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Journal articles on the topic 'Gasoline – Prices'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 February 2022

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1

Chang, Dongfeng, and Apostolos Serletis. "OIL, UNCERTAINTY, AND GASOLINE PRICES." Macroeconomic Dynamics 22, no. 3 (August 18, 2016): 546–61. http://dx.doi.org/10.1017/s1365100516000249.

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In this paper we investigate the relationship between crude oil and gasoline prices and also examine the effect of oil price uncertainty on gasoline prices. The empirical model is based on a structural vector autoregression that is modified to accommodate multivariate GARCH-in-Mean errors. We use monthly data for the United States over the period from January 1976 to September 2014. We find that there is an asymmetric relationship between crude oil and gasoline prices, and that oil price uncertainty has a positive effect on gasoline price changes. Our results are robust to alternative model specifications and alternative measures of the price of oil.

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Pokrivčák, J., and M. Rajčaniová. "Crude oil price variability and its impact on ethanol prices." Agricultural Economics (Zemědělská ekonomika) 57, No. 8 (August 23, 2011): 394–403. http://dx.doi.org/10.17221/42/2010-agricecon.

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The world annual biofuel production has exceeded 100 billion litres in 2009. The development of the biofuel production is partly influenced by the government support programs and partly by the development of oil prices. The main purpose of this paper is to analyze the statistical relationship between ethanol, gasoline and crude oil prices. We aim to check the correlation among these variables and to analyze the strength and direction of a possible linear relationship among the variables. We are interested in analyzing how each variable is related to another, so we evaluate the inter-relationship among the variables in the Vector Autoregression (VAR) and the Impulse Response Function (IRF). In order to achieve our goal, we first collected weekly data for each variable from January, 2000 to October, 2009. The results provide evidence of the cointegration relationship between oil and gasoline prices, but no cointegration between ethanol, gasoline and ethanol, oil prices. As a result, we used a VAR model on first differences. After running the Impulse Response Function, we found out that the impact of the oil price shock on the other variables is considerable larger than vice versa. The largest impact of oil price shock was observed on the price of gasoline.  

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Lee, Jihoon, and Hong Chong Cho. "Impact of Structural Oil Price Shock Factors on the Gasoline Market and Macroeconomy in South Korea." Sustainability 13, no. 4 (February 18, 2021): 2209. http://dx.doi.org/10.3390/su13042209.

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This study decomposed shocks of the global crude oil (GCO) market and Korean gasoline (KG) market into six types using the structural vector auto-regressive model. Breaking down the shocks into six, we analyzed how each shock affects the macroeconomy and gasoline market in Korea. Results of the analysis revealed that the oil supply shock did not cause a large fluctuation in gasoline prices, but it harmed the macroeconomy. By contrast, the two shocks on the demand side of the GCO market caused a large increase in domestic gasoline prices, but they did not negatively affect the macroeconomy. Meanwhile, in the KG market, gasoline-refining shock and gasoline demand shock caused a significant increase in gasoline prices. Both shocks had some negative effects on the Korean macroeconomy at a certain point, but the effects are not as strong as the oil supply shock. However, the gasoline distribution shock in Korea rarely caused negative consequences for major macroeconomic variables. Moreover, analyzing the KG prices through historical decomposition, we found that the two demand-side factors of the GCO market and the demand shock of the KG market have had the most important influence on the gasoline price since the 2000s. From the analysis, the increase in gasoline prices in Korea since the 2000s can be inferred to have no significant negative impact on the macroeconomy. Therefore, the essential factors of price fluctuations must be focused on in analyzing domestic gasoline price and their impact on the macroeconomy.

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Chi, Guangqing, and Jamie Boydstun. "Are Gasoline Prices a Factor in Residential Relocation Decisions? Preliminary Findings from the American Housing Survey, 1996–2008." Journal of Planning Education and Research 37, no. 3 (August 1, 2016): 334–46. http://dx.doi.org/10.1177/0739456x16657159.

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Residential relocation choice is affected by numerous factors, but gasoline prices as a potential factor have not been investigated. This study examines gasoline price changes and residential relocation choice using 1996–2008 American Housing Survey data. We found higher gasoline prices are associated with a higher percentage of movers choosing locations closer to workplaces. The findings have implications for addressing the impacts of volatile gasoline prices on land use planning and policies; resilient “smart cities or communities” are one possible solution.

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Puspsosari, Luthfiya Fathi. "PENGARUH HARGA BBM TERHADAP INFLASI DI JAWA TIMUR." J-PIPS (Jurnal Pendidikan Ilmu Pengetahuan Sosial) 3, no. 1 (December 30, 2016): 47. http://dx.doi.org/10.18860/jpips.v3i1.6854.

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<p>The aim of this study is to describe how much influence the fuel price (the price of petrol and diesel prices) on Inflation in East Java-year period 2000-2015. This type of research is explanatory research with quantitative approach. The research data include the price of fuel (gasoline) at 2000 to 2015, the fuel price (Solar) at 2000-2015 and Inflation rate at 2000-2015 in East Java. Analysis of the results of research using Multiple Linear Regression. Results showed that the price of gasoline partially significant effect on inflation in East Java, but the price of diesel fuel does not influence significantly on inflation in East Java. Fuel price includes the price of gasoline and diesel prices affect the simultaneous inflation in East Java, meaning that one of the factors that caused a inflation in East Java affected by changes in the price of gasoline and diesel prices.</p><p><strong>Keywords: </strong>Price of Fuel (Gasoline and Solar), Inflation and East Jawa</p>

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6

Kim, C. S., Glenn Schaible, and Stan Daberkow. "The Relative Impacts of U.S. Bio-Fuel Policies on Fuel-Energy Markets: A Comparative Static Analysis." Journal of Agricultural and Applied Economics 42, no. 1 (February 2010): 121–32. http://dx.doi.org/10.1017/s1074070800003333.

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Rapidly declining gasoline prices from their record high during the summer of 2008, while ethanol prices remained relatively high, made it difficult for many bio-fuel policy modelers to fully explain the impacts of U.S. bio-fuel policies on fuel prices. Using profit-maximization models for blenders, refiners, and distillers, we conduct a comparative static analysis to measure the relative magnitudes of the impacts of tax credits and blending mandates on fuel-energy market equilibrium prices. Our results indicate that first, the prices of all fuels including conventional gasoline, ethanol, and blended gasoline decline as the biofuel tax credit increases, but they increase as the rate of the blending mandate increases. Second, the shadow value of a blending mandate represents the marginal rate of substitution between the marginal price change associated with a blending mandate and the marginal price change associated with a bio-fuel tax credit. Therefore, bio-fuel policies can affect the prices of all fuels including conventional gasoline, ethanol, and blended gasoline. Finally, ethanol imports are affected by domestic blender's market-power effects, more than by the import duty imposed to offset the tax credit associated with the use of imported ethanol in the blending process.

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7

Wright, Jesse T., Raymond L. Placid, and Marcus T. Allen. "Price Gouging In A Hurricane: Do Free Market Forces Circumvent Price Controls?" Journal of Business & Economics Research (JBER) 16, no. 2 (November 1, 2019): 19–30. http://dx.doi.org/10.19030/jber.v16i2.10319.

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This study analyzes gasoline prices in Florida and Georgia before and after Hurricane Irma, a major weather event that affected both states in 2017. The analysis reveals that gasoline prices in both states increased and stabilized well in advance of state of emergency declarations that triggered the states’ price gouging laws. Price gouging laws thus appear to be inconsequential. Free market forces determine prices unhindered by government price controls during hurricane emergencies.

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Bonn, Mark A., Nathaniel D. Line, and Meehee Cho. "Low Gasoline Prices." Journal of Travel Research 56, no. 2 (August 4, 2016): 263–78. http://dx.doi.org/10.1177/0047287515626306.

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9

Anderson, Soren T., Ryan Kellogg, James M. Sallee, and Richard T. Curtin. "Forecasting Gasoline Prices Using Consumer Surveys." American Economic Review 101, no. 3 (May 1, 2011): 110–14. http://dx.doi.org/10.1257/aer.101.3.110.

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This paper analyzes the predictive power of a new data set of consumer gasoline price forecasts taken from the Michigan Survey of Consumers (MSC). MSC data generally perform as well as a no-change forecast in predicting future gasoline prices, and they substantially out-perform the no-change forecast during the recent economic crisis, during which time they track futures market prices. Finally, the cross-respondent dispersion of the MSC forecasts increases substantially during the economic crisis, paralleling the large increase in price volatility at this time.

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Adamec, Václav. "Short‑Term and Long‑Term Relationships Between Prices of Imported Oil and Fuel Products in the U. S." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 64, no. 4 (2016): 1285–93. http://dx.doi.org/10.11118/actaun201664041285.

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In this study, we analyzed a system of five monthly time series integrated I(1): average price of crude oil imported to the U.S. from OPEC countries (Opec), imported oil price from other than OPEC countries (NonOpec) in USD per barrel, average price of regular gasoline in the U.S. (Regular), premium quality gasoline price (Premium) and kerosene price (Kerosene) in U.S. cents per gallon. Cointegration was established by EG test and the series were analyzed by VECM model with lag selected via BIC criterion. Cointegration rank was determined by the Johansen procedure. According to VECM coefficients, prices of oil from OPEC countries and beyond OPEC exert influence upon all commodity prices in the system, but in a contradictory manner. Responses to innovation shocks in Opec and NonOpec stabilized within 8 to 10 months upon a nonzero shift and further became permanent. Innovation shock in both types of gasoline and Kerosene had only short-term significant impact upon the system. Forecast error variance in all variables is explained mainly by variation in oil prices, especially Opec, which persists with increased horizon. For a short horizon h = 1, FEVDs in gasoline and kerosene prices are primarily made of variation in the respective fuel prices.

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FILKIN, M. E. "RETAIL GASOLINE PRICES IN MOSCOW DURING THE COVID-19 PANDEMIC." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 1, no. 4 (2021): 99–107. http://dx.doi.org/10.36871/ek.up.p.r.2021.04.01.011.

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The article is devoted to the analysis of retail gasoline prices in Moscow in the period after the start of the spread of coronavirus infection. We analyze the statistical data on changes in wholesale and retail prices for the main brands of gasoline and diesel fuel during the pandemic. Empirical data reveal the effect of the damper price regulation mechanism, which makes it possible to soften the reaction to sharp fluctuations in world oil prices. It is shown that positive and negative price shocks in the world oil market during the pandemic smoothed out at the level of wholesale prices for oil products in Russia, and practically neutralized at the level of retail prices.

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Mizik, Tamás, Lajos Nagy, Zoltán Gabnai, and Attila Bai. "The Major Driving Forces of the EU and US Ethanol Markets with Special Attention Paid to the COVID-19 Pandemic." Energies 13, no. 21 (October 27, 2020): 5614. http://dx.doi.org/10.3390/en13215614.

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Ethanol is a widely produced fuel, as well as a fuel additive. Its price is closely related to the price of gasoline, its major substitute. This paper focuses on the impacts of the related variables on regional ethanol prices. Additionally, the length of the price dataset made it possible to isolate the impacts of COVID-19 on the ethanol prices. Using multiple regression and Confirmatory Factor Analyses, we found no significant correlation between the European and US ethanol prices because the major influencing factors were regionally different. In the case of the European ethanol markets, the positive factors were wheat, maize, and potassium chloride prices, while the European sugar and diammonium phosphate prices were negative. In the US markets, gasoline, sugar, and most of the artificial fertilizer prices were positive, while wheat prices were negative. Based on factor analysis, artificial fertilizers and maize factors proved to be important to the European markets, while US ethanol prices were driven by the crude oil-gasoline and raw materials factors. The COVID variable showed no significant connection with the EU prices, but negatively affected the US ethanol prices. This is explained by the different market characteristics, as the US is not only the major consumer, but also the major producer of the different oil products. Therefore, COVID-19 had a double effect on their oil and ethanol markets.

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FILKIN, M. E. "HETEROGENEITY OF MARKET POWER IN RUSSIAN RETAIL GASOLINE MARKETS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 2, no. 11 (2020): 102–11. http://dx.doi.org/10.36871/ek.up.p.r.2020.11.02.014.

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The paper is devoted to empirical monitoring of the gasoline market structure in Russian Federation. Concentration indices of the retail gasoline market in all Federal subjects of Russia are determined. The relationship between the average level of gasoline prices in the region and the concentration level expressed by the Herfindahl – Hirschman index, as well as the volume of production of the corresponding brand of gasoline in the Federal district to which the region belongs, is analyzed. We revealed a weakly positive relationship between prices and level of concentration and a weakly negative correlation between price and level of production in the regions.

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Belyaev, S. G., and I. A. Kapitonov. "Gasoline prices in Russia — conscious upward movement?" Russian competition law and economy, no. 3 (September 30, 2019): 68–77. http://dx.doi.org/10.32686/2542-0259-2019-3-68-77.

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Today, the rise in fuel prices becomes more and more notorious, and at the same time it increases the potential explosive power of the discontented of consumers masses, which notes that growth. Simultaniously, in the conditions of globalization it is impossible to consider prices and price processes in one, separately taken economy since it exists in the conditions of the global economy which provides flows of the capital, goods, labor resources. Thus, in this article, to answer the question whether the level of good prices (in this case — gasoline) in the economy is high, the authors offer a comparison of countries key macroeconomic indicators with similar levels of gasoline prices.

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Oh, Chi-Ok, and William E. Hammitt. "Impact of Increasing Gasoline Prices on Tourism Travel Patterns to a State Park." Tourism Economics 17, no. 6 (December 2011): 1311–24. http://dx.doi.org/10.5367/te.2011.0093.

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Because tourism and outdoor recreation are highly travel dependent, they are influenced by gasoline prices. Unstable and increasing gasoline prices can affect travel participation, and behavioural adaptations are likely to occur. This paper examines the impact of higher gasoline prices on park visitation and investigates the degree to which certain behavioural and socio-demographic variables mediate the direct impact of gasoline prices on travel decisions to visit a park. The study findings revealed that the influence of increasing gasoline prices on travel decisions was progressively intensified and mitigated by several behavioural variables.

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Shafiei, Marzieh, Keikhosro Karimi, Hamid Zilouei, and Mohammad J. Taherzadeh. "Economic Impact of NMMO Pretreatment on Ethanol and Biogas Production from Pinewood." BioMed Research International 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/320254.

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Processes for ethanol and biogas (scenario 1) and biomethane (scenario 2) production from pinewood improved by N-methylmorpholine-N-oxide (NMMO) pretreatment were developed and simulated by Aspen plus. These processes were compared with two processes using steam explosion instead of NMMO pretreatment ethanol (scenario 3) and biomethane (scenario 4) production, and the economies of all processes were evaluated by Aspen Process Economic Analyzer. Gasoline equivalent prices of the products including 25% value added tax (VAT) and selling and distribution expenses for scenarios 1 to 4 were, respectively, 1.40, 1.20, 1.24, and 1.04€/l, which are lower than gasoline price. The profitability indexes for scenarios 1 to 4 were 1.14, 0.93, 1.16, and 0.96, respectively. Despite the lower manufacturing costs of biomethane, the profitability indexes of these processes were lower than those of the bioethanol processes, because of higher capital requirements. The results showed that taxing rule is an effective parameter on the economy of the biofuels. The gasoline equivalent prices of the biofuels were 15–37% lower than gasoline; however, 37% of the gasoline price contributes to energy and carbon dioxide tax which are not included in the prices of biofuels based on the Swedish taxation rules.

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Xu, Feng, Mohamad Sepehri, Jian Hua, Sergey Ivanov, and Julius N. Anyu. "Time-Series Forecasting Models for Gasoline Prices in China." International Journal of Economics and Finance 10, no. 12 (November 5, 2018): 43. http://dx.doi.org/10.5539/ijef.v10n12p43.

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Accurate prediction of gasoline price is important for the automobile makers to adjust designs and productions as well as marketing plans of their products. It is also necessary for government agencies to set effective inflation monitoring and environmental protection policies. To predict future levels of the gasoline price, due to difficulties of obtaining accurate estimates of influential external factors, data driven time-series forecasting models thus become more suitable given the convenience and practicability they are providing. In this paper, five popular time-series forecasting models, i.e., ARIMA-GARCH, exponential smoothing, grey system, neural network, and support vector machines models, are applied to predict gasoline prices in China. Comparing the performances of these models, it is noted that for this specific time series, a parsimonious ARIMA model performs the best in predicting the gasoline prices for a short time horizon, while for the medium length and long run the SVR and FNN models outperforms others respectively.  

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Klutse, Senanu Kwasi, and Gábor Dávid Kiss. "Test for asymmetry on the ex-pump price of premium gasoline in Ghana, Kenya, and Colombia." Hungarian Statistical Review 4, no. 1 (2021): 73–89. http://dx.doi.org/10.35618/hsr2021.01.en073.

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Once again, the World has been faced with an oil price shock as a result of the SARS-CoV-2 coronavirus pandemic. This has resurrected an old debate of whether retail fuel prices adjust significantly to either increases or decreases in international crude oil prices. With many countries moving towards the deregulation of their petroleum sub-sector, the impact of the US dollar exchange rate on retail fuel prices cannot be overlooked. This study investigates the rate at which positive and negative changes in international Brent crude oil prices and the US dollar exchange rate affected the increases or decreases in the ex-pump price of premium gasoline between February 2012 and December 2019. Using a non-linear auto-regressive distributed lag model, the exchange rate was found to play a significant role in fluctuations in the retail price of premium gasoline in Ghana and Colombia in the long run, howev-er, the rate of adjustment between the negative and positive changes was not significant, dispelling the perception of price asymmetry. There was no significant relationship between the ex-pump price of premium gasoline and the international Brent crude oil price in Ghana and Kenya in the long run. This study recommends that the aforementioned countries prioritise the creation of ex-change rate buffers to prevent exchange rate shocks that may affect retail fuel prices.

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Hammoudeh, Shawkat, Seong-Min Yoon, and Ali Kutan. "Do low gasoline prices cause more traffic fatalities in the 50 states of the USA? The importance of other factors." Journal of Economic Studies 46, no. 3 (August 2, 2019): 777–95. http://dx.doi.org/10.1108/jes-05-2018-0175.

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Purpose Motivated by the news media and a lack of comprehensive research on the USA, the purpose of this paper is to examine the relationship between changes in road fatalities and gasoline prices, per capita disposable personal income, alcohol consumption per adult, blood alcohol concentration (BAC) limits and gender. Design/methodology/approach This study employs both static and dynamic panel data models, making use of annual data over the 2000–2013 period collected from the 50 states of the USA and the consistent system GMM estimators of the parameters, to estimate the impact of these variables on fatalities per 100,000 persons and per 100,000 vehicles. Findings The results highlight the importance of gasoline prices in determining the level of road fatalities, underscoring that a 10 percent decrease in gasoline prices leads to a 248 increase in the total number of road fatalities, but with many more injuries. Increases in the female-to-total driver ratio have a greater significant positive impact on road fatalities where a 10 percent increase in this ratio increases road fatalities by 1,008 deaths. Increases in registered vehicles per capita also increase the number of fatalities. Other variables such as alcohol consumption per adult and BAC limits are not as important. Policy implications are also provided. Research limitations/implications The results of this study highlight the importance of gasoline prices in determining the number of road fatalities. This factor can be an effective policy measure by which policymakers can offset increases in fatalities due to further drastic declines in future gasoline prices. But the effects of the gasoline prices in determining the number of road fatalities are not as strong as the media would lead us to believe. The media ignores the impact of other factors on fatalities, which results in an overestimation of the impact of gasoline prices. Originality/value This study uses the panel data of 50 US states and the dynamic panel data model. In addition to gasoline price effects on the road fatalities, this study also considers other factors such as gender, gasoline taxes, per capita disposable personal income, per capita alcohol consumption, BAC limits and number of registered vehicles.

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Li, Shanjun, Joshua Linn, and Erich Muehlegger. "Gasoline Taxes and Consumer Behavior." American Economic Journal: Economic Policy 6, no. 4 (November 1, 2014): 302–42. http://dx.doi.org/10.1257/pol.6.4.302.

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Gasoline taxes can be employed to correct externalities from automobile use and to raise government revenue. Our understanding of the optimal gasoline tax and the efficacy of existing taxes is largely based on empirical analysis of consumer responses to gasoline price changes. In this paper, we examine directly how gasoline taxes affect gasoline consumption as distinct from tax-inclusive retail gasoline prices. We find robust evidence that consumers respond more strongly to gasoline tax changes under a variety of model specifications. We discuss two potential reasons for our main findings as well as their implications. (JEL D12, H21, H25, H31, L71, Q35)

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Byrne, David P., and Nicolas de Roos. "Learning to Coordinate: A Study in Retail Gasoline." American Economic Review 109, no. 2 (February 1, 2019): 591–619. http://dx.doi.org/10.1257/aer.20170116.

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This paper studies equilibrium selection in the retail gasoline industry. We exploit a unique dataset that contains the universe of station-level prices for an urban market for 15 years, and that encompasses a coordinated equilibrium transition mid-sample. We uncover a gradual, three-year equilibrium transition, whereby dominant firms use price leadership and price experiments to create focal points that coordinate market prices, soften price competition, and enhance retail margins. Our results inform the theory of collusion, with particular relevance to the initiation of collusion and equilibrium selection. We also highlight new insights into merger policy and collusion detection strategies. (JEL G34, L12, L13, L71, L81, Q35)

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Angerer, Martin. "Regulation of retail gasoline prices." Finance Research Letters 36 (October 2020): 101331. http://dx.doi.org/10.1016/j.frl.2019.101331.

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Wilson, Nathan E. "VERTICAL SEPARATION INCREASES GASOLINE PRICES." Economic Inquiry 53, no. 2 (January 23, 2015): 1380–91. http://dx.doi.org/10.1111/ecin.12203.

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Yilmazkuday, Demet, and Hakan Yilmazkuday. "Redistributive Effects of Gasoline Prices." Networks and Spatial Economics 19, no. 1 (January 7, 2019): 109–24. http://dx.doi.org/10.1007/s11067-018-9435-9.

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Brown, Jennifer, Justine Hastings, Erin T. Mansur, and Sofia B. Villas-Boas. "Reformulating competition? Gasoline content regulation and wholesale gasoline prices." Journal of Environmental Economics and Management 55, no. 1 (January 2008): 1–19. http://dx.doi.org/10.1016/j.jeem.2007.04.002.

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Plummer, P., R. Haining, and E. Sheppard. "Spatial Pricing in Interdependent Markets: Testing Assumptions and Modeling Price Variation. A Case Study of Gasoline Retailing in St Cloud, Minnesota." Environment and Planning A: Economy and Space 30, no. 1 (January 1998): 67–84. http://dx.doi.org/10.1068/a300067.

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In this paper we present an empirical evaluation of assumptions about consumer purchasing behavior for gasoline. Previous research has developed a theoretical model of spatial pricing in oligopolistically competitive markets in which it is hypothesized that retail prices vary because of both consumer price sensitivity and the choice sets available to consumers as well as awareness of prices at competing locations. With the use of household survey data collected from St Cloud, Minnesota we evaluate the plausibility of these assumptions, finding evidence to support the consumer purchasing behavior assumed in the theoretical model. By means of a spatial time series of gasoline price data for the same metropolitan area, we develop an empirical model of spatial price variation that incorporates some of the hypotheses of the original model. The results suggest support for the proposition that spatial price variations depend on the service characteristics of individual retailers and the accessibility or locational advantage of individual gasoline stations within the spatial configuration of the urban market. There also is empirical support for the conjecture that those sites which are more accessible, have larger choice sets, and charge lower prices tend to be those which attract the most sales from other retailers.

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K. Paswan, Audhesh, John C. Crawford, Waros Ngamsiriudom, and Thuy Nguyen. "Consumer reaction to price increase: an investigation in gasoline industry." Journal of Product & Brand Management 23, no. 3 (May 13, 2014): 220–29. http://dx.doi.org/10.1108/jpbm-09-2013-0377.

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Purpose – The aim of this study is to investigate the impact of increase in price of an essential product (i.e. gasoline) toward the focal product and other seemingly non-related products. Design/methodology/approach – A self-administered survey was used to collect data from the drivers at a large metroplex in Southwest USA. Multiple regression and scanning electron microscope procedures were used to analyze and test the proposed hypotheses. Findings – When consumers notice the increase in gas prices, they become very anxious. This anxiety is positively associated with average gas bought in gallons and negatively associated with threshold price. Further, this consumer anxiety has the strongest influence on lifestyle changes, followed by automobile technology change and transportation mode change, and has the weakest influence on gasoline brand/type change. Research limitations/implications – We focus on only anxiety as a mediator between increase in gas prices and the behavioral outcomes, and collect data from only one location. Practical implications – Managers must be cognizant that a price increase in essential goods not only influences the demand for focal products but also for products that may not seem related to the focal products. Social implications – Increase in gasoline price will not only affect the demand for gasoline, but also the demand for alternate forms of transportation, fuel efficient vehicles, and other aspects of life. Originality/value – This study is the first to look at the role of anxiety as a mediator and looks at the effects of increase in gas prices in a holistic manner.

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Levin, Laurence, Matthew S. Lewis, and Frank A. Wolak. "High Frequency Evidence on the Demand for Gasoline." American Economic Journal: Economic Policy 9, no. 3 (August 1, 2017): 314–47. http://dx.doi.org/10.1257/pol.20140093.

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Daily city-level expenditures and prices are used to estimate the price responsiveness of gasoline demand in the United States. Using a frequency of purchase model that explicitly acknowledges the distinction between gasoline demand and gasoline expenditures, the price elasticity of demand is consistently found to be an order of magnitude larger than estimates from recent studies using more aggregated data. Estimating demand using higher levels of spatial and temporal aggregation is shown to produce increasingly inelastic estimates. A decomposition is then developed and implemented to understand the relative importance of several different factors in explaining this result. (JEL C51, L71, Q35)

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Zhang, Guangyong, Lixin Tian, Wenbin Zhang, Xu Yan, Bingyue Wan, and Zaili Zhen. "A Study on the Similarities and Differences of the Conventional Gasoline Spot Price Fluctuation Network between Different Harbors." Sustainability 12, no. 2 (January 18, 2020): 710. http://dx.doi.org/10.3390/su12020710.

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According to the fluctuation series of the conventional gasoline spot prices (CGSP) in New York Harbor (NYH) and U.S. Gulf Coast (GC), this paper defines the fluctuation modes by the coarse-grained method based on the CGSP series in the two harbors. The fluctuation series are converted into the characters by means of the sliding window, where five symbol series is used as a fluctuation mode, one day was used as a step to slide in the data window, and the conventional gasoline spot prices fluctuation network (CGSPFN) is constructed in the two harbors. Then the evolutionary rule of the new nodes in the CGSPFN is analyzed, such as the strength and distribution, average shortest paths, conversion cycle, betweenness, and clustering coefficient of the nodes are calculated in different periods. The result indicates that the cumulative time of the new nodes which appeared in the CGSPFN is not random but presents a high linear growth trend, which reveals the linear features of the cumulative time of abnormal points when the gasoline price fluctuation appears. The betweenness and clustering coefficient shows that the nodes with the larger strength have smaller betweenness and clustering coefficients, the nodes with the larger betweenness have smaller strength and clustering coefficients, and the nodes with the larger clustering coefficients have smaller betweenness and strength. Meanwhile, the gasoline prices are in a transitional period when the larger indicators appear and have a rising trend, and identifying the transitional period will help the decision maker to grasp the regularity of the changes of the gasoline prices.

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Radchenko, Stanislav, and Dmitry Shapiro. "Anticipated and unanticipated effects of crude oil prices and gasoline inventory changes on gasoline prices." Energy Economics 33, no. 5 (September 2011): 758–69. http://dx.doi.org/10.1016/j.eneco.2011.01.002.

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Daviend Benaya Nugroho, Tandya, Albert Gunadhi, Evelyn Raguindin, and Hartono Pranjoto. "Tire Pressure and the Availability of Gasoline Monitoring Tools Based on IOT." E3S Web of Conferences 188 (2020): 00024. http://dx.doi.org/10.1051/e3sconf/202018800024.

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This final project discusses the design and manufacture of tire pressure and the availability of gasoline monitoring tools based on internet of things (IOT). Tire pressure monitoring tools are made because many of the motorcycle driver don’t have a time to check tire pressure, and often experience a reduction in pressure to leak on the highway. While the gasoline monitoring tool is made so that driver can see the contents of the available motorcycle tank volume, and estimate the price paid when filling in the gas. Conventional methods of estimating gasoline prices often cause failure to refuel at gas stations, and make motorists complain about improper prices. Basically this tool works by means of a gasoline indicator and is connected to the ADC port of the NodeMCU microcontroller. As for tire pressure, the measurement is done by using a pressure sensor and additional ADC, because the microcontroller only has one ADC port. Both of these tools work in the second way the microcontroller receives input data from the gasoline ADC indicator, and there is data processing in the microcontroller to connect the monitoring system via the internet.

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Pleshcheva, Vlada, and Daniel Klapper. "The Moderating Effect of Fuel Prices on the Market Value of Fuel Economy, Driving Intensity, and CO2 Emissions." Marketing ZFP 42, no. 1 (2020): 48–66. http://dx.doi.org/10.15358/0344-1369-2020-1-48.

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In this paper, we explore co-movements of the vehicle price sensitivity to fuel economy with changes in fuel prices. Previous literature has investigated the responsiveness of vehicle prices to fuel prices or fuel economy. We are interested in the interaction effect of fuel prices and fuel economy and answer the question of how exactly the market value of fuel economy depends on the fuel price. By looking at the role of fuel prices as a moderator for the market value of fuel economy, we are able to differentiate between consumers’ valuation of fuel economy versus their reaction to changes in fuel prices. We apply a hedonic price model to the German automobile market by using data on detailed technical specifications of high-sales vehicles of three consecutive model years. In contrast to previous research, where the marginal benefits of driving a car with a particular fuel economy remained constant, we allow it to vary with fuel prices. It enables us to investigate two sources of changes in the market value for fuel economy. The first source, as in the previous studies, corresponds to changes in the budget for driving a car, whereas the second source reflects changes in the capital investments in a better fuel economy. The total effect of these two sources may lead to either a decrease or an increase in the vehicle distance traveled. We study the differences in the impact of fuel prices for various car makes of both diesel and gasoline engines. Our results suggest that there are substantial differences in the market values of fuel economy between diesel and gasoline vehicles and their responsiveness to changes in fuel prices. Diesel cars are characterized by the more elastic price gradient of fuel economy to fuel prices compared to gasoline cars. The revealed high responsiveness of the market value of fuel economy to fuel prices results in an optimal annual driving intensity that is an increasing function of fuel prices. It implies that, during the period of investigation, the marginal benefit of driving a car of a specific fuel economy was higher than the corresponding fuel price effect on the budget for driving. Using the quantified impact of fuel prices on the market value of fuel economy, we also assess the implied changes in the kilometers driven with cars and the resulting CO2 emissions. The current study presents an empirical application of statistical analysis to a topic of interest to readers in the areas of quantitative economics and economic policy.

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Li, Shanjun, Christopher Timmins, and Roger H. von Haefen. "How Do Gasoline Prices Affect Fleet Fuel Economy?" American Economic Journal: Economic Policy 1, no. 2 (July 1, 2009): 113–37. http://dx.doi.org/10.1257/pol.1.2.113.

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Exploiting a rich dataset of passenger vehicle registrations in 20 US MSAs from 1997 to 2005, we examine the effects of gasoline prices on the automotive fleet's composition. We find that high gasoline prices affect fleet fuel economy through two channels: shifting new auto purchases towards more fuel-efficient vehicles, and speeding the scrappage of older, less fuel-efficient used vehicles. Policy simulations suggest that a 10 percent increase in gasoline prices from 2005 levels will generate a 0.22 percent increase in fleet fuel economy in the short run and a 2.04 percent increase in the long run. (JEL H25, L11, L69, L71)

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Gibbs, Crystal. "Media Clips: Gasoline Prices / Cigarette Butts." Mathematics Teacher 103, no. 9 (May 2010): 634–37. http://dx.doi.org/10.5951/mt.103.9.0634.

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… The cost of gas dropped across North America in recent weeks, partially because reserves have increased. Analysts have linked it to people driving less.… It is predicted that Canadians will drive 800 kilometres less this year versus a year ago.

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Grabowski, David C., and Michael A. Morrisey. "Gasoline prices and motor vehicle fatalities." Journal of Policy Analysis and Management 23, no. 3 (2004): 575–93. http://dx.doi.org/10.1002/pam.20028.

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Gibbs, Crystal. "Media Clips: Gasoline Prices / Cigarette Butts." Mathematics Teacher 103, no. 9 (May 2010): 634–37. http://dx.doi.org/10.5951/mt.103.9.0634.

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… The cost of gas dropped across North America in recent weeks, partially because reserves have increased. Analysts have linked it to people driving less.… It is predicted that Canadians will drive 800 kilometres less this year versus a year ago.

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de Gorter, Harry, David R. Just, and Qinwen Tan. "The Socially Optimal Import Tariff and Tax Credit for Ethanol with Farm Subsidies." Agricultural and Resource Economics Review 38, no. 1 (April 2009): 65–77. http://dx.doi.org/10.1017/s1068280500000198.

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We determine how the U.S. ethanol tax credit and import tariff affect the corn-ethanol-gasoline markets and how farm subsidies interact with these policies. We show how the ethanol tax credit and import tariff each uniquely affect the ethanol and gasoline prices. The ethanol import tariff alone increases the terms of trade in ethanol imports and corn exports, but decreases the terms of trade in gasoline imports and the tax costs of farm price supports. With price-contingent farm subsidies in place, the optimal tariff and tax credit will depend on the price level. When farm subsidy expenditures are high, import subsidies for ethanol may increase social welfare due to the substantial size of the fuel market relative to the corn market.

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Widodo, Eko Muh, Muhammad Imron Rosyidi, Tuessi Ari Purnomo, and Muji Setiyo. "Converting Vehicle to LPG/Vigas: A Simple Calculator to Assess Project Feasibility." Automotive Experiences 2, no. 2 (August 10, 2019): 34–40. http://dx.doi.org/10.31603/ae.v2i2.2744.

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One of the reasons for the slow conversion program from gasoline to LPG/Vigas is the uncertainty of profit or loss. Therefore, this article presents a simple calculator to assess the feasibility of investing in vehicle conversion, from gasoline to LPG/Vigas. Input parameters include estimated annual mileage, fuel consumption, gasoline prices, LPG / Vigas prices, the cost of the converter kit and its installation, engine standardization costs, maintenance costs with gasoline, and maintenance costs with LPG considered to produce output parameters that include Break Even Point (BEP), Payback period (PP), Net Present Value (NPV), and Internal Rate of Return (IRR).

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Borenstein, S., A. C. Cameron, and R. Gilbert. "Do Gasoline Prices Respond Asymmetrically to Crude Oil Price Changes?" Quarterly Journal of Economics 112, no. 1 (February 1, 1997): 305–39. http://dx.doi.org/10.1162/003355397555118.

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Noel, Michael D., and Lanlan Chu. "Forecasting gasoline prices in the presence of Edgeworth Price Cycles." Energy Economics 51 (September 2015): 204–14. http://dx.doi.org/10.1016/j.eneco.2015.06.017.

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Yuan, Chaoqing, Yingjie Yang, Sifeng Liu, and Zhigeng Fang. "Relation between China’s gasoline prices and international crude oil prices." Energy Sources, Part B: Economics, Planning, and Policy 11, no. 10 (October 2, 2016): 953–59. http://dx.doi.org/10.1080/15567249.2014.898716.

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Davis, Michael C. (Michael Connelly), and James D. (James Douglas) Hamilton. "Why Are Prices Sticky? The Dynamics of Wholesale Gasoline Prices." Journal of Money, Credit, and Banking 36, no. 1 (2004): 17–37. http://dx.doi.org/10.1353/mcb.2004.0003.

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Li, Wei Qi, Lin Wei Ma, Feng Fu, and Ya Ping Dai. "A Density-Method-Based Model for Allocating the Refining Cost of Gasoline and Diesel in China." Advanced Materials Research 524-527 (May 2012): 1773–79. http://dx.doi.org/10.4028/www.scientific.net/amr.524-527.1773.

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In this paper, we present a density-method-based model to allocate the refining cost to petroleum products such as gasoline and diesel. By using this model, we also present an empirical study of China, which is based on a virtual crude oil refining process proposed referring to the technical configuration of oil refining industry in China. Three scenarios of the cost of gasoline and diesel are illustrated referring to different settings of the change of the international crude oil prices. The results indicate that the cost of gasoline and diesel change nearly the same amplitude as the change of crude oil price. However, the margin between the cost of gasoline and diesel will slightly increase with the rise of crude oil price. Besides, we also present a sensitivity analysis of the operation cost of each unit in the refining process. The results reveal that the operation cost of catalytic reforming is the most important influencing factor of the cost of gasoline, while the operation cost of hydrogen cracking influences the cost of diesel mostly.

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Kusdarwati, Eny, and Djoni Hartono. "Pengaruh Harga Bensin terhadap Kecelakaan Lalu Lintas di Indonesia." Jurnal Ekonomi dan Pembangunan Indonesia 16, no. 2 (January 1, 2016): 173–86. http://dx.doi.org/10.21002/jepi.v16i2.708.

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The Impact of Gasoline Price on Trac Accident in IndonesiaTraffic accident ranks the ninth largest of the cause of death in Indonesia. The most of researches studying Indonesia on traffic accidents were only blaming on human, motor vehicles, and environment as main culprits, not incorporating economic factors into the models. This study aims to analyze the impact of real gasoline prices on trac accident in Indonesia and the factors of influence them. This research employs time series data from 1970 to 2013 with OLS analysis world crude oil prices as instrument variable. The estimator results show that real price of gasoline and the policy of usage of motorcycle light insignificant on traffic accident. Meanwhile, real GDP and asphalt roads significantly decrease the traffic accident. However, motorcycles significantly increase the traffic accident.Keywords: Real Price of Gasoline; Trac Accident; Externality AbstrakKecelakaan lalu lintas menempati urutan kesembilan penyebab kematian di Indonesia. Kebanyakan penelitian kecelakaan di Indoneia menitikberatkan pada faktor manusia, kendaraan, dan lingkungan, tetapi belum ada yang memasukkan faktor-faktor ekonomi ke dalam modelnya. Tujuan penelitian ini adalah ingin mengetahui pengaruh harga riil bensin terhadap kecelakaan lalu lintas di Indonesia serta faktor-faktor yang memengaruhinya. Penelitian ini menggunakan data time series Indonesia dari tahun 1970 hingga 2013 dan menggunakan OLS dengan variabel instrumen harga minyak mentah dunia. Hasil estimasi menunjukkan bahwa harga riil bensin dan kebijakan penggunaan lampu utama sepeda motor tidak signifikan terhadap kecelakaan lalu lintas. Sedangkan PDB riil dan jalan aspal signifikan berpengaruh menurunkan kecelakaan. Namun, sepeda motor berdampak signifikan meningkatkan kecelakaan lalu lintas.

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Iseki, Hiroyuki, and Rubaba Ali. "Fixed-Effects Panel Data Analysis of Gasoline Prices, Fare, Service Supply, and Service Frequency on Transit Ridership in 10 U.S. Urbanized Areas." Transportation Research Record: Journal of the Transportation Research Board 2537, no. 1 (January 2015): 71–80. http://dx.doi.org/10.3141/2537-08.

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Gasoline price increases since 1999 have generated substantial discussion about their effect on travel behavior. With panel data for 10 selected U.S. urbanized areas between 2002 and 2011, this study analyzed the effects of gasoline prices and three factors that were internal to transit agencies—fare, service supply, and service frequency—on ridership of bus, light rail, heavy rail, and commuter rail, as well as their aggregate ridership. Improving on past studies on the subject, this study accounted for the simultaneous relationship between service supply and ridership and controlled for factors that were external to transit agencies' control but might have influenced ridership. With fixed-effects models that examined temporal changes within each urbanized area, the analysis found that the possibility of simultaneity was low. The results of estimated coefficients showed that the short-term increase in ridership due to gasoline price increases was relatively small for bus and aggregate transit and marginal for rails, certainly smaller than the effects of the three internal factors. The total influence of the three internal factors was found to be more substantial than that of external factors; this finding indicated the potential to increase ridership by transit agencies' efforts when resources were available. In addition, it is recommended that transit agencies prepare for a ridership increase more for bus than for rail because of gasoline prices, considering that even a small increase could require a substantial service increase to accommodate travelers' needs during peak periods.

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García-Mirantes, Andrés, Beatriz Larraz, and Javier Población. "A Proposal to Fix the Number of Factors on Modeling the Dynamics of Futures Contracts on Commodity Prices." Mathematics 8, no. 6 (June 14, 2020): 973. http://dx.doi.org/10.3390/math8060973.

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In the literature on modeling commodity futures prices, we find that the stochastic behavior of the spot price is a response to between one and four factors, including both short- and long-term components. The more factors considered in modeling a spot price process, the better the fit to observed futures prices—but the more complex the procedure can be. With a view to contributing to the knowledge of how many factors should be considered, this study presents a new way of computing the best number of factors to be accounted for when modeling risk-management of energy derivatives. The new method identifies the number of factors one should consider in the model and the type of stochastic process to be followed. This study aims to add value to previous studies which consider principal components by assuming that the spot price can be modeled as a sum of several factors. When applied to four different commodities (weekly observations corresponding to futures prices traded at the NYMEX for WTI light sweet crude oil, heating oil, unleaded gasoline and Henry Hub natural gas) we find that, while crude oil and heating oil are satisfactorily well-modeled with two factors, unleaded gasoline and natural gas need a third factor to capture seasonality.

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Malloy, Brandon. "The Supply Network and Price Dispersion in the Canadian Gasoline Market." Review of Network Economics 17, no. 2 (June 26, 2018): 75–107. http://dx.doi.org/10.1515/rne-2019-0016.

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Abstract This paper examines the impact of variation in transportation options – what I denote the “supply network” – on observed price differences between locations for a specific good, retail gasoline. I use a unique data set of weekly gasoline prices across 44 Canadian cities to analyze how the existence of variation in the available modes of transportation for gasoline between cities (via pipeline, marine tanker, rail or truck) accounts for observed price differences across locations. I find that the supply network is significant – cities connected by lower cost-per-unit methods like pipelines or seaports exhibit smaller mean- and weekly-price differences than those connected only by road or rail, after controlling for distance, regional effects and market size. A pipeline connection results in a reduction in weekly price dispersion equivalent to a 53% reduction in distance between cities, while a maritime connection has the equivalent effect of a 38% reduction in distance between cities.

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Pham, A. Z., and S. A. Senotova. "APPLICATION FOR PREDICTING GASOLINE PRICES (AI-92)." Scientific Papers Collection of the Angarsk State Technical University 1, no. 1 (June 12, 2019): 21–30. http://dx.doi.org/10.36629/2686-7788-2019-1-1-21-30.

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Chi, Guangqing, Arthur G. Cosby, Mohammed A. Quddus, Paul A. Gilbert, and David Levinson. "Gasoline prices and traffic safety in Mississippi." Journal of Safety Research 41, no. 6 (December 2010): 493–500. http://dx.doi.org/10.1016/j.jsr.2010.10.003.

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Barron, John M., Beck A. Taylor, and John R. Umbeck. "Will Open Supply Lower Retail Gasoline Prices?" Contemporary Economic Policy 22, no. 1 (January 2004): 63–77. http://dx.doi.org/10.1093/cep/byh006.

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