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This paper examines the factors responsible for changes in crude oil prices. The paper reviews the statistical behavior of oil prices, relates this to the predictions of theory, and looks in detail at key features of petroleum demand and supply. Topics discussed include the role of commodity speculation, OPEC, and resource depletion. The paper concludes that although scarcity rent made a negligible contribution to the price of oil in 1997, it could now begin to play a role.

This study was aimed to estimate the domestic demand function on tea imports in Iraq using the Autoregressive Distributed Lag model (ARDL) for co-integration during the period 1990-2020.The data are verified for stationary by using unit root tests basis on Augmented Dickey - Fuller Test. The existence of a long-run equilibrium relationship among tea import quantity, current prices of tea and coffee buying, gross national income, and number of buyers is proved using bounds test method to co-integration. Results of estimating short and long-run models of the demand of tea imports by using the unrestricted error correction approach showed that the error correction parameter is adjusted annually by 140%. Results of estimating price elasticity of demand in the short run showed that the absolute coefficient of price elasticity of demand is less than one and more than zero, which means that tea is a necessary commodity for the Iraqi shopper. Additionally the cross elasticity coefficient had a positive sign in the short and long run, which means that coffee, is an alternative good for tea from the viewpoint of the Iraqi consumer. With regarding to the coefficient value of the income elasticity of demand, it was positive and less than one in the short and long run, which means that tea, is a necessary normal commodity for Iraqi buyers. The study recommended that it is necessary to diversify the sources of national income in the local economy by utilizing all available resources in order to reduce dependence on oil revenues, which were a major source of financing imports in the country.

Trade market power serves as a significant indicator of pricing power within the trade market. This paper aims to examine the market structure of global forage trade from 1997 to 2020 and assess the market power of forage exporters in major importing countries, namely Japan, China, and South Korea, by utilizing an extended G-K model based on the theory of residual elasticity of demand. The findings of this analysis provide several key insights. Firstly, it is revealed that the United States and Australia hold a monopoly on forage trade, while China has emerged as the most pivotal market for worldwide forage trade. Notably, China’s growing demand for forage imports is profoundly influencing the global forage trade landscape. Secondly, the extent and effectiveness of exporting countries’ market power in forage-importing nations, such as China, varies considerably. Lastly, the market power of forage-exporting countries is determined by various factors, including the demand for forage in importing nations, export monopoly, import structure, demand elasticity, and the level of marketization.

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.

Background Salt consumption control strategies can help to decrease hypertension and related cardiovascular diseases. Taxation mechanisms help to reduce the utilization of harmful commodities like salts. This study aims to analyze the impact of taxing salty foods on salt intake in Iran by examining the price elasticity of demand (PED) and cross-price elasticity of demand (XED) for salty foods. Methods This study used 38,328 household-level data from the 2019 Iranian Household Income and Expenditures Survey. This PED and XED for salty foods were calculated, and changes in household salt consumption due to salt taxation were estimated using a mathematical simulation method. Results The findings revealed that the PEDs for noodles and pilaffs (− 4.89) and bread (− 2.03) are higher than that for other commodities. Noodles and salt (− 4.55) and breads and salt (− 1.61) exhibited the highest XED. Following 20% taxation, total salt intake is projected to increase by approximately 125 g per month. Conclusion Taxing mechanisms are ineffective in reducing the consumption of salty foods. Instead of reducing salt intake, households tend to shift to lower-quality, cheaper salty foods after the tax are implemented. However, these mechanisms can be used for increasing the government revenue.

Policymakers and stakeholders can use insights from price elasticity and income elasticities of energy demand to devise targeted interventions that promote energy efficiency, reduce reliance on fossil fuels, and drive the transition to more sustainable and resilient energy systems. This study seeks to examine how changes in income elasticity and price elasticity affect energy consumption over time using the ARDL model and a time-varying parameter technique, state-space Kalman filter. The study’s findings reveal that energy prices have a negative and significant impact on energy consumption, whereas GDP per capita and population growth have a positive and significant impact on energy consumption in both the short and long run. The findings underline the importance of economic growth and increasing population in driving growing energy demand in India, which is consistent with the country’s energy-intensive development aspirations. The time-varying analysis shows that the price elasticity of energy consumption follows a U-shaped pattern across time. However, from the onset of the new millennium decade, the elasticity of energy consumption with regard to its price has continually decreased, reaching − 0.54 by 2020. Furthermore, the findings imply that the income elasticity of India's energy demand has stabilized around unity, indicating that the country is currently near the middle of the energy intensity-GDP inverted-U trajectory. Given these evolving elasticities, policymakers should take a flexible and forward-thinking strategy to achieve optimal energy consumption levels.

Investigation shows that train travel has a lower pollution impact on the environment than flight travel or car travel. A stated preferences (SP) survey can effectively obtain the data of the commuter’s response to the hypothetical train price changes beyond the scope of previous observations. To this end, based on SP survey, we estimate the price elasticity of train travel demand and analyze its variation rules. It is shown that: (1) the own-price elasticities of demand are −1.049028 during peak period and −1.090438 during off-peak period, respectively; (2) the cross-price elasticities of demand are 0.001280 for train and air and 0.001156 for train and car during peak period; and 0.001350 for train and air and 0.001230 for train and car during off-peak period; (3) the own and cross-price elasticities of demand during off-peak period are bigger than the ones during peak period; (4) when the influence factors’ influence degree is 3 or 5, the own and cross-price elasticities of demand are largest; when the influence degree is 1, the own and cross-price elasticities of demand are smallest. A result application example shows that the elasticities obtained from this paper could be used to reduce energy used and CO2 emissions effectively.

For reducing fossil fuel demand and its environmental damages in Iran, the UN suggests removal of fossil fuel subsidies in this developing country which has the largest amount of energy subsidies in the world within 2010s. This research investigates the effectiveness of subsidy removal as a price policy in reducing the consumption of diesel which has the highest share in the total fossil fuel demand portfolio. The novelty of this research is that it compares the effects of price policy and energy efficiency on reducing diesel demand and improving sustainability to reveal which one is a more effective policy. To this aim, our study employs dynamic model, static model and error-correction model for estimating the diesel demand elasticities during 1976–2017. The results show that the diesel demand responds to changes in energy efficiency substantially, while it responds to changes in price slightly. Based on our findings, energy efficiency is about 30 times more effective than the price policy on reduction of diesel demand and improvement of the sustainable development pillars including economy, environment and social (health). A 10% improvement in energy efficiency at the first year of the studied period could reduce more than 87 billion liters of diesel consumption, 3 billion tons of CO2 emissions and 65 thousand deaths from the air pollution during the period. Therefore, the strategists should improve the technology especially the efficiency of energy-consuming utilities like cars, rather than increasing the price and removal of subsidy, to reduce diesel demand and improve sustainability.

This paper examines the problem of unobserved heterogeneity in urban water demand. It uses a panel quantile regression (QR) approach to focus on segments of consumers with different levels of water consumption. This estimation strategy is applied to a rich set of panel microdata capturing the consumption of water for 4,023 households in Valencia (Spain) between the years 2009 and 2011. To capture heterogeneity in a city’s residential household water consumption, a QR approach is applied to the specified water demand model, enabling analysis for different quantiles (levels) of consumption. The QR shows the behaviour of the parameters for different consumption levels. It enables differentiation of consumer reactions to different independent variables at each quantile of the distribution of the dependent variable. The results provide strong evidence of unobserved heterogeneity at different levels. This approach is useful in that it can lead to better-informed tariff design by providing an understanding of heterogeneity in price elasticities.

The empirical literature on residential water demand employs various data aggregation methods, which depend on whether the aggregation is over consumption, sociodemographic variables, or both. In this study, we distinguish three dataset types—aggregated data, disaggregated data, and semi-aggregated data—to compare the consequences of using a large sample of semi-aggregated data vis-à-vis a small sample of fully disaggregated data on the water price elasticity estimates. We also analyze whether different aggregation levels in the sociodemographic variables affect the water price elasticity estimates when the number of observations is fixed. We employ a discrete-continuous choice model that considers that consumers face an increasing block price structure. Our results demonstrate that the water price elasticities depend upon the level of aggregation of the data used and the sample size. We also find that the water price elasticities are statistically different when comparing a large semi-aggregated sample with a small disaggregated sample.