Can Regional Variations in Demographic Structure Explain Regional Differences in Car Use? A Case Study in Austria

• Published in: Population and environment 2002-01, Vol.23 (3), p.315-345
• Main Authors: Ewert, Ulf Christian, Prskawetz, Alexia
• Format: Article
• Language: English
• Subjects: Air pollution; Austria; Automobiles; Carbon; Case studies; Commuting; Demographics; Demography; Developing countries; Diesel engines; Educational levels; Emissions; Environment; Environmental behavior; Environmental impact; Fuel consumption; Geographic regions; Households; Industrialized nations; Infrastructure; LDCs; Pollutant emissions; Population; Population density; Population growth; Regional analysis; Regional differences; Regions; Sulfur; Traffic; VOCs; Volatile organic compounds
• ISSN: 0199-0039; 1573-7810
• DOI: 10.1023/A:1013003830023

Due to its manifold impact on the environment private car use represents an important dimension of environmental behavior in industrialized countries. Obviously, private car use is related to demographic characteristics of households such as the life-cycle stage and the living arrangement the household lives in. In addition systematic regional differences of private car use have to be taken into account. In this paper a causal model is derived, which aims to explain regional differences in car ownership and car use by regional demographic differences and region-specific control factors such as the car technology and institutional factors. Using aggregate data from a household survey in Austria and data from Austrian official statistics causal effect coefficients are then estimated. By applying path analysis the estimated effects of regional demographic characteristics on region-specific car ownership and car use can be decomposed into direct and indirect effects, with the latter effects being mediated by the control factors. Except for the average age of household heads and population density no significant direct demographic effects on regional patterns of car ownership and car use can be found. Car ownership and car use are best predicted by using the considered control factors as predictor variables. Nevertheless, many of the presumed indirect effects turn out to be of importance since demographic factors are closely linked to measures of regional institutional settings like per captia income, ownership of house/apartment and net commuting index.