Conversable Economist

When import tariffs are proposed, there\’s a lot of talk about unfairness and helping workers. But when the tariffs are enacted, the standard pattern is that consumers pay more, profits for the protected firm go up, and jobs are reshuffled from unprotected to protected industries. Back in 1911, satirist Ambrose Bierce defined \”tariff\” this way in The Devil\’s Dictionary: \”TARIFF, n.A scale of taxes on imports, designed to protect the domestic producer against the greed of his consumer.\”

Back in fall 2017, the Trump administration announced worldwide tariffs on imported washing machines. Aaron Flaaen, Ali Hortaçsu, and Felix Tintelnot,  look at the results in “The Production, Relocation, and Price Effects of US Trade Policy: The Case of Washing Machines.” A readable overview of their work is here; the underlying research paper is here. 

Following the late-2017 announcement of tariffs on all washers imported to the United States, prices increased by about 12 percent in the first half of 2018 compared to a control group of other appliances. In addition, prices for dryers—often purchased in tandem with washing machines—also rose by about 12 percent, even though dryers were not subject to a tariff. … [T]hese price increases were unsurprising given the tariff announcement. … One revealing finding in this work is the tight price relationship between washers and dryers, even when washers, for example, are the product that is subject to tariffs. Among the five leading manufacturers of washers, roughly three- quarters of models have matching dryers. When the authors compare only electric washers and dryers, they show that in about 85 percent of the matching sets, the washers and dryers have the same price.

\”Financial advisers in the United States manage over $30 trillion in investible assets, and plan the financial futures of roughly half of U.S. households. At the same time, trust in the financial sector remains near all-time lows. The 2018 Edelman Trust Barometer ranks financial services as the least trusted sector by consumers, finding that only 54 percent of consumers `trust the financial services sector to do what is right.\’\”

Mark Egan, Gregor Matvos and Amit Seru went looking for actual data on misconduct by financial managers. Matvos and Seru provide an overview of their research in \”The Labor Market for Financial Misconduct\” (NBER Reporter 2019:1). For the details, see M. Egan, G. Matvos, and A. Seru, \”The Market for Financial Adviser Misconduct,\” NBER Working Paper No. 22050, February 2016.

The authors figured out that the Financial Industry Regulatory Authority keeps a record of the complete employment history of the 1.2 million people registered as financial adviser from 2005-2015 at its BrokerCheck website. This history includes employers, jobs tasks, and roles. In addition, \”FINRA requires financial advisers to formally disclose all customer complaints, disciplinary events, and financial matters, which we use to construct a measure of misconduct.\” They write:

Roughly one in 10 financial advisers who work with clients on a regular basis have a past record of misconduct. Common misconduct allegations include misrepresentation, unauthorized trading, and outright fraud— all events that could be interpreted as a conscious decision of the adviser. Adviser misconduct results in substantial costs: In our sample, the median settlement paid to consumers is $40,000, and the mean is $550,000. These settlements cost the financial industry almost half a billion dollars per year.

Looking at this data generates some provocative insights.  

A \”household equivalence\” scale offers an answer to this question: How much more income is needed by a a household with more people so that it has the same standard of living as a household with fewer people? The question may seem a little abstract, but it has immediate applications.

For example, the income level that officially defines the poverty line was $13,064 for a single-person household under age 65 in 2018. For a two-person household, the poverty line is $16,815 if they are both adults, but $17,308 if it\’s one adult and one child. For a single parent with two children the poverty line is $20,331; for a single parent with three children, it\’s $25,554. The extent to which the poverty line rises with the number of people, and with whether the people are adults or children or elderly, is a kind of equivalence scale.

Similarly, when benefits the poor and near-poor are adjusted by family size, such adjustments are based on a kind of equivalence scale.

And bigger picture, if you are comparing average household income between the early 1960s and the present, it presumably matters that the average household had 3.3 people in the early 1960s but closer to 2.5 people today (see Table HH-4).

However, it often turns out that poverty lines and poverty programs are set up with their own logic of what seems right at the time, but without necessarily using a common household equivalence scale. Richard V. Reeves and Christopher Pulliam offer a nice quick overview of the topic in \”Tipping the balance: Why equivalence scales matter more than you think\”  (Brookings Institution,  April 17, 2019). Here\’s a sample of some common household equivalence scales:

Reeves and Pulliam point out that if you look at the 2017 Tax Cuts and Jobs Act, and how it affects \”households\” at different income levels, your answer will look different depending on whether you apply a household equivalence scale. For example, think about ranking households by income using an equivalence scale. If there are two households with the same income, but one household has more children, then the household with more children will be treated as having a lower standard of living (or to put it another way, a household with more children would need more income to have the same standard of living). The 2017 tax law provides substantial benefits to families with children.

But setting aside that particular issue, it\’s  topic that matters to people planning a household budget, if they think about the question of whether living together will save money, or how much more money they will need if they have children. The commonly used \”square root\” approach, for example, suggests that a a household of two people will need 1.414 times the income of a single-person household for an equivalent standard of living, a household of three people will need 1.732 times the income of a single-person household for an equivalent standard of living and so on. Pick another household equivalence scale, if you prefer, but then plan accordingly.

As we move toward the end of the academic year for many colleges and universities, it is perhaps useful for students to be reminded that the final grade for any given course is quite unlikely to have a long-lasting influence on your life. Here are some thoughts from the syndicated newspaper column written by Calvin Trillin, which I would sometimes read to my introductory economics students on the last day of class. (I don\’t have an online link, but my notes tell me that I originally read the column in the San Jose Mercury News, May 26, 1990, p. 9C). Trillin wrote:

I wrote a few weeks back that the American Statistical Association has published a special issue of it journal, the American Statistician, with a lead article proposing the abolition of \”statistical significance\” (\”Time to Abolish `Statistical Significance\’\”?). John Ioannidis has estimated that 90% of medical research is statistically flawed, so one might expect him to be among the harsher critics of statistical significance.  But in the Journal of the American Medical Association, he goes the other way in \”The Importance of Predefined Rules and Prespecified Statistical Analyses: Do Not Abandon Significance\” (April 4, 2019). Here are a few of his themes:

The result of statistical research is often a yes-or-no outcome. Should a medical treatment be approved or not? Should a certain program or policy be expanded or cut? Should one potential effect be studied more, or should it be ruled out as a cause? Thus, while it\’s fine for researchers to emphasize that all results come with degree of uncertainty, at some point it\’s necessary to decide both how research and how applications of that research in the real world should proceed. Ioannidis writes:

Changing the approach to defining statistical and clinical significance has some merits; for example, embracing uncertainty, avoiding hyped claims with weak statistical support, and recognizing that “statistical significance” is often poorly understood. However, technical matters of abandoning statistical methods may require further thought and debate. Behind the so-called war on significance lie fundamental issues about the conduct and interpretation of research that extend beyond (mis)interpretation of statistical significance. These issues include what effect sizes should be of interest, how to replicate or refute research findings, and how to decide and act based on evidence. Inferences are unavoidably dichotomous—yes or no—in many scientific fields ranging from particle physics to agnostic omics analyses (ie, massive testing of millions of biological features without any a priori preference that one feature is likely to be more important than others) and to medicine. Dichotomous decisions are the rule in medicine and public health interventions. An intervention, such as a new drug, will either be licensed or not and will either be used or not.

Yes, statistical significance has a number of problems. It would be foolish to rely on it exclusively. But what will be used instead? And will it be better or worse as a way of making such decisions? No method of making such decisions is proof against bias. Ioannidis writes: 

Many fields of investigation (ranging from bench studies and animal experiments to observational population studies and even clinical trials) have major gaps in the ways they conduct, analyze, and report studies and lack protection from bias. Instead of trying to fix what is lacking and set better and clearer rules, one reaction is to overturn the tables and abolish any gatekeeping rules (such as removing the term statistical significance). However, potential for falsification is a prerequisite for science. Fields that obstinately resist refutation can hide behind the abolition of statistical significance but risk becoming self-ostracized from the remit of science. Significance (not just statistical) is essential both for science and for science-based action, and some filtering process is useful to avoid drowning in noise.

In 1840, Henry Wadsworth Longfellow published a poem called \”The Village Blacksmith.\” In my humble economist-opinion, not his best work. But the opening four lines are very nice:

Under a spreading chestnut tree
The village smithy stands;
The smith, a mighty man is he,
With large and sinewy hands …

When I was a little boy, and my father read the poem to me, I remember the pleasure in his voice at that word \”sinewy.\” Indeed, there was at time when every town of even modest size had at least one blacksmith. When did they go away?
Jeremy Atack and Robert A. Margo answer the question in \”Gallman revisited: blacksmithing and American manufacturing, 1850–1870,\” published earlier this year in Cliometrica (2019, 13: 1-23).  Gallman is an earlier writer who classified blacksmiths as a service industry, while Atack and Margo argue that they instead should be treated as an early form of manufacturing. From a modern view, given the concerns over how technology may affect current and future jobs, blacksmiths offer an example of how a prominent industry of skilled workers went away. Atack and Margo write:

The village blacksmith was a common sight in early nineteenth-century American communities, along with cobblers, shoemakers, grist mill operators, and other artisans. Blacksmiths made goods from wrought iron or steel. This metal was heated in a forge until pliant enough to be worked with hand tools, such as a hammer, chisel, and an anvil. Others also worked with metal but what distinguished blacksmiths was their abilities to fashion a wide range of products from start to finish and even change the properties of the metal by activities such as tempering, as well as repair broken objects. …

Blacksmiths produced a wide range of products and supplied important services to the nineteenth-century economy. In particular, they produced horseshoes and often acted as farriers, shoeing horses, mules, and oxen. This was a crucial service in an economy where these animals provided the most of the draft power on the farm and in transportation and carriage. The village blacksmith also produced a wide range of goods from agricultural implements to pots and pans, grilles, weapons, tools, and carriage wheels among many other items familiar and unfamiliar to a modern audience—a range of activities largely hidden behind their generic occupational title.

Blacksmithing was a sufficiently important activity to qualify as a separate industrial category in the nineteenth-century US manufacturing censuses, alongside more familiar industries as boots and shoes, flour milling, textiles, and clock making. The 1860 manufacturing census, for example, enumerated 7504 blacksmith shops employing 15,720 workers … —in terms of the number of establishments, the fourth most common activity behind lumber milling, flour milling, and shoemaking. …

As ‘‘jacks-of-all-trades,’’ they [blacksmiths] were generally masters of none (except for their service activities). Moreover, the historical record reveals that several of those who managed to achieve mastery moved on to become specialized manufacturers of that specific product. Such specialized producers had higher productivity levels than those calling themselves blacksmiths producing the same goods, explaining changes in industry mix and the decline of the blacksmith in manufacturing. …

Consider the goods produced historically by blacksmiths, such as plows. Over time, blacksmiths produced fewer and fewer of these, concentrating instead on services like shoeing horses or repairs. But even controlling for this, only the most productive of blacksmiths (or else those whose market was protected from competition in some way) survived—a selection effect. On the goods side of the market, production shifted toward establishments that were sufficiently productive that they could specialize in a particular ‘‘industry,’’ such as John Deere in the agricultural implements industry. As this industry grew, it drew in workers—some of whom in an earlier era might have opened their own blacksmith shops, but most of whom now worked on the factory floor, perhaps doing some of the same tasks by hand that blacksmiths had done earlier but otherwise performing entirely novel tasks, because production process was increasingly mechanized. On average, such workers in the specialized industry were more productive than the ‘‘jack-of-all-trades,’’ the blacksmith, had been formerly. The village smithy could and did produce rakes and hoes, but the village smithy eventually and increasingly gave way to businesses like (John) Deere and Company who did it better. …

During the first half of the nineteenth century, blacksmiths were ubiquitous in the USA, but by the end of the century they were no longer sufficiently numerous or important goods producers to qualify as a separate industry in the manufacturing census.

When the US economy was a larger share of the world economy, then access to the US market meant more. For example, World Bank statistics say that the US economy was 40% of the entire world economy in 1960, but is now about 24%. The main source of growth in the world economy for the foreseeable future will be in emerging markets.

For a sense of the shift, consider this figure from chapter 4 of the most recent World Economic Outlook report, published by the IMF (April 2019). The lines in the figure show the trade flows between countries that are at least 1% of total world GDP. The size of the dots for each country is proportionate to the country\’s GDP.

In 1995, you can see international trade revolving around the United States, with another hub of trade happening in Europe and a third hub focused around Japan.  Trade between the US and China shows up on the figure, but China did not have trade flows greater than 1% of world GDP with any country other than the US.

The picture is rather different in 2015. The US remains an international hub for trade. Germany remains a hub as well, although fewer of its trade flows now exceed 1% of world GDP. And China has clearly become a hub of central importance in Asia.

The patterns of trade have also shifted toward greater use of global value chains–that is, intermediate products that are shipped across national borders at least once, and often multiple times, before they become final products. Here\’s the overall pattern since 1995 of falling tariffs and rising participation in global value chains for the world economy as a whole.

Several decades ago, emerging markets around the world worried about having access to selling in US and European markets, and this market access could be used by the US and European nations as a bargaining chip in economic treaties and more broadly in international relations. Looking ahead, US production is now more tied into global value chains, and the long-term growth of US manufacturing is going to rely more heavily on sales to markets outside the United States.

For example, if one is concerned about the future of the US car industry, the US now produces about 7% of the world\’s cars in 2015, and about 22% of the world\’s trucks. The future growth of car consumption is going to be primarily outside the US economy. For the health and long-term growth of the US car business, the possibility of unfair imports into the US economy matters a lot less than the access of US car producers to selling in the rest of the world economy.

The interconnectedness of global value chains means that General Motors already produces more cars in China than it does in the United States. In fact, sales of US multinationals now producing in China are already twice as high as exports from the US to China. Again, the long-term health of many US manufacturers is going to be based on their ability to participate in international value chains and in overseas production.

Although what caught my eye in this chapter of the World Economic Outlook report was the shifting patterns of world trade, the main emphases of the chapter are on other themes that will come as no surprise to faithful readers of this blog.  One main theme is that shifts in bilateral and overall trade deficits are the result of macroeconomic factors, not the outcome of trade negotiations, a theme I\’ve harped on here (for example, here, here, and here).

The IMF report also offers calculations that higher tariffs between the US and China will cause economic losses for both sides. From the IMF report:

US–China trade, which falls by 25–30 percent in the short term (GIMF) and somewhere between 30 percent and 70 percent over the long term, depending on the
model and the direction of trade. The decrease in external demand leads to a decline in total exports and in GDP in both countries. Annual real GDP losses range from –0.3 percent to –0.6 percent for the United States and from –0.5 percent to –1.5 percent for China … Finally, although the US–China bilateral trade deficit is reduced, there is no economically significant change in each country’s multilateral trade balance.

Some advocates of higher tariffs take comfort in noting that the estimated losses to China\’s economy are bigger than the losses to the US economy.  Yes, but it\’s losses all around! As the 21st century economy evolves, the most important issues for US producers are going to involve their ability to
compete in unfettered ways in the increasingly important markets outside the US.

For anyone who can do arithmetic, it did not come as a surprise that the \”baby boom generation,\” born from 1946 up through the early 1960s, started turning 65 in 2010. Here\’s the pattern over time of the \”Daily Average Number of People Turning 65.\” The jump of the boomer generation is marked.

Because two major federal spending programs are focused on older Americans–Social Security and Medicare–it has been utterly predictable for several decades that the long-run federal budget situation would come under strain at about this time. That figure comes from a report by the US Government Accountability Office, \”The Nation’s Fiscal Health Action Is Needed to Address the Federal Government’s Fiscal Future\” (April 2019).

Here\’s a breakdown of the GAO predictions on federal spending for the next 30 years. The \”all else\” category bumps up about 0.6% of GDP during this time, and normal politics could deal with that easily enough. Social Security spending is slated to bump up about 1% of GDP, which is a bigger problem. Still, some mixture of limits on benefits (like a later retirement age) and a modest bump in the payroll tax rate could deal address this. Indeed, it seems to me an indictment of the US political class, from both parties, that no forward-looking politician has built a movement around steps to \”save Social Security.\”

But the projected rise in government health care spending of 3.2% of GDP is a challenge that no one seems to know how to fix. It\’s a combination of the rising share of older people, and in particular the rising share of the very-old who are more likely to face needs for nursing home and Alzheimer\’s care, combined with an overall trend toward higher per person spending on health care. As I\’ve noted before, every dollar of government health care spending represents both care for a patient and income for a provider, and both groups will fight hard against cutbacks.

Meanwhile, this rise in spending, coupled with the assumption that tax revenues remain on their current trajectory, means higher government deficits and borrowing. Over time, this also means higher government interest payments. So if we lack the ability to control the rise in deficits, interest payments soar. In 2018, about 7.9% of federal spending is interest payments on past borrowing. By 2048, on these projections, about 22% of all federal spending will be interest payments on past debt. Of course, this also means that finding ways to reduce the deficit with spending and tax changes also has the benefit that it avoids this soaring rise in interest payments.

As a side note, I thought a figure in the GAO report showing who holds US debt was interesting.  The report notes:

Domestic investors—consisting of domestic private investors, the Federal Reserve, and state and local governments—accounted for about 60 percent of federal debt held by the public as of June 2018, while international investors accounted for the remaining 40 percent. International investors include both private investors and foreign official institutions, such as central banks and national government-owned investment funds. Central banks hold foreign currency reserves to maintain exchange rates or to facilitate trade. Therefore, demand for foreign currency reserves can affect overall demand for U.S. Treasury securities. An economy open to international investment, such as the United States, can essentially borrow the surplus of savings of other countries to finance more investment than U.S. national saving would permit. The flow of foreign capital into the United States has gone into a variety of assets, including Treasury securities, corporate securities, and direct investment.

The arguments for restraint on federal borrowing are fairly well-known. There\’s the issue that too much debt means less ability to respond to a future recession, or some other crisis. There\’s an issue that high levels of federal borrowing soak up investment capital that might have been used more productively elsewhere in the economy. There\’s a concern that federal borrowing is financing a fundamental shift in the nature of the federal government: it used to be that most of government spending was about making investments in the future–infrastructure, research and development, education, and so on–but over the decades it has become more and more about cutting checks for immediate consumption in spending programs.

But at the moment, I won\’t argue for this case in any detail, or offer a list of policy options. Those who want to come to grips with the arguments should look at William Gale\’s just-published book, Fiscal Therapy: Curing America\’s Debt Addiction and Investing in the Future,  For an overview of Gale\’s thinking, a useful starting point is the essay \”Fiscal therapy: 12 framing facts and what they mean\” (Brookings Instution, April 3, 2019).

Of course, I personally like some of Gale\’s proposals better than others. But overall, what I really like is that he takes the issue of rising government debt in the long-run seriously, and takes the responsibility of offering policy advice seriously. He doesn\’t wave his hands and assume that faster economic growth will bring in additional waves of tax revenue; or that \”taxing the rich\” is a magic elixir; or that the proportion of older people who are working will spike upward; or that we can ignore the deficit for five or ten or 15 years before taking some steps; or that government spending restraint needs nothing more than avoiding duplication, waste, and fraud. He uses mainstream estimates and makes concrete suggestions. For an outside analysis of his recommendations, John Ricco, Rich Prisinzano, and Sophie Shin run his proposals through the Penn Wharton Budget Model in \”Analysis of Fiscal Therapy: Conventional and Dynamic Estimates (April 9, 2019).

As a reminder, here\’s the pattern of US debt as a share of GDP since 1790. Through most of US history, the jumps in federal debt in the past are about wars: the Revolutionary War, the Civil War, World Wars I and II. There\’s also a jump in the 1930s as part of fighting the Great Depression, and the more recent jump which was part of fighting the Great Recession.

But the aging of the US population and rising health care spending are going to take federal spending and deficits to new (peacetime) levels. On the present path, we will surpass the previous high of federal debt at 106% of GDP in about 15-20 years. It would b imprudent to wait and see what happens.

The Gallup Poll has been asking Americans since the 1950s whether they think that the income tax they pay is \”too high\” or \”about right.\” The figure shows the responses over time including the 2019 poll, taken in early April. (The \”don\’t know\” and the \”too low\” answers are both quite small, and are not shown on the figure.)

What\’s interesting to me here is that from the late 1960s up through the 1990s, a healthy majority of Americans consistently viewed their income taxes as too high. But since around 2000, the gap has been much narrower. Indeed, the share of Americans saying that their income taxes are \”about right\” has been at its highest historical level in 2018 and 2019.

In more detailed questions, the Gallup poll also asks different income groups, and whether they are paying too much, a fair amount, or too little. Unsurprisingly, the general sentiment is that those with upper income levels could pay more. But there are some patterns I wouldn\’t necessarily have expected in the results, as well. Here are the results for what people think about what upper-income people are paying in federal taxes (for readability, I omitted the 2-4% in the \”don\’t know\” column):

What jumps out at me is that the proportion saying that upper-income people are paying a fair share of federal taxes was at its highest ever in 2019, while the share saying that upper-income people are paying \”too little\” was at its lowest ever. Yes, there\’s still a majority saying that upper-income people are paying \”too little.\” But it\’s a shrinking majority. Given trends toward greater inequality of incomes over the 25 years shown in the table, I wouldn\’t have expected that pattern.

Here\’s the pattern for federal taxes paid by middle-income people:

Here, you can see the pattern from the figure above: that is, the share saying that middle-income people pay too much is falling, while the share saying that they pay their fair share seems to have risen over time.

For the share paid by lower-income people, the pattern looks like this:

Overall, the most common answer is that lower-income people pay \”too much\” in federal taxes. But it\’s interesting that the share saying that lower income people pay \”too little\” is higher than the share saying that middle-income people pay \”too little.\” The share saying that lower-income people pay \”too little\” in federal taxes was especially high in 2014 and 2015, although it\’s dropped off a little since then,

Of course, questions about whether a tax code is fair are going to be influenced by political partisanship. For example, here are some poll responses from the Pew Research Center. Their polling shows that the share of American thinking the federal tax system is very or moderately fair rose overall slightly in the last year overall. However, this modest overall rise is a result of Republicans being much more willing to say the tax system is fair than at any time in the last 20 years, and Democrats being much less willing to say so.

As I\’ve pointed out in the past, poll responses on economic questions like whether free trade offers benefits are also influenced dramatically by political preferences. During the past couple of years, as President Trump has inveighed against international trade and called for protectionism, Democrats have suddenly become much more positive about trade. One suspects that this pattern emerged more from anti-Trump feeling than from increased time spent reading economics textbooks.

Still, it\’s interesting to me that a plurality of American now see the federal income tax as \”about right,\” while the proportion saying that upper-incomes pay too little is down, the proportion saying that middle-incomes pay a fair share is up, and the proportion saying that lower incomes pay too little has risen. Perhaps politicians who call for cutting taxes, or for dramatic tax increases, are refighting battles from the 1990s that are of less relevance to current voters.

\”Between the summer of 1830 and the summer of 1832, riots swept through the English countryside. Over no more than two years, 3,000 riots broke out – by far the largest case of popular unrest in England since 1700. During the riots, rural laborers burned down farmhouses, expelled overseers of the poor and sent threatening letters to landlords and farmers signed by the mythical character known as Captain Swing. Most of all, workers attacked and destroyed threshing machines.\”

 Bruno Caprettini and  Joachim Voth provide a readable overview of their research on the riots in \”Rage against the machines New technology and violent unrest in industrializing England,\” written as a Policy Brief for the UBS International Center of Economics in Society (2018, #2). They write:

\”Threshing machines were used to thresh grain, especially wheat. Until the end of the 1700s, threshing grain was done manually and it was the principal form of employment in the countryside during the winter months. Starting from the Napoleonic Wars (1803-1815), threshing machines spread across England, replacing workers. Horse-driven or water-powered threshers could finish in a matter of weeks a task that would have normally kept workers busy for months. Their use arguably depressed the wages of rural workers.\” 

Here\’s a figure showing locations of the Captain Swing riots: 

The authors collect evidence about where threshing machines were being adopted based on newspaper advertisements for the sale of farms–which listed threshing machines at the farm as well as other property included with the sale. They show a correlation between the presence of more threshing machines and rioting. But as always, correlation doesn\’t necessarily  mean causation. For example, perhaps areas where local workers were already more rebellious and uncooperative were more likely to adopt threshing machines, and the riots that followed only show why local farmers didn\’t want to deal with their local workers.