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For years now, competent commentators have tried to explain that tariffs do no one any good (on net). They are taxes. They increase business costs. They force businesses to cough up to the government for no particular reason. They don’t work to open economies. They sow seeds of distrust. They invite retaliation thus ruining export markets in addition to raising prices and tipping small businesses into the failing side of thin margins.
Time was when protectionist policies benefited powerful industrial interests by insulating them from competition. But with more than 60% of world GDP now bound up with imports and exports, those times are over. Tariffs have never really worked on the whole; now they are literally outmoded.
Not a single incident of mercantilist policies in history refutes those points.
Now we are living through a real-time experiment that is testing these propositions once again. Daily, reports appear that reveal that we are once again discovering what we already knew: to be a “tariff man” is to be a person who lives in denial of reality.
Let us review here the authoritative evidence.
The New York Fed just conducted a business survey and found the following.
When asked how much, if at all, recent increases in tariffs have raised input costs—either directly or indirectly—79 percent of manufacturers and 60 percent of service firms said at least slightly, with 14 percent and 12 percent, respectively, characterizing the increase as substantial. The data illustrate a considerably more widespread effect of higher input costs among service firms than in last year’s survey. Businesses were also asked how they saw changes in trade policy affecting the prices they pay, their selling prices, and other measures in 2019 and in 2020. For both years, roughly two-thirds of manufacturers saw an upward effect on prices paid, and roughly 45 percent saw an upward effect on selling prices. Among service-sector respondents, the numbers were somewhat lower but up noticeably from last August’s survey: for the current year, 60 percent saw an upward effect on prices paid (up from 49 percent in the 2018 survey), and 39 percent reported an upward effect on their selling prices (up from 32 percent last year).
Here is a Tweet storm by importer Josh Jordon that provides some flavor to what business is dealing with here.
Since my business is now caught up in the trade war, I want to go over how crippling it is not just from the tariffs alone, but the uncertainty that Trump’s constant back and forth are causing for a lot of small businesses like myself.
Over the last few years we’ve had products made in the US and in China. The products we make in China would cost anywhere from 2-4x what the cost to make in China.
What that means is if we made them in the US, we would have almost no sales. You can only increase prices so much.
In making these products in China, we have to put or orders in about 45 days before they ship. This is normally not a problem, but when Trump unilaterally slaps tariffs on items with little notice it becomes one.
This has happened with two of our orders this month alone.
We placed two orders that will be “on the water” before Sept 1, but Trump is giving no exemption for those containers.
In other words, we placed the order well before Trump’s new tariff announcement, they will leave China before 9/1, but we’re still going to pay 10% tariffs.
These are low margin products that sell well during the holidays which now have a 10% tariff tax attached to them.
That forces us to either increase the costs to consumers or to eat the tariffs. We’re looking at that now, but will likely increase slightly and eat some of them.
The uncertainty makes this so difficult, and there are so many small businesses like mine doing the same thing (I know because I talk to them), and so many are trying now to get orders in for the holidays.
While Trump delayed *some* of these new tariffs, he left most in place.
By Trump delaying some of the new tariffs until 12/15, he arbitrarily chose winners and losers.
In other words – Trump went through a list of products and decided which categories (companies) he did not want to harm for holiday sales, and which he didn’t care about either way.
So now we have two containers that are coming in that will have a 10% tariff bill attached to them that we will have to pay 100% of — China will not pay one cent of the tariffs as I’ve screamed about for months.
And now we’re looking at the next orders and wondering what to do.
Every order placed now will have a 10% tariff attached to it, with Trump threatening to raise it to 25% if China doesn’t back off.
And while the 10% tariff will be very painful to our small business, a 25% tariff would be crippling.
So many businesses are going through this.
I hope this illustrates how chaotic Trump’s trade policies are for US businesses, and why Trump’s impulsive tariff decisions are devastating.
We all fear that Trump will add/increase the tariffs while orders are en route to us, and it’s really awful to plan a business that way.
If you made it this far, thanks for reading.
If you did not read the thread, here’s a TLDR: Trump’s trade war is making life tough for small businesses, China isn’t paying one cent of the tariffs, and I will be hit with tariffs next month.
“Trade wars are good and easy to win.”
Meanwhile, the Peterson Institute comments:
The typical effect of an import tariff is to raise prices. For imported inputs like semiconductors or steel, these taxes mean higher costs for American businesses that use them to then provide other goods and services. Because Trump’s tariffs to date have focused on these imported parts, the main impact on the US economy has arisen through American companies finding it more difficult to compete with firms in other countries that do not face these tariffs on their inputs. And different US firms react in different ways. Some pass along the higher costs to end consumers in the form of higher prices. Others choose to earn lower profits, or to cut costs elsewhere, including by keeping wages low.
The channels through which the US economy is affected by Trump’s tariffs may change with the September 1 duties. Imposing tariffs directly on consumer products may mean that households see price increases even more quickly than has been the case thus far….
These next two rounds of tariffs will nearly double the coverage of affected products. The September 1, 2019 tariffs on $112 billion of Chinese imports will increase product coverage to 68.5 percent of all US imports from China. And the 10 percent tariffs on another $160 billion of new products on December 15 will result in 96.8 percent of US imports from China being affected by Trump’s extra tariffs…. There is no good news in these tariff announcements. The only minor consolation comes in their timing. By putting off the next two rounds until the import surges have already arrived to stock this year’s back-to-school and winter holiday shopping seasons, President Trump may be coming around, albeit belatedly, to the economic evidence on the costs of his trade war. Thus far, it is American consumers and companies—and not China—who are bearing the burden of his tariffs.
And the academic evidence is piling up too:
We analyze the impacts of the 2018 trade war on the U.S. economy. We estimate import demand and export supply elasticities using changes in U.S. and retaliatory tariffs over time. Imports from targeted countries declined 31.5% within products, while targeted U.S. exports fell 11.0%. We find complete pass-through of U.S. tariffs to variety-level import prices. Using a general equilibrium framework that matches these elasticities, we compute the aggregate and regional impacts. Annual consumer and producer losses from higher costs of imports were $68.8 billion (0.37% of GDP). After accounting for higher tariff revenue and gains to domestic producers from higher prices, the aggregate welfare loss was $7.8 billion (0.04% of GDP). U.S. tariffs favored sectors located in politically competitive counties, but retaliatory tariffs offset the benefits to these counties. We find that tradeable-sector workers in heavily Republican counties were the most negatively affected by the trade war.
But again, does the evidence actually matter? Maybe not to politicians in power but markets, the fierce honey badger that doesn’t care about powerful wishes, are responding as one might expect.
Jeffrey A. Tucker
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Gas and Apparel Pull Everyday Prices Down in November
AIER’s Everyday Price Index fell 0.1 percent in November after posting a 0.4 percent increase in October. The Everyday Price index has fallen in four of the last six months. The Everyday Price Index measures price changes people see in everyday purchases such as groceries, restaurant meals, gasoline, and utilities. It excludes prices of infrequently purchased, big-ticket items (such as cars, appliances, and furniture) and prices contractually fixed for prolonged periods (such as housing).
The Everyday Price Index including apparel, a broader measure that includes clothing and shoes, decreased 0.3 percent in November after a 0.3 percent rise in October. The Everyday Price Index including Apparel has fallen in three of the past six months. Apparel prices fell 2.5 percent on a not-seasonally-adjusted basis in November and are down 1.6 percent over the past year. Apparel prices tend to be volatile, registering sporadic large gains or declines in between stretches of relatively steady prices.
The Consumer Price Index, which includes everyday purchases as well as infrequently purchased, big-ticket items and contractually fixed items, fell 0.1 percent in November, matching the decline in the Everyday Price Index. The Everyday Price Index is not seasonally adjusted, so we compare it with the unadjusted Consumer Price Index.
Over the past year, the Consumer Price Index is up 2.1 percent. Over the same period, the Everyday Price Index has risen 1.2 percent while the Everyday Price Index including apparel is up 0.9 percent. The modest increases in both indexes over the past year are largely due to weak energy and grocery store prices.
Motor-fuel prices fell 1.1 percent for the month on a not-seasonally-adjusted basis. Over the past year, motor-fuel prices are off 1.3 percent. Motor fuel prices are largely a function of crude oil prices. West Texas Intermediate crude oil prices fluctuated dramatically from mid-2017 through mid-2019, rising to a peak above $75 per barrel in October 2018 before plunging to less than $45 by December 2018. Crude prices have been relatively stable since May, bouncing around in a range of $50 to $60.
Grocery prices fell 0.3 percent in November and are up just 1.0 percent from a year ago. Over the last five years, grocery prices are essentially unchanged.
The components with the largest weights in the Everyday Price Index are food at home (weighted 20.8 percent and declining 0.3 percent in November), food away from home (17.6 percent and a 0.2 percent rise), household fuels and utilities (13.3 percent and a 0.3 percent drop), and motor fuel (11.8 percent with a 1.1 percent decrease). Together, these four categories account for 63.5 percent of the Everyday Price Index.
Overall, net changes in the Everyday Price Index remain modest. Energy prices are the most volatile component and have been, on balance, a negative contributor in recent months. Grocery prices (food at home) have also been rising at a slow pace and stand in sharp contrast to restaurant prices (food away from home) which have been rising more quickly and persistently. Apparel prices also remain volatile but in general have been a negative contributor. Other smaller components have had significant but largely offsetting trends. Notably, gardening and lawncare services prices are up 8.4 percent from a year ago, while tobacco products have risen 5.5 percent, postage and delivery services are up 5.4 percent, recreational reading materials are up 4.9 percent, and pet and pet products are up 3.3 percent. Partially offsetting these were audio discs and tapes, down 2.6 percent and video discs, down 2.5 percent. Several other smaller components have increases close to zero.
Robert Hughes
Related Articles – Everyday Price Index
Manual Labor Will Be Revived
In a previous column, I looked at the way automation and AI are likely to transform the world of work and employment. There is a lot of discussion about this, most of which focuses on the likely impact in terms of the kinds of paid work that will disappear. What there is much less of is discussion of the new kinds of paid work that will come into being.
If the result of automation is to create jobs more than to destroy them, then what kinds of work are likely to expand in the future? This is related to but distinct from the first question. In one way, this is a very hard question to answer. Many of the new kinds of employment that will appear are literally unimaginable — if we could imagine them, they would already exist.
Back in the 1980s, nobody could have told people worrying about the decline of jobs in the steel industry that there would be work designing apps for mobile phones, for example. So we can be confident that new kinds of work will appear but have no idea about what it will be — it’s for entrepreneurs to invent and discover that.
However, we can do some thinking about it because while the details may not be clear, there are cases where we can have a strong notion as to what will appear. In the 1900s, for example, there were a large number of jobs associated with horses, at that time still the main power for transport. Almost all of them were gone by 1930, but people could guess that a lot of new work would be created servicing and supporting (as well as producing) the motor vehicles that were replacing horses. Thinking like this about the present situation should lead us to a number of conclusions and to one in particular that many will find both surprising and heartening.
At-Risk Jobs
If you read the various studies that have been done over the last five years, there is widespread agreement about the kinds of jobs that are “at risk.” A recent study by the Brookings Institution estimated that 25 percent of current US jobs are at greater than 50 percent risk of automation. Some are not surprising. Any job that is both boring and repetitive is likely to be at risk. You might suppose that this would mean low-paid manual occupations would be at high risk, and indeed many are — shelf stacking, waitressing, and data entry are all at high risk.
On the other hand, many better-paying jobs are at considerable risk of disappearing. A range of jobs in the transport industry, from truck and taxi drivers to train and bus drivers, are likely to go in the medium term because of the rise of autonomous vehicles (most new metros around the world already have driverless trains). A wide range of clerical and administrative tasks are also likely to be handed over to algorithms, from financial services to company administration and financial advice.
The last example brings up another point. A recent study by the OECD argued that jobs involving face-to-face contact were more likely to survive — which suggests a rosier future for financial advisors. However, experience suggests this is actually not true. When the ATM was introduced, some argued that it would not catch on because customers preferred the human interaction with a teller. Experience suggests that actually the opposite was the case. The same is likely to be true in a range of occupations and not just financial advice and wealth management.
The common factor is that these are activities that can be readily reduced to a tick list of standard questions and hence an algorithm. Routine medical care and diagnosis is one; another is most standard legal work. This suggests that the risk of automation is actually high for many professional occupations such as medical general practice and routine attorney work. In the future, we will probably consult an algorithm rather than a human doctor or lawyer or accountant. However, surgery and nursing are still almost certain to be done by flesh and blood humans.
That particular example can lead us to the surprising and heartening conclusion mentioned earlier. Much of the commentary argues that we are moving into a world where the labor market will be dominated by two kinds of employment. There will be creative jobs that are open to highly educated people and which pay very well, and there will be unskilled and low-productivity jobs (hence low paying), but there will not be a range of middle-skill jobs that pay a decent or even high wage. The view is captured in the title of Tyler Cowen’s work Average Is Over. This has a number of alarming implications, most notably that access to high-paying work is going to become even more dependent than it already is on higher-education qualifications. We should be more sanguine, however.
A Heartening Conclusion
Economic theory, confirmed by empirical research, tells us that people will in general only adopt a new technology when the expected gain from doing so is greater than the cost (technically, when the marginal gain exceeds the marginal cost). This means there are many things that are technologically feasible that do not happen because they do not pass the test of their benefit being greater than their cost.
One example is supersonic passenger flight. This is certainly technically feasible — we know this because two such aircraft were in commercial service for some time. However, there are none now and no prospects for any. The reason, as Boeing discovered while trying to develop a supersonic transport, is that the benefit (getting from London to New York in three hours rather than seven, for example) is not valuable enough to consumers to exceed the costs of such an aircraft, which are due to the technology available and the unavoidable challenges of traveling at such a speed in the Earth’s atmosphere in a way that will meet standards of comfort and safety for passengers. (Military personnel have a different set of criteria, which is why supersonic combat aircraft are commonplace; plus, the buyers of such aircraft, namely governments, are not as price sensitive as airlines.)
One classic example of this is the artificial reproduction of manual dexterity or, to put it another way, of the combination of the human hand with the human brain and the complex feedback and control system (touch and sight) that connects the two. Despite much effort and research, this has proven incredibly difficult to reproduce artificially. Consequently, for most tasks involving manual dexterity and manipulation, it is still cheaper to use a human rather than a robot, and this seems likely to be the case for a long time. This explains why nursing and surgery are both at very low risk of being automated by everyone’s estimation, despite the fact that most surgical procedures and nursing tasks are standard and routine in many ways.
Manual Trades and Personal Services
So, there is a wide range of tasks and work that will not be automated because of this. However, the response might be that the kinds of jobs this applies to are precisely the low-productivity and low-skill jobs mentioned earlier, such as cleaning. Certainly, this is true, but it is not the whole truth. There is also a wide range of work involving manual dexterity that is skilled and highly paid, and the likely impact of AI will actually be to make that kind of work more productive and hence higher paid. Meanwhile, other foreseeable changes will increase the demand for these kinds of work and hence the number of employment opportunities, even allowing for the increase in productivity of individual workers.
This kind of work is that of skilled manual trades such as plumbing, painting and decorating, electricians, and construction work of all kinds. Another is personal-service work such as personal trainers or coaches. Teaching and researching are other examples (at the moment, these are thought of as jobs that require a degree, but that is more about rationing access than reality). Manual trades, for example, are very difficult because of the need for close-up manipulation — a robot that could do an electrician’s or plumber’s job would be seriously expensive.
At this point, another feature of innovation comes into play. What much innovation does is not so much replace human labor as enhance it and make it more productive. AI and associated control systems are a classic example of this. You will still need the manual dexterity of the surgeon or plumber, but the AI and associated technology will increase the range of things that they can do and make them much more effective. In other words, it will increase the value of the service they provide as well as the quantity per unit of time worked — which is the real definition of increased productivity. This translates into higher incomes for people delivering this kind of service.
Moreover, the demand for this kind of labor and service (as well as the others mentioned) is almost certain to increase. For one thing, the people earning very high incomes doing creative knowledge work will want to employ those providing these services in very large numbers (not least because the principle of comparative advantage means it makes sense for them to do this so they can concentrate on their own work). Another feature of AI is that it will make it much cheaper to personalize skilled work and services and so make it more valuable to the end consumer.
What we are likely to see, in fact, as well as the disappearance of a range of familiar jobs, is a revival in the value (and maybe the status?) of manual trades and personal services of all kinds. These will also become higher paying than many are at present (some, of course, already pay well). To give just one example, nursing and personal care are going to have their productivity significantly increased, while the demand for such services is going to rise organically because of the rise in the average age.
This will also mean an increase in the kind of work that requires a trade education and a relative decline in the need and demand for academic higher education. That sector will have to find another market to replace or supplement people looking for certification to have a shot at knowledge or creative work — the business of providing education and tutoring as a leisure and consumption good is one possibility.
In fact, one outcome of AI and automation may well be a revival of manual labor and of the traditional working class — maybe becoming more like an artisan class again. It is actually the credentialed and salaried white collar middle class that is more at risk in the years to come.
The overall effect will be massively positive, as economics leads us to expect. Thus a recent study by Price Waterhouse predicts that automation and AI will contribute an additional $15.7 trillion to the global economy by 2030, with a boost to local GDP of up to 26 percent by the same date. We should be sanguine about the impact of this latest wave of innovation, not just in terms of its overall impact on the wealth of the world but also in terms of its likely sociological impact.
Stephen Davies
