Assessing the Macroeconomic Importance of Gasoline and Vehicle Spending

Technical Report · Sun May 01 04:00:00 EDT 2016

DOI:https://doi.org/10.2172/1281141· OSTI ID:1281141

Santini, Danilo J. ^[1]; Poyer, David A. ^[2]

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1. Argonne National Lab. (ANL), Argonne, IL (United States)
2. Morehouse College, Atlanta, GA (United States)

Vector error correction (VEC) was used to test the importance of a theoretical causal chain from transportation fuel cost to vehicle sales to macroeconomic activity. Real transportation fuel cost was broken into two cost components: real gasoline price (rpgas) and real personal consumption of gasoline and other goods (gas). Real personal consumption expenditure on vehicles (RMVE) represented vehicle sales. Real gross domestic product (rGDP) was used as the measure of macroeconomic activity. The VEC estimates used quarterly data from the third quarter of 1952 to the first quarter of 2014. Controlling for the financial causes of the recent Great Recession, real homeowners’ equity (equity) and real credit market instruments liability (real consumer debt, rcmdebt) were included. Results supported the primary hypothesis of the research, but also introduced evidence that another financial path through equity is important, and that use of the existing fleet of vehicles (not just sales of vehicles) is an important transport-related contributor to macroeconomic activity. Consumer debt reduction is estimated to be a powerful short-run force reducing vehicle sales. Findings are interpreted in the context of the recent Greene, Lee, and Hopson (2012) (hereafter GLH) estimation of the magnitude of three distinct macroeconomic damage effects that result from dependence on imported oil, the price of which is manipulated by the Organization of Petroleum Exporting Countries (OPEC). The three negative macroeconomic impacts are due to (1) dislocation (positive oil price shock), (2) high oil price levels, and (3) a high value of the quantity of oil imports times an oil price delta (cartel price less competitive price). The third of these is the wealth effect. The VEC model addresses the first two, but the software output from the model (impulse response plots) does not isolate them. Nearly all prior statistical tests in the literature have used vector autoregression (VAR) and autoregressive distributed lag models that considered effects of oil price changes, but did not account for effects of oil price levels. Gasoline prices were rarely examined. The tests conducted in this report evaluate gasoline instead of oil.

• Research Organization: Argonne National Lab. (ANL), Argonne, IL (United States)
• Sponsoring Organization: USDOE Office of Energy Policy and Systems Analysis (EPSA)
• DOE Contract Number: AC02-06CH11357
• OSTI ID: 1281141
• Report Number(s): ANL--16/04; 127446
• Country of Publication: United States
• Language: English

Related Subjects

29 ENERGY PLANNING, POLICY, AND ECONOMY
Capital for energy substitution
Cointegration
Consumer debt
Gasoline price
Gasoline spending
Housing equity
Leisure activities
Macroeconomic
Oil wealth effect
Petroleum reserve
Real business cycle
Technology transition
Transport cost
Vector error correction
Vehicle spending