Renewable Energy Distribution and Economic Growth in the U.S.

Abstract

This study investigates linear and nonlinear causality among the industrial renewable energy consumption (IREC) sector, the residential and commercial renewable energy consumption (RCEC) sector, the transportation renewable energy consumption (TREC) sector, the electric power renewable energy consumption (EPEC) sector, and real GDP (RGDP) for the U.S. data from 1989 to 2008. The findings show (i) a bidirectional causality between IREC and RGDP, but neutrality among RCEC, TREC, EPEC, and RGDP regarding linear causality; (ii) a bidirectional causality between EPEC and RGDP, and an unidirectional causality among RCEC, TREC, and RGDP concerning nonlinear causality; and (iii) a greater renewable energy consumption demanding share represents a stronger causality relation with economic growth. Based on (i), (ii), and (iii), this work suggests that energy policy formulators could encourage more tax credits or rebates on IREC, TREC, and EPEC sectors to achieve economic growth.

Keywords:

• Renewable energy consumption
• Causality
• Economic growth

Notes

Renewable Energy Consumption and Electricity Preliminary Statistics (2010) from the U.S Energy Information Administration.

² Haar and Theyel (2006)-investigtaed data over 100 interviews with utility managers reveals that production tax credits significantly influence the percentage of renewable energy in a utility's portfolio.

³Most economists use GDP to measure and represent economic growth (Bodie, Alex, and Salan 2001).

⁴The consumption summary of percent source is according to the U.S. Dept. of Energy, “U.S. Primary Energy Consumption by Source and Sector, 2008.”

⁵Renewable energy source represents energy consumption related to biomass, geothermal, hydroelectric power, solar, and wind power.

⁶The commonly used seasonal adjustment packages are those in the X11 family. X11 was developed by the U.S Bureau of the Census and began operation in the United States in 1965. In this paper, we use Eviews software to run X11 seasonal adjustment.

⁷ Baek and Brock (1992) tried a nonlinear Granger causality test to solve the nonlinearity problem. They applied the Monte Carlo simulation and proved that the forecasting performance of nonlinear models is better than the linear one.

⁸Note that the sectoral renewable energy consumption demanding share of IREC, RCEC, TREC, and EPEC are 28%, 10%, 11%, and 51%. EPEC (51%) and IREC (28%) occupy 79% of the amount of sectoral renewable energy consumption demanding share and have bidirectional causality with RGDP. In contrast, the smaller percent occupation of RCEC (10%) and TREC (11%) merely represent a neutral and unidirectional causality with RGDP in linear and nonlinear causality, showing that a greater renewable energy consumption-demanding share represents a stronger causality relation to economic growth.