Gasoline Demand with Heterogeneity in Household Responses

Abstract

Fuel demand elasticities are typically based on aggregate data to determine consumer responses to tax increases or price shocks. However, this fails to capture the detailed distributional effect on different socio-economic groups, which is often needed to fully understand the impact of fuel tax measures. This paper presents results from a household level gasoline demand model which accommodates variation in price and income elasticity with increasing income as well as for different socio-economic groups in the USA. We find substantial heterogeneity in price and income elasticities based on demographic groupings and income groups.

Comparative Analysis of Wind Power Energy Potential at Two Coastal Locations in Bangladesh

“…It is well known that the power of the wind at speed (v) through a blade sweep area (A) increases as the cube of its velocity (Wadud et al, 2010).…”

“…For a developing country like Bangladesh, the number of advanced monitoring sta tions (e.g., towermounted anemometers) are limited to precisely evaluate the meteorological patterns, direc tional distribution, and vertical wind shear. Because the preexisting stations provide readings only in the low est layer of the planetary boundary atmosphere (first 10 25 m in the troposphere), they are not efficient enough to acquire proper data for windturbines with conven tional power generators (Hasib et al, 2011;Wadud et al, 2010;WB, 2010;Carta et al, 2009;Ramírez and Carta, 2005). This is not pragmatic for the operation of commercial turbines to provide low cost electricity to a large number of households (Rofiqul Islam et al, 2008).…”

Beyond the Average Elasticity – Applying Quantile Panel Regression to German Household Mobility Data

“…Basso and Oum, 2007;Dahl, 2012), virtually all of the studies on fuel price elasticities employ some variant of mean regression, thereby effectively assuming that the magnitude of the elasticity is homogeneous across the population. Wadud et al (2010) is one of the first studies to relax this assumption by including interaction terms in a random effects model to allow for differential elasticities according to the household's income, geographic location, and other socioeconomic attributes.…”

Model for Investigating Substitution Effect between Renewable Resources and Non-Renewable Resources

“…However, according to Archibald and Gillingham (1980), Hausman and Newey (1995), Schmalensee and Stoker (1999), Wadud et al 2010a and2010b; the main determinant of gasoline price is the crude oil price. [14][15][16][17][18]This suggests that if we simply regress the supply of gasoline with the crude oil price, the crude oil price will be correlated with the endogenous variable gasoline price. Hence, the paper uses the main determinants of crude oil price to capture the effect of crude oil price.…”