Price Elasticity Research Articles

Analyzing tourist expenditures incurred on long-, medium-, and short-haul trips to Taiwan

This study examined the consumption demands of short-, medium-, and long-haul tourists in Taiwan, considering the effects of tourism attractiveness, generational cohorts, and nationalities on tourism consumption demand. We employed an Almost Ideal Demand System model to estimate the expenditures and price elasticities based on tourism expenditure data of 3018 visitors to Taiwan. The results indicated that varying degrees of price elasticity were observed among short-, medium-, and long-haul tourists. Long-haul tourists exhibited the highest elasticity in terms of shopping prices and expenditure. The factors influencing tourists' attraction to Taiwan were identified as the geographical convenience of their travel and their nationalities, which, in turn, affected their consumption demands. Thus, based on tourists' relevant characteristics to implement targeted marketing strategies.

Unlocking Market Potential: Strategic Consumer Segmentation and Dynamic Pricing for Balancing Loyalty and Deal Seeking

Background: This paper examines the economic implications of market segmentation on consumer purchasing behavior with a particular emphasis on intertemporal pricing strategies in dynamic markets. Methods: In order to analyze optimal discount rates and the timing for price reductions for consumer segments, including loyal and deal-prone customers, a detailed mathematical model was developed. The model incorporates theories of consumer behavior and pricing elasticity to simulate market responses to price changes throughout a product’s lifecycle. Results: This research indicates that market segmentation enhances sales by targeting the distinct preferences of loyal consumers, who are less price-sensitive and who stabilize revenue streams, and deal-prone consumers, who respond to price reductions. Customizing pricing strategies for loyal consumers and deal-prone consumers increases sales volumes and optimizes profitability. Conclusions: This research improves our comprehension of market segmentation and dynamic pricing, providing a practical framework for businesses to create effective pricing strategies that can be promptly implemented. It emphasizes the significance of understanding consumer behavior and price sensitivity in the interest of revenue promotion. This study also emphasizes the social implications of equitable pricing practices, promoting the implementation of transparent and value-based strategies to promote market inclusivity and consumer trust.

Modelling the potential impact of a tax on fruit juice in South Africa: implications for the primary prevention of type 2 diabetes and health financing

BackgroundSouth Africa is experiencing a persistent growth in non-communicable diseases. Diabetes is among the top ten causes of mortality, especially among women, which is partly driven by high levels of added sugar consumption and obesity. To reduce obesity rates and the incidence of diabetes, South Africa introduced a tax on sugar sweetened beverages (also known as the Health Promotion Levy (HPL)) in 2018. The tax is applicable to sugar-sweetened beverages but excludes 100% fruit juice. The government is currently considering extending the tax to include fruit juices. This study models the potential health and economic impact of taxing fruit juices at 20% of the retail price of one liter.MethodsTo analyze the distributional impact of the tax, this study uses extended cost-effectiveness analysis methodology. Data on price elasticities, healthcare cost, income, fruit juice consumption were sourced from the literature and representative national surveys. The potential impact of the tax on diabetes incidence, prevalence, mortality, and financial benefits were estimated for each income group (lowest, quintile 1 to highest, quintile 5).FindingsWe estimate that a 20% tax on fruit juice would avert 156,640 incident cases of type 2 diabetes mellitus over 20 years, with most disease averted occurring among the first- and fifth-income groups. Averted deaths from diabetes would average 2,000 deaths per quintile (for quintiles 1 to 4) and about 2,800 in quintile 5. The improved health resulting from averted incidence and deaths will reduce overall healthcare expenditure by R7.5 billion over 20 years, of which R2.3 billion will occur in the fifth quintile. The South African government will also save about R300 million in subsidizing diabetes-related healthcare cost as a result of prevention; and would raise R8.6 billion in tax revenues per annum. Out-of-pocket expenditure savings will be R303 million and a financial risk protection (money-metric value of insurance) of R4.6 billion over the 20-year period.ConclusionWe conclude that an HPL that significantly raises the retail price of fruit juices would reduce consumption and diabetes-related morbidity and mortality. The tax will also provide significant financial benefits in the form of reduced healthcare costs for both government and households as well as providing financial risk protection to individuals. Health taxes are win-win policies that improve population health and generate revenue for governments to fund public health services delivery and thus improve overall health financing activities of the government. Therefore, population level disease prevention measures such as health taxes are important for achieving universal health coverage.

How much are we willing to pay for quality wine? A meta‐analysis and meta‐regression analysis

AbstractThis paper performs a meta‐analysis and a meta‐regression analysis on the price semi‐elasticity of wine quality ratings in the context of estimating hedonic price functions. To do so, we thoroughly search for publications that have estimated hedonic functions in this market, resulting in 223 articles estimating 1595 functions, although not all of them incorporate quality ratings. Additionally, 60 aspects of the different studies are coded, including sample characteristics, incorporated attributes, and other implemented methodological choices. The meta‐analysis is then performed, revealing evidence of selection and publication biases. Taking them into account, the price elasticity is found to be around 5%–6%, remaining robust to several robustness checks. The meta‐regression explores the unexplained heterogeneity in the price elasticities observed in the meta‐analysis. Results indicate that quality ratings are more influential in the context of red wines, and less important in the case of sparkling and organic wines. The nature of the data source matters, but generally not the type of price used except the ones obtained from auction and en primeur sales. The influence of the remaining attributes incorporated in the hedonic function is relatively small, except for other quality aspects, reputation, and environment. The econometric techniques used in the estimation do not affect the effect size. This is also the result found for the type of publication, except for studies published in books. Finally, we find that the most cited studies are those that show a smaller effect.

Proactive pricing strategies for on-street parking management with physics-informed neural networks

Effective pricing is important for on-street parking management and proactive parking pricing is an innovative strategy to achieve optimal parking utilization. For proactive parking pricing, accurately predicting parking occupancy and deriving the price elasticity of parking demand are necessary. In recent years, there have been an increasing number of studies applying big data technology for parking-occupancy prediction. However, existing research has not incorporated economic knowledge into modeling, thus preventing application of the price elasticity of parking demand. In this study, proactive pricing strategies are proposed to adjust on-street parking prices which involve a parking-occupancy prediction model and a price-optimization method. Physics-informed neural networks are employed to achieve accurate prediction of parking occupancy and calculation of parking price elasticity. An elasticity-occupancy parking-management strategy is proposed for on-street parking management which leverages parking occupancy and price elasticity to guide pricing interventions. A case study shows that the parking-occupancy prediction model can make accurate predictions and derive the price elasticity of parking demand. Proactive parking pricing enables drivers to plan their trips in advance, allowing parking occupancy within an optimal range.

Cooperation mode selection strategies in platform ecosystems: analyzing brand value, cross-selling, and platform empowerment

Purpose This paper aims to investigate the vertical cooperative relationship between the core enterprise and the manufacturer within the platform ecosystem, specifically analyzing the optimal decision-making processes of both parties under the original equipment manufacturer (OEM) and original brand manufacturer (OBM) modes. Design/methodology/approach This paper uses game theory to analyze the problem, considering factors such as brand value difference, cross-selling and platform empowerment. It constructs the game models for both OEM and OBM modes and discusses the selection strategies for the cooperation mode. Findings The results indicate that the choice of cooperation mode by the manufacturer and the core enterprise depends on the relative size of their brand values. In cases of inconsistent choices, cooperation can be improved by designing a transfer payment contract. When the brand value is constant, the product price is comprehensively affected by cross-selling revenue, price elasticity coefficient, cost coefficient of sales effort and cost coefficient of platform empowerment. The enterprise reduces the price only when the potential revenue brought by increasing product sales exceeds the marginal profit brought by increasing product pricing; otherwise, it raises the sales price. Originality/value The platform ecosystem is emerging as a future direction for business mode development. However, there is a paucity of research on the cooperation modes between manufacturers and core enterprises within the platform ecosystem.

Structural transformation without industrialization? Evidence from Tanzanian consumers

AbstractExport‐oriented industrialization was central to many Asian countries' structural transformation processes, but many African countries are bypassing industrialization, and the prospects for competing in global manufacturing markets are poor. Alternative structural transformation pathways all rely on domestic markets, and thus understanding their trajectories requires uncovering consumer preferences. Using detailed household expenditures data from a nationally representative panel survey in Tanzania, I estimate a flexible, stylized consumer demand system. I recover estimates of expenditure elasticities of demand for goods, services, and food in the aggregate, along with price elasticities of demand, identified using within‐household variation in prices and expenditures. I find that, across the expenditures distribution and in both rural and urban areas, consumer preferences are service facing. In particular, I show that (1) consumers sharply increase spending on services relative to goods and food as incomes increase; (2) demand for services in the aggregate is somewhat sensitive to changes in service prices; and (3) food, goods, and services are substitutes for each other. On one hand, a high propensity to consume the types of services that generate large local economic growth multipliers is consistent with driving growth in service sector employment. However, sustained growth in the long run may be limited because these services are low productivity and nontradable, and domestic markets are size constrained.

Measurement and Validation of Market Power in China’s Log Import Trade—Empirical Analysis Based on PTM Model and AIDS Model

China is the world’s largest importer of logs, possessing the scale to exert significant influence in the international market. This paper uses a fixed-effect variable coefficient Pricing-to-Market panel model to measure China’s market power in log import trade. It also utilizes the Almost Ideal Demand System model from an elasticity perspective to explore the market behavior characteristics of various source countries in China’s log import trade, thereby validating the mechanism of market power. The results indicate that: ① China’s main trading partners can be categorized into four groups according to their market power in the log import trade. Specifically, China holds superlative market power in log imports from Indonesia, Malaysia, and Myanmar; holds strong market power in log imports from Russia, the Democratic Republic of the Congo, and Mozambique; holds weak market power in log imports from Papua New Guinea, Equatorial Guinea, France, Germany, Australia, and New Zealand; and holds no market power in Japan, Cameroon, and the United States. ② As China’s expenditure on log imports increases, there is a tendency to purchase high-quality precious wood and a greater concern for the legality of market transactions. Consequently, China is anticipated to augment its imports from source countries with no or weak market power. ③ The simple price elasticity of log imports from each source country is negative. Source countries with stronger market power tend to increase prices to achieve higher total revenue, while those with weaker market power are more inclined to lower prices to achieve the same. ④ Log products from various source countries are complementary in the Chinese market, indicating that China’s substantial demand for logs relies on the simultaneous supply from multiple countries and diverse wood types. Based on the existence or absence of market power in China’s log import trade, this paper provides targeted insights into enhancing international market power and reducing trade losses.

Long-Term Forecasting Models of Oil Demand Emerging from the Global Petrochemical Sector

In the global energy mix by 2040, the growth in demand for oil and gas will be predominantly driven by the petrochemical sector across all regions of the world. The strong performance of this industry is anticipated to necessitate additional volumes of key feedstocks. Therefore, understanding the demand dynamics within the petrochemical sector is crucial for policy makers and industry stakeholders to make informed decisions regarding economic diversification, economic planning, and environmental sustainability. However, there is a notable lack of existing literature that explicitly addresses comprehensive regional and product-level demand modeling for petrochemical feedstocks. In this context, this study aims to estimate the demand for four main petrochemical feedstocks (Naphtha, Ethane, Liquefied Petroleum Gas (LPG), and other petrochemical feedstocks) across eight regions of the world. By estimating a total of 30 equations for price and income elasticities of demand in both the short and long term, the study provides detailed insights into the factors driving demand across different regions. The results demonstrate the robustness of the model, with good econometric properties and significant coefficients. In-sample regional simulations revealed small percentage errors across all regional equations, highlighting the model’s accuracy in tracking historical data. For each of the four feedstocks, an aggregate world equation—in other words, one single econometric world equation for each of the four petrochemical feedstocks’ categories mentioned earlier—was also estimated and compared against the aggregation of the regional simulations, with the latter found to track the history of global petrochemical feedstock demand better in-sample than a single econometric world equation. Overall, the study offers valuable contributions to the existing literature by filling a gap in comprehensive demand modeling for petrochemical feedstocks. It underscores the importance of regional and product-level analyses in understanding global demand patterns and informing strategic decisions in the industry.

Price index for computer games: What is hidden from the naked eye?

This paper presents a study of the price dynamics of a wide range of video games in the time period from 2008 to 2020. During the research, a necessary database for analysis was created, video game prices were modeled using econometric methods, and price indices were constructed for various game genres: RPG (Role-Playing Game), strategy (Strategy), action (Action), adventure games (Adventure), causal games (Casual), indie games (Indie), simulators (Simulators) etc. Hypothetically, the price range of video games by genre and system requirements were due to the different amount of effort required to create them. During the construction of hedonistic price indices, prices were cleared from the characteristics of the quality of products (computer games). Video game system parameters were used as characteristics. The work also uses various approaches to modify hedonistic indices by considering genre heterogeneity. Thanks to the study, it is possible to track the dynamics of the behavior of the cost of video games over the considered period of time, with the representation of lagging and advancing trends. Genre diversification of the price elasticity of key variables used during the construction of models was provided.

Vehicle miles traveled induced demand, rebound effect, and price and income elasticities: A US spatial econometric analysis

The economic literature on transportation is extensive, with travel demand being a well-studied topic. However, research on light-duty vehicle travel has not fully explored spatial dependencies arising from neighboring regions' driving activities. This study uses state-level panel data from 2000 to 2019 to examine U.S. vehicle miles traveled (VMT), focusing on spatial spillover effects through a Spatial Durbin Model. Our results reveal significant spatial interactions between states. Increased VMT in one state leads to spillover effects, increasing VMT in neighboring states. We present our findings as marginal effects, distinguishing between direct and indirect impacts. The direct price elasticity is estimated at −0.257, with a positive spillover impact of 0.036, yielding a total elasticity of −0.221. Induced travel exhibits a larger indirect effect than a direct effect, resulting in an overall impact of 0.276. Additionally, direct and total income elasticities are 0.194 and 0.146, respectively, while direct and total fuel economy rebound effects are 0.546 and 0.496, respectively. Moreover, higher numbers of licensed drivers, registered vehicles, and urbanization significantly influence a state's VMT. This research highlights the importance of regional planning among states, especially considering transportation infrastructure and environmental concerns related to driving and vehicle emissions.

Welfare effects of health insurance reform: The role of elastic medical demand

Some medical demand is inelastic to price fluctuations, but not all. This paper examines the role of the price elasticity of medical demand on the welfare effects of public health insurance reform. I develop a computational general equilibrium life-cycle model for heterogeneous agents with varying income, wealth, and health that allows for endogenous medical spending. I calibrate the model for the Japanese economy. If medical spending is totally price-inelastic, increasing copayments will improve the welfare of future generations, but harm all current generations, particularly older people with low income or poor health. In contrast, the welfare gain for newborns is significantly greater in the empirically observed situation where medical spending includes some price-elastic components. Moreover, the reform reduces welfare losses for current individuals and may benefit younger generations.

Current state of tourism services for tourists: a study in Hanoi City, Vietnam

Assessing tourist satisfaction has become a hot topic for tourism research in recent years. Many studies have shown that improving tourist satisfaction not only has a positive impact on service providers and destination reputation, but also increases tourist loyalty, lowers price elasticity, lowers future transaction costs, and increases production efficiency (Chen et al., 2012; Nguyen Trong Nhan et al., 2014). Some other studies have also shown that improving tourist satisfaction will stimulate word-of-mouth advertising (Ekinci, 2004; Gonzalez et al., 2007; cited by Chen et al., 2012). Therefore, assessing tourist satisfaction is very important, it helps to find out the existing problems, limitations or strengths of service quality from the perspective of tourists, thereby finding solutions to contribute to improving the ability to provide better and better services. Hanoi as the capital, the economic - political - social center of Vietnam. Therefore, the tourism - hotel industry not only attracts tourists but also diplomatic, business and economic - political - social event participants. Hanoi has great potential for tourism - hotel with hundreds of famous landscapes, historical and cultural relics, traditional craft villages, festivals. In terms of natural tourism resources, Hanoi is famous for Huong Tich as "Nam Thien De Nhat Dong". A series of lakes such as West Lake, Hoan Kiem Lake, Dong Mo, Suoi Hai, Quan Son, not to mention the potential of mineral water resources. Hanoi also has many scenic spots around the foot of Ba Vi mountain, creating branded eco-tourism resorts such as Ao Vua, Vua Ba, Khoang Xanh, Suoi Tien, Thac Da, Thac Nga, Ba Vi National Park, etc. Keywords: Satisfaction, Tourists, Service Quality.

Food and fraud: On the Codfather and harvest mislabeling

AbstractWe study incentives to mislabel output in multispecies fisheries managed by tradeable catch shares. Firms can save quota costs by misreporting species harvested, as seen in criminal proceedings against the Codfather. We show that price elasticities for the abundant species reported in the cheating will be higher for compliant than non‐compliant firms. Using data from the New England groundfish fishery, we test this prediction using a latent class hedonic price equation to identify compliant versus non‐compliant firms. We then estimate multi‐output technologies for compliant and noncompliant firms to identify differences in substitution possibilities. Our empirical results align with theoretical expectations and are robust to placebo tests.

Energy shocks as Keynesian supply shocks: Implications for fiscal policy

This paper analyses the economic impact of and the optimal policy response to energy supply shocks in a flexible price model with heterogeneous households. We introduce energy as a consumption good on the demand side and as an input to production on the supply side. A distinguishing feature is that, in line with empirical evidence, we allow households’ energy demand to be non-homothetic. The model provides three main insights. First, (negative) energy supply shocks act as a (negative) demand shock, or Keynesian supply shock, when two conditions are met: On the demand side household income inequality needs to be large, while on the supply side, the price elasticity of consumption goods needs to be high. Second, the social planner can implement the first-best allocation by subsidising firms and poor households while taxing rich households. Energy shocks then act as standard supply shocks. Last, issuing public debt can help implement the first best allocation when energy shocks are large and/or the economy’s overall energy intensity is low.

Effects of Socio-Economic and Demographic Factors on Meat Consumption Pattern in Iran: A Demand System Approach

Meat as one of the most important resources of protein has a special role in human nutrition. Understanding the meat consumption structure of households is essential for planning and policymaking in this regard. In this research, we studied consumption patterns of meat products including chicken, veal, lamb, and fish for households in Iran (Mashhad city) using demand system estimation. The hypothesis of this study is that chicken is a necessary goods and other types of meat are luxury goods. Given the cross-sectional nature of the data and presence of zero expenditure for some households, we used the censored demand model based on a consistent two-step approach. For this purpose, at first, four Probit models were estimated to determine the factors affecting the probability of purchasing each selected meat product. After that, the probability density function (PDF) and the cumulative distribution function (CDF) were calculated for each selected meat product, and the Almost Ideal Demand System (AIDS) considering PDF and CDF was estimated for all types of meat using a non-linear seemingly unrelated regression. Also, the effect of demographic variables on meat consumption pattern was considered in demand system. The results of expenditure elasticities confirmed the hypothesis. The highest own-price elasticity was related to veal. Based on compensated price elasticities, all types of meat were net substitutes for chicken and chicken was also a net complement for all types of meat. On the other hand, the only substitute for lamb and chicken was veal, but with compensating income effect fish also became a substitute for them. So, in the event of an increase of the price of lamb and chicken, we recommend subsidizing the consumers with low purchasing power in order to increase the diversity of consumption of protein products. This can increase the consumption of fish.

The Effects of the Expansion of Dental Care Coverage for the Elderly.

Expanding dental care coverage for the elderly is globally recommended but not widely implemented due to its high costs and intangible benefits. This study examined the impact of such an expansion in Korea using the imputation-based method proposed by Borusyak et al. We analyzed data from the Korea National Health and Nutrition Examination Survey (2007-2019) on dental service utilization and chewing ability among older adults. The policy resulted in a 13.5% increase in partial denture use and a 60.5% increase in dental implants among those aged 65 and above. These changes corresponded with reductions in severe chewing difficulty by 23.3% and 13.0%, respectively. No significant changes were observed in full denture use. The price elasticity of demand for partial dentures and dental implants was estimated to be -0.19 and -0.86, respectively. These findings underscore the critical role of affordability in enhancing the utilization of dental implants among the elderly and highlight the importance of appropriately expanding dental insurance coverage to improve oral health outcomes in this population.

Economic management of microgrid using flexible non-linear load models based on price-based demand response strategies

Demand response programmes are used in microgrid research without considering the different price elasticity of distinct load types. To evaluate the impacts of demand response efforts, it is necessary to utilise a mix of nonlinear and linear models for creating load-responsive models in a manner that is realistic. With an aim to address this gap in research, an exhaustive technoeconomic investigation is being conducted to determine the effect that price-dependent demand response programmes have on the optimal scheduling of microgrids when linear and nonlinear load models are present. The flexible elasticity model is used to accurately describe how customers respond to changes in electricity price. Four load models, including exponential, hyperbolic, linear, and logarithmic, were constructed for each demand response programme. Rime is a newly created physics-based algorithm that has been deployed to handle the anticipated energy management problem that the microgrid may be experiencing. To evaluate the efficacy of the proposed strategy, four case studies based on grid price and participation scenarios have been carried out. The findings from our research are notably impactful, revealing an 8 % reduction in energy consumption when applying the critical peak price (CPP) load demand model. This efficiency gain translates into a notable enhancement in the load factor, increasing from 0.83 to 0.86, and a significant drop in overall generation costs from $25,463 to $21,823 under optimal conditions. These results vividly illustrate the practical value of our proposed research work, showcasing their ability to generate substantial energy savings and cost efficiencies in microgrid operations. The improvements in operational efficiency and cost-effectiveness underscore the potential of these models to refine microgrid management, delivering both economic and performance gains that are crucial for advancing sustainable energy solutions.

Catalyzing green transformation: mitigating oil price impact on CO2 emissions in Saudi Arabia via renewable energy transition

AbstractExploring the relationship between international oil prices, income, and carbon dioxide (CO2) emissions in Saudi Arabia, this study examines if renewable energy consumption plays a lowering tool in international oil prices' impact on CO2 emissions, employing conventional econometric methods and the functional coefficient approach. The study reveals that the interaction between renewable energy consumption and international oil prices has a negative and statistically significant impact on CO2 emissions. This emphasizes the potential for Saudi Arabia to reduce carbon emissions by prioritizing renewable energy projects. In addition, a positive and statistically significant relationship between income and CO2 emissions is found, emphasizing the need to decouple economic growth from emissions growth. Furthermore, an interesting decoupling effect between oil price elasticity of CO2 emissions and per capita GDP is noted from the early 2000s–2015. This indicates that economic growth driven by rising oil prices can be managed to mitigate environmental impact, showcasing Saudi Arabia's commitment to sustainable development. Policy recommendations involve intensifying efforts to promote renewable energy implementation, lowering fossil fuel dependence in power generation, and incentivizing emissions reduction for a more sustainable energy future.

Unraveling the effect of electricity price on electric vehicle charging behavior: A case study in Shenzhen, China

Estimating price elasticity of demand for electric vehicle charging contributes to the accurate determination of charging price, thereby improving electric vehicle adoption and energy sustainability. However, few studies have studied the impact of electricity price on electric vehicle charging behavior, especially the demand spillover effect caused by price fluctuations. To fill the gaps, on a citywide dataset of public charging piles in Shenzhen, China, first, correlation coefficients and hypothesis tests are used to determine the relationship between charging demand and price. A learning model incorporating two-layer graph attention, temporal pattern attention, and knowledge-embedded meta-learning is developed for accurate spatio-temporal regression. Impulse response analysis is conducted to unravel several noteworthy phenomena: (1) public charging demand is inelastic to electricity price, with an average elasticity of −0.76, and distinction between different functional areas and times is revealed; (2) negative price impulses marginally change the elasticity, while positive ones make electric vehicle charging users more price sensitive, and (3) the spillover effects caused by price increases and decreases bring 89.48% and 53.88% of its local demand changes to neighbors, respectively, with a scope of 3.45 kilometer. These findings provide policy implications for promoting electric vehicle charging to facilitate renewable energy transition.