Long-run relationship among transport demand, income, and gasoline price for the US

Abstract

Energy used in transport is a particularly important focus for environment-development studies because it is increasing in both developed and developing countries and is largely carbon-intensive. This paper examines whether a systemic, mutually causal, cointegrated relationship exists among mobility demand, gasoline price, income, and vehicle ownership using US data from 1946 to 2006. We find that those variables co-evolve in a transport system; and thus, they cannot be easily disentangled in the short-run. However, estimating a long-run relationship for motor fuel use per capita was difficult because of the efficacy of the CAFE standards to influence fleet fuel economy. The analysis shows that the fuel standards program was effective in improving the fuel economy of the US vehicle fleet and in temporarily lessening the impact on fuel use of increased mobility demand. Among the policy implications are a role for efficiency standards, a limited impact for fuel tax, and the necessity of using a number of levers simultaneously to influence transport systems.

Short-Run and Long-Run Elasticities of Diesel Demand in Korea

“…This can be driven by omitted variable bias. For example, Liddle [6,7] considered vehicle stock in addition to income and fuel price. However, we cannot reject the null hypothesis of no specification error, as discussed above.…”

“…However, most studies do not provide a consensus on both short-run and long-run. Liddle [6,7] suggested that additional variables could be included (e.g., vehicle stock, vehicle-miles and motor fuel use, etc. ), under the assumption that there are the systemic relationships among the variables.…”

Examination of Granger-causality between the road freight transport and economic growth on the example of Poland

“…Autor zauważa, że istnieje długookresowa zależność przyczynowa pomiędzy popytem na transport a cenami benzyny, dochodem i wskaź-nikiem motoryzacji indywidualnej. Jednak dodaje też, że ceny benzyny w krótkim okresie nie mają znaczącego wpływu na pojazdomile, ale za to mają wpływ na wskaźnik motoryzacji indywidualnej (Liddle, 2009).…”

Accounting for Nonlinearity, Asymmetry, Heterogeneity, and Cross-Sectional Dependence in Energy Modeling: US State-Level Panel Analysis

“…More recently, several single-country studies (Holtedahl and Joutz 2004;Halicioglu 2007;Dergiades and Tsoulfidis 2008;Liddle 2009) have focused on either residential energy/electricity or gasoline consumption and employed time-series based methods (i.e., methods that address nonstationarity/cointegration). In addition, other recent studies have used panel methods that address both nonstationarity and heterogeneity-but not cross-sectional dependence-e.g., Narayan et al (2007), who considered residential electricity consumption demand, and Liddle (2012), who focused on gasoline demand.…”