Price Auction Research Articles

Coupon Design in Advertising Systems

Online platforms sell advertisements via auctions (e.g., VCG and GSP auction) and revenue maximization is one of the most important tasks for them. Many revenue increment methods are proposed, like reserve pricing, boosting, coupons and so on. The novelty of coupons rests on the fact that coupons are optional for advertisers while the others are compulsory. Recent studies on coupons have limited applications in advertising systems because they only focus on second price auctions and do not consider the combination with other methods. In this work, we study the coupon design problem for revenue maximization in the widely used VCG auction. Firstly, we examine the bidder strategies in the VCG auction with coupons. Secondly, we cast the coupon design problem into a learning framework and propose corresponding algorithms using the properties of VCG auction. Then we further study how to combine coupons with reserve pricing in our framework. Finally, extensive experiments are conducted to demonstrate the effectiveness of our algorithms based on both synthetic data and industrial data.

Do Pay-As-Bid Auctions Favor Collusion? Evidence from Germany's market for reserve power

We analyze a drastic price increase in the German auction market for reserve power that did not appear to be driven by increased costs. Studying the market structure and bidding strategies using micro-level bidding data, we find a concentrated market with highly pivotal suppliers in an environment with completely inelastic demand and high entry barriers. We provide descriptive evidence that the price increase was triggered by an abuse of the “guess the clearing price” principle of discriminatory auctions via repeated pretended “bad guessing” of the marginal bid by the most dominant supplier. As intentional “bad guessing” of marginal bids is hard to prove, this suggests that the auction design is crucial for the competition authority's monitoring power – an issue that is often neglected in the discussion on the properties of auction designs. In fact, given regulatory threats, the deemed main advantage of pay-as-bid auctions over uniform price auctions and the popular belief that they reduce dominant suppliers' withholding incentives and diminish their ability to tacitly collude may be questioned in non-static settings. This suggests that pay-as-bid auctions may not necessarily reduce incentives for strategic capacity withholding and collusive behavior, but can even increase them when market power is high and demand inelastic, which is the case in virtually all energy markets.

Auction theory and a note on game mechanisms

Abstract This paper will review important topics on the subject of auction theory and mechanism design, these include: efficiency first and foremost, also revenue comparison between different types of auctions and the issue of incentive compatibility, individual rationality with the general idea and proof that bilateral trade is inefficient. Mechanism design theory tells us that if buyers and sellers both have private information full efficiency is impossible, however Vickrey auction (single unit auction) will be efficient i.e. will put the goods in the hands of the buyers that value them most. However, the conclusion from this paper is that because of overvaluation of bidders the main result is inefficient, i.e. bids are too high. When weak and strong bidders are compared the main conclusion is that strong bidders’ expected payoff is higher in second price auction (SPA), while weak bidder prefers first price auction (FPA) bid.

123 Kentucky's equine markets amidst COVID-19

COVID-19 pandemic-related restrictions on society have resulted in a recession, which is commonly defined as 2 consecutive quarters of decline in GDP (gross domestic product) growth. Restrictions within the equine industry have varied, with some governments mandating the closure of equine facilities to reduce the spread of the virus and minimize the chance of injuries, while others provided health guidelines and assigned responsibility to equine operation owners/managers. Because the equine industry is one of the most important sectors in Kentucky's agricultural economy, understanding the potential impact of COVID-19 on Kentucky's equine markets is vital. To that end, in this study we examined short run COVID-19 impacts on Kentucky's equine markets. In particular, we focused on 2 segments of the industry associated with vigorous business activities. First, we examined how Thoroughbred and Quarter Horse breeding activity and auction markets have responded to general market changes precipitated by COVID-19 restrictions. Second, we investigated the effect of COVID-related regulations on equine enterprises, including stallion farms, boarding/training/lesson operations (BTLO's) and competition enterprises. To achieve the first objective, for the calendar year 2020, we collected and analyzed data on number of mares bred, stud fees, and auction results. To accomplish the second objective, we designed and distributed a survey to 280 commercial equine enterprise owners/managers across the state. Data were collected between November 30, 2020, and January 11, 2021, and the average response rate was about 25%. Preliminary results from the first objective suggest that while there are downward trends in breeding activities and mean auction prices, few of those short-run declines are statistically significant. For the second objective, survey results suggest at least minimal impacts on most commercial enterprises. About 46% of stallion farms reported anticipate revenues losses of 10% or less, but about 23% expect revenue losses of 26 to 50%. Just under 60% of BTLO's anticipate a revenue loss of 10% or less, while about 10% expect a loss of more than 50%. The most damaging effects appear to have been experienced by competition enterprises. About 35% expect only minimal revenue losses, while nearly 40% expect losses of $50,000 or more. Overall, results from our study suggest that with the exception of competition-related enterprises, Kentucky's commercial equine enterprises may have avoided serious short run impacts; however, it will be some time before the long run impact of COVID-19 related restrictions on the industry can be fully determined.

Fairness and Efficiency in Online Advertising Mechanisms

Online advertising often involves targeting ads to certain types of consumers where ads are commonly sold by generalized second price auctions. However, such an auction or mechanism could be considered unfair if similar consumers are consistently shown different ads or consistently receive different payoffs. Results show that such ascending bid auctions may result in unfair treatment and additionally that uncertainty regarding an ad’s value can result in inefficiency. An alternative way to assign ads to consumers is presented called the random assignment mechanism. Results show that the random assignment can improve fairness while improving efficiency in some circumstances.

Mobile Broadband for Inclusive Connectivity: What Deters the High-Capacity Deployment of 4G-LTE Innovation in India?

The global market uptake of the fourth generation-Long-Term Evolution (4G-LTE) Mobile Broadband (MoBro) services are steadily rising, leading to higher capital investments by mobile network operators (MNOs) to scale-up their infrastructure for meeting the impending demand for MoBro data the world over. However, MNOs face uncertainties about financial returns from such investments, owing to a host of technological and market-related factors, which impact the enablement of such 4G-LTE MoBro services. These challenges are clearly evident in the Indian market. Firstly, 4G-LTE subscribers in the rural India contribute to less than one-third of the overall market size. Secondly, India performs poorly in terms of minimum capacity requirements of the 4G-LTE MoBro services. Thirdly, the rise in per-user consumption of MoBro data does not translate into a similar rise in the MNOs’ revenue. Fourthly, the socio-economic-geographic segregation of India into twenty-two administrative zones (referred to as telecom circles) add to the complexities in the capital investment decisions of MNOs. To address the above challenges, we model various cost and profitability scenarios of a hypothetical MNO providing universal 4G-LTE deployment across the twenty-two telecom circles in India using the available spectrum bands. Our proposed model is firmly established in the “network investment economics” framework for telecom innovations. We adopt a technology diffusion-based approach to forecast the 4G-LTE subscribers in India. We focus on the requirements of 4G-LTE MoBro infrastructure investments, including the spectrum selection decisions by MNOs, and show that, for valuation of the spectrum, the policymakers in India need to take into account the potential of the spectrum in terms of financial returns to an MNO deploying 4G-LTE using that spectrum, as against merely valuing the spectrum based on primarily the technical characteristics of its carrier frequency and benchmarks of prior spectrum auction prices in a particular telecom circle. Finally, we also show that a nationwide 4G-LTE network, which is universal, inclusive, and adhering to the global standards in terms of service quality, can be financially lucrative for MNOs, if enabled by appropriate policies instituting collaborative frameworks for infrastructure sharing, and price rationalization of spectrum bands across the twenty-two telecom circles.

STATE POLICY OF KAZAKHSTAN ON IMPLEMENTING OF RENEWABLE ENERGY SOURCES IN TEXTILE INDUSTRY COMPANIES

The article discusses the mechanisms of state support for the development of renewable energy sources (RES) in the Republic of Kazakhstan. The authors consider the prospects of using solar energy in the textile industry. The analysis revealed that the level of organization of work in companies in the field of energy conservation and energy efficiency of production depends on the following factors: timely observation of the current power supply and possible future energy potential; development and implementation of energy-effective measures; use of RES with purpose of saving energy resources. According to the authors, the dominance of electric and thermal forms of energy in the cost structure leads to a loss of competitiveness of the company's products in the textile industry. The article considers the transition to combined generation of electric and thermal energy in textile industry companies using renewable energy sources. The calculation of the energy saving coefficients of electric and thermal energy produced by the authors proved the possibility of reducing the cost of textile products by introducing renewable energy sources. The results of the assessment, based on the construction of a correlation and regression model, showed the economic efficiency of using renewable energy in the textile industry, while the authors recommend paying special attention to state regulation of tariffs and the auction price for renewable energy. Keywords : renewable energy sources, solar energy, textile industry. JEL Classifications: Q42, Q48, L60 DOI: https://doi.org/10.32479/ijeep.10659

Consignment auctions revisited

This paper studies the consignment auction as an allocation mechanism for emission permits among polluting firms. By assuming firms have non-increasing marginal values for the permits and linear bid functions, we characterize the linear equilibrium in a divisible consignment auction with positive trading volumes and a unique equilibrium price. We further compare the consignment auction with its uniform-price counterpart. We show that as firms acquire revenues from selling their consigned permits, they have incentives to overstate demands, which results in a higher equilibrium price in a consignment auction than in a uniform-price auction; nevertheless, the ex post efficiency ranking of these two auctions are generally ambiguous. Our results suggest that the non-trade equilibrium of Khezr and MacKenzie (2018) only appears when firms have a constant marginal value.

Anchoring effects in the Chinese art market

Using a large auction dataset for traditional Chinese paintings, we test for anchoring effects in the art market. We find that bidders and auctioneers both anchor on past auction prices (which is an externally-provided anchor) and anchoring effects become stronger if time intervals between two auctions of the same paintings are relatively short. When a painting is reauctioned by the same auction house, auctioneers are influenced by both past auction prices (an externally-provided anchor) and auctioneers’ previous estimates (a self-generated anchor). If time intervals between two auctions are relatively short, the influence of the externally-provided anchor prevails over that of the self-generated anchor.

Linear Program-Based Approximation for Personalized Reserve Prices

We study the problem of computing data-driven personalized reserve prices in eager second price auctions without having any assumption on valuation distributions. Here, the input is a data set that contains the submitted bids of n buyers in a set of auctions, and the problem is to return personalized reserve prices r that maximize the revenue earned on these auctions by running eager second price auctions with reserve r. For this problem, which is known to be NP complete, we present a novel linear program (LP) formulation and a rounding procedure, which achieves a 0.684 approximation. This improves over the [Formula: see text]-approximation algorithm from Roughgarden and Wang. We show that our analysis is tight for this rounding procedure. We also bound the integrality gap of the LP, which shows that it is impossible to design an algorithm that yields an approximation factor larger than 0.828 with respect to this LP. This paper was accepted by Chung Piaw Teo, Management Science Special Section on Data-Driven Prescriptive Analytics.

Resource Allocation Scheduling Algorithm Based on Incomplete Information Dynamic Game for Edge Computing

With the advent of the 5G era, the demands for features such as low latency and high concurrency are becoming increasingly significant. These sophisticated new network applications and services require huge gaps in network transmission bandwidth, network transmission latency, and user experience, making cloud computing face many technical challenges in terms of applicability. In response to cloud computing's shortcomings, edge computing has come into its own. However, many factors affect task offloading and resource allocation in the edge computing environment, such as the task offload latency, energy consumption, smart device mobility, end-user power, and other issues. This paper proposes a dynamic multi-winner game model based on incomplete information to solve multi-end users' task offloading and edge resource allocation. First, based on the history of end-users storage in edge data centers, a hidden Markov model can predict other end-users' bid prices at time t. Based on these predicted auction prices, the model determines their bids. A dynamic multi-winner game model is used to solve the offload strategy that minimizes latency, energy consumption, cost, and to maximizes end-user satisfaction at the edge data center. Finally, the authors designed a resource allocation algorithm based on different priorities and task types to implement resource allocation in edge data centers. To ensure the prediction model's accuracy, the authors also use the expectation-maximization algorithm to learn the model parameters. Comparative experimental results show that the proposed model can better results in time delay, energy consumption, and cost.

Consignment Auctions Revisited

This paper studies the consignment auction as an allocation mechanism for emission permits among polluting firms. By assuming firms have non-increasing marginal values for the permits and linear bid functions, we characterize the linear equilibrium in a divisible consignment auction with positive trading volumes and a unique equilibrium price. We further compare the consignment auction with its uniform-price counterpart. We show that as firms acquire revenues from selling their consigned permits, they have incentives to overstate demands, which results in a higher equilibrium price in a consignment auction than in a uniform-price auction; nevertheless, the ex post efficiency ranking of these two auctions are generally ambiguous. Our results suggest that the non-trade equilibrium of Khezr and MacKenzie (2018) only appears when firms have a constant marginal value.

딥러닝 기반 경매 알고리즘과 데이터 과학 플랫폼 응용

본 논문에서는 분산 자원할당 문제에서 많이 활용되는 경매 알고리즘에 대해서 고찰하고 해당 알고리즘의 데이터과학 플랫폼으로의 응용에 대해서 논한다. 경매 알고리즘 중에서 차가경매(SPA: Second Price Auction)는 신뢰성 있는 운영을 위해서 가장 대표적으로 상용되는 방식이지만, 옥션의 경매자(Auctioneer)가 최대의 이익을 얻지 못한다는 단점이 존재한다. 이러한 단점을 극복하기 위하여 최근 딥러닝기반의 연산을 활용한다. 본 논문에서는 딥러닝기반 경제 알고리즘을 통한 분산자원할당 알고리즘을 제시하고 데이터과학 플랫폼으로의 응용에 대해서 논한다.

Step‐ahead spot price densities using daily synchronously reported prices and wind forecasts

AbstractThis paper uses non‐linear methodologies to follow the synchronously reported relationship between the Nordic/Baltic electric daily spot auction prices and geographical relevant wind forecasts in MWh from early 2013 to 2020. It is a well‐known market (auctions) microstructure fact that the daily wind forecasts are information available to the market before the daily auction bid deadline at 11 a.m. The main objective is therefore to establish conditional and marginal step ahead spot price density forecast using a stochastic representation of the lagged, synchronously reported and stationary spot price and wind forecast movements. Using an upward expansion path applying the Schwarz (Bayesian information criterion [BIC]) criterion and a battery of residual test statistics, an optimal maximum likelihood process density is suggested. The optimal specification reports a significant negative covariance between the daily price and wind forecast movements. Conditional on bivariate lags from the SNP information and using the known market information for wind forecast movements at t1, the paper establishes one‐step‐ahead bivariate and marginal day‐ahead spot price movement densities. The result shows that wind forecasts significantly influence the synchronously reported spot price densities (means and volatilities). The paper reports day‐ahead bivariate and marginal densities for spot price movements conditional on several very plausible price and wind forecast movements. The paper suggests day‐ahead spot price predictions from conditional and synchronously reported wind forecasts movements. The information should increase market participants spot market insight and consequently make spot price predictions more accurate and the confidence interval considerably narrower.

Plummeting costs of renewables - Are energy scenarios lagging?

Wind and solar energy play a pivotal role in deep decarbonization pathways for the future. However, energy scenario studies differ substantially in the contribution of these technologies, as the technology selection in models strongly depends on the choice of techno-economic parameters. In this article, we systematically compare the cost assumptions for solar and wind technologies in global, regional and national energy scenario studies with costs observed in reality and with recent remuneration from market auctions. Specially, we compared the capital expenditure (CAPEX) and the levelized cost of electricity (LCOE) towards the year of 2050 when available with historical market prices and auction prices. Our results indicate that the trend of rapid cost declines has been structurally underestimated in virtually all future energy scenario analyses and suggest that even the most recent studies refer to obsolete or very conservative values. This leads to underestimating the future role and level of deployment of renewable technologies. We recommend an open database for costs of renewable technologies to enhance the accuracy and transparency of future energy scenarios.

Reconstruction Parate Execution of Liability Rights and Roles the Parties in the Determination of Auction Price Limit Value Justice Based Warranty

Determining the Price Limit Value at the Parate Auction for Execution of Collateral Goods Bound to Mortgage, departs from the issues discussed, namely how the parate reconstruction of mortgage execution and the role of the parties in determining the limit value of the auction price of goods justice based guarantees? The purpose of this research is to analyze and find the reconstruction of the execution parate of mortgage rights and the role of the parties in determining the limit value of the auction price of collateral based on justice. The research method uses normative legal research, with a statutory approach (statute approach) and a case approach (case approach). Sources of legal materials used consist of primary, secondary and tertiary legal materials, while the analysis of legal materials is carried out in a descriptive qualitative manner. Based on the results of the research, it can be concluded that the parate reconstruction of mortgage execution must be based on justice, meaning that execution through parate execution based on the provisions of Article 6 of the Mortgage Rights Law, must also be balanced with other prerequisites that must be passed in order to minimize the arising of arbitrariness. The role of the parties in determining the limit value of the collateral auction price will be well realized if in determining the limit value determined based on the results of the appraiser's assessment, where the auction limit value must be as low as the liquidation value so that the auction office has the authority to reject the auction request. submitted by the seller, if it does not comply with the standards specified in the Minister of Finance Regulation No.27 / PMK.06 / 2016.

Asymmetric Cost Pass‐Through in Multi‐Unit Procurement Auctions: An Experimental Approach*

We explore input cost pass‐through in multi‐unit procurement auctions. Whether cost shocks are private versus common across firms has important implications for discriminatory, but not uniform price auctions. We provide evidence of asymmetric pass‐through of private cost shocks in discriminatory auctions. Unlike uniform price auctions, revenue‐maximizing bidders in discriminatory auctions ‘pad’ bids close to the expected clearing price for units with costs below that price, but they do not bid below cost on higher cost units. Therefore, if costs are higher than expected, the clearing price rises and if costs are lower than expected, the clearing price remains high.

What Type of Title Would You Put on Your Paintings?: The Impact on the Price of Artwork According to Its Title

This paper investigated the impact of the type of title on the price of the artwork effects using the hammer price of the paintings auctioned in Korea during a two-year period from December 2017 to November 2019. The results of the analysis showed that a descriptive title had a negative effect on the prices fetched, whereas a more elaborate title had a positive effect on auction prices. Also, it was found that elaborate titles for abstract paintings had a significant positive impact on the hammer price. In the case of unknown artists, a descriptive title had a negative effect on the auction price, while the absence of a title had a positive impact. The findings of this study suggest that artists must make careful decisions when titling their work because the title of the work affects the purchase decisions of art collectors.

Factors affecting dairy calf price in auction markets in Québec, Canada: 2008–2019

Dairy calves not kept for replacement are sold at young age in Québec auction markets for white and grain-fed veal calf production. The province of Québec produces 80% of the Canadian veal meat, but little information is available on the factors associated with the calves' price per crude weight (Can$/kg; Can$1 = US$0.78 at time of writing). The characteristics of calves sold in Québec auction markets from 12 complete years (2008-2019) were retrospectively studied. The calves' weight, breed and sex, the year and season of sale, the auction site, as well as the estimated distance traveled between the farm of origin and the auction site were analyzed as potential covariates associated with calf price. Two multivariable logistic models associated with low sale value (below the 10th or the 25th percentile of the day price) and 2 models associated with good sale characteristics (above the 50th or the 75th percentile of the day price) were built. The median distance between the farm and the auction site was 52 km (interquartile range: 30-95 km). Only 5% of calves traveled distances greater than 220 km. The weight, breed, sex, and auction sites explained most of the variability in the different models. Distance traveled and multiple interactions were also significantly associated with the outcomes. Calves with body weight from 48 to <56 kg were sold in higher percentiles of the day than lighter or heavier calves. Beef-crossed calves had better sale prices than Holstein, whereas colored dairy calves had lower sale characteristics than both Holstein and beef-crossed calves. The effect of distance traveled was complex, varying depending on the model and interactions, and explained a small portion of the total deviance in every model. Calves traveling from distances ≥110 km had lower sale characteristics in summer and fall in the different studied models. This study gives relevant insights on calves' characteristics associated with good versus low sale prices in Québec auction markets.

Demand dynamics across secondary German Book markets: an information aggregation and synthetization approach

This paper focuses on the increasing competition between resale opportunities for heterogeneous items with limited demand, i.e. long-tail products. This paper examines if commercial dealers offer higher purchase prices than purchase prices fixed in public auctions. To analyze this issue, we review options for customers to resell their belongings online after use. We use a proprietary software system to download, validate, and join item data across 14 data sources, like Amazon, eBay, and twelve commercial dealers in Germany for 1673 textbooks. We analyze the question which option to resell belongings online maximizes profit of the seller, while controlling for item, demand, supply, and auction specific characteristics. Besides a detailed analysis of the price spread, we exploit listing decisions among those resale options by non-commercial dealers and execute an arbitrage trading strategy using a purely deterministic model. We find that commercial dealers offer a higher purchase price than public auctions. We argue that commercial dealers offer these higher prices as they can shift item demand over time. In addition, prices in public auctions could be depressed because on consumer-to-consumer online auction markets a strategy called “sniping” is widespread, which might hamper the price mechanism. Our results are relevant for end-consumers who are willing to dispose of items in their belonging and for commercial dealers who want to optimize their sourcing. These results can be devolved on market microstructures of other standardized products like, for example, financial products.