This line of studies has found that aggregate GAAP earnings are good predictors of future macroeconomic activities, especially GDP and inflation. The mechanism underlying this connection has, however, not been entirely understood till now.
Theory 1: the investment demand hypothesis
One possible theory on why corporate earnings are linked to inflation and GDP growth is based on the idea that higher GAAP earnings prompt companies to increase their demand for production goods, both the stock that the firm intends to re-sell and those goods and services needed to maintain or expand the operating capacity of the firm in question. When many firms in an economy similarly update their investment decisions, the aggregate-level profit shocks cause an immediate impact on the macro-demand for production goods. As the supply of these goods cannot be easily increased in the short term, an inevitable rise in the price of such goods follows. This explanation is known as the investment demand hypothesis.
Theory 2: the consumption demand hypothesis
The alternative explanation focuses on the consumer, rather than the firm. Higher corporate earnings are seen to feed consumption by investors and employees. When a firm is unusually successful, it shares its success with its employees by issuing bonuses. It also shares its success with investors, through increased share prices and dividends. These increase the spending ability of individuals and at the aggregate level, boosts demand for consumption goods. But, as with production goods, the supply of these consumption goods cannot easily be increased in the short term, thus there is an impact on inflation. This explanation is known as the consumption demand hypothesis.
Depending on which hypothesis proves to be correct, a different inflation measure will reflect the impact of GAAP earnings growth on prices. Should the investment demand hypothesis provide the likeliest explanation, then the Producer Prices Index (PPI) would show the most marked reaction. If, on the other hand, the consumption demand hypothesis explains the mechanism linking earnings and inflation, then the Consumer Prices Index (CPI) ought to be where the impact is clearest.
What if it’s just coincidence?
There is, of course, the possibility that neither producer nor consumer prices will show much reaction to changes in corporate earnings, in which case the pre-existing evidence of a link, which we mentioned at the start, may result from coincidence rather than cause and effect.
However, our research shows strong support for the investment demand hypothesis and a weak relationship between earnings growth and consumption. Changes in the PPI are positively impacted by corporate earnings growth in the following one to two months, but there appears to be no significant relationship between earnings growth and changes to the CPI.
In other words, the investment demand hypothesis is the only theory that is well-supported. Even though our findings do not directly support the consumption demand hypothesis, our findings are not to be interpreted as implying that corporate earnings growth does not matter for consumption. Quite the opposite, the increased investments that we observe following a rise in corporate earnings could hardly be justified were there to be no expected rise in future consumption demand.
What is more, the new investment will generate additional returns distributed to investors, who will then be in a position to increase their consumption. The key point is that, in the short term, it is through the investment rather than the consumption channel that the effect of corporate earnings growth on future inflation is transmitted.
Here’s why macro-forecasters get GDP growth forecasts wrong
What can this tell us about the previously documented inefficiencies in the GDP growth forecasts of macro-economists, in particular their failure properly to take into account macro information in aggregate GAAP earnings when forecasting GDP? Well, investment and consumption are two important components of GDP. If, as we find, corporate earnings impact inflation via firm-level investment rather than through increased consumer spending, then it is possible, even likely, that errors in forecasting GDP as a whole arise from inefficiencies in forecasting business investment and forecasting inflation.
We look at the accuracy of macro-economists’ forecasts for investment, consumption and inflation and find that aggregate changes in GAAP earnings reliably predict errors in macro-economists’ forecasts for investment over the next quarter and the PPI during the next two months.
By contrast, there is no pattern of inefficiency regarding their forecasts for consumption or for the CPI.
It’s because of these forecasting errors for investment and the PPI inflation that the corporate GAAP earnings figures can predict macroeconomists’ errors in GDP growth forecasts. Put simply, macroeconomic forecasters are, at least partly, overlooking what the GAAP earnings figures in aggregate can tell them about the course of investment and the consequent impact on the PPI.
Implications for regulators, policymakers and practitioners
Our findings have a variety of implications. Firstly, our findings suggest that practitioners and regulators can make better decisions relying on aggregate GAAP earnings numbers, which can be updated almost daily based on listed corporations’ earnings announcements. The aggregate earnings numbers are more timely and hence more useful for predicting future macroeconomic activities as compared to NEA Corporate Profit figures.
For those charged with creating a non-inflationary climate for sustained economic growth, such as central bankers and finance-ministry officials, our study sheds light on how corporate investment decisions resulting from unexpectedly high or low profits have a macroeconomic impact on near-term demand for production goods and, consequently, on inflation of these goods.
Similarly, macro-economists, armed with a much clearer understanding of the channel through which corporate profitability impacts future macroeconomic data, will be in a better position to incorporate this information in their forecasts to improve accuracy.
This article was originally published at London Business School.
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