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This study is used to model and forecast Nigerian motor gasoline consumption using the Trigonometric Regression model which has the capabilities of handling nonlinear time series. The time plot of Nigerian motor gasoline consumption showed the series is nonlinear. The Trigonometric regression model was estimated using the Ordinary Least Square method. From the result, the coefficients of the model influenced Nigerian motor gasoline consumption and a unit increase may lead to an increase or decrease. The values of coefficient of determination (R^2) revealed that the coefficients of the model explained the variations in Nigerian motor gasoline consumption up to 83%. The value of the adjusted coefficient of determination (R ̅^2 ) also revealed that the model is a good fit and has high predictive power. Therefore, the Nigerian motor gasoline consumption forecast from 1980 to 2038 indicated continuous fluctuations from year to year. The shape of the out-sample forecast from 2019 to 2038 exhibited a bell shape. Conclusively, based on the results obtained, the proposed model can be used to obtain future values for Nigerian motor gasoline consumption. This will enhance the Government and shareholders to put in place proper plans and logistics to curtail the challenges that may arise from Nigerian motor gasoline consumption and distribution presently and in the future.

ABSTRACT The United States is the world's largest oil consumer demanding about twenty five percent of the total world oil production. Whenever there are difficulties to supply the increasing quantities of oil demanded by the market, the price of oil escalates leading to what is known as oil price spikes or oil price shocks. The last oil price shock which was the longest sustained oil price run up in history, began its course in year 2004, and ended in 2008. This last oil price shock initiated recognizable changes in transportation dynamics: transit operators realized that commuters switched to transit as a way to save gasoline costs, consumers began to search the market for more efficient vehicles leading car manufactures to close "gas guzzlers" plants, and the government enacted a new law entitled the Energy Independence Act of 2007, which called for the progressive improvement of the fuel efficiency indicator of the light vehicle fleet up to 35 miles per gallon in year 2020. The past trend of gasoline consumption will probably change; so in the context of the problem a gasoline consumption model was developed in this thesis to ascertain how some of the changes will impact future gasoline demand. Gasoline demand was expressed in oil equivalent million barrels per day, in a two steps Ordinary Least Square (OLS) explanatory variable model. In the first step, vehicle miles traveled expressed in trillion vehicle miles was regressed on the independent variables: vehicles expressed in million vehicles, and price of oil expressed in dollars per barrel. In the second step, the fuel consumption in million barrels per day was regressed on vehicle miles traveled, and on the fuel efficiency indicator expressed in miles per gallon. The explanatory model was run in EVIEWS that allows checking for normality, heteroskedasticty, and serial correlation. Serial correlation was addressed by inclusion of autoregressive or moving average error correction terms. Multicollinearity was solved by first differencing. The 36 year sample series set (1970-2006) was divided into a 30 years sub-period for calibration and a 6 year "hold-out" sub-period for validation. The Root Mean Square Error or RMSE criterion was adopted to select the "best model" among other possible choices, although other criteria were also recorded. Three scenarios for the size of the light vehicle fleet in a forecasting period up to 2020 were created. These scenarios were equivalent to growth rates of 2.1, 1.28, and about 1 per cent per year. The last or more optimistic vehicle growth scenario, from the gasoline consumption perspective, appeared consistent with the theory of vehicle saturation. One scenario for the average miles per gallon indicator was created for each one of the size of fleet indicators by distributing the fleet every year assuming a 7 percent replacement rate. Three scenarios for the price of oil were also created: the first one used the average price of oil in the sample since 1970, the second was obtained by extending the price trend by exponential smoothing, and the third one used a longtime forecast supplied by the Energy Information Administration. The three scenarios created for the price of oil covered a range between a low of about 42 dollars per barrel to highs in the low 100's. The 1970-2006 gasoline consumption trend was extended to year 2020 by ARIMA Box-Jenkins time series analysis, leading to a gasoline consumption value of about 10 millions barrels per day in year 2020. This trend line was taken as the reference or baseline of gasoline consumption. The savings that resulted by application of the explanatory variable OLS model were measured against such a baseline of gasoline consumption. Even on the most pessimistic scenario the savings obtained by the progressive improvement of the fuel efficiency indicator seem enough to offset the increase in consumption that otherwise would have occurred by extension of the trend, leaving consumption at the 2006 levels or about 9 million barrels per day. The most optimistic scenario led to savings up to about 2 million barrels per day below the 2006 level or about 3 millions barrels per day below the baseline in 2020. The "expected" or average consumption in 2020 is about 8 million barrels per day, 2 million barrels below the baseline or 1 million below the 2006 consumption level. More savings are possible if technologies such as plug-in hybrids that have been already implemented in other countries take over soon, are efficiently promoted, or are given incentives or subsidies such as tax credits. The savings in gasoline consumption may in the future contribute to stabilize the price of oil as worldwide demand is tamed by oil saving policy changes implemented in the United States. ; 2009-05-01 ; M.S. ; Engineering and Computer Science, Department of Civil and Environmental Engineering ; Masters ; This record was generated from author submitted information.

Gasoline prices are often a heated topic during presidential election campaigns in the United States. Yet, presidents have limited control over gasoline prices. Do voters reward or punish the president for changes in gasoline prices? Why might voters blame the president for an outcome beyond direct presidential control? This study addresses these questions by testing the effects of gasoline prices on pocketbook retrospection by voters. To capture the personal economic burden of gasoline prices, we rely on average driving times to work, given the inelastic nature of gasoline consumption for commuting. The results provide evidence for pocketbook voting: constituencies with longer average driving times to work are more likely to hold the president accountable for gasoline price increases. These findings have broader implications regarding electoral accountability and rationality in voting.

Intro -- GASOLINE PRICES AND THEIR EFFECTS ON BEHAVIOR -- GASOLINE PRICES AND THEIR EFFECTS ON BEHAVIOR -- CONTENTS -- PREFACE -- CONSUMERS' RESPONSES TO HIGHER GASOLINE PRICES -- Driving Behavior -- Purchases of New Vehicles -- GASOLINE PRICES, POLICY, AND TOTAL GASOLINE CONSUMPTION -- End Notes -- Chapter 1 GASOLINE PRICES AND DRIVING BEHAVIOR∗ -- VOLUME OF TRAFFIC -- Expected Effects of Higher Gasoline Prices -- Findings -- Relationship between Traffic Volumes and Rail Ridership -- SPEED OF TRAFFIC -- How Much Slowing Is "Sensible" When Fuel Prices Rise? -- Findings -- APPLICABILITY OF FINDINGS TO OTHER REGIONS OF THE UNITED STATES -- End Notes -- Chapter 2 GASOLINE PRICES AND VEHICLE MARKETS -- MARKET SHARES FOR CARS AND LIGHT TRUCKS -- GASOLINE PRICES AND VEHICLE MARKET SHARES -- CHANGES IN NEW-VEHICLE FUEL ECONOMY AND PRICING -- CHANGES IN THE USED-VEHICLE MARKET -- End Notes -- Chapter 3 APPENDIX A. STUDY DATA -- TOTAL TRIPS -- VEHICLE SPEED -- End Notes -- Chapter 4 APPENDIX B. ANALYTICAL APPROACH AND ECONOMETRIC RESULTS -- TOTAL TRIPS -- End Notes -- Chapter 5 REFERENCES -- INDEX -- Blank Page

The objective of this paper was to investigate the determinants of gasoline demand in Kuwait and to assess their impact on consumption. We used the Standard Demand Equation (SDE), the Cointegration Techniques, and the Error Correction Model (ECM) on annual time-series data for Kuwait from 1972 to 2018. We obtained a price elasticity of -0.341 in the long-run, while the short-run price elasticity was insignificant, indicating that changes in prices had minimal or no effect on gasoline consumption in Kuwait. This may be at least in part due to consumers shifting their consumption from a higher grade of gasoline to a less expensive grade when prices changed. We also found that the income elasticity is 0.175 in the short-run and 0.234 in the long-run, indicating that income will be more effective in changing consumption in the long-run. We conclude that reducing gasoline subsidies could result in substantial governmental savings, but this may have an inequitable impact on low-income Kuwaitis.

Time-series estimation of gasoline demand elasticities often does not take into account the possibility of non-stationarity in the underlying data, which may render the parameter estimates spurious. Studies have shown that the time trending variables used to explain gasoline demand could be difference stationary and therefore may require cointegration analysis to assess the relationship among the trending variables. In this work we use the cointegration technique to derive long run and short run demand elasticities of non-commercial gasoline consumption using time-series data for the USA from 1949 to 2004. We also attempt to incorporate the presence of a structural break in the data generation process of the time trending variables. Our results show that the consumption of gasoline and lifetime income have a long term stable relationship after the second oil shock of 1978. Prior to the first oil shock of 1973, no such long run relationship could be established through cointegration.

We examine the impacts of increased US gasoline taxes in a model that links the markets for new, used, and scrapped vehicles and recognizes the considerable heterogeneity among households and cars. Household choice parameters derive from an estimation procedure that integrates individual choices for car ownership and miles traveled. We find that each cent-per-gallon increase in the price of gasoline reduces the equilibrium gasoline consumption by about 0.2 percent. Taking account of revenue recycling, the impact of a 25-cent gasoline tax increase on the average household is about $30 per year (2001 dollars). Distributional impacts depend importantly on how additional revenues from the tax increase are recycled. (JEL D12, H22, H25, L62, L71)

AbstractWhy do some governments subsidize gasoline consumption, despite its very high economic and environmental costs? We answer this question by examining how a state's political regime and level of institutional capacity jointly determine its level of fossil fuel price distortion. We find that, without sufficient institutional capacity, democratic regimes do not necessarily provide less fuel subsidies, as those governments are unable to pursue other more efficient welfare policies. Using data on monthly domestic gasoline prices from 2003 to 2015, we demonstrate that democratic governments with high institutional capacity are less likely to control domestic gasoline prices. Democratic institutions and strong institutional capacity jointly mitigate the effect of the benchmark oil price increases on the domestic price. These results suggest that the combination of motive (democratic accountability) and means (institutional capacity) can help countries avoid inefficient subsidy policies.

In Indonesia, consumers can choose to consume either high or low quality gasoline based on their preferences. Changing preference to a higher quality that is affected by the declining relative price can lead to an Alchian-Allen (A-A) phenomenon. This study aims to determine whether the A-A Phenomenon occurs on the behavior of consumers before and after the existence of Pertalite. The regression model used is the panel data regressions and the regression result proves that there is an A-A phenomenon in market share in Indonesia before and after Pertalite. This indicates that the high difference of relative prices between high and low quality gasolines has a negative impact towards their relative consumption. Prior to Pertalite, consumers continued changing preference into high quality gasoline in the 2nd and 3rd month intervals when relative price difference decreased. After the existing of Pertalite, consumers did not quickly transfer their preferences from Premium to Pertalite when the relative price declined, so that the A-A phenomenon did not occur in this low and middle grade gasoline consumption pattern. However, Pertamax's consumption to Pertalite increases when the relative price between them declines; thus raising the A-A phenomenon. This implies that the government of Indonesia could use their authority to make arrangements on price differences between gasoline qualities