Wage Stagnation and Globalization

William Gladstone wrote in the Wall Street Journal on August 14 that "wage stagnation is everyone's problem." I agree, but I strongly disagree with his analysis of cause and effect. Wage stagnation is a problem for the economy's growth and very much a problem for the people who find their wages stagnating. The challenge is doing something about it. Something that will work.

After looking at many possible causes of wage stagnation, Gladstone quotes a single Federal Reserve Bank of San Francisco publication that attributes 85% of the decline in labor's share to globalization. Since I know that there have been hundreds, if not thousands, of articles written about the many impacts of globalization, it made me wonder why he chose only one single article to support a very extreme claim. I promise I will read that article and get back to you. But today I decided to look at some relevant data and see what it says.

I didn't look at wage data because I know that wages are not the exclusive source of income for most workers. Most of us get benefits at work. Some grocery workers lift a banana now and then, and many of us have retirement and health benefits. When you combine wages and benefits, you get something called earnings. If a worker accepts a better health plan in lieu of a wage increase, one should count that benefit. So earnings is a superior measure of what the employee gains.

I also chose constant dollar earnings because that deflates the earnings figure for changes in the cost of living. The Labor Department deflates earnings with the consumer price index. With constant dollar earnings, we get a pretty good measure of how much the spending power of employees changes over time.

I chose the time period from 2001 to 2018 because Gladstone argued that most of the labor wage problems stemmed from that time period. The data found in the table below come from the US Bureau of Labor Statistics.

BLS loves to collect this kind of data. Among the many economic times series they publish, I found information about constant dollar earnings for a number of occupations and industries. I was hoping by looking at this information I could see if there is a strong case for a large impact of globalization on the earnings of US workers. It is well known and often cited that foreign countries have stolen jobs from America, especially manufacturing jobs.

The table presents data for various US occupations and industries. The numbers for June of 2001 and June of 2018 are called index numbers and represent the levels of constant dollar earnings in those years. The last column presents the cumulative change over those 17 years. At the top is the average for all civilian workers. The table shows that the buying power of wages plus benefits rose by 10.2% over those 17 years. The typical employee in 2018 could buy about 10% more than he could in 2001.

The next part of the table gives similar data for various occupations. The strongest real earnings growth was the 14% increase for the occupation called Office and Administration. The lowest increase was earned by the category called Management, Business, Finance. Other weak growth occupations included Production and Management Professional. While this occupation information has no direct bearing on which industries were impacted the most, it does show that a broad spectrum of employees had less than average earnings growth. Production workers were among that group with less than average buying power increases. But so were many office workers.

The bottom of the table shows changes by industry. Workers at Hospitals and those in Administrative industries did the best while those that produced Goods and Manufacturing did the worst. Aha, you say. See, globalization hurt production workers! But by how much? The average worker saw her buying power increase by 10.2%. Goods producing workers earnings expanded by 9.2%. That is a cumulative difference over 17 years. That means that the buying power of the average worker beat that of the goods producer by 0.06% per year. If the average worker had an increase of $100 in a given year, then the production worker had an increase of $99.40.

Workers in Public Administration firms saw their buying power rise by 16.8% over those 17 years. That is 7.6% more than workers at Production firms. That sounds like a lot but when you look at the average yearly amount the major difference disappears. The gap suggests an improvement of 0.45% per year. If a worker at a Public Administration firm had an increase of $100, then the worker at a Production company would have gained purchasing power of about $99.54.

I redid these calculations several times, and they are correct. The reason why we might disbelieve them is that an increase in the buying power of wages of around 10% over one year is great -- but over 17 years it is tiny. Thus the differences among industries and occupations are even tinier. Maybe globalization did impact production workers -- but the Labor Department tables suggest that average employees of none of these occupations and industries got rich.

I'm not sure globalization had much to do with all that but it is worth pondering the real causes. The US is a very large economy and trade is a relatively minor part. If employee earnings have grown too slowly, we might want to look a little harder at what is causing that. Check out this blog next week. I will offer one explanation then.

Constant Dollar Employment Cost Index As of June in each year

	2001	2018	%     Change
All Civilian Workers	94.5	104.1	10.2
Occupation
Management, Professional	94.6	103.8	9.7
Management, Business, Finance	96.1	104.7	8.9
Sales and Office	94.2	104.3	10.7
Office, Administration	93.6	106.7	14.0
Natl Resource, Constrn, Maint.	93.8	104.4	11.3
Construc, Extraction, Farming, etc	94	104.3	11.0
Installation, Maintenance, Repair	93.6	104.5	11.6
Production	94.1	102.6	9.0
Transportation	95.5	106.6	11.6
Services	95.2	105.4	10.7
Industry
Goods	93.6	102.2	9.2
Manufacturing	93.3	102.1	9.4
Services	94.7	104.5	10.3
Education	93.5	103.9	11.1
Healthcare and Social Assistance	93.5	103.6	10.8
Hospitals	90.9	104	14.4
Public Administration	91.4	106.8	16.8
https://www.bls.gov/web/eci/ecconstnaics.txt

Wage Growth in a Tight Labor Market

Much has already been written about the employment report for May 2018 that was published on Friday, June 1. The unemployment rate, like your friendly mole, once again dug deeper and went to an 18-year low of 3.8%. This means that the labor market is growing tighter, which means that firms are finding it harder to find the right employees. There are many articles being written now about this business challenge as firms use innovative ways to try to attract new employees or to hold on to existing ones. Of course, a common approach to attracting and keeping workers is raising wages and benefits. 

Wages, therefore, become a critical economic variable these days. This week I decided to look at wage behavior in the USA to see if there are signs of firms using wages to ameliorate labor market tightness. The graph at the bottom looks at monthly percentage changes in average earnings for all employees. 

Reading graphs is definitely an art form. I ain't Picasso but let's give it a shot. Each dot on this graph records how much earnings grew in that month. If you go to the very last dot on the graph, it says that in May of 2018 earnings grew by 0.298 compared to the value in April of 2018. The one-month percentage change was 0.298%. For sake of our eyeballs, let's round up and call that a one-month increase of about 0.3% in May. If that one-month increase lasted for a full year, then wages would increase by about 3.6%. 

That's a big if and is only suggested so that we can put the one-month gain into an annual perspective. If Lebron scored 12 points in the first quarter of a game, he scored 12 points! But we could say something like -- dude, that's like scoring 48 points in a whole game. Wow. Groovy. He may or may not score 48 in that game but the 48 gives us another way of understanding the 12 he did score in Q1. 

Whew. I am thirsty. So if you read the above, you know that the 0.298 increase in May of 2018 is about a 3.5% annualized increase. That sounds pretty good. If the cost of living went up by 2% in May, then you might be happy that your wages grew faster than your expenses. 

The reason I placed the whole graph below is that we can evaluate the most current increase better by looking at past changes. This graph has monthly ups and downs from April of 2006 to May of 2018, so we can compare over a 13-year period. My task today is to evaluate the 0.298 of May 2018. 

Is it the highest point on the graph? 

     Absolutely not. Just in the last couple of years there were many months that had stronger growth in earnings. 

Is it the lowest point on the graph? 
     Absolutely not. There are even more months in which earnings grew much slower than 0.298. 

Is there any pattern to the monthly changes? 
     It looks like whack-a-mole to me. Most ups are followed swiftly by downs and vice versa.

Do you observe an upward or downward trend in the dots? 
     From about April 2006 through June 2010, there seems to be a downward trend. That is, on average, wage growth seemed to decline. Wages were growing but at a slower pace.  
     But from June 2010 to about October 2011, the wage growth picked up. From my eyeball, it appears that the average monthly percentage change during that time was about 0.2 or an annual rate of about 2.4%. 

     Then from 2012 to now, there appears to be no discernible trend change in earnings. For six years, we got ups and downs around a mean that suggests wage change at about 2.4% per year. If you removed the crazy negative data point in October of 2017, you might see some increase in trend starting around October of 2016. Of course, you might also see pink elephants.

Why go through all this madness? Because there is nothing like the data. You will see a lot of interesting and intelligent articles about wage change in the USA. Smart people will discuss the May data point and tell you that the 3.5% growth in May is higher than the 2.4% rate that prevailed over the last eight years. These folks may want to convince you that wages are spiraling higher -- and maybe they are. But looking at this graph from beginning to end does not make me very confident that we are on a new upward trend. I remain skeptical that the 3.5% means much of anything. I wonder what we will learn in July about June. 

Are Wage Gains Ready to Skyrocket?

Most people take for granted that wages have shown lackluster growth over the last 20 years or so. So I put my data cap on and starting looking at numbers. My first takeaway is that there are way too many numbers. We might want to know how wages have kept up with productivity. That seems reasonable. But then one needs to find companion series for wages and productivity, so we can compare apples with apples. That can be done but do we want to compare these series for all workers? For all manufacturing workers? For medium-income workers? Over how many decades?

Another comparison of wages could focus instead on how wages changed compared to prices – that is, did wages keep up with inflation? Again, there are many indicators from which to choose – various measures of wages and even more measures of inflation. To makes matters even more challenging – some of the series go back to 1929 while others just got started in 2006.

What I am saying here if it isn’t obvious is that it is time for a nice cold JD. It is also time to make some decisions. No matter which choice I make some of you will want to scold me. But I made a decision anyway. I decided to focus on the years from 1968 to 2017. Going back to 1968 means we have a rich enough data set so that we can put today’s low inflation numbers in perspective with past times when US inflation was higher. I also decided to use the CPI as my inflation variable. Earnings of Production and Nonsupervisory Workers in the Business Sector is my measure of wages.

What I examined is how earnings kept up with inflation during the past half-century. To do this I calculated three times series –  % change in earnings (Edot), % change in prices (Pdot), and % change in the buying power of the earnings (calculated as the first series minus the second one (Edot minus Pdot)). For example, in 1970 the % change of earnings was 6.1%. Prices rose by 5.6%. Therefore the buying power of the earnings rose by 0.5% (6.1-5.6) in 1970. 1970 is an example of a year when earnings did quite well. The wage increase of these production and nonsupervisory workers was larger than the increase in the cost of living.

As I look down my table (below) I notice there are lots of years when the buying power of earnings was positive while there were also years when workers did not keep up with inflation (buying power of earnings was negative). When the buying power of earnings was negative – it meant that workers were getting behind – and that they might at some point want to catch up. 

The earnings buying power went down considerably from 1973 to 1975 and then again from 1978 to 1981. In those years inflation was hitting double digits and despite some good years of earnings growth – these earnings just couldn’t keep up with inflation. In 1980 earnings rose by almost 9% but since inflation was 12.5% workers fell behind. And strangely enough, it was not until 1995, after the inflation rate had fallen considerably that earnings began rising faster than inflation. The years 1995 to 2002 were catch-up years. During those years earnings rose a total of about 10 points more than inflation.   

Between 2003 and 2012 there was no real pattern. But then between 2013 and 2017 there was a very clear pattern – and brace yourself for this – wherein inflation  generally stayed below 2% per year – wages of production and non-supervisory workers were rising by about 2.4% per year. Thus, earnings were catching up as the buying power of earnings increased. 

There are lots of ways to go from this point. But let’s not forget one thing. While workers always want higher wages – the thrust for higher wages is often driven by how far wages stretch to buy goods and services. This data suggests that while there have been times when the buying power of the wages declined (in the 1970s and then from the mid-80s to the mid-90s) – the last 15 years cannot be classified as a time when inflation robbed workers of their buying power. Especially the last 15 years show just the opposite. Workers might not love the size of their wage increases – but these increases have been well above the inflation rate. And therefore, there is no clear pent-up explosion of wage increases looming around the corner.

As I said above, there are lots of ways to go from here. I am not saying that all workers are just fine. I am not saying there are no labor market issues to deal with. What I am saying is that the rate of growth of earnings compared to the cost of living is important for understanding future wage and price growth. The earnings of production and nonsupervisory workers in the USA might not be growing rapidly but they have, of late, been growing faster than the cost of living. That needs to be factored into our forecasts for the future. 

Table

	Earnings			CPI						Edot -
Year	Dec			Dec		Edot		Pdot		Pdot
1968		3.11	35.5
1969		3.30	37.7		6.1		6.2		-0.1
1970		3.50	39.8		6.1		5.6		0.5
1971		3.73	41.1		6.6		3.3		3.3
1972		4.01	42.5		7.5		3.4		4.1
1973		4.25	46.2		6.0		8.7		-2.7
1974		4.61	51.9		8.5		12.3		-3.9
1975		4.87	55.5		5.6		6.9		-1.3
1976		5.23	58.2		7.4		4.9		2.5
1977		5.61	62.1		7.3		6.7		0.6
1978		6.10	67.7		8.7		9.0		-0.3
1979		6.57	76.7		7.7		13.3		-5.6
1980		7.13	86.3		8.5		12.5		-4.0
1981		7.64	94.0		7.2		8.9		-1.8
1982		8.02	97.6		5.0		3.8		1.1
1983		8.33	101.3		3.9		3.8		0.1
1984		8.61	105.3		3.4		3.9		-0.6
1985		8.87	109.3		3.0		3.8		-0.8
1986		9.01	110.5		1.6		1.1		0.5
1987		9.28	115.4		3.0		4.4		-1.4
1988		9.60	120.5		3.4		4.4		-1.0
1989		9.98	126.1		4.0		4.6		-0.7
1990		10.35	133.8		3.7		6.1		-2.4
1991		10.64	137.9		2.8		3.1		-0.3
1992		10.90	141.9		2.4		2.9		-0.5
1993		11.18	145.8		2.6		2.7		-0.2
1994		11.47	149.7		2.6		2.7		-0.1
1995		11.81	153.5		3.0		2.5		0.4
1996		12.25	158.6		3.7		3.3		0.4
1997		12.76	161.3		4.2		1.7		2.5
1998		13.22	163.9		3.6		1.6		2.0
1999		13.70	168.3		3.6		2.7		0.9
2000		14.29	174.0		4.3		3.4		0.9
2001		14.75	176.7		3.2		1.6		1.7
2002		15.21	180.9		3.1		2.4		0.7
2003		15.47	184.3		1.7		1.9		-0.2
2004		15.86	190.3		2.5		3.3		-0.7
2005		16.36	196.8		3.2		3.4		-0.3
2006		17.05	201.8		4.2		2.5		1.7
2007		17.69	210.0		3.8		4.1		-0.3
2008		18.38	210.2		3.9		0.1		3.8
2009		18.84	215.9		2.5		2.7		-0.2
2010		19.22	219.2		2.0		1.5		0.5
2011		19.56	225.7		1.8		3.0		-1.2
2012		19.89	229.6		1.7		1.7		-0.1
2013		20.34	233.0		2.3		1.5		0.8
2014		20.73	234.8		1.9		0.8		1.2
2015		21.25	236.5		2.5		0.7		1.8
2016		21.78	241.4		2.5		2.1		0.4
2017		22.31	246.5		2.4		2.1		0.3