Price Elasticity Research Articles

Long-Term Investors, Demand Shifts, and Yields

Abstract I exploit a Dutch reform in the regulatory discount curve that makes the liabilities of pension funds and insurance companies (P&Is) more sensitive to changes in 20-year interest rates but less so to longer maturity rates. Following the reform, P&Is reduced their longest maturity bond holdings but increased those with 20-year maturities, steepening the long end of the yield curve. Using the reform as a shock to identify price elasticities of demand at the sector level based on holdings across maturity buckets and time, I show that banks are more price elastic than other investors and absorb demand shocks. (JEL G12, G18, G22, G23, G28)

National survey reveals elastic price sensitivity for select equine veterinary services.

The objective of this study was to estimate the price elasticity of demand for 3 common equine veterinary services: vaccinations (a routine service), lameness examinations (an elective service), and emergency colic surgery (an urgent service). Data were collected via a nationwide online survey of horse owners from August 15 to September 11, 2023, eliciting their willingness to pay for each service. The link to the online survey was distributed through participating organizations' social media and email lists to the target audience of US residents aged ≥ 18 years who were financially responsible for at least 1 horse, pony, mule, or donkey. Statistical software was used to estimate the demand models. The survey received a total of 4,915 usable responses, with at least one response from every state in the US. Results revealed elastic demand for all 3 services and subsample analyses provided reassurance as to the robustness of the results, suggesting that quantity demanded of these services would decrease more in a relative sense as compared to the increase in price. Understanding the current and future trends of equine veterinary service demand is vital in ensuring the long-term financial sustainability of equine veterinary practices. Moreover, due to vast differences in the pricing structure of small animal and equine practice procedures, business models for these types of practices should be treated separately. Although it may seem counterintuitive for practice growth, the estimated price elasticity of demand suggests that strategic price increases could enhance profitability. While higher prices may reduce service volume, they could also lead to lower costs, potentially offsetting any revenue reduction. Moreover, the findings on elastic demand can also inform decisions regarding discounts, service bundles, and the development of tiered service offerings.

Empirical insights into India's energy demand: unveiling elasticity dynamics for strategic policy initiatives.

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 apositive 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.

Dynamic pricing and demand forecasting: Integrating time-series analysis, regression models, machine learning, and competitive analysis

Abstract. Dynamic pricing is a critical strategy for businesses seeking to optimize revenue and stay competitive in fluctuating markets. This paper explores the integration of various demand forecasting techniques, including time-series analysis, regression models, and machine learning algorithms, with competitive analysis methodologies to enhance dynamic pricing strategies. Time-series analysis focuses on decomposing data into trend, seasonality, and random fluctuations, using ARIMA models for accurate demand prediction. Regression models delve into the complexities of variable interactions, extending beyond linear relationships to include advanced techniques like Ridge, Lasso, and Elastic Net regression. Machine learning algorithms, such as decision trees, random forests, gradient boosting, and neural networks, revolutionize demand forecasting by uncovering complex patterns in large datasets. Competitive analysis incorporates market scanning, price elasticity estimation, and competitor behavior modeling to inform dynamic pricing decisions. Optimization algorithms, including linear programming, genetic algorithms, and simulated annealing, are employed to refine pricing strategies, while revenue management techniques like yield management and overbooking ensure maximum revenue from perishable goods and services. This comprehensive approach enables businesses to dynamically adjust prices in real-time, maintaining competitiveness and maximizing profitability in an ever-evolving market landscape.

Identification of Agricultural Socioeconomic Factor and Its Relationship with Exports of Palm and Palm Kernel Oils in Indonesia

The research aim was to study the influence of area size consisting of Government Estate (Government Estate), Private Estate (PBS), Smallholder (PR), price and exchange rate on production, and the influence of production, price and Exchange rate on palm oil exports which consists of Crude Palm Oil (CPO) and Palm Kernel Oil (PKO) using panel data for 2000-2022. Whether viewed from CPO or PKO, the results of the analysis show that the Government State has a real negative influence on production where the elasticity of the Government Estate for CPO towards production is lower than for PKO. The increase in production was significantly caused by the increase in PR for both CPO and PKO, where the elasticity of the increase in PR for CPO was higher than the increase in PKO. PBS provides a positive influence on production which is significant for PKO but not significant for CPO, while prices and exchange rates do not have an influence on CPO production, nor on PKO production. CPO and PKO exports are significantly influenced by prices, where CPO's price elasticity is higher than that of PKO. Furthermore, production and exchange rates have no influence on exports of either CPO or PKO, while the increase in CPO exports is determined significantly by PR, where the elasticity of CPO is higher than PKO.

Time-Varying Income and Price Elasticities of Oil Demand in OECD Countries

This study examines the long-run income and price elasticities of oil demand in 21 OECD countries using quarterly data from 1980:Q1 to 2021:Q3. We find that oil demand is inelastic with respect to both income and prices at 0.117 and −0.179, respectively. The cointegration tests reveal instability in oil price elasticities over time. The time-varying panel data estimates support these findings, showing significant variations in elasticities influenced by oil market dynamics and global events. Income elasticities reached their highest levels during the COVID-19 pandemic, while price elasticities ranged from −0.396 to 0.275. Significantly, the sign of oil price elasticities shifted from negative to positive after 2015, contrary to the law of demand, probably because of declining oil prices during that period. The largest positive and statistically significant price elasticity occurred in early 2020, which can be attributed to the COVID-19-induced decline in oil prices. Overall, this analysis contributes to understanding oil demand dynamics and highlights the impact of economic and oil market factors on elasticities.

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.

Price Sensitivity and Information Barriers to the Take-Up of Naloxone

We conducted a field experiment that randomized advertisements, advertisement content, and prices across 2,204 counties in the United States to study the impacts on online purchases of naloxone, an opioid overdose reversal drug. Advertising increased web-site users but only impacted purchases when combined with a price reduction. Messages emphasizing the discreet nature of online sales had no additional impact on purchases. Comparing counties with advertisements featuring a highly discounted price to those featuring the full price, we estimate a price elasticity of demand for online naloxone of −1.3. Price is a significant barrier to online purchases of this lifesaving medication. (JEL C93, H75, I12, I18, L65, M37)

Welfare implications of rising imported food costs in the Caribbean

Vulnerability to external shocks such as supply shortages, price increases, disasters and political discord has severe implications for Caribbean food and nutrition security and the scale of economic losses. There is a need to understand how food price shocks impact Caribbean consumers, who are particularly vulnerable due to their heavy reliance on imported food. This study assessed the welfare impacts of rising imported food prices on Caribbean consumers using the linear approximated almost ideal demand system (LA-AIDS) model and compensating variation. The welfare implications of rising prices were assessed using three price shocks in: 2006–2008, 2010–2011, and 2020–2021. Hicksian price elasticities revealed that most imported food categories in the Caribbean region have inelastic demand, except for imported meat and seafood which was found to be elastic. Imported cereals and staples and fats and oils were the least responsive to price changes, while imported meat and seafood was highly responsive. The results of the compensating variation revealed that there were significant welfare losses in 2006–2008 and 2010–2011, when food prices drastically increased, as well as during the first year of the COVID-19 pandemic (2020–2021). Between 2006-2008 and 2010–2011, welfare losses were approximately US$1.54 billion and US$692.52 million, respectively, while food price inflation during the first year of the COVID-19 pandemic resulted in losses estimated at US$1.09 billion. This research highlights the need for regional policies to minimize welfare losses from rising food prices, including social safety nets for vulnerable households and investments in domestic agriculture and supply chain resilience.

The Bitter Taste of Brazil's Temporary Import Ban on Robusta Coffee

ABSTRACTBrazil, a leading Robusta coffee producer and exporter, faced a significant drought in 2016–2017, which drastically reduced production and depleted stocks. Consequently, Brazil temporarily permitted the import of one million 60‐kg bags of Robusta coffee in the spring 2017. An import ban was imposed shortly afterward due to lobbying by domestic Robusta farmers. We examine the welfare and trade impacts of the drought and subsequent import ban on stakeholders in the Robusta bean and soluble coffee markets. The import ban improved the welfare of Brazilian Robusta producers by $174.85–$280.26 million, nearly offsetting the drought's effects. However, it increased unit cost for Brazilian soluble processors by 10% and reduced consumer surplus in Brazil by $108.35–$174.44 million. Deadweight losses remained minimal due to the markets' price inelasticity. Major Robusta exporters faced reduced exports to Brazil and up to 9% lower prices, losing 0.3363–0.7564 million 60‐kg bags. Additionally, foreign consumers of Brazilian soluble coffee lost $62–$107 million in welfare from higher prices. without the import ban, global stakeholders would have seen a $12.61/bag higher world bean price. The drought benefitted Robusta sellers outside Brazil but harmed net importers, even with the ban in place.

Optimal strategies for contract farming supply chain with government subsidies under e-commerce assistance to farmers.

The agricultural issue is a focal point of concern for each country, and e-commerce assistance to farmers, as an emerging model, is gaining increasing attention. Considering this trend, this paper bases on e-commerce assistance to farmers and considers four types of government subsidies: no subsidy, price subsidy model with the farmer as the subsidy target, price subsidy model with the e-commerce platform as the subsidy target, and area subsidy model. Based on this, a game model of the contract farming supply chain involving a farmer and an e-commerce platform was established to explore the optimal decision-making in the contract farming supply chain considering various government subsidies under the background of e-commerce assistance to farmers. The results indicate that: (1) Consumer preference for supporting farmers and consumer premiums can stimulate the farmer to expand farm size, increase agricultural production, increase the purchase price of agricultural products and promote the growth of profits for the farmer and the e-commerce platform, contributing to the growth of social welfare. Output volatility can lead to a decrease in farm size and a reduction in the purchase price of agricultural products. (2) Government subsidies can support the farmer in expanding farm size and contribute to increased profits for the farmer and the e-commerce platform. However, government subsidies do not universally have a positive impact on every variable. The influence of government subsidies on the purchase price of agricultural products is contingent upon the method of subsidy distribution. Similarly, the effects of government subsidies on social welfare are influenced by factors such as price elasticity and agricultural productions per unit area. (3) From the perspectives of farm size, the purchase price of agricultural products, and profits of the farmer and the e-commerce platform, the government will have different and more targeted subsidy models, and the corresponding subsidy models are influenced by the agricultural productions per unit area. The research conclusion can provide references for optimal decision-making in contract farming under the model of e-commerce assistance to farmers.

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.

Willingness to pay and price elasticity of demand for long-acting injectable cabotegravir among men who have sex with men in Guangxi, China.

There is still no study focused on willingness to pay for long-acting injectable cabotegravir (CAB-LA) after it was available on the market in the United States in 2021. Here, we explored the willingness to pay for CAB-LA and associated factors and price elasticity of demand (PED) of CAB-LA among men who have sex with men (MSM) in Guangxi, China. A cross-sectional study was conducted. Univariate and multivariate ordinal logistic regression analyses were performed to explore the associated factors of willingness to pay for CAB-LA. PED was used to measure the change in the number of participants willing to pay to a change in price. A total of 1,006 MSM were recruited, among which 84.1% were aged between 18 and 39years old. The median (interquartile) of the maximum amount of willing to pay for CAB-LA was 200 (100-500) Chinese yuan (CNY) per month. Most (84.2%) were willing to pay less than 600 CNY per month. The number of participants willing to pay for CAB-LA significantly increased with decrease in the price. When the price (CNY per month) decreased from 600 to 500, 500 to 400, 400 to 300, and 300 to 200, PED was 3.13, 1.64, 1.33, and 1.17, respectively. The maximum amount of willing to pay for CAB-LA was positively associated with younger age (vs. ≥40years group, 18-24years group, aOR: 1.94, 95% CI: 1.32-2.85; 25-39year group, aOR: 1.70, 95% CI: 1.20-2.42), being high educated (vs. middle school or lower group, high school or college group, aOR: 1.61, 95% CI: 1.06-2.48; bachelor's degree or above group, aOR: 2.21, 95% CI: 1.41-3.49), monthly income ≥6000 CNY (vs. <3000 CNY, aOR: 1.46, 95% CI: 1.02-2.09), being bisexual/unsure sexual orientation (vs. gay, aOR: 1.73, 95% CI: 1.24-2.43), and heard of PrEP and used (vs. never heard of PrEP, aOR: 1.76, 95% CI: 1.11-2.77). The maximum amount of willing to pay for CAB-LA was low in Guangxi, China. PED of CAB-LA is relatively elastic. The waived patent protection should be considered for the wide promotion of CAB-LA, and the health education should be strengthened to improve the recognition of CAB-LA.

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.