My first step was to start tracking economic numbers in terms of year-to-year change. Government bureaus and economists present their data on a month-to-month or quarter-to-quarter basis to show short-term momentum. But if you look at a chart that shows, say, monthly retail sales changes for the last 10 years, or real consumer spending quarter-to-quarter, it looks like a plate of spaghetti. You rarely go two or three periods in a row without a significant change in monthly or quarterly direction. This makes economic reporters optimistic one month and pessimistic the next, and the true underlying trend almost impossible to discern. How often have you heard, “Retail sales rose 1.4 percent last month, after falling 0.6 percent the month before,” with the prior month also having been materially restated?
S+B: The noise of month-by-month ups and downs, in other words, obscures the important signals about economic direction.
ELLIS: That’s correct. But when you take that same data and chart it on a year-over-year basis, you give yourself a 12-month span in which the patterns of change can become apparent. Also, when you measure those data against those of the same period, one year earlier, you eliminate the seasonal adjustment vagaries, which can be considerable and are often filled with errors.
The next important thing is to run pairs of indicators on this year-over-year basis, to see how they rise or fall in sequence. I like to say, “Let’s go to the videotape!” — i.e., the chart — where we can test every thesis about which indicator drives the other. In short, we needn’t wonder. This is just common sense, not rocket science, and yet it’s remarkable how little it’s done on Wall Street or elsewhere.
Starting in the mid-1970s, for example, we compared 45 years of year-over-year rates of change in consumer spending in the United States with year-over-year growth for industrial production. The picture was really consistent. Relatively small ups and downs in consumer spending growth precipitated more volatile ups and downs in industrial production. The effects of the inventory cycle were well known, but the consistency of the sequence and relative volatility were impressive. This was the inventory cycle at work, driving production to fill the pipelines when the economy was accelerating and collapsing when business slowed down. In another chart, we showed that swings in industrial production were leading — by 6 to 12 months — somewhat more volatile swings in year-over-year growth in capital spending, which therefore lags.
And yet there was a whole school of economic thought — and it still exists today, in fact — that states that you can drive the economy, even cyclically, with capital spending.
S+B: Did this approach change the way you thought about research and recommendations?
ELLIS: I realized that the process of forecasting individual industries could be much less random. Every Monday morning on Wall Street, every research department has a meeting of all its analysts. They’ve all been talking to companies for the past week, and this is the big moment when they offer their “real-time analysis.” But typically, the research director will randomly say, “Well, OK, Harry, how did capital spending do last week? And Mary, how did the hotel industry and the airlines do? And Jack, how is retail spending?”
That unsystematic approach misses the consistent sequence in which the cycle passes through our business sectors. In every single cycle, momentum starts in retail and consumer spending and then moves to manufacturing and then to capital spending. The research director should review them in that order. These three business sectors — I didn’t mention services, because it’s much harder to measure — are the backbone of corporate profits. Whatever happens to them will also drive the ups and downs in profit growth. And corporate profits, in turn, drive the employment rate, which is the last indicator in the economy to turn.