STEVEN W. KOHLHAGEN | Former Professor of Economics, University of California, Berkeley
D. SYKES WILFORD | W. Frank Hipp Distinguished Chair in Business Administration, The Citadel

Mismeasured GDP is now the norm. In a period when policy implications for inflation, new structures in monetary and fiscal policies, and the efficacy of historical models of policy are being argued, with hyperbole, it is time to move away from the narrow, typical GDP-centered economic analysis to look holistically at the measurement problem. The COVID-19 shock has led to multiple mini-shocks and numerous policy actions while at the same time the Third (and maybe Fourth via AI) Industrial Revolution is taking place. Responses to shocks are often driven by historical measures of GDP and the ancillary issues of inflation, productivity, and economic wellbeing. Unfortunately, they are likely based upon incorrect, badly measured data. 

This paper discusses these measures, the problems associated with them, and the implications arising from mismeasurement. It points out that while macroeconomic models are calculus-based and can, thus, be used effectively to analyze and predict what will happen to, say, GDP if there is a small change in an independent variable, they are absolutely ineffective in predicting what will happen if there is a massive pandemic or a series of massive exogenous government actions. It further suggests that the actual real economic output being experienced in the United States and the advanced economies is terribly underestimated and concludes with policy and forecasting dilemmas created by the lack of reliable measures for output, inflation, productivity, the actual state of the economy and the ineffective forecasting ability of macroeconomic models in a period of massive shocks.