Price Elasticity Of Gasoline Demand Research Articles

Estimating the price elasticity of gasoline demand in correlated random coefficient models with endogeneity

SummaryWe propose a per‐cluster instrumental variable (PCIV) approach for estimating linear correlated random coefficient models in the presence of contemporaneous endogeneity and two‐way fixed effects. This approach estimates heterogeneous effects and aggregates them to population averages. We demonstrate consistency, showing robustness over standard estimators, and provide analytic standard errors for robust inference. In Monte Carlo simulation, PCIV performs relatively well in finite samples in either dimension. We apply PCIV in estimating the price elasticity of gasoline demand using state fuel taxes as instrumental variables. We find significant elasticity heterogeneity and more elastic gasoline demand on average than with standard estimators.

Heterogeneity in the pass-through from oil to gasoline prices: A new instrument for estimating the price elasticity of gasoline demand

We propose a new instrument for estimating the price elasticity of gasoline demand that exploits systematic differences across U.S. states in the pass-through of oil price shocks to retail gasoline prices. We show that these differences are primarily driven by the cost of producing and distributing gasoline, which varies with states’ access to oil and gasoline transportation infrastructure, refinery technology, and environmental regulations, creating cross-sectional gasoline price shocks in response to an aggregate oil price shock. Time-varying estimates do not support the view that the gasoline demand elasticity has declined in absolute value to near zero since the 1980s. The elasticity was stable near −0.3 until the end of 2014. It rose to about −0.2 in 2015–16, but has remained stable since 2016. Gasoline demand is more responsive in states with lower personal income, higher unemployment rates and lower urban population shares. There is no evidence for an asymmetry in the elasticity with respect to positive and negative gasoline price shocks. We illustrate how these elasticity estimates inform the recent policy debate about the impact of gasoline tax holidays on consumers’ discretionary income and about the demand destruction from the spike in gasoline prices after the invasion of Ukraine.

Debiasing the Price Elasticity of Gasoline Demand with Double Machine Learning

Debiasing the Price Elasticity of Gasoline Demand with Double Machine Learning

Heterogeneity in the Pass-Through from Oil to Gasoline Prices: A New Instrument for Estimating the Price Elasticity of Gasoline Demand

Heterogeneity in the Pass-Through from Oil to Gasoline Prices: A New Instrument for Estimating the Price Elasticity of Gasoline Demand

Heterogeneity in the Pass-Through from Oil to Gasoline Prices: A New Instrument for Estimating the Price Elasticity of Gasoline Demand

Heterogeneity in the Pass-Through from Oil to Gasoline Prices: A New Instrument for Estimating the Price Elasticity of Gasoline Demand

Heterogeneity in the Pass-Through from Oil to Gasoline Prices: A New Instrument for Estimating the Price Elasticity of Gasoline Demand

Heterogeneity in the Pass-Through from Oil to Gasoline Prices: A New Instrument for Estimating the Price Elasticity of Gasoline Demand

What do one hundred million transactions tell us about demand elasticity of gasoline?

The price elasticity of gasoline demand is a key parameter in evaluation of various policies. However, most of the literature uses aggregate data to identify this elasticity. Temporal and spatial aggregation make such elasticity estimates biased. We employ a unique dataset of all gasoline transactions in Iran during a 4-month period around an unexpected exogenous price change to identify that price elasticity. We also identify a significant withholding behavior by consumers in response to anticipated price changes. The consumers reduce or postpone their purchases when they expect a decrease in prices. Controlling for date fixed effects would eliminate homogeneous withholding responses. However, heterogeneous responses to this anticipated price change would lead to an overestimation of price elasticity. After controlling for date, individual, and location fixed effects as well as the withholding behavior, we estimate a robust significant price elasticity of − 0.085. Aggregation of the same data by week, month, and city yields an estimate of − 0.3, indicating a significant bias in earlier studies.

The effect of fuel prices on traffic flows: Evidence from New South Wales

Abstract Understanding how traffic flows respond to fuel price changes is useful for traffic management. This study uses a dataset of 11.9 million hourly observations from 118 traffic count stations over 2010–2017 to investigate the relationship between gasoline prices and traffic flows in the state of New South Wales, Australia. The findings suggest that higher gasoline prices reduce traffic flows, with an average effect size of −0.04 in the hourly estimates. The elasticity is particularly pronounced during off-peak periods, both on weekdays (−0.10) and weekends (−0.07). In contrast, a positive effect of gasoline prices on traffic flows is observed for peak periods on weekdays (0.06). Evidence is also obtained that afternoon peak-hour speeds are faster when gasoline prices are higher, consistent with a lowering of traffic density. The research also finds a negative price elasticity of gasoline demand and that people are more likely to use public transport when gasoline prices are higher. The findings suggest that fuel excise plays a role in both reducing overall road dependence and alleviating the severity of some peak-hour traffic jams.

The Effect of Fuel Prices on Traffic Flows: Evidence from New South Wales

Understanding how traffic flows respond to fuel price changes is useful for traffic management. This study uses a dataset of 11.9 million hourly observations from 118 traffic count stations over 2010–2017 to investigate the relationship between the gasoline price and traffic flows in the state of New South Wales, Australia. The findings suggest that higher gasoline prices reduce traffic flows, with an average effect size of –0.04 in the hourly estimates. The elasticity is particularly pronounced during off-peak periods, both on weekdays (–0.10) and weekends (–0.07). In contrast, a positive effect of gasoline prices on traffic flows is observed for peak periods on weekdays (0.06). Evidence is also obtained that afternoon peak-hour speeds are faster when gasoline prices are higher, consistent with a lowering of traffic density. The research also finds a negative price elasticity of gasoline demand and that people are more likely to use public transport when gasoline prices are higher. The findings suggest that fuel excise plays a role in both reducing overall road dependence and alleviating the severity of some peak-hour traffic jams.

Revisiting income and price elasticity of gasoline demand in India: new evidence from cointegration tests

This study investigates cointegration among gasoline demand, real price of gasoline and real GDP for India for the period 1971–1972 to 2012–2013. It also estimates short-run and long-run elasticity of gasoline demand with respect to its price and GDP. Johansen–Juselius and ARDL bounds test methods establish that gasoline demand, gasoline price and GDP are cointegrated. Regime shift cointegration tests with endogenous structural breaks, on the other hand, ascertain cointegration between gasoline demand and GDP. Gasoline demand is found to be highly elastic with respect to real income and real price in the long-run. However, in the short-run, price is inelastic. The study deviates from previous studies in two important aspects. First, price is found to be elastic in the long-run as opposed to being inelastic in both short term and long term as established in the previous studies. Second, income elasticity has declined in magnitude. These findings are quite intriguing and are consistent with policy changes in the Indian economy. The Toda–Yamamoto version of Granger causality tests establishes long-term unidirectional causality from real income to gasoline consumption. The study discusses possible reasons behind the empirical findings, and finally, a set of policy prescriptions are suggested to reduce the consumption of gasoline, which should have no adverse impact on economy in the long-run.

Anticipation, Tax Avoidance, and the Price Elasticity of Gasoline Demand

SummaryLeast‐squares estimates of the response of gasoline consumption to a change in the gasoline price are biased toward zero, given the endogeneity of gasoline prices. A seemingly natural solution to this problem is to instrument for gasoline prices using gasoline taxes, but this approach tends to yield implausibly large price elasticities. We demonstrate that anticipatory behavior provides an important explanation for this result. Gasoline buyers increase purchases before tax increases and delay purchases before tax decreases, rendering the tax instrument endogenous. Including suitable leads and lags in the regression restores the validity of the IV estimator, resulting in much lower elasticity estimates. Copyright © 2016 John Wiley & Sons, Ltd.

Anticipation, Tax Avoidance, and the Price Elasticity of Gasoline Demand

Traditional least squares estimates of the responsiveness of gasoline consumption to changes in gasoline prices are biased toward zero, given the endogeneity of gasoline prices. A seemingly natural solution to this problem is to instrument for gasoline prices using gasoline taxes, but this approach tends to yield implausibly large price elasticities. We demonstrate that anticipatory behavior provides an important explanation for this result. We provide evidence that gasoline buyers increase gasoline purchases before tax increases and delay gasoline purchases before tax decreases. This intertemporal substitution renders the tax instrument endogenous, invalidating conventional IV analysis. We show that including suitable leads and lags in the regression restores the validity of the IV estimator, resulting in much lower and more plausible elasticity estimates. Our analysis has implications more broadly for the IV analysis of markets in which buyers may store purchases for future consumption.

Anticipation, Tax Avoidance, and the Price Elasticity of Gasoline Demand

Traditional least squares estimates of the responsiveness of gasoline consumption to changes in gasoline prices are biased toward zero, given the endogeneity of gasoline prices. A seemingly natural solution to this problem is to instrument for gasoline prices using gasoline taxes, but this approach tends to yield implausibly large price elasticities. We demonstrate that anticipatory behavior provides an important explanation for this result. We provide evidence that gasoline buyers increase gasoline purchases before tax increases and delay gasoline purchases before tax decreases. This intertemporal substitution renders the tax instrument endogenous, invalidating conventional IV analysis. We show that including suitable leads and lags in the regression restores the validity of the IV estimator, resulting in much lower and more plausible elasticity estimates. Our analysis has implications more broadly for the IV analysis of markets in which buyers may store purchases for future consumption.

Gasoline taxes or efficiency standards? A heterogeneous household demand analysis

Using detailed consumer expenditure survey data and a flexible semiparametric dynamic demand model, this paper estimates the price elasticity and fuel efficiency elasticity of gasoline demand at the household level. The goal is to assess the effectiveness of gasoline taxes and vehicle fuel efficiency standards on fuel consumption. The results reveal substantial interaction between vehicle fuel efficiency and the price elasticity of gasoline demand: the improvement of vehicle fuel efficiency leads to lower price elasticity and weakens consumers’ sensitivity to gasoline price changes. The offsetting effect also differs across households due to demographic heterogeneity. These findings imply that when gasoline taxes are in place, tightening efficiency standards will partially offset the strength of taxes on reducing fuel consumption.

Gasoline prices, gasoline consumption, and new-vehicle fuel economy: Evidence for a large sample of countries

Countries differ considerably in terms of the price drivers pay for gasoline. This paper uses data for 132 countries for the period 1995–2008 to investigate the implications of these differences for the consumption of gasoline for road transport. To address the potential for simultaneity bias, we use both a country's oil reserves and the international crude oil price as instruments for a country's average gasoline pump price. We obtain estimates of the long-run price elasticity of gasoline demand of between −0.2 and −0.5. Using newly available data for a sub-sample of 43 countries, we also find that higher gasoline prices induce consumers to substitute to vehicles that are more fuel-efficient, with an estimated elasticity of +0.2. Despite the small size of our elasticity estimates, there is considerable scope for low-price countries to achieve gasoline savings and vehicle fuel economy improvements via reducing gasoline subsidies and/or increasing gasoline taxes.

Demand for gasoline is more price-inelastic than commonly thought

One of the most frequently examined statistical relationships in energy economics has been the price elasticity of gasoline demand. We conduct a quantitative survey of the estimates of elasticity reported for various countries around the world. Our meta-analysis indicates that the literature suffers from publication selection bias: insignificant or positive estimates of the price elasticity are rarely reported, although implausibly large negative estimates are reported regularly. In consequence, the average published estimates of both short- and long-run elasticities are exaggerated twofold. Using mixed-effects multilevel meta-regression, we show that after correction for publication bias the average long-run elasticity reaches − 0.31 and the average short-run elasticity only − 0.09.

The empirical effects of a gasoline tax on CO2 emissions reductions from transportation sector in Korea

The introduction of carbon tax is expected to mitigate GHG emissions cost-effectively. With this expectation identifying the impacts of carbon tax on energy demand and GHG emission reductions is an interesting issue. One of the basic methods of estimating these impacts is using the price elasticity.There are, however, some unanswered questions regarding the use of price elasticity. First, which elasticity estimates are appropriate to measure the impacts of carbon tax on energy demand? The existing estimates are estimated in the presence of a substitute. To assess the impact of carbon tax could we use these estimates? Second, how can we compromise the differences among the existing estimates depending on estimation methods and specifications? For example, how can we accommodate the difference in the estimates from the regional panel specification and the aggregate specification?This paper tries to answer these questions with the price elasticity of gasoline demand. With an appropriate price elasticity, we show how much gasoline consumption and GHG emissions are reduced by carbon tax for different scenarios of carbon tax rate.

The Effect of Determining Gasoline Price According to Market Mechanism on Environment Pollution (Case Study of Iran)

In Iran, prices of gasoline as the other energy carriers are set by government. This price is lower than gasoline price according to market mechanism and its international level. Lower price of gasoline relative to other consumption goods had increased the growth rate of gasoline consumption and environmental pollution. From the other side, according to the economic theories, change in relative price of the gasoline will directly and indirectly affect the gasoline demand. So, adjustment of gasoline price has an important role on pollution emission. In this paper, precisely effects of gasoline price increase on gasoline demand and environmental emission will be analyzed using a dynamic econometric model. The model is an error correction version of auto regressive distributed lag models. For running of the model an annual time series between 1959-2008 has been used. Based on the estimated models, the short-run and long-run price elasticity of gasoline demand is –0.12 and –0.23 respectively. So, a 1% increase in prices of gasoline, will decrease the gasoline consumption and its environmental pollution about 0.12% and 0.23% in the short and long-run respectively.

Evidence of a Shift in the Short-Run Price Elasticity of Gasoline Demand

Understanding the sensitivity of gasoline demand to changes in prices and income has important implications for policies related to climate change, optimal taxation and national security. The short-run price and income elasticities of gasoline demand in the United States during the 1970s and 1980s have been studied extensively. However, transportation analysts have hypothesized that behavioral and structural factors over the past several decades have changed the responsiveness of U.S. consumers to changes in gasoline prices. We compare the price and income elasticities of gasoline demand in two periods of similarly high prices from 1975 to 1980 and 2001 to 2006. The short-run price elasticities differ considerably: and range from -0.034 to -0.077 during 2001 to 2006, versus -0.21 to -0.34 for 1975 to 1980. The estimated short-run income elasticities range from 0.21 to 0.75 and when estimated with the same models are not significantly different between the two periods.

A meta-analysis of the price elasticity of gasoline demand. A SUR approach

Automobile gasoline demand can be expressed as a multiplicative function of fuel efficiency, mileage per car and car ownership. This implies a linear relationship between the price elasticity of total fuel demand and the price elasticities of fuel efficiency, mileage per car and car ownership. In this meta-analytical study we aim to investigate and explain the variation in empirical estimates of the price elasticity of gasoline demand. A methodological novelty is that we use the linear relationship between the elasticities to develop a meta-analytical estimation approach based on a Seemingly Unrelated Regression (SUR) model with Cross Equation Restrictions. This approach enables us to combine observations of different elasticities and thus increase our sample size. Furthermore, it allows for a more detailed interpretation of our meta-regression results. The empirical results of the study demonstrate that the SUR approach leads to more precise results (i.e., lower standard errors) than a standard meta-analytical approach. We find that, with mean short run and long run price elasticities of − 0.34 and − 0.84, respectively, the demand for gasoline is not very price sensitive. Both in the short and the long run, the impact of a change in the gasoline price on demand is mainly driven by responses in fuel efficiency and mileage per car and to a slightly lesser degree by changes in car ownership. Furthermore, we find that study characteristics relating to the geographic area studied, the year of the study, the type of data used, the time horizon and the functional specification of the demand equation have a significant impact on the estimated value of the price elasticity of gasoline demand.