber arrived, he said that he was a professional economist but did plumbing in his spare time. He arrived with just a single tool. And he looked around the kitchen for a problem to which he could apply that one tool. You might think he should stick to economics. But when dealing with economic problems, you should also hope that he had a box of tools from which it was possible to choose the relevant one. And there are times when there is no good model to explain what we see. The proposition that `it takes a model to beat a model\’ is rather peculiar. Why does it not take a fact to beat a model? And although models can be helpful, why do we always have to have one? After the financial crisis, a degree of doubt and skepticism about many models would be appropriate.\”
It would take some odd mixture of clueless, heartless, and moral blindness to argue that poverty in the United States or other high-income countries should be defined in the same way as in low-income countries. But by similar logic, it seems unsuitable to use the same poverty line for what the World Bank would classify as \”low-income\” countries with a per capita GDP of less than $1,005 per year (for example, Afghanistan, Ethiopia, and Haiti), \”lower middle income\” countries with a per capita GDP between $1,006 TO $3,955 (like Bangladesh, Nicaragua, and Nigeria), and \”upper middle-income\” countries with a per capita GDP from $3,956 TO $12,235 (like Mexico, China,and Turkey). Thus, the World Bank is now planning to use \”A Richer Array of Poverty Lines,\” in the words of Franciscon Ferreira.
The figure shows per capita income on the horizontal axis, with the groups of countries separated by income level. The corresponding poverty line for each country as determined by that country is plotted on the vertical axis. The horizontal line shows an average poverty line for the countries within that income group. The underlying data for national poverty lines is from an article by Dean Jolliffe and Espen Beer Prydz, \”Estimating international poverty lines from comparable national thresholds,\” which appeared in the Journal of Economic Inequality (2016, 14, pp. 185-198). An ungated version is available from the World Bank here.
Both technological developments and international trade can disrupt an economy, and in somewhat similar ways, but many people have very different reactions to these forces. To illustrate the point, I sometimes pose this question:
There\’s a US company which has developed a new technology that allows them to make a certain product more cheaply. This company hires some additional workers, but the other firms trying to make that same product don\’t have the technology, so they lay off workers or even go bankrupt. Should step be taken to ban or limit the use of this new technology?
Pause for thought. The usual reaction that emerges from the discussion is that we can\’t hope to freeze technology in place. Ultimately, we don\’t want to be a society with lots of workers who light gas streetlamps, or who operate telegraphs or who plow fields with oxen. Sure, it\’s important to have social policies to cushion the transition to new industries, but overall, we need to be facilitating new technology rather than blocking it.
All of which is fair enough, but here\’s the kicker. Now you discover that the \”new technology\” from the US firm is that it is importing more cheaply from a foreign provider. The same disruption of the US labor force is occurring, but as a result of an expansion of international trade rather than as a result of technology. Personally, my response to the economic disruption of trade is essentially same as my response to the economic disruption of technology: that is, I believe in assisting the transition for dislocated workers no matter the reason behind the dislocation. But for many people, their reaction to economic disruption is different depending on whether the underlying cause is technology or trade.
As a starting point, here\’s a figure from DeLong\’s paper about the rise of globalization. The red line shows the sum of exports and imports compared to world GDP. The first explosion of globalization starting in the 19th century, and the more recent rise of globalization, are both readily apparent. But of course, a rise in trade isn\’t the only economic change taking place. Brad points out that the fall in blue-collar and manufacturing jobs was well underway back in the 1950s and 1960s, well before globalization had restarted in force–because of changes in technology Indeed, I\’ve written before about \”Automation and Job Loss: The Fears of 1964\” (December 1, 2014). Brad readily admits that the shock of increased trade with China starting around 2001 was an important event, and of course the Great Recession had a powerful effect on jobs too. But overall, he writes:
by his calculations. only a very minor part of the decline in blue-collar jobs since 1948 is about international trade: it\’s mostly about technological change, and to some extent about the rising strength of economies in other parts of the world and misjudgments of macroeconomic policy by the US government.
\”To repeat, because it bears repeating: globalization in general and the rise of the Chinese export economy have cost some blue-collar jobs for Americans. But globalization has had only a minor impact on the long decline in the portion of the economy that makes use of high-paying blue-collar labor traditionally associated with men. … Pascal Lamy, the former head of the World Trade Organization, likes to quote China’s sixth Buddhist patriarch: `When the wise man points at the moon, the fool looks at the finger.\’ Market capitalism, he says, is the moon. Globalization is the finger.\”
Given that comment from Lamy, it is perhaps unsurprising that the World Trade Report 2017 takes a position similar to DeLong. There are roughly a jillion examples of how technology both improves productivity but also can also disrupt job markets. The report summarizes:
\”By making some products or production processes obsolete, and by creating new products or expanding demand for products that are continuously innovated, technological change is necessarily associated with the reallocation of labour across and within sectors and firms. Such technology-induced reallocations affect workers differently, depending on their skills or on the tasks they perform. ICTs tend to be used more intensively and more productively by skilled workers than by unskilled workers. Automation tends to affect routine activities more than non-routine activities, because machines still do not perform as well as humans when it comes to dexterity or communication skills. … [T]he labour market effects of technology are relatively more favourable to skilled workers and to workers performing tasks that are harder to automate.\”
What about the worry that technology will lead to a dramatic reduction in the total number of jobs? Obviously, this prediction is not an extrapolation from history. The US and world economy have been experiencing technological growth in a serious way for a couple of centuries, and there is no long-run downward trend in the total number of jobs. Why is that? The report offers these reasons (citations omitted):
\”The view that the new technological advances in artificial intelligence and robotics will not lead to a `jobless future\’ is based on historical experience. Although each wave of technological change has generated technological anxiety and led to temporary disruptions with the disappearance of some tasks and jobs, other jobs have been modified, and new and often better jobs have eventually been developed and filled through three interrelated mechanisms.
\”First, new technological innovations still require a workforce to produce and provide the goods, services and equipment necessary to implement the new technologies. Recent empirical evidence suggests that employment growth in the United States between 1980 and 2007 was significantly greater in occupations encompassing more new job titles.
\”Second, the new wave of technologies may enhance the competitiveness of firms adopting these technologies by increasing their productivity. These firms may experience a higher demand for the goods or services they produce, which could imply an increase in their labour demand. Several empirical studies … find that the adoption of labour-saving technologies did not reduce the overall labour demand in European countries and other developed economies.
\”Finally, … the upcoming technological advances may complement some tasks or occupations and therefore increase labour productivity, which could lead to either higher employment or higher wages, or both. The new workers and/or those benefitting from a pay rise may increase their consumption spending, which in turn tends to maintain or raise the demand for labour in the economy. Recent empirical evidence suggests that the use of industrial robots at the sector level has led to an increase in both labour productivity and wages for workers in Australia, 14 European countries, the Republic of Korea and the United States.\”
It\’s of course impossible to prove that future patterns will be similar. But the historical evidence suggests that finding ways to stimulate and work with technology is a better path to prosperity than trying to limit or block it.
In the discussion of trade and jobs, the report readily admits that trade (like technology) causes economic change and dislocation. After a substantial discussion of the empirical evidence, here are some conclusions from the report:
\”First, evidence consistently shows that the welfare gains from trade are considerably larger than the costs. Effects on aggregate employment are minor and tend to be positive. The net effect on welfare depends on the magnitude of adjustment costs and trade gains. But existing evidence evaluates costs to be just a fraction of the gains.
\”Second, the debate over the labour market effects of import competition needs to be qualified. While some manufacturing jobs may be lost in some local labour markets, other jobs may be created in other zones or in the services sector. When researchers take these effects into account their findings suggest a positive overall effect of trade on employment. Similar results are found when input-output linkages are taken into account or when the response of the labour supply to increased real wages is accounted for. Clearly, those who lose jobs because of import competition are not necessarily the same workers who get new jobs in exporting firms, because they are likely to have different skillsets or limited labour mobility. These adjustment costs need to be taken into account, but without losing sight of the overall picture.
\”Third, there is evidence that export opportunities are associated with employment growth. In developing countries, improved access to foreign markets has contributed to the movement of workers away from agriculture and towards services and manufacturing, as well as away from household businesses toward firms in the enterprise sector, and away from state-owned firms toward private domestic and foreign-owned firms. Although more should be done to understand how labour markets in least-developed countries (LDCs) are affected by trade opening, there is evidence that the involvement of LDCs in GVCs [global value chains] has been a vehicle for developing employment opportunities.
\”Fourth, trade offers opportunities for better-paid jobs. A significant share of jobs is related to trade, either through exports or imports, and both exporters and importers pay higher wages. This is because trading is a skills-intensive activity. International trade requires the services of skilled workers, who can ensure compliance with international standards, manage international marketing and distribution, and meet the demanding standards of customers from high-income countries; and trade leads to the selection of more productive firms and provides firms with an incentive to upgrade their technology. There is evidence that better access to foreign markets benefits exporting firms and thus their workers. This in turn positively affects regions where these firms are located, as well as occupations that are intensively used by these firms.
\”As regards the evidence on the impact of trade on wage dispersion, there is evidence that by increasing the demand for skills, trade contributes to wage differences between high- and low-skilled workers. … It is also worth noting that most of the existing analysis fails to account for the fact that most of the gains from trade opening come through a reduction in prices. Workers are also consumers. Trade impacts their well-being not only through changes in the wage received, but also through changes in the price of the goods that they consume. Given that most of the gains from trade opening through the consumption channel accrue to lower-income groups, failing to account for the income-group specific price changes overestimates the impact on wage disparity.\”
For some additional discussion of concerns that technology (or trade) would decimate the number of jobs, see:
