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Published: February 28, 2007

 
 

Joseph Ellis: The Thought Leader Interview

Drivers of Consumer Spending

S+B: If retail drives the economy, and consumer spending drives retail, what then causes consumer spending to rise or fall? Is it the employment rate?
ELLIS:
Not really. This is one of the most interesting issues to emerge from this work. Most of us are so personally invested in the concept that “my job allows me to spend” that we tend to think that jobs are the primary influence on consumer spending. We forget that consumer spending, which is over two-thirds of our economy, also in turn drives employment. So the big question is, “Which leads which?” Well, when we “go to the videotape,” the charts prove that growth patterns in employment lag changes in consumer spending. And this is not so surprising. Workers get hired after business gets good, and they get fired after business turns poor.

My son, Jonathan Ellis, who teaches philosophy at the University of California at Santa Cruz, labeled this phenomenon “asymmetrical circular causality,” meaning that although consumer spending and employment drive one another, one of them — in this case consumer spending — drives the other to a much greater extent and therefore leads the cycle.

The same is true of consumer spending and capital spending. Conservative economists who say that capital spending drives consumer spending are about one-third correct and two-thirds wrong. Yes, when you put up a new plant, you create jobs and wages and, therefore, consumer spending power. But that impact pales relative to the causality that exists in the other direction: the influence of consumer spending on capital spending. Consumer spending represents the demand for goods and services that strain capacity, leading to orders to build those factories and equipment. So, cyclically, capital spending lags consumer spending, and the charts pretty much prove it. Like employment, capital spending tells us where the economy has been, not where it is headed. That role belongs to consumer spending.

I can’t overemphasize this point. If we don’t correctly identify the lagging indicators like employment and capital spending, we are vulnerable to being told that employment or capital spending actually leads the economy. This almost guarantees that we pin our hopes on the wrong, lagging measures, which in turn means staying positive well past the peak of the cycle or negative well past the trough.

S+B: Where do changes in consumer spending come from?
ELLIS:
Of course, consumer spending is affected by hundreds of different factors, from the stock market to terrorism to changes in mortgage rates. The key is to boil your analysis down to the one or two “true drivers,” the factors that have the most consistent influence, cycle after cycle. And there are two primary drivers. The first is the average wages per worker, adjusted for inflation — in other words, the purchasing power of the employed. The U.S. Bureau of Labor Statistics publishes this statistic in a series called “real average hourly wages.” It is a much more significant leading indicator than what people typically pay attention to — the unemployment statistics. The second key driver of consumer spending is interest rates.

S+B: So in any given society, growth in the real average wages is the best predictor of consumer spending and thus of economic growth?
ELLIS:
Cyclically, in the U.S., there is a fairly good leading relationship, and it’s evident from our charts. Now, there are some weaknesses. Because average hourly wages is a pretax measure, changes in taxes affect consumer spending as well.

The Taxi Stand Fallacy

S+B: How can using consumer spending as a point of entry help people in business make better predictions?
ELLIS:
Well, for any company whose business produces machines to manufacture consumer products, it makes sense to say, “What part of consumer spending would drive my piece of industrial production or capital spending? Might I find an analog in the consumer sector to forecast for my industry or even my own company’s sales?” For example, we could take the growth in retail sales of appliances or other metal consumer products, and use that to forecast sales. Companies really need to understand this methodology — the approach to running year-over-year charts of cause and effect that I describe in my book — to adopt it for their own business.

 
 
 
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