An Analysis of the Short-Run Consumer Demand for Gasoline Using Household Survey Data

Abstract

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.The resulting slacks for the various years are the inputs of K, L, E and M that would not have been needed to be utilised if the technologies of 1966, 1969 and 1971 were then available.The most common "binding constraint" in this LP analysis is the level of intermediate materials, M. It is not necessary to infer that output in those years was in fact restricted by M. Rather, intermediate material usage, and to some extent energy usage, has, in general, been linearly related to output even in short term movements. By contrast, as expected, slack capital increases in years of actual production decline, e.g., 1954, 1958, 1970. Slacks are computed as the residual resources after the theoretical output has been produced. The lack of secular trend in slack K appears after the theoretical production of the efficient output, not the actual output.The strength of fine inferences really depends on the accuracy of the data as economic measurements. Nevertheless, an important and robust result is that large declines in productive efficiency appear in years of economic downturn-1948, 1954 and 1968. The resulting slacks for the various years are the inputs of K, L, E and M that would not have been needed to be utilised if the technologies of 1966, 1969 and 1971 were then available.The most common "binding constraint" in this LP analysis is the level of intermediate materials, M. It is not necessary to infer that output in those years was in fact restricted by M. Rather, intermediate material usage, and to some extent energy usage, has, in general, been linearly related to output even in short term movements. By contrast, as expected, slack capital increases in years of actual production decline, e.g. , 1954, 1958, 1970. Slacks are computed as the residual resources after the theoretical output has been produced. The lack of secular trend in slack K appears after the theoretical production of the efficient output, not the actual output.The strength of fine inferences really depends on the accuracy of the data as economic measurements. Nevertheless, an important and robust result is that large declines in productive efficiency appear in years of economic downturn-1948, 1954 and 1968.

Gasoline Demand with Heterogeneity in Household Responses

“…This finding is similar to Archibald and Gillingham (1980), who reported parameter estimates of -0.22 for female and 0.22 for nonwhite household head.…”

“…7 In cases where vehicle fuel economy could not be matched for missing data for one vehicle, we assigned the household the mean fuel economy of other vehicles for which data was available. We acknowledge the limitations of these assumptions, yet we believe the derived fuel economy is a better indicator of fuel consumption than the number of cylinders as used by Archibald and Gillingham (1980).…”

“…Archibald and Gillingham (1980) first utilized such a framework, which was later followed by Greening et. al.…”

“…It is assumed that preferences are functions of households' demographic characteristics. Demographic variables that have been found to affect the household consumption of gasoline are the size and composition of the household, number of earners in the household, age, race, gender, and education of the household, among other possible factors (Archibald and Gillingham 1980, 1981, Greening et. al.…”

“…These enable an understanding of the aggregate impact on demand due to a rise in fuel price or taxes; however, they likely miss the detailed distributional effect of price changes on different socio-economic groups. Recent studies of gasoline and travel demand suggest that there could be significant heterogeneity in the price sensitivity of different socio economic groups or geographic areas (Archibald and Gillingham 1980, 1981, Greening et. al.…”