Personal Consumption Expenditures and the Stock Market

A reader, citing the book Ahead of the Curve by Joseph Ellis, inquired about the hypothesis that consumer spending drives economic cycles and is therefore a leading indicator for the stock market. For example, Mr. Ellis presents a chart relating quarterly annualized change in Personal Consumption Expenditures (PCE) to quarterly S&P 500 Index return and states: “Most bear markets…proceed as (the rate of growth in) consumer spending continues to slow, and are largely over by the time recessions…are under way. Conversely, most bear markets end…when consumer spending and S&P 500 profits are at, or even prior to, their worst Y/Y comparisons.” Does PCE usefully predict stock market behavior? The Bureau of Economic Analysis (BEA) releases seasonally adjusted, annualized total PCE monthly with a lag of about one month (Summary Table 2.85, Line 1: “Personal Income and Its Disposition, Monthly”). Using this series and monthly S&P 500 Index levels for January 1959 through January 2012 (636 months), we find that…

The following chart compares the behaviors of seasonally adjusted PCE and the S&P 500 Index over the entire sample period on logarithmic scales. Although both series generally rise over time, the large mismatch in volatilities makes it very difficult to discern any tradable relationship between them.

For a closer look, we compare monthly changes in the two variables.

The following scatter plot relates monthly S&P 500 Index return to two-month lagged change in PCE over the entire sample period. The two-month lag accounts for the delay an investor experiences in acting on PCE releases. For example, BEA releases PCE for January at the end of February, so an investor reacting to the release could invest accordingly starting in March. The Pearson correlation between the two series is -0.05 and the R-squared statistic 0.00, indicating that changes in PCE explain none of S&P 500 Index returns two months hence.

Might changes in PCE reliably predict stock market behavior at some other horizon?

The next chart plots Pearson correlations for various lead-lag scenarios between monthly change in PCE and monthly S&P 500 Index return, ranging from stocks lead consumption by 12 months (-12) to consumption leads stocks by 12 months (12) over the entire sample period and since 1990. Results suggest that:

• The stock market may lead PCE positively by one to six months, with an advancing (declining) stock market stimulating (depressing) consumption. This effect is elevated in the recent subsample.
• PCE may modestly lead the stock market by a month, but any such effect is not exploitable due to the release delay. The first exploitable relationship is month 2.

To investigate non-linearities in the relationship, we consider average stock market return by range of ranked changes in PCE.

The next chart shows average S&P 500 Index monthly return by quintile of monthly change in PCE lagged by two months over the entire sample period (123 observations per quintile) and two equal subperiods (63 observations per quintile). The average monthly return for all months in the sample is 0.6%.

Results suggest that the lowest (most negative) changes in PCE indicate a relatively strong stock market during the month following release. A possible interpretation is that the stock market is rebounding after poor returns that preceded the worst PCE announcements. However, lack of systematic progressions across quintiles and inconsistencies between subperiods undermine belief in a reliable relationship.

Might quarterly data be more useful than monthly due to some cumulative effect?

The following scatter plot relates quarterly S&P 500 Index return to quarterly change in PCE, lagged to account for release delay, over the entire sample period (212 quarters). The Pearson correlation between the two series is -0.03 and the R-squared statistic 0.00, indicating that changes in PCE explain none of S&P 500 Index returns over the next actionable quarter.

Might changes in PCE reliably predict stock market behavior at some other horizon?

The final chart plots Pearson correlations for various lead-lag scenarios between quarterly change in PCE and quarterly S&P 500 Index return (with release delay), ranging from stocks lead consumption by six quarters (-6) to consumption leads stocks by six quarters (6) over the entire sample period and since 1990. Results generally confirm those above for monthly data, with stock market behavior understandably affecting future consumption. There is no indication that PCE releases usefully predict stock market behavior.

In summary, evidence from simple tests does not consistently support a belief that changes in Personal Consumption Expenditures usefully predict stock market returns at monthly and quarterly horizons. The strongest indication is that stock market returns are above average during the month after announcement of relatively weak PCE growth.

Cautions regarding findings include:

• Retroactive adjustments to PCE data may confound measurement of its predictive power for stocks.
• This analysis does not rule out the possibility that surprises in PCE, relative to some measurable expectation, more usefully forecast stock market returns.
• The subsample since 1990 is small in terms of number of economic cycles.

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