The consumer-to-producer temperature gradient predicts leading indicators: a new economic measurement based on physical principles and cause and effect

Abstract The Consumer-to-Producer Temperature Gradient (CPTG) is a completely new leading economic indicator derived in relation to first principles and incorporates human nature into economic theory. We propose that consumer purchasing causes cash to flow from consumer to producer much as heat energy flows from hotter to colder temperatures. Simple equations convert the widely-used Consumer Sentiment Index (CSI) and Purchasing Managers Index (PMI) into the equivalent of Consumer and Producer economic temperatures to determine CPTG. We show that in contrast to these confidence indexes, CPTG as a gradient describes economic expansion and contraction. We use Capacity Utilization (CU), which is both an important leading indicator and a measure of value delivered to society, as a proxy to measure CPTG’s effects. CPTG prediction of CU, serves as proof of concept. Regressions of CU against CPTG lags show that CPTG predicts CU up to four months in advance. Histogram and normal quantile plots expose clusters in the residuals of the regressions. Applying these clusters to formulate a prediction method, we find CPTG forecasts CU with up to a 96% correlation, that is very much greater than either confidence index achieves on its own. The regression analyses for Gross Domestic Product (GDP) and Unemployment Rate (UE) against CPTG data show parallel correlation results that corroborate causality. CPTG also can provide information for assessing results of government fiscal and monetary actions. We expect that both its predictive and responsive capabilities will make CPTG a useful tool to help policymakers choose among actions to moderate disruptive fluctuations in the financial system.