Fuel prices vs. automobile fuel economy standards in a CO2-constrained transport sector
Date
2006Source
Proceedings of the International Energy Workshop, 2006, Cape Town, South AfricaGoogle Scholar check
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One way to raise the fuel efficiency and reduce CO2 emissions of new cars is through fuel economy (FE) standards more than 20 countries worldwide currently implement such standards. A second way is to increase fuel taxation in order to induce purchases of more efficient cars and discourage private car travel. Although the adoption of standards has induced FE improvements, there are arguments against standards and in favor of fuel tax increases. The aim of this paper is to analyze the impact of FE standards and fuel prices in new car fuel economy with the aid of cross-section time series analysis of data from 18 countries. Similar work was previously conducted for the U.S. only, and mostly with data up to 1990. We estimated a log-linear equation with new-car FE as the dependent variable and the following explanatory variables: FE standard, real gasoline price (with lags of 0 to –3), and a time trend to capture autonomous technical progress and changing consumer preferences. Data were obtained from official sources such as the U.S. EPA, the IEA and the European Commission, covering the U.S. (cars and trucks), Canada (cars and trucks), Australia, Japan, Switzerland and 13 EU countries, thus building an unbalanced panel of 279 observations. For Japan and some EU countries, we employed Chow tests to test for the existence of a structural break between two periods: one for the years up to 1995 (approximately the time of adoption of the first FE target values in both Japan and the EU), and one for the post-1995 ‘with standards’ period. For all those countries, the hypothesis of no break was clearly rejected. Therefore, we ran separate regressions for the ‘pre-standard’ and the ‘with standards’ sample using the above mentioned variables through pooled least squares with country fixed effects. In both samples, only one price variable was found to be statistically significant, that of lag 1. Estimated coefficients (i.e. ‘elasticities’) for the ‘with standards’ panel were app