The Impact of Gas Price Trends on Vehicle Type Choice

ABSTRACT When shopping for cars, customers consider several factors, including comfort, safety, and cost. Due to recent fluctuations in gas prices, fuel economy has become increasingly critical among these factors. As a result, the auto industry is experiencing new demand patterns among their vehicle inventory: demand for high-consumption vehicles (i.e. SUVs) is down, and demand for gas-efficient cars (i.e. hybrids) is up. Quantifying the impact of gas prices on vehicle choice is the subject of many studies in the literature. Those studies have typically investigated the short-term effects of gas price changes on customer behavior. This article addresses the impact of fuel cost fluctuations on customers' vehicle choice, a long-term decision, through the analysis of U.S. automobile sales data from 1990 to 2007. KEYWORDS: Transportation Economics, Traveler Behavior, Gas Price, Demand Elasticity. (ProQuest: ... denotes formulae omitted.) INTRODUCTION The cost of energy is an important factor for all sectors of the economy - government, private sectors, and consumers. The recent fluctuations in energy cost have altered the decisions and behavior of many groups. Among all sectors, transportation accounts for nearly 67 percent of all petroleum consumption in the United States. From 1977-2002, the transportation sector's petroleum usage grew by 35 percent, but overall national petroleum use only increased by 7 percent (EIA, 2007). This indicates that overall non-transportation petroleum usage declined during this period while transportation usage more than doubled the net national increase. Additionally, transportation distillate use (highway, rail, and marine) constituted the fastestgrowing element of national petroleum use. American passenger-miles have more than quadrupled since 1950, far exceeding the population growth rate. Since transportation costs are dependent on fuel prices, the auto industry needs to study customer responses to fuel cost increases. Modeling customer choice and providing the vehicles consumers prefer helps the auto industry to improve their market share, and makes the economy less susceptible to the global oil market shocks. This in turn allows the economy to reduce the oil dependency and respond to fuel shortages more efficiently. Two major oil price increases have occurred in the U.S. history: in the 1970s, and since 2004. After the first increase, people altered their shopping and recreational trips, but avoided altering their automobile trips to work. After oil prices dropped in the 1980s, household vehicle trips increased, primarily for non-work trips (Loeta, 2007). While there are many studies about the long-term and short-term effects of oil price increase of the 1970s, few studies have been performed about recent fuel price fluctuations. Haire and Machemehl (2006) analyzed five cities in the United States and found that most transit systems have experienced a ridership growth of approximately 0.09 percent for each additional cent of fuel price. In a 2005 survey of 500 residents of Austin, Texas, Bomberg and Kockelman (2007) found that travelers reduce their overall driving and/or chain their trips together to cope with high gas prices. They also reported that households drove their most fuelefficient vehicles more when gasoline prices increased in 2005. Goodwin et al. (2004) reviewed empirical studies since 1990 and found that a 10 percent increase in the real price of fuel produces: a 1.0 percent reduction in vehicle miles traveled; a 2.5 percent reduction in fuel consumption; a 1.5 percent increase in the fuel efficiency of vehicles; and a less than 1.0 percent decrease in net vehicle ownership. El tony (1993) attempted to model gasoline demand for Canada. He demonstrated through regression models that in response to a gas price increase, households planning to buy a new car either postpone their vehicle purchases or buy a more fuel -efficient car, and households that already own a car drive fewer miles. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.