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With the Office of the U.S. Trade Representative announcing the increase of tariffs on imported Chinese goods from 10 percent to 25 percent on $200 billion worth of goods, and a directive from the executive branch to increase tariffs on an additional $300 billion in Chinese goods, how will publicly traded companies’ earnings be impacted?

According to a May 10 press release from the office of the United States Trade Representative (USTR), tariffs of 10 percent on imported Chinese goods, consisting of $200 billion, increased to 25 percent. The press release also indicated that the remaining amount of Chinese imports, about $300 billion, will now be subject to tariffs. Based on a June 14 USTR press release, hearings on implementation of the additional tariffs on Chinese goods will be held during the second half of June. This, as the press release notes, is being considered in addition to the pre-existing $250 billion in Chinese tariffs.

Based on a recent publication from the International Monetary Fund (IMF), the United States-China trade war has had an ongoing impact on both U.S. businesses and consumers of Chinese imports. When it comes to Chinese imports headed for the United States, there has been a record amount of American importers increasing their orders to hedge tariff rate increases or additional products subject to tariffs.

The IMF’s piece found that increased tariff costs have been passed onto consumers by American businesses in some instances. One example the piece noted is increased consumer prices of washing machines due to increased tariffs on Chinese imports. In other instances, however, companies have decided to accept reduced profit margins versus increasing the prices of other imported Chinese goods subject to higher tariffs.

How This Impacts Consumer Spending

Analysis of recent economic data reveals that American households consume between 1.5 percent and 2.5 percent of goods imported from China. Using midpoint of 2 percent and a mean consumption rate of $60,000 per American household, the additional tariffs would cost a minimum of $300 more per household for the same imported Chinese goods. 

According to a Trade Partnership study conducted in February 2019, the calculation of Chinese steel and aluminum tariffs plus the 25 percent rate of the initial $250 billion of imported Chinese goods – would result in the average American household spending $767 more.

When it comes to recent and longer-term consumer surveys, the news is mixed; however, it doesn’t portend well over the long-term, especially if the trade issues persist. This is based on survey results from the University of Michigan for June 2019.

The survey found that “consumer sentiment” fell after May’s gain because of both a slower increase in job production and the tariff situation, including the real potential for Mexican tariffs and ongoing Chinese trade issues. It also found that many consumer respondents thought the nationwide economic growth would slow, thereby creating fewer new jobs.

This trend is evident from the survey. In June of 2018, 40 percent of respondents looked poorly at tariffs, compared to 21 percent of those surveyed in May 2018, and 35 percent in July 2018. The respondents similarly indicated, without prompting, that 19 percent of consumers would buy ahead of tariff implementation during the start of June 2019, compared to only 12 percent doing so in May 2019, and 21 percent of those surveyed doing so in March of 2018. Overall, “real personal consumption expenditures” is expected to increase by 2.5 percent in the year ahead.    

The survey’s Sentiment Index improved because consumers said they’re planning to make more “large household durables” purchases sooner to stave off the impact of increased tariffs. This aligns with other experts referenced but can be argued as pulling demand ahead with the potential for fewer future sales.

While there’s no way to predict future sales, for companies reliant on Chinese imports and consumers facing higher costs due to tariffs, consumer sales could very well be lower in the future.

During the first three months of 2019, non-farm labor productivity grew 3.6 percent, according to the U.S. Bureau of Labor Statistics. This is coupled with a 4.1 percent increase in output, along with hours worked increasing by one-half of one percent. Comparing the rates from 2019’s Q1 to the first three months of 2018, productivity grew by 2.4 percent, year over year. Looking at the trend over 12 months, the BLS reported a 3.9 percent uptick in output and a 1.5 percent uptick in hours worked. 

With the BLS defining the non-farm business sector accounting for nearly four-fifths (77 percent) of America’s gross domestic product, it’s still noteworthy to see what it doesn’t include. It doesn’t account for government entities, households, farms and non-profits that deal with individuals.

Understanding the Measure of Productivity

The BLS defines a few terms relevant to how it can and will impact a business’ profitability. When it comes to labor productivity – alternately defined as hourly production – this measure is determined by taking an index of real output and dividing it by a pre-determined number of hours from employees, business owners and non-compensated family workers.

Specifically, unit labor costs dropped by 0.9 percent for the non-farm business sector during Q1 of 2019, despite growing 0.1 percent during the past 12 months. This, the BLS notes, is the slowest four-quarter increase – compared to 2013’s 1.7 percent drop in the fourth quarter.

The federal department looks at unit labor costs as how much individuals are paid per hour compared to how much they produce per hour. The more individuals are paid, the higher the unit labor costs, while higher output per hour lowers this ratio.

The BLS provides an interesting illustration of past improvements in labor productivity and what it might mean for the future of work. In the piece, “What can labor productivity tell us about the U.S. economy?” it mentions that Americans clocked in 194 billion hours in both 2013 and 1998. This figure is noteworthy because in the 15-year time frame, with the U.S. population growing by 40 million, the American economy added $3.5 trillion in increased output, despite the same number of hours worked.

An example from the BLS shows how a car factory goes from making 30 cars an hour compared to a previous 20 per hour capacity, resulting in a 50 percent gain. This increase in efficiency comes from a factory upgrade and additional employee training, which translates into labor productivity growth.

The December 2016 White House report titled “Artificial Intelligence, Automation and the Economy” explains how increased productivity has impacted workers and business owners over time.

The report found that beginning in the mid-1970s, the lowest 90 percent of American households saw their incomes drop from two-thirds to 50 percent of all U.S. income. While American workers became more productive, the report found that for low- and middle-income American workers, wages didn’t increase accordingly.

Beginning in about 2000, it found profits of corporations growing as a percentage of GDP. In contrast, workers’ share of GDP started to fall, albeit reversing very recently. The report found in 2016 corporate profits were just under 65 percent of GDP, compared to approximately 58 percent of GDP for the non-farm labor share.

While innovation and using technology for greater efficiency is nothing new and artificial intelligence (software and smart machines) becomes more capable of assisting less skilled workers increase labor productivity, this signifies an overall trend to make jobs less complex, and therefore able to command less compensation.

Examples could include entry level accounting professionals using tax software (supervised by certified professionals) or medical imaging technicians aided by software (supervised by radiologists) to make diagnoses, saving time to complete bulk work. While software and artificial intelligence engineers are on the higher end of the workforce, it’s expected that more work in the future will be deskilled, and result in lower pay.  

If these trends are predictive of the future, the U.S. economy will see greater efficiency and bigger corporate profits.