Price Auction Research Articles

Do the Most Important Artists Make the Most Expensive Paintings?

Art experts have disagreed about whether art markets accurately reflect artistic importance. This paper uses published surveys of art history to construct a critical ranking of the 30 most important American painters of the last century, then uses auction records to identify the most expensive paintings by these artists. The results show a strong positive association between critical rankings and auction prices: there is a high rank correlation between the critical ranking of artists and a ranking of the artists by their single highest auction price, and the top artists in the critical ranking are highly disproportionately represented among auction sales over $10 million, $30 million, and $50 million. Auction markets do recognize artistic importance: the greatest artists produce the most expensive paintings, and it is their most important works that sell for the highest prices.

Reducing information asymmetry in the auctioning of non-perishable experience goods: The case of online wine auctions

We highlight the importance of reducing the perceived risk associated with information asymmetry for experience goods. We analyse a major online non-perishable experience good, wine, from the seller's perspective. The mechanism for lowering information asymmetry is the verification service offered by the auctioneer. By focusing on unsold items/lots, the wine and auction characteristics affecting the probability of a sale are identified. Results show that the verification of the wine's provenance increases the probability of sale by 5.7 percent and leads to an expected increase of 5.1 percent in the auction price. When both effects are combined, the increase in the expected revenue of the seller is 7.3 percent. We test and find no evidence of selection bias. Given the heterogeneity in wine prices, a quantile regression analysis shows how the results differ for high-priced wines compared to lower priced wines. Results highlight how the mechanisms to lower the degree of information asymmetry work both in attracting bidders to online auctions and encouraging bidders to submit higher bids.

Is Gender in the Eye of the Beholder? Identifying Cultural Attitudes with Art Auction Prices

In the secondary art market, artists play no active role. This allows us to isolate cultural influences on the demand for female artists’ work from supply-side factors. Using 1.5 million auction transactions in 45 countries, we document a 47.6% gender discount in auction prices for paintings. The discount is higher in countries with greater gender inequality. In experiments, participants are unable to guess the gender of an artist simply by looking at a painting and they vary in their preferences for paintings associated with female artists. Women's art appears to sell for less because it is made by women.

A Privacy Preservation Based Scheme for Task Assignment in Internet of Things

With the rapid increasing demands of social services, mobile crowd sensing (MCS) is getting growing attraction with the wide applicability of mobile applications. This effective paradigm depends on sensing services from crowd contributors for sensing data collection and sharing. However, on one hand, the sensing data is tampered by malicious users without the reputation evaluation. On the other hand, the privacy information is exposed when mobile users submit sensing data to others. Moreover, the efficiency of task assignment is low without incentives. Therefore, we propose a privacy preservation based scheme for task assignment in internet of things (IoT) to improve the performance of crowd sensing. Firstly, a novel trusted framework is developed to judge mobile user's reputation value. In the proposed framework, the reputation evaluation scheme is established based on the social trust, recommendation credibility, and history evaluation. Secondly, the location-privacy preservation algorithm (LPA) based differential privacy method is designed to protect mobile user's location privacy and select the credible users to complete sensing tasks. Thirdly, to incentivize mobile users, we model the transaction process between mobile requesters and mobile responders as the first-order sealed price auction game. After that, the task assignment based bidding-preferred (TAB) algorithm is proposed to assign tasks to mobile users. Finally, simulation results demonstrate that the proposed scheme can effectively improve the number of finished tasks and bring more utilities to mobile users compared with the conventional methods.

Financial contracts as coordination device

AbstractWe study the use of financial contracts as bid‐coordinating device in multi‐unit uniform price auctions. Coordination is required whenever firms face a volunteer's dilemma in pricing strategies: one firm (the “volunteer") is needed to increase the market clearing price. Volunteering, however, is costly, as inframarginal suppliers sell their entire capacity whereas the volunteer only sells residual demand. We identify conditions under which signing financial contracts solves this dilemma. We test our framework exploiting data on contract positions by large producers in the New York power market. Using a Monte Carlo simulation, we show that the contracting strategy is payoff dominant and provide estimates of the benefits of such strategy.

Vaccination against Pneumococcal Infections of High-Risk People: Pharmacoeconomic Aspects

Relevance. Vaccination of people at high risk against pneumococcal infection with a 13-valent conjugate vaccine (PCV13) can significantly reduce the corresponding incidence and mortality.The aim of the work was to assess the pharmacoeconomic aspects of vaccination of 65 year olds with a high risk of pneumococcal infection.Material and methods. The analysis was carried out by the method of Markov modeling from the position of the health care system. The time horizon is 5 and 15 years. It was assumed that vaccination is carried out with 1 dose of PCV13 and 1 dose of polysaccharide pneumococcal vaccine (PPV23) after 8 weeks with revaccination with 1 dose of PPV23 after 5 years. The costs of treatment of pneumococcal infections were calculated on the basis of the Compulsory medical insurance rates for St. Petersburg in 2019. The costs of vaccination were calculated on the basis of the price of auctions for the purchase of PCV13 and PPV23 for 2019.Results. For 15 years, vaccination of 100 ths people from the high risk group will prevent 1.7 ths cases of community-acquired pneumonia, 1.4 ths cases of invasive pneumococcal infections, and 397 cases of pneumococcal infections deaths. The cost-effectiveness ratio with a 15-year horizon is 161.4 ths rubles/quality-adjusted life year gained (QALY). Even if the time horizon is reduced to 5 years, vaccination can be considered as an economically highly effective intervention (cost-effectiveness ratio –571.9 ths rubles/QALY). At the same time, in 5 years, 37.6% of the money spent on vaccination will be returned to the budget of the health care system, and in 15 years – 49.3%.Conclusion. Vaccination of citizens of the Russian Federation from a high-risk group against pneumococcal infection can be considered as a socially and economically highly effective intervention that provides a significant reduction in the incidence and mortality caused by it.

COMBIMA: truthful, budget maintaining, dynamic combinatorial market

One-sided auctions have long been studied in economics and the computer science multi-agent planning domain [10, 12, 21]. Onesided auctions aim to find a high-social welfare (SWF) (efficient) allocation of a commodity to a set of agents, while ensuring that agents' best strategy is to truthfully report their input. An important extension of one-sided auctions are one-sided combinatorial auctions [17, 19, 20] where multiple commodities are offered for sale. Agents bid on bundles of commodities, which allows agents to express complex preferences over subsets of commodities (see [9] for many examples within). An elegant and well-studied class of combinatorial one-sided auctions are the sequential posted price auctions in which agents are presented sequentially with a vector of prices and must choose their preferred bundle given the price vector (among the first studied are [1, 18]). One-sided combinatorial auctions have been applied to various problems, including airport time-slot allocation [17], distributed query optimization [20] and transportation service procurement [19].

The Impact of Color Palettes on the Prices of Paintings

We emphasize that color composition is an important characteristic of a painting. It impacts the auction price of a painting but it has never been considered in previous studies on art markets. By using Picasso's paintings, we demonstrate the method to analyze color compositions. In the case of Picasso's paintings sold at Chrisite's and Sotheby's auctions between 1998 and 2014 in New York, our econometric analysis shows that [controlling for all conventional painting and sale characteristics] some colors are associated with high prices. We also find that contrastive paintings (defined as works with colors that are distant from each other in the RGB color space) get high prices. We also analyse the works of Color Field Abstract Expressionists and find that, in the case of this school, the more distant the work's color composition is from the black/gray spectrum, the higher work's market price.

Regret Minimization and Separation in Multi-Bidder Multi-Item Auctions

We study a robust auction design problem with a minimax regret objective, where a seller seeks a mechanism for selling multiple items to multiple bidders with additive values. The seller knows that the bidders' values range over a box uncertainty set but has no information on their probability distribution. We propose a mechanism that sells each item separately via a second price auction with a random reserve price and characterize an upper bound on its optimality gap. We show that this upper bound vanishes and that the proposed auction becomes optimal if the bidders are symmetric. We then interpret the auction design problem as a zero-sum game between the seller, who chooses a mechanism, and a fictitious adversary or 'nature,' who chooses the bidders' values from within the uncertainty set with the aim to maximize the seller's regret. We characterize the Nash equilibrium of this game analytically when the bidders are symmetric. The Nash strategy of the seller coincides with the optimal separable second price auction, whereas the Nash strategy of nature is mixed and constitutes a probability distribution on the uncertainty set under which each bidder's values for the items are comonotonic. We also study a restricted auction design problem over deterministic mechanisms. In this setting, we characterize the suboptimality of a separable second price auction with deterministic reserve prices and show that this auction becomes optimal if the bidders are symmetric.

Information Diffusion and Revenue Optimization in Distribution Market

Intermediaries refer to agents that facilitate the resource allocation under certain constrain conditions. In a distribution market, buyers and sellers often interact via intermediaries and pay commissions to them. Due to the inadequacy of information spreading, a commodity can only be allocated to some agent who is close to the seller, which not only decreases the economic efficiency but also limits the seller's revenue. To tackle these two problems simultaneously, which is commonly a difficult objective in multi-agent systems, we use mechanism design theory and graph algorithms to develop a new auction protocol called Multi-Level Diffusion Mechanism (MLDM). Even when there are costs for assisting in others' trades, this mechanism can encourage every intermediary to help spread the selling information, either or not she has personal preference of the commodity. We show MLDM performs better than the second price auction both in theory and in numerical simulation no matter how agents' valuations and commissions are distributed.

A Theory of Auctions with Endogenous Valuations

We derive the revenue maximizing allocation of m units among n symmetric agents who have unit demand, and who take costly actions that influence their values before participating in the mechanism. The allocation problem with costly actions can be represented by a reduced form model where agents have convex, non-expected utility preferences over the interim probability of receiving an object. Both the uniform m+1 price auction and the discriminatory pay-your-bid auction with reserve price constitute symmetric revenue maximizing mechanisms. Contrasting the case with exogenous valuations, the optimal reserve price reacts to both demand and supply. We also identify a condition under which the optimal mechanism is indeed symmetric, and illustrate the structure of the optimal asymmetric mechanism when the condition fails. The main tool in our analysis is an integral inequality, due to Fan and Lorentz (1954), involving majorization, super-modularity and convexity.

Intelligent System for Price Premium Prediction in Online Auctions

The use of data mining techniques in the field of auctions has attracted considerable interest from the research community. In auctions, the users try to achieve the highest gain and avoid loss as much as possible. Therefore, data mining techniques can be implemented in the auctioning domain to develop an intelligent method that can be used by the users in online auctions. However, determining the factors that affect the result of an auction, especially the initial price, is critical. In addition, the intelligent system must be established based on clean data to ensure the accuracy of the results. In this paper, we propose an intelligent system (classifier) to predict the initial price of auctions. The proposed system uses the double smoothing method (DSM) for data cleaning in terms of preprocessing. This system is implemented on a data set collected from the eBay website and cleaned using the proposed DSM. In the training phase, the CART technique is employed for the classifier construction. Compared to similar techniques, the proposed system exhibits a better performance in terms of the accuracy and robustness against noisy data, as determined using ROC curves.

A Model of Collusion Formation and Measurement in the Open Ascending Bid Auctions in Agricultural Commodity Markets

This paper derives a method of measuring the degree of collusion among the bidders in agricultural commodity markets in India and derives the distribution of the change in equilibrium bid prices with respect to time in open ascending price auction when the cartel is there. The important assumption is the bidding is repetitive with a set of common bidders. The theory has been derived based on the behavior of the wholesale market of agricultural commodities in India. This means the paper is based on full information model in the collusion formation. The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation.

Discriminatory price auctions with resale and optimal quantity caps

We present a model of a discriminatory price auction in which a large bidder competes against many small bidders, followed by a post‐auction resale stage in which the large bidder is endogenously determined to be a buyer or a seller. We extend results on first‐price auctions with resale to this setting and use these results to give a tractable characterization of equilibrium behavior. We use this characterization to study the policy of capping the amount that may be won by large bidders in the auction, a policy that has received little attention in the auction literature. Our analysis shows that the trade‐offs involved when adjusting these quantity caps can be understood in terms familiar to students of asymmetric first‐price single‐unit auctions. Furthermore, whether one seeks to maximize welfare or revenue can have contradictory implications for the choice of cap.

Measurement of Collusion in the Agricultural Commodity Auction Markets

This paper derives a method of measuring the degree of collusion among the bidders in an open ascending repetitive price auction in agricultural commodity markets in India. The paper first derives the theoretical structure of the bidders' behavior and thereafter derives a measure of collusion formation. Finally, degree of cartel has been computed using time series wholesale price data of potato and onion crops. The findings of the present research are useful for the study to link between the supply of the agriculture commodity and the degree of collusion. Using the proposed method in the present research, if the APMC measures cartel for each market and publish periodically, it will help the farmers to choose the right market to sell the produce. The farmers would select the market where the degree of collusion is relatively lower. Identification of different small cartel groups at different times with respective to the supply of the agriculture commodity would help to avoid the incidence of distress selling by farmers, which is the main hindrance in the development of farming community in India.

Analysis of Tea Auction Prices Using Non-Cointegration Based Techniques

Favorable product prices act as a set off for any commercial activity normally and perhaps its sustainability. Tea is a significant commercial crop in Kenya and has contributed immensely to the economy’s Gross Domestic Product (GDP) through its export earnings. However, tea industry has gone through many phases of ups and downs, particularly in terms of its export performance recently. Therefore, there is need to study the behavior of tea auction prices to get a deeper perspective into the behavior of the tea prices and to develop a model that is suitable to forecast the tea auction prices precisely. The study aimed at analyzing the trend of tea auction prices in Kenya, fit a suitable model for forecasting tea auction prices and finally, forecast the future tea prices using the most optimal model. The findings of this study will therefore inform the government and other policy makers in terms of its policy formulation regarding the tea sector in order to accord it a competitive position in the global arena. The study used univariate and multivariate forecasting techniques which do not impose co-integration restrictions such as the Autoregressive Integrated Moving Average (ARIMA) and the Vector Autoregressive (VAR). The techniques used were chosen because of their flexibility, wide acceptability and they are also easy to utilize. The study used secondary data for the Mombasa Tea Auction Centre for a period of 2009 to 2018. Augmented Dicker-Fuller (ADF) test was performed for unit root tests to check for stationary of the price series. ACF and PACF functions were estimated to assist in deciding the most appropriate orders of AR (p) and MA (q) models. AIC test was used because were considering several ARIMA models and the model with the lowest AIC was chosen. VAR model showed a high forecasting error with MAPE of 85.64% compared to that ARIMA of 9.2% for tea prices. ARIMA model performed much better than VAR model because of its high forecasting accuracy.

QoS-enhanced bandwidth reallocation mechanism based on auction model in mobile clouds

In recent years, mobile cloud has become a promising platform to offer elastic and scalable service for our daily life. Even so, the features of mobile communication introduce a series of new challenges to conventional bandwidth allocation service. In this paper, we propose an auction-based bandwidth reallocation mechanism to handle the bandwidth shifting issue which may significantly degrade user's QoS satisfactory. To take both resource provider's revenue and user's QoS requirement into consideration, we formulate the bandwidth reallocation problem as constrained optimisation problem, and then design an auction model which introduces a trade-off parameter to adjust the auction price with aiming at improving the user QoS satisfactory in terms of resource cost. Theoretical analysis indicates that the proposed auction model is capable of balancing the benefits between cloud providers and mobile users. Performance evaluation in a realistic mobile cloud shows that the proposed bandwidth reallocation mechanism outperforms existing approaches in terms of various performance metrics.

QoS-enhanced bandwidth reallocation mechanism based on auction model in mobile clouds

In recent years, mobile cloud has become a promising platform to offer elastic and scalable service for our daily life. Even so, the features of mobile communication introduce a series of new challenges to conventional bandwidth allocation service. In this paper, we propose an auction-based bandwidth reallocation mechanism to handle the bandwidth shifting issue which may significantly degrade user's QoS satisfactory. To take both resource provider's revenue and user's QoS requirement into consideration, we formulate the bandwidth reallocation problem as constrained optimisation problem, and then design an auction model which introduces a trade-off parameter to adjust the auction price with aiming at improving the user QoS satisfactory in terms of resource cost. Theoretical analysis indicates that the proposed auction model is capable of balancing the benefits between cloud providers and mobile users. Performance evaluation in a realistic mobile cloud shows that the proposed bandwidth reallocation mechanism outperforms existing approaches in terms of various performance metrics.

Power Sector Emissions under Tightening Carbon Dioxide Quotas

The Regional Greenhouse Gas Initiative (RGGI) was passed by an original collection of 10 northeastern states and is the first cap-and-trade policy in the United States to specifically target carbon dioxide emissions from the electricity sector. We exploit the introduction of this policy and subsequent tightening of the carbon cap to assess how carbon dioxide emissions have changed within RGGI states while also evaluating emissions leakages that may have occurred. While RGGI auction prices are relatively low compared to estimates of the social cost of carbon, the policy represents a direct increase in the cost of production and should have behavioral impacts on producers. Using plant-level data and several identification strategies, we find that there are reductions in emissions from coal-fired plants in RGGI states, but there is mixed evidence at natural gas-fired plants. We also show that the emissions cap reductions enacted in 2014 is where the policy began to have more significant impacts on emissions. These conclusions are strongest with careful evaluation of control states since spillover effects of the policy to non-RGGI states are possible within the Eastern Interconnection.

농지 경매의 낙찰가율에 대한 영향 요인 연구

농지 경매의 낙찰가율에 대한 영향 요인 연구