Abstract

Governments use direct transfers as a fiscal measure to stimulate economic activities during shocks. As COVID-19 continues to ravage economies globally, governments worldwide have responded with fiscal and monetary policies to manage the pandemic’s economic impact. In addition, the U.S. government has intervened with direct transfers to provide liquidity to prevent a prolonged shock. However, opinions are divided on the efficacy of the Keynesian stimulus policy. This study used a mixed-method research design to analyze the classical Keynesian model and compares it with the monetarist model to provide insight into the stimulus policy outcomes of the Coronavirus Aid Relief and Economic Security (CARES) Act of 2020 and subsequent policies used to manage the COVID-19 shock. Time-series data from the Bureau of Economic Analysis (BEA), Bureau of Labor Statistics (BLS), and the Federal Reserve Bank (the Fed) of the percentage changes in GDP, disposable personal income (DPI), and personal consumption expenditure (PCE), as well as unemployment rates (UR), interest rates (INT), and inflation rates (IFL), were collected and analyzed. The study used multiple regression (MR) to empirically examine the variables' relationships to ascertain both models’ short-term efficacy. The results suggest that DPI, PCE, and UR significantly predicted the percentage change in GDP in the Keynesian model, whereas, UR, INT, and IFL did not substantially predict the change in GDP in the monetarist model.

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