Estimates Of Price Elasticities Research Articles

The time-varying elasticity of South African electricity demand

This paper estimates the price and income elasticity coefficients of domestic electricity demand for the period 1980 to 2018 in South Africa. South African electricity prices were falling in real terms between 1983 and 2005. It then increased sharply in response to substantial tariff increases between 2008 and 2011. A time-varying parameter model with the Kalman filter is applied to estimate the evolution of the elasticities over time. This allows the analysis to distinguish between the two regimes of decreasing and increasing real electricity prices and evaluate the evolution of demand elasticities accordingly. The main result, consistent with existing South African literature, is that electricity consumption was unresponsive to price changes in the period of falling real electricity prices up to 2005. However, when real prices started increasing, the price elasticity coefficient increased markedly in absolute terms. The key result that policymakers should take note of is that aggregate price sensitivity is notably higher when real prices are increasing. While price elasticity estimates remain lower than unity (i.e. relatively inelastic), further price increases may incentivise consumers to substitute into alternative sources of energy. This result is echoed by findings from the comparable international literature.

Fuel economy and the price of gasoline: Evidence from fueling-level micro data

The short-term elasticity of gasoline consumption is determined by both vehicle distances traveled and the efficiency with which each mile is driven. Rarely is the latter observed. We use novel micro-level data on on-road fuel consumption and fuel prices in Japan to estimate both the contemporaneous and dynamic effects of gasoline prices on on-road fuel economy. Our estimate of the contemporaneous price elasticity of on-road fuel economy is approximately 0.07, suggesting that approximately 19% of the price elasticity of gasoline consumption comes from improvements in fuel-conserving behavior. We also find limited habit formation of fuel economy changes; fuel economy effectively responds only to current gasoline prices. This is consistent with substantial utility costs for behavioral adjustments in fuel saving.

THE DIRECT REBOUND EFFECT AND ENERGY EFFICIENCY POLICY: AN ECONOMETRIC ESTIMATION IN THE CASE OF TUNISIAN TRANSPORT SECTOR

In this paper, we estimate the sensitivity of the fuel and travel demand with respect to the fuel price and the income variation, in the case of the road transport in Tunisia, during the 1987-2016 period, resorting to two different econometric approaches: the error correction model (ECM) and the dynamic model. The price and income elasticity estimation, in the long term and the short term, allow the assessment of the direct rebound effects. We shall show that (1) the dynamic model is considered to be the most appropriate approach for our database; (2) the fuel price increase, in both the short term and long the long term, has a negative impact on the energy consumption. Hence, we recommend the public decision-maker to review his/her energy subsidies, in order to improve the energy efficiency in the road transport sector and to control the CO2 emissions; (3) an increase of the income entails an increase of the energy consumption and, hence, the travel demand; (4) the rebound effects from the fuel price increase will be compensated in the form of a more significant fuel use indicate that if the energy efficiency increases by 1%, 0.21% and 0.29% of the savings resulting.Keywords: Fuel and travel demand elasticities; the rebound effect; the error correction model; the dynamic model. JEL Classifications: L91, Q43, Q54, R48DOI: https://doi.org/10.32479/ijeep.11456

Carbon pricing in Germany's road transport and housing sector: Options for reimbursing carbon revenues

In 2021, Germany launched a national emissions trading system (ETS) in its road transport and housing sectors that increases the cost burden of consumers of fossil fuels, the major source of carbon dioxide (CO2) emissions. A promising approach to secure public acceptance for such a carbon pricing would be to entirely reallocate the resulting “carbon” revenues to consumers. This article discusses three alternatives that were discussed in the political arena prior to the introduction of the national carbon pricing: a) a per-capita reallocation to private households, b) the reduction of electricity prices by, e.g., decreasing the electricity tax, as well as c) targeted financial aid for vulnerable consumers, such as increasing housing benefits. To estimate both the revenues originating from carbon pricing and the resulting emission savings, we employ a partial equilibrium approach that is based on price elasticity estimates on individual fossil fuel consumption from the empirical literature. Most effective with respect to alleviating the burden of poor households would be increasing housing benefits. While this measure would not require large monetary resources, we argue that the remaining revenues should be preferably employed to reduce Germany's electricity tax, which becomes more and more obsolete given the steadily increasing amount of electricity generated by renewable energy technologies.

Demand price elasticity of mobile voice communication: A comparative firm level data analysis

This study estimates the price elasticity of mobile voice communication in developed and developing countries using quarterly operator data from 2000 to 2017. Using a dynamic panel model through system-GMM, the study finds that the demand price elasticity is higher for operators in developed countries. Controlling for cross-price elasticity with internet data prices reveals that voice communication is a substitute for internet data usage in developed countries. Another important finding is that, for operators in developing countries, the price elasticity decreases with market development level, whereas it increases for those in developed countries. Demand for mobile voice communication is thus more sensitive to price changes in the less penetrated markets in developing countries and the mature markets in developed countries. Furthermore, over time, price elasticity has decreased across operators in developing countries, highlighting the need for updating regulatory frameworks for the telecommunications sector to reflect the sector's various developments. In addition, when formulating regulatory and tax policies, some important economic factors, such as income level and domestic market characteristics, should be considered to avoid losses in consumer welfare. The high estimated price elasticities suggest that operators do not have an obvious interest in engaging in collusive behavior that would hinder competition. Moreover, since there is no differential effect due to operators’ positions or market shares, asymmetric regulation of the dominant operators should be avoided.

Household Demand Analysis for Pakistan: Recent Evidence

The objective of this study is to analyze household demand system for Pakistan by estimating various elasticities of demand. This study combines nine different rounds of Household Integrated Economic Survey data to estimate Almost Ideal Demand System (AIDS). Household level data are supplemented with rich price information available for all the twelve months of the nine years. This approach yields efficient estimates of income and price elasticities, which are non-linear combinations of the parameters of AIDS. Standard errors for all the elasticity estimates are computed on the basis of Monte-Carlo simulations. The results show that household demand responses to income changes are similar between rural and urban households, while the response to price changes differ considerably. On average, rural households are found to be more responsive to price changes than the urban households. The study recommends that on equity grounds transport and communication and miscellaneous non-food goods and housing can be taxed more heavily as compared to other goods.

Price and expenditure elasticity of cigarette demand in El Salvador: a household-level analysis and simulation of a tax increase

BackgroundIn El Salvador, 8.8% of adults 15 years and older smoke cigarettes. Little is known about the sensitivity of cigarette consumption among the adults in El Salvador to tax and...

Characterizing patient assistance program use and patient responsiveness to specialty drug price for multiple sclerosis in a mid-size integrated health system.

BACKGROUND: There is concern that increasingly common use of patient assistance programs (PAPs), out-of-pocket assistance provided by manufacturers or foundations, distorts our understanding of patient behavior and insurance design incentives. Yet the current literature on prescription drug cost sharing largely overlooks their use. PAPs prevalence and impact on drug demand and price elasticity is a major knowledge gap. OBJECTIVE: To examine the use of PAPs among patients with multiple sclerosis (MS) and the association with drug demand in a specialty pharmacy program within a regional integrated health system that facilitates their use. METHODS: We used pharmaceutical claims data from December 2017 to December 2018 linked to detailed payer information from Kaiser Permanente Washington to characterize the prevalence of PAPs for users of 7 MS specialty drug molecules. We estimated price elasticity of demand (PED) in a two-part model by using the presence of copayment assistance as a source of cost variation. The first part estimated marginal probability of a claim in a given month with a probit model, comparing PAP users and nonusers, whereas the second part estimated days supplied of a medication, given a claim was made as a measure for demand. RESULTS: Of 789 unique patients, 480 (60.7%) used PAPs in at least 1 drug claim during the 13-month time frame, and 248 patients (31.4%) used PAPs for all of their MS drug claims. When used, copay assistance covered 100% of out-of-pocket (OOP) charges for 98% of claims and reduced patient annual OOP cost by $3,493 on average. People who used PAPs had much higher OOP charges, a lower Charlson comorbidity score, and were more likely to have insurance through an exchange. The OOP costs charged to patients was higher for claims where patient assistance was used than claims where assistance was not used ($294 vs $42, P < 0.001). Total claim amount was higher for claims that used assistance ($6,169) than claims that did not ($5,503, P < 0.001). The probability of a patient having a drug claim in a given month was 1.9% higher among those using patient assistance, although this finding was not significant (P = 0.258). An average change in price of -$168.21 with PAP use led to an average change in demand of -0.05 days, for an overall price elasticity of demand (SD = 0.028, P = 0.852) given PAP use of 0.005, indicating that the presence of PAPs did not significantly affect demand. PED estimates were not statistically significant by drug, and the exclusion of Medicare patients did not change this interpretation. CONCLUSIONS: In a mid-size integrated health system in the state of Washington, a program that promotes adherence to specialty drugs via facilitated PAP use was found to reduce patient OOP costs but had no effect on prescription drug utilization. Payers may consider embracing PAPs to remove patient financial barriers to necessary medications and use tools other than cost sharing to influence patient consumption of specialty drugs. DISCLOSURES: This manuscript was funded in part through a Pre-Doctoral Fellowship in Health Outcomes from the PhRMA Foundation awarded to Brouwer for the completion of her dissertation work. Yeung receives some salary support from Kaiser Permanente. The other authors have nothing to disclose.

How price-responsive is residential retail electricity demand in the US?

Using a panel data analysis of a newly developed sample of monthly data by state for January 2005 to December 2019, we estimate a series of error correction models for US residential electricity demand postulated to move with electricity price, natural gas price, income, and weather. Our key findings are as follows. First, the short-run own-price elasticity estimate is not statistically different from zero (p-value > 0.8). Second, the long-run own- and cross-price elasticity estimates are −0.054 (p-value = 0.000) and 0.019 (p-value = 0.000) under the double-log specification, smaller in size than the long-run own- and cross-price elasticity estimates of −0.120 (p-value = 0.000) and 0.069 (p-value = 0.000) under the linear demand specification. Third, price elasticity estimates have been shrinking in size over time. Fourth, erroneously ignoring the panel data's cross-sectional dependence tends to more than double the long-run price elasticity estimates. Fifth, mismatching the timing of price information's availability and consumption decision leads to anomalous price elasticity estimates. Finally, our new empirics' key takeaway of low price-responsiveness supports continuation of energy efficiency standards and demand-side management programs.

Evaluating the influence of energy prices on tight oil supply with implications on the impacts of COVID-19

Tight oil reached about 8% of world oil production in 2019, a fraction only lower than Russia and Saudi Arabia. With such a large amount, the fluctuation in tight oil production can substantially influence the balance of the world oil market. However, due to the short history of large-scale tight oil development, the influence of oil prices on tight oil supply is not well studied. This paper analyzes the price responsiveness of tight oil supply in the United States using an econometric method and well-level play-specific panel data. The result is further used to estimate the influence of COVID-19 on tight oil production. The regression results show that the oil price elasticity was 2.0 for tight oil drilling and 0.5 for tight oil production in 2010–2016. The gas price elasticity is insignificant in both cases. Forecasts using the estimated econometric model show that tight oil production will decrease by 1.3–2.3 million barrels per day (16–28%) under different price scenarios. However, tight oil is not likely to be a “swing producer” and OPEC will continue to lead production cuts under low prices. The estimated price elasticities contribute to more accurate forecasts of tight oil supply. The conclusions also have significant policy implications for major oil-producing countries.

Price and Income Elasticities of Natural Gas Demand in Egypt: A Bound Test Approach

AbstractThis paper provides short and long-run estimates of price and income elasticities of Egypt’s natural gas demand using the ARDL bounds testing approach to cointegration over the period 1983–2015. The results show that the long-run income and price elasticities, in absolute values, are greater than their counterparts in the short run. This result is due to the fact that consumers can modify their consumption habits and plans in the long run as a response to changes in the income or the price. Moreover, natural gas demand is more responsive to changes in income than changes in price in both the short and long run. Finally, the study examines the causality relationship between natural gas consumption and economic growth for the gas-consuming sectors in Egypt. The results indicate that there is no causal relationship between the two variables for the electricity, petroleum, and household sectors in the short-run. By contrast, there is a unidirectional causality running from natural gas consumption to the economic activity of the transportation sector and a unidirectional causality running from economic activity to natural gas consumption by the industry sector.

Sensitivity of Water Price Elasticity Estimates to Different Data Aggregation Levels

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.

Estimation of price and income elasticity of residential water demand in the Czech Republic over three decades

AbstractThis paper contributes to residential water demand literature by providing price and income elasticity estimates for a country which has undergone deep structural, institutional and economic changes. We analyze short‐run and long‐run residential water demand using household‐level data for the Czech Republic for the period of 1993–2016, during which the price of water nearly tripled, consumption decreased by a third, and families became considerably richer. Our estimates of price and income elasticity indicate low responsiveness of households to changes of these factors. Income elasticity is about +0.16 and it is robust across models. The short‐run price elasticity is about −0.22, on the low end of estimates derived for other developed economies. Long‐run price elasticity is around −0.30. While households were more price responsive during the period of economic transformation, they became completely unresponsive during the later economic boom.

Price elasticity estimation for deep learning-based choice models: an application to air itinerary choices

One of the most popular approaches to model choices in the airline industry is the multinomial logit (MNL) model and its variations because it has key properties for businesses: acceptable accuracy and high interpretability. On the other hand, recent research has proven the interest of considering choice models based on deep neural networks as these provide better out-of-sample predictive power. However, these models typically lack direct business interpretability. One useful way to get insights for consumer behavior is by estimating and studying the price elasticity in different choice situations. In this research, we present a new methodology to estimate price elasticity from Deep Learning-based choice models. The approach leverages the automatic differentiation capabilities of deep learning libraries. We test our approach on data extracted from a global distribution system (GDS) on European market data. The results show clear differences in price elasticity between leisure and business trips. Overall, the demand for trips is price elastic for leisure and inelastic for the business segment. Moreover, the approach is flexible enough to study elasticity on different dimensions, showing that the demand for business trips could become highly elastic in some contexts like departures during weekends, international destinations, or when the reservation is done with enough anticipation. All these insights are of a particular interest for travel providers (e.g., airlines) to better adapt their offer, not only to the segment but also to the context.

Estimation of Price and Income Elasticity of Water: A Case Study of Darjeeling Town, West Bengal, India

Estimation of Price and Income Elasticity of Water: A Case Study of Darjeeling Town, West Bengal, India

Real-Time Price Elasticity in Electricity: Evaluating Regression-Based Methods

With access to highly-detailed data, this paper presents a method of accurately computing real-time price elasticity of demand in wholesale electricity markets. The resulting values facilitate the first empirical validation of regression-based estimates of price elasticities, for which the accuracy has never before been evaluated.

Distilling Network Effects from Steam

This paper identifies direct network effects in the demand for video games using minimal network data, but leveraging within-consumer variation. I separately identify price elasticities on isolated individuals on the network, and on non-isolated individuals. I then use the discrepancies between estimated price elasticities to identify the direct network effect. As an empirical application, I estimate video game demands and network effects on Steam, the largest video game digital distributor in the world. I compare my method to “traditional” IV-strategies in the literature, which require detailed network data, and find similar results. A 1% increase in friends’ demands, increases demand by .3%. In counterfactuals, I find strong incentives for firms to promote the game through “influencers,” and some incentives for games to merge their gaming networks.

The effect of a soft drink tax in Mexico: evidence from time‐series industry data

We use a time‐series approach and industry data to estimate the effect on consumption of a relatively large excise tax on soft drinks imposed recently in Mexico. The tax caused a price increase of 12.8 per cent and reduced per‐capita consumption about 3.8 per cent. This effect is small in comparison with the effects that are suggested by most studies that estimate price elasticities using an almost ideal demand system and household survey data. Moreover, we find that the effects of the tax on consumption vary throughout the year. The effect of the tax tends to be higher in the winter but vanishes during the summer. We also find that the effect of the tax does not vary from one year to another.

US Import Demand for Softwood Plywood: A Cointegration Approach

Abstract In this article, we present a model and estimates of US import demand for softwood plywood from Brazil, Canada, Chile, and China using a cointegration framework. We find evidence of long-run cointegration for time series variables in US import demand functions from Brazil, Canada, and China but not from Chile. The short-run own price elasticity estimates of US import demand from Brazil, Canada, Chile, and China are at –0.53, –0.80, –0.82, and –0.91, respectively. The estimates of long-run price elasticity suggest that US import demand for softwood plywood from the three countries is more sensitive to softwood plywood price change.

Shrinkage Priors for High-Dimensional Demand Estimation

Estimating demand for wide assortments of differentiated goods requires the specification of a demand system that is sufficiently flexible. However, flexible models are highly parameterized so estimation requires appropriate forms of regularization to avoid overfitting. In this paper, we study the specification of Bayesian shrinkage priors for price elasticity parameters within a log-linear demand system where the number of price elasticity parameters grows quadratically in the number of goods. Traditional regularized estimators shrink regression coefficients towards zero which can be at odds with many economic properties of price effects. We propose a hierarchical extension of the class of global-local priors commonly used in regression modeling to allow the direction and rate of shrinkage to depend on a product classification tree. We use both simulated data and retail scanner data to show that, in the absence of a strong signal in the data, estimates of price elasticities and demand predictions can be improved by imposing shrinkage to higher-level group effects rather than zero.