Price Elasticity Of Supply Research Articles

Estimating leakage rates for Ontario forest offset projects

Forest offset projects can contribute to climate change mitigation. The key question is whether mitigation benefits of forest offset projects are undermined by shifting emissions elsewhere—a problem known as leakage. In this study, we estimated leakage caused by market effects for forest offset projects in Ontario, Canada, using a well-known method developed by Murray et al. (2004). Leakage was calculated using price elasticities of supply and demand from a literature search of studies relevant to Ontario. The average leakage rate was 52.2%, with the 5–95th percentile range from 24.7% to 76.2%. Leakage estimates were tested for sensitivity to policy scale and substitutability parameters.

A Poor but Efficient Crop: Supply-Side Responses in the Greek Tobacco Sector, 1953-64

We analyzed the price elasticities of the Greek tobacco supply at three different levels of analysis (cross-varietal, cross-regional, and two-dimensional) using secondary-level data published by the Greek National Tobacco Board for the years 1953 to 1964. Our panel suggest that the development of postwar Greece’s tobacco sector was largely determined by market forces rather than by state-led purchasing programs. However, market pressures impacted production and sales volume to varying degrees, depending on the tobacco varieties grown in different parts of the country. Given that tobacco was postwar Greece’s most important export crop, and that it was the object of considerable state support, the often-made claim that state interventionism has disincentivized the adaptation of the Greek agricultural sector to evolving markets needs to be revised. Our findings support Shultz’s poor-but-efficient hypothesis regarding farmers.

Factors affecting the costs of broiler chicken production in light of urgent international variables

The study aims to analyze the costs of broiler chicken production in the Fayoum governorate, and in particular the effects that the Russia–Ukraine war has had on production costs. The results indicate increased production costs due to the war and a decreased net return for the three production capacities and the sample average: the return index on invested dollars before the war was 0.71, 0.89, 1.0, and 0.87, respectively; however, this decreased after the war to 0.35, 0.53, 0.66, and 0.51, respectively. The war has led to an increase of 43.93% in the minimum price as the production costs have risen. The value of the price elasticity of supply was about 0.233 at the minimum price and 0.041 at the current price level. If the prevailing price increases by 10% to become $2.13 thousand per ton, the price elasticity of supply becomes about 0.037. The study recommends producing cheap, high-quality, non-traditional feed and focusing on small production capacities. It also suggests integrating and developing them to increase profits. KEYWORDS capacity savings, cost functions, economic efficiency, equivalence price, quantitative equivalence, supply function

Цінова еластичність попиту та пропозиції на ринку плодів в Україні

The state of development of the domestic fruit market is considered. It has been established that the main part of their product supply is formed by households and at the expense of imports. Based on the determination of indicators of the sufficiency of food consumption in Ukraine, it was established that the most critical is the provision of domestic demand for fruit. Elasticity indicators for prices, incomes and substitute products were determined. The coefficients of price elasticity of demand and supply show that consumers and producers respond to price changes – when they increase, demand decreases, and as a result, supply volumes. It was determined that the demand for stone fruits and nuts changes most noticeably when the income of the population varies. The coefficients of the cross-elasticity of the demand for fruits have a positive value. Therefore, there is a direct dependence on the price change for substitute products.

Price volatility and demand of vegetables in three Brazilian Southeast supply centers between 2017 and 2021

Vegetable consumption has increased in recent years due to the predisposition of people to have a healthy diet, which includes the ingestion of fibers, vitamins, and minerals present in fruits and vegetables. In Brazil, lettuce, tomato, carrot, onion, and potato are the five vegetables with the highest consumption. In this study, the price volatility and the price elasticity measure (price elasticity of supply, price elasticity of demand, or price inelasticity) of lettuce, tomato, carrot, onion, and potato were evaluated in three supply centers (CEAGESSP, CEASAMINAS e CEASA/RJ) between 2017 to 2021. The results indicated that all the evaluated products had similar price volatility behavior between 2019 to 2021 in the three supply centers. Moreover, the years with higher instabilities of prices were 2020 for potatoes and carrots, 2019 for lettuce, and 2018 for onion. The price elasticity or inelasticity had independent behavior per supply center. However, there are some periods of inelasticity where the price does not influence the quantity demanded or supplied of the evaluated products. In conclusion, there is high variability of price and volume for tomato, potato, onion, lettuce, and carrot during the year. There was a negative in the price and volume of vegetables which indicates that the reduction of volume increases the price of vegetables. The prices of commercialized vegetables are strongly influenced by the forces of supply and demand, which configures a seasonal characteristic.

Spatial Procurement of Farm Products and the Supply of Processed Foods: Application to the Tomato Processing Industry

AbstractIncreased transportation and logistical costs in agricultural markets have affected the spatial allocation of production in the agricultural and food sectors of the economy. We develop a spatial model of farm product procurement by a food processor, which is designed to capture the effects of supply-chain disruptions on the spatial procurement of farm products in the processed food sector. We use detailed data on production and procurement from a large California tomato processor to estimate the key parameters of the model, which allow us to calculate the price elasticity of supply for California tomato paste production and describe how changes in energy prices and transportation costs for primary agricultural products affect the supply of processed food.

Estimating oligopsonistic market power in Uganda’s rice industry

ABSTRACT The study applies the conjectural variations approach to determine whether Ugandan rice traders exercise oligopsony power in the market for domestic rice. The trader margin for milled rice is found to be 10.20% on average. Using an econometric system of four equations, the null hypothesis of competitive behaviour holds at different price elasticities of farm supply, ranging from inelastic to elastic supply. This implies that there is no evidence that rice traders apply oligopsony power when procuring milled rice from farmers. However, since the study does not examine the existence of trader bargaining power, we cannot completely rule out the existence of market power at this node of the value chain. Therefore, future studies should examine trader bargaining power to be able to ultimately determine if there is need to intervene at this segment of rice value chains to ensure competitive behaviour.

The impact of oil price shocks on the U.S. and Chinese stock markets: A quantitative structural analysis

This paper applies sign restrictions to identify oil structural shocks by imposing nonzero restrictions on the short-term price elasticity of oil supply. With the help of oil inventory data, flow supply, flow demand and speculative demand shocks in the global oil market are identified. Then, the impact of different kinds of oil price shocks on fluctuations of the U.S. and Chinese stock markets is examined and some insights from the perspective of frequency domain are provided. We observe that the U.S. and Chinese stock markets are extensively influenced by the three types of oil structural shocks. In particular, oil price shocks induced by speculation can significantly affect the performance of stock markets in both countries. Under the frequency domain, we notice that the flow demand shock is the most important driver of the variance in U.S. and Chinese stock returns and volatility, particularly at low and business cycle frequencies. Meanwhile, we note that short-term fluctuations in Chinese stock market returns and volatility are more vulnerable to speculative demand shocks. These analysis results are not only useful for policymakers to take targeted measures to deal with the impact of oil price shocks on the stock market, but also useful for investors to adjust their stock portfolios to achieve excess returns.

Policy Note: Why Irrigation Water Pricing is Difficult

Could irrigation water pricing be reformed so that the practice of irrigation is less harmful? Answering this question requires insights into how water pricing reform works for different irrigators/crops each with its own price elasticity of irrigation water demand and water supply, and into the political complexity of irrigation water pricing reform. In particular, the full benefits and costs associated with irrigation are an important, but often inadequately understood, element in irrigation water pricing reform. In this paper, these insights are investigated using the theoretical concepts of supply and demand. It is shown that the market cannot provide the full benefits from irrigation and ignores the full costs. It is also shown that the shape of the irrigation water supply and demand schedules, the current equilibrium position and the size of the charge required to get to a socially optimum position all work against irrigation water pricing as a tool that can be used to reduce demand. These concepts can be used to assess the implications of irrigation pricing reform comprehensively, explicitly and consistently, so that the implicit subsidies and externalities become visible.

Price Dynamics of a Delay Differential Cobweb Model

The paper uses a new technique to find a unique solution to a delay differential cobweb model (formulated from a joint supply-demand function of price) with real model parameters via the Lambert W-function without considering any complex branches. The dynamics of the model are demonstrated with simulations and found to complement previous studies using literature values. However, the condition for instability δ / β > 1 in the previous studies was defied by our model due to the time delay associated with the supply function. The practical application and advantage of this model over the existing models are that the stability of this model is not limited to only the ratio of price elasticity of demand and supply but also the time-delay parameter (i.e., a missing link in the previous models). Our model, on the other hand, loses its stability when the time delay associated with the supply function is fixed at τ = 1.8 . Since most of the physical systems, including economical systems, are time-delay inherent and such stability conditionalities should not limit their performance, it is recommended that such systems be modelled using delay differential functions. The novelty of this research is that there has not been a definite general solution to the cobweb model with a time delay whose price dynamics mimic the behaviour of the existing cobweb models in the literature. An illustrative example in a delayed fractional-order differential equation also buttressed the importance of the time delay in the model, aside from the impact of the ratio of the price elasticity of supply and demand.

The importance of supply and demand for oil prices: Evidence from non‐Gaussianity

When quantifying the importance of supply and demand for oil price fluctuations, a wide range of estimates have been reported. Models identified via a sharp upper bound on the short‐run price elasticity of supply find supply shocks to be minor drivers. In turn, when replacing the upper bound with a weakly informative prior, supply shocks turn out to be substantially more important. In this paper, I revisit the evidence in a model that combines weakly informative priors with identification by non‐Gaussianity. For this purpose, a SVAR is developed where the unknown distributions of the structural shocks are modeled nonparametrically. The empirical findings suggest that once identification by non‐Gaussianity is incorporated into the model, posterior mass of the short‐run oil supply elasticity shifts toward zero and oil supply shocks become minor drivers of oil prices. In terms of contributions to the forecast error variance of oil prices, the model arrives at median estimates of just 6% over a 16‐month horizon.

Delays in access to an Alzheimer’s treatment for individuals dually eligible for Medicare and Medicaid in the U.S.

AbstractBackgroundPrior research has predicted substantial wait times for access to a disease‐modifying Alzheimer’s treatment because of the combination of a highly prevalent disease and a complex diagnostic process. Access could be particularly limited for individuals dually eligible for Medicare and Medicaid in the U.S. in some states. Medicaid programs cover Medicare cost‐sharing requirements for their indigent members, but under the so‐called “lesser of” policy, states may elect to pay only up to the Medicaid rate which is typically less than the Medicare rate. In states with that policy, providers will only receive the lower Medicaid rate, which is known to reduce appointment availability. We estimate the effect of the policy on wait times.MethodWe use a Markov model to predict wait times for dually eligible and regular Medicare beneficiaries. Counts of both groups by age, sex and states came from Census data and Medicare enrollment records, specifics of each state’s Medicaid policy from published data and inquiries to states, and prevalence and incidence data as well as price elasticity of supply from published data.ResultAt total of 35 states and the District of Columbia have a “lesser of” policy and pay less than the Medicare rate for elective specialty care. The average wait time for dually eligibles is between 5.9 and 48.5 months with an average of 17.5 compared to between 3.6 and 42.5 with an average of 13.8 for regular Medicare beneficiaries in those states. Conversely, wait times are indistinguishable in states without that policy, as Figure 1 illustrates. As Figure 2 shows, the difference means that duals have a 30.3% higher average wait times than regular Medicare beneficiaries with a range of 61.2% in DC and 1.2% in Georgia.ConclusionThe “lesser of” policy is likely to reduce access for the socio‐economically disadvantaged group of dually eligibles, who also suffer from a higher disease burden. The delays would translate into avoidable disease progression and mortality, raising concerns about health equity.

An integrated model for electricity market coupling simulations: Evidence from the European power market crossroad

Motivated by the project of European Power Exchanges to develop a single price-coupling solution to calculate electricity prices across Europe that respects the cross-border capacity constraints on a day-ahead basis, we empirically examine and quantify market inefficiencies in non-coupled day-ahead electricity markets. These result from inefficient cross-border capacity allocation and its underlying effect on the market clearing prices. Efficient cross-border capacity allocation and new market clearing prices are simulated using a social welfare maximisation algorithm for the capacity of relevant network elements, whereas the order book generation process is reproduced by the econometrically estimated supply price elasticity functions. The estimated vector autoregression model and the underlying impulse response functions examine price shock transmission under different market regimes. The market coupling process is simulated on the historical non-coupled day-ahead market realisations at the junction of three regional power markets: Central Western Europe, Northern Italian, and South Eastern European markets. Simulation results confirm steady, efficient cross-border capacity utilisation, reduced price variance, improved overall price convergence and amplified price shock transmission in coupled electricity markets. Furthermore, in the simulated period, we have estimated an increase in the overall suppliers' and consumers’ surplus of almost EUR 16 million. The proposed simulation framework is a clear choice for applied simulation in coupled day-ahead electricity markets, offering valuable visual insights into the cross-border capacity allocation and its implications on electricity prices.

Disentangling Housing Supply to Shift towards Smart Cities: Analysing Theoretical and Empirical Studies

The search for a pleasant home has concerned people ever since. Paradoxically, people are facing strong difficulties in finding a decent place to settle their lives in cities. As such, the housing market regained momentum in connection with the development of Smart Cities, where life quality of residents is strongly emphasized. Well-being in the metropolis is affected by a wide variety of factors with housing supply being among the most important, hence stirred by financing costs, construction costs, vacancy rate, sales delay, inflation rate, housing stock, price of agricultural land, and regulation. The present article reviews empirical studies on housing supply for a better understanding of the dynamics in this market, shedding some light on the expectable outcomes of policy actions in the promotion of sustainable housing towards the smart city transition. Our review shows that the long-run price elasticity of housing supply is larger than the short-run, as well as the existence of substantial differences in the price elasticity across countries and regions. As such, overall, the hypothesis of a perfectly elastic supply is rejected. In addition, our review highlights that housing supply is negatively related to financial costs, inflation, sales delay, and the existence of regulatory or physical constraints. Also, the elasticity is lower when there are regulatory constraints. Newfangled strategic interaction models, though overlooked in the literature, reinforce that housing does not fit the perfect competition frame. The review proves that we are in face of a non-competitive market in which policy intervention is required to maximize social welfare; policy packages to grant people access to the housing market may be required. However, policy interventions should be carefully designed and clear, to mitigate their potentially negative impact on the housing supply as adverse results may be harmful to the transition towards a smart city.

Open Space in US Urban Areas: Where Might There Be Too Much or Too Little of a Good Thing?

The considerable variations in the share of open space across US cities raise two questions: What determines the optimal amount of open space in an urban area? Is the existing amount socially optimal? To address these questions, we first process data to measure the amount of natural, preserved, and developable open space in US metropolitan areas. We then develop a framework to characterize the optimal amount of open space in an urban area. This framework reveals that the geography-imposed land scarcity, price elasticities of housing demand and supply, economies of scale in municipal services provision, and marginal benefits from open-space conservation are the key parameters that determine the optimal amount of open space. By implementing the framework empirically, we find that most US metropolitan areas—97.39% according to our preferred model—have insufficient open space in their developed areas and additional open-space conservation in those areas will improve social welfare.

Applying the pricing mechanism to address imbalances in the dairy industry: Regional issues

Subject. This article discusses the issues of development of the raw milk market. Objectives. The article aims to analyze the impact of the process of linking capital and profit on the performance of agricultural organizations considering the Saratov Oblast as a case study. Methods. The harmonization of the provisions of the neoclassical concept of price elasticity of supply and the classical theory of reproduction forms the methodological basis of the study. Results. The article finds that a significant increase in the cost of a tonne of raw milk arises due to unequal exchange with the agro-industrial complex branches and the financial and credit sphere, the withdrawal of the producer's surplus as a result of the abuse of the dominant position by processors, and a decrease in the incentive to effective management. Conclusions. The scarce raw milk market generates a wide range between the estimated and actual price of milk, which makes it possible for the processor to vary the amount of production consumption to restrain the movement towards equilibrium in the market. A weak incentive to increase the volume of milk sales in all categories of farms does not allow considering the price as an adequate tool for solving the problem of shortage.

Investment choices and production dynamics: The role of price expectations, financial deficit, and production constraints

We propose a model that helps answer two questions: (1) what motivates firms to invest in novel technologies, often characterized by low (or negative) returns, forgoing high-profitability projects, and (2) why responses to price changes of seemingly similar firms may differ substantially. The developed framework reveals how financial limitations, production capacity constraints, and expectations on intertemporal price differences and productivity improvements alter investment decisions and the elasticity of supply. Using the U.S. unconventional oil and gas investment and production data, we reveal the trade-off between profit generation and investment-driven improvements in productivity. Then, with simulations, we show how the price elasticity of supply may differ across firms with different financial and production capabilities and how learning abilities and price expectations explain the negative elasticity (or “backward-bending” supply curve) phenomenon.

Reducing the United States’ risks of dependency on China in the rare earth market

Rare earth elements (REE) are crucial in supporting multiple industries with new technologies. Thus the U.S.’ demand for rare earth oxide (REO) is on the rise. Yet, most of the REO supply comes from China, which exposes the U.S. to supply risks similar to that observed by the export quota imposed by China in 2010–2011. This paper uses supply and demand models to evaluate the effects of the U.S. government's proposed strategies to reduce supply risks associated with potential export restrictions from China. We show that there are multiple policies available to mitigate the impact of China's dominance in the market by attenuating the price increases and supply shortfalls, with the size of the changes depending on the price elasticity of demand and supply for REOs. In addition, there are varying degrees of welfare gains from each proposal. Specifically, reducing domestic demand for newly-extracted REEs through substitution (such as recycling or finding alternatives to REEs in production) provides the largest welfare gains. The next best welfare-improving proposal is discovering new domestic supplies of REOs, followed by plans to gain access to foreign REO sources.

Facts and fiction in oil market modeling

A series of recent studies has called into question the validity of traditional VAR models of the global market for crude oil. These studies seek to replace existing oil market models by structural VAR models of their own based on different data, different identifying assumptions, and a different econometric approach. Their main aim has been to revise the consensus in the literature that oil demand shocks are a more important determinant of oil price fluctuations than oil supply shocks. The purpose of this paper is to discuss the main differences between these competing approaches and to highlight the key points in dispute, including the way the priors are specified, the nature of the priors about the one-month price elasticity of oil supply, the pros and cons of alternative methods of econometric inference, the measurement of global crude oil inventories, oil consumption growth and global real activity, and the replicability of the results in Kilian and Murphy (2014). I make the case that the concerns regarding the existing VAR oil market literature have been overstated and that the results from these models are quite robust to changes in the model specification.

Optimal stochastic scheduling in microgrids under managed risk

This paper addresses the stochastic optimal day-ahead microgrid (MG) energy resources scheduling, considering the uncertain load, price of electricity, and generated electrical power by wind and solar units. Moreover, the vehicle-to-grid (V2G) implementation, load curtailment cost, and spinning reserve requirements are modeled to make the results more practical and applicable. Furthermore, the price elasticity of supply is considered to explore the relation between V2G capability and the optimization process. The stochastic energy resources scheduling problem is formulated in a two-level optimization framework. The unit commitment of dispatchable resources is analyzed in the upper level, and the lower level is formulated as a scenario-based two-stage stochastic programming problem that minimizes the operation cost of MG considering all the constraints. The risk of attaining unfavorable high costs of MG scheduling is considered using the variance approach. The generated scenarios are reduced by using the backward reduction method for each uncertain variable at each hour, independently. The artificial intelligent-based methods, including differential evolution algorithm (DEA), particle swarm optimization (PSO), and covariance matrix adaptation evolution strategy (CMAES) are applied to solve the problem. The effectiveness of the proposed approaches is confirmed by simulations on a modified 13-bus IEEE test system, in two cases of neglecting the risk and including the managed risk by applying the real-world data. The results confirmed the better performance of CMAES for solving such optimization problems.