Bid Vector Research Articles

Assessing Willingness to Accept a Compensation for Evicted Land in Peri-urban Areas: A Contingent Valuation Method

Urban expansion in developing countries like Ethiopia is causing political turmoil in peri-urban areas due to inadequate compensation for evicted farmers because of the absence of a land market, which is prohibited by Ethiopia's land policy. This paper applies the contingent valuation method to measure the compensation value considered acceptable to those who are evicted from their farm land. The west Gojjam and Awi zones of Amhara region, Ethiopia are chosen for the case study based on 393 completed questionnaires. It has been demonstrated that a willingness to accept compensation is essential for maintaining sustainable livelihoods. The study applied single-bounded contingent valuation and double-bounded contingent valuation methods to estimate the mean willingness to accept compensation value. Based on the finding, double-bounded contingent valuation could be more optimal for the welfare of the evictees in detecting and correcting respondent’s bias due to its narrow confidence interval. Pilot survey was employed to ensure reliability and validity of the methods employed. Therefore, the optimal bid vector for multiplying the average land output preceding three years of eviction is 29.27. Additionally, variables such as initial bid, age, education, and total annual income significantly affect the willingness to accept compensation. The study recommends that federal and local governments should provide adequate compensation offers that prioritize the well-being of peri-urban communities during urban expansion programs, as farmers are losing their most valuable asset. This is crucial for sustainable living and poverty reduction among those who have been evicted.

Learning Strong Substitutes Demand via Queries

This article addresses the computational challenges of learning strong substitutes demand when given access to a demand (or valuation) oracle. Strong substitutes demand generalises the well-studied gross substitutes demand to a multi-unit setting. Recent work by Baldwin and Klemperer shows that any such demand can be expressed in a natural way as a finite list of weighted bid vectors. A simplified version of this bidding language has been used by the Bank of England. Assuming access to a demand oracle, we provide an algorithm that computes the unique list of weighted bid vectors corresponding to a bidder’s demand preferences. In the special case where their demand can be expressed using positive bids only, we have an efficient algorithm that learns this list in linear time. We also show super-polynomial lower bounds on the query complexity of computing the list of bids in the general case where bids may be positive and negative. Our algorithms constitute the first systematic approach for bidders to construct a bid list corresponding to non-trivial demand, allowing them to participate in “product-mix” auctions.

Estimating discount rates for environmental goods: Are People’s responses inadequate to frequency of payments?

Most stated preference studies estimate discount rates using a split-sample approach. Each sample faces a different payment frequency (for instance, 1, 5, 10) together with a randomly assigned bid vector; both the frequency of payments and the bid are fixed for a specific individual. This paper evaluates whether allowing respondents to choose their preferred payment frequency affects the estimated discount rate. We use data from a contingent valuation survey of a network of marine reserves and estimate discount rates using both an exogenous and endogenous approach. The former calculates the mean of the willingness to pay (WTP) for each sample and then finds the discount rate that makes the present value of each payment frequency equivalent. The latter estimates the WTP and the discount rate jointly. Results show that allowing people to choose the payment schedule significantly reduces the implicit discount rate. We observed the highest reductions in discount rates when we used all the information available from the valuation questions to bound the WTP distribution. Our analysis suggests that the exogenous approach would not be recommended for testing the adequacy of people’s responses to the frequency of payments.

Greedy Decentralized Auction-based Task Allocation for Multi-Agent Systems

We propose a decentralized auction-based algorithm for the solution of dynamic task allocation problems for spatially distributed multi-agent systems. In our approach, each member of the multi-agent team is assigned to at most one task from a set of spatially distributed tasks, while several agents can be allocated to the same task. The task assignment is dynamic since it is updated at discrete time stages (iterations) to account for the current states of the agents as the latter move towards the tasks assigned to them at the previous stage. Our proposed methods can find applications in problems of resource allocation by intelligent machines such as the delivery of packages by a fleet of unmanned or semi-autonomous aerial vehicles. In our approach, the task allocation accounts for both the cost incurred by the agents for the completion of their assigned tasks (e.g., energy or fuel consumption) and the rewards earned for their completion (which may reflect, for instance, the agents' satisfaction). We propose a Greedy Coalition Auction Algorithm (GCAA) in which the agents possess bid vectors representing their best evaluations of the task utilities. The agents propose bids, deduce an allocation based on their bid vectors and update them after each iteration. The solution estimate of the proposed task allocation algorithm converges after a finite number of iterations which cannot exceed the number of agents. Finally, we use numerical simulations to illustrate the effectiveness of the proposed task allocation algorithm (in terms of performance and computation time) in several scenarios involving multiple agents and tasks distributed over a spatial 2D domain.

Prior-free multi-unit auctions with ordered bidders

Prior-free auctions are robust auctions that assume no distribution over bidders' valuations and provide worst-case (input-by-input) approximation guarantees. In contrast to previous work on this topic, we pursue good prior-free auctions with non-identical bidders.Prior-free auctions can approximate meaningful benchmarks for non-identical bidders only when sufficient qualitative information about the bidder asymmetry is publicly known. We consider digital goods auctions where there is a total ordering of the bidders that is known to the seller, where earlier bidders are in some sense thought to have higher valuations. We use the framework of Hartline and Roughgarden (STOC'08) to define an appropriate revenue benchmark: the maximum revenue that can be obtained from a bid vector using prices that are nonincreasing in the bidder ordering and bounded above by the second-highest bid. This monotone-price benchmark is always as large as the well-known fixed-price benchmark F(2), so designing prior-free auctions with good approximation guarantees is only harder. By design, an auction that approximates the monotone-price benchmark satisfies a very strong guarantee: it is, in particular, simultaneously near-optimal for essentially every Bayesian environment in which bidders' valuation distributions have nonincreasing monopoly prices, or in which the distribution of each bidder stochastically dominates that of the next. Even when there is no distribution over bidders' valuations, such an auction still provides a quantifiable input-by-input performance guarantee.In this paper, we design a simple O(1)-competitive prior-free auction for digital goods with ordered bidders. We also extend the monotone-price benchmark and our O(1)-competitive prior-free auction to multi-unit settings with limited supply.

Click efficiency: a unified optimal ranking for online Ads and documents

Ranking of search results and ads has traditionally been studied separately. The probability ranking principle is commonly used to rank the search results while the ranking based on expected profits is commonly used for paid placement of ads. These rankings try to maximize the expected utilities based on the user click models. Recent empirical analysis on search engine logs suggests unified click models for both ranked ads and search results (documents). These new models consider parameters of (i) probability of the user abandoning browsing results (ii) perceived relevance of result snippets. However, current document and ad ranking methods do not consider these parameters. In this paper we propose a generalized ranking function--namely Click Efficiency (CE)--for documents and ads based on empirically proven user click models. The ranking considers parameters (i) and (ii) above, optimal and has the same time complexity as sorting. Furthermore, the CE ranking exploits the commonality of click models, hence is applicable for both documents and ads. We examine the reduced forms of CE ranking based upon different underlying assumptions, enumerating a hierarchy of ranking functions. Interestingly, some of the rankings in the hierarchy are currently used ad and document ranking functions; while others suggest new rankings. Thus, this hierarchy illustrates the relationships between different rankings, and clarifies the underlying assumptions. While optimality of ranking is sufficient for document ranking, applying CE ranking to ad auctions requires an appropriate pricing mechanism. We incorporate a second price based mechanism with the proposed ranking. Our analysis proves several desirable properties including revenue dominance over Vickrey Clarke Groves (VCG) for the same bid vector and existence of a Nash equilibrium in pure strategies. The equilibrium is socially optimal, and revenue equivalent to the truthful VCG equilibrium. As a result of its generality, the auction mechanism and the equilibrium reduces to the current mechanisms including Generalized Second Price Auction (GSP) and corresponding equilibria. Furthermore, we relax the independence assumption in CE ranking and analyze the diversity ranking problem. We show that optimal diversity ranking is NP-Hard in general, and a constant time approximation algorithm is not likely. Finally our simulations to quantify the amount of increase in different utility functions conform to the results, and suggest potentially significant increase in utilities.

Ranking alternatives by a fair bidding rule: A theoretical and experimental analysis

We apply a procedurally fair rule to a situation where people disagree about the value of three alternatives in the way captured by the voting paradox. The rule allows people to select a final collective ranking by submitting a bid vector with six components (the six possible rankings of the three alternatives). We test experimentally the robustness of the rule to subsidies and taxes as well as to tie-breaking assumptions. We have two main results. First, the most frequently chosen ranking is the socially efficient one when ties are broken in favor of the alternative generating the highest social welfare, but not when ties are broken randomly. Second, subsidies slightly enhance overbidding. Furthermore, an analysis of individual bid vectors reveals interesting behavioral regularities that result from selfishness, other-regarding preferences, and indifference.

Does gender-specific starting point bias in choice experiments prevail among well-informed respondents: evidence from an empirical study

Welfare estimates in discrete choice experiments studies are found to be sensitive towards the applied bid vector, i.e. anchoring bias or starting point bias. Furthermore, there are some evidence that female respondents might be more prone to starting point bias compared to male respondents. Using a market good, starting point bias is tested and found on the preference margin only to be evident among female respondents with less experience with the market good. Experienced female and male respondents do not state significant starting point biased preferences. This suggests that starting point bias might be less severe among well-informed respondents.

A Two-Tier Matrix Game Approach for Obtaining Joint Bidding Strategies in FTR and Energy Markets

Transmission congestion results in revenue collected from the loads that often exceeds the payment made to the generators. The financial transmission right (FTR) is an instrument that allows the independent system operator (ISO) to redistribute the excess revenue (congestion charge) among the market participants. Generators and loads hold FTRs to hedge against congestion charges. Since the revenues from the FTR and energy markets are interdependent, each generator and load must have a joint bidding strategy for FTR and energy markets to maximize its total payoff. This paper presents a two-tier matrix game model that allows the generators and loads to obtain joint bidding strategies. The model also allows the ISOs and the market designers to assess the impact of various network configurations and rules on market performance (e.g., market power). The two-tier model considers multiple participants, multidimensional bid vectors, network contingencies, and varying demand. We conducted a numerical validation of our model by analyzing the three-node network studied by Joskow and Tirole (2000). Additional numerical studies were conducted on a five-node network to examine the impact of holding FTRs on the bidding strategies in the energy market and joint payoffs of the participants.

On Best-Response Bidding in GSP Auctions

How should players bid in keyword auctions such as those used by Google, Yahoo! and MSN? We model ad auctions as a dynamic game of incomplete information, so we can study the convergence and robustness properties of various strategies. In particular, we consider best-response bidding strategies for a repeated auction on a single keyword, where in each round, each player chooses some optimal bid for the next round, assuming that the other players merely repeat their previous bids. We focus on a strategy we call Balanced Bidding (bb). If all players use the bb strategy, we show that bids converge to a bid vector that obtains in a complete information static model proposed by Edelman, Ostrovsky and Schwarz (2007). We prove that convergence occurs with probability 1, and we compute the expected time until convergence.

Nonmarket valuation of water quality in a rural transition economy in Turkey applying an a posteriori bid design

In this paper, we investigate the economic benefits associated with public investments in wastewater treatment in one of the special protected areas along Turkey's touristic Mediterranean coast, the Köyceğiz‐Dalyan watershed. The benefits, measured in terms of boatable, fishable, swimmable and drinkable water quality, are estimated using a public survey format following the contingent valuation (CV) method. The study presented here is the first of its kind in Turkey. The study's main objective is to assess public perception, understanding, and valuation of improved wastewater treatment facilities in the two largest population centers in the watershed, facing the same water pollution problems as a result of lack of appropriate wastewater treatment. We test the validity and reliability of the application of the CV methodology to this specific environmental problem in a rural transition economy and evaluate the transferability of the results within the watershed. In order to facilitate willingness to pay (WTP) value elicitation we apply a novel dichotomous choice procedure where bid design takes place a posteriori instead of a priori. The statistical efficiency of different bid vectors is evaluated in terms of the estimated welfare measures' mean square errors using Monte Carlo simulation. The robustness of bid function specification is analyzed through average WTP and standard deviation estimated using parametric and nonparametric methods.

Proapoptotic BID Is an ATM Effector in the DNA-Damage Response

The "BH3-only" proapoptotic BCL-2 family members are sentinels of intracellular damage. Here, we demonstrated that the BH3-only BID protein partially localizes to the nucleus in healthy cells, is important for apoptosis induced by DNA damage, and is phosphorylated following induction of double-strand breaks in DNA. We also found that BID phosphorylation is mediated by the ATM kinase and occurs in mouse BID on two ATM consensus sites. Interestingly, BID-/- cells failed to accumulate in the S phase of the cell cycle following treatment with the topoisomerase II poison etoposide; reintroducing wild-type BID restored accumulation. In contrast, introducing a nonphosphorylatable BID mutant did not restore accumulation in the S phase and resulted in an increase in cellular sensitivity to etoposide-induced apoptosis. These results implicate BID as an ATM effector and raise the possibility that proapoptotic BID may also play a prosurvival role important for S phase arrest.

Willingness to pay for on-demand and prophylactic treatment for severe haemophilia in Sweden.

The objective of the present paper was to provide an estimate of the benefits of on-demand and prophylaxis treatment strategies for severe haemophilia in monetary terms. Using the contingent-valuation method, which simulates a missing market by asking people about their willingness to pay (WTP), we asked a representative sample (n = 609) of the Swedish population if they would be willing to pay a specific amount (bid) so that patients with severe haemophilia could receive on-demand treatment and another bid for prophylactic treatment. Different respondents were offered different bids and the bid vector ranged from 71 Euro cents to EUR 130. The order of the bid questions was randomized so that half of the respondents were asked first about their WTP for on-demand treatment, and then about their WTP for prophylaxis, while the order was reversed for the other half of the respondents. The mean estimated WTP (year 2002) was EUR 39 (95% CI 31-47) for on-demand and EUR 65 (95% CI 55-73) for prophylaxis. Our sensitivity analysis showed that the ranking of the two treatment alternatives was robust in that the WTP was greater for prophylaxis in all possible subsets. The point estimates of WTP varied somewhat in subsets defined by individual characteristics, but confidence intervals always overlapped that of the main results. The WTP for on-demand and prophylaxis exceeded the calculated cost of treatment per taxpayer of providing on-demand and prophylactic treatment, respectively, based on our previous results.

Auction-Based Slot Allocation for Traffic Demand Management at Hartsfield Atlanta International Airport: A Case Study

Ongoing research is described for an auction model, a hybrid demand management approach for congested airports. This approach is intended to optimize the use of airport time slots by maximizing passenger throughput with safe capacity, decreasing congestion, and less delay. The two submodels mathematically formulate conflicting optimization problems of efficiency-driven airport regulators and cost-driven airlines. By ranking key factors such as monetary bidding, flight origin-destination pairs, enplanement capability, and airlines' previous investments, a framework is presented that is open to many design alternatives. Two design alternatives are analyzed in a case study of Hartsfield Atlanta International Airport, Georgia, to compare different allocation schemata and resulting airport performance. The performance analysis used a queuing model simulation. By varying weighting coefficients for bid vectors, it is proposed that the effects of administrative coordination and market force on outcomes of the auction process could be monitored to achieve airport-specific benefits. It is also suggested that the conventional auction format that uses monetary bidding alone could lead to potential distortions of the marketplace and fail to meet air transportation officials' concerns about the efficient use of national resources and policy makers' concerns about market structure and competitiveness. Future work will enlist the input from both airlines and airports.

Influence of bid and subsample vectors on the welfare measure estimate in dichotomous choice contingent valuation: Evidence from a case-study

After briefly outlining recent studies on the formulation of dichotomous choice contingent valuation surveys, the authors describe the sampling design procedures followed to assess the recreational value of the ‘Tablas de Daimiel’ National Park, in which the truncated mean was used as the welfare measure.With the data obtained from 167 interviews, a posteriori Monte Carlo simulations were conducted to estimates bias and variance of the welfare measure estimator, varying the following parameters: (1) the number and magnitude of the bids; (2) allocation of the sample among the various bid levels; and (3) the value used to truncate the willingness-to-pay distribution.Welfare measure estimator bias was found to be negligible in all the experiments conducted — each one with 1000 samples containing 400 observations — whereas sample allocation proved to have a greater effect on the accuracy of the welfare estimator than the number or magnitude of the bids.Here, the accuracy of the truncated mean estimates obtained with designs using the Cooper method is compared, for different truncation points, with the accuracy of the estimates obtained using an empirically constructed bid vector and a subsample size vector determined as per the Duffield and Patterson approach. The latter were found to be comparable to the Cooper optimal designs.

Some issues in the application of closed-ended willingness to pay studies to valuing health goods: an application to antenatal care in Scotland

Limited resources coupled with unlimited demands means that decisions have to be made concerning the allocation of scarce health care resources. The economic instrument of willingness to pay (WTP) is one instrument that can be used to help this decision-making process. Recommendations from the environmental economics literature suggest that the closed end (CE) WTP approach should be used. This approach is just beginning to be used to value health goods. This paper addresses the sensitivity of the closed-ended WTP approach to three issues: the design of the bid vector; the upper and lower limits of integration; and the method of analysis. These are discussed with reference to a study looking at the value of alternative models of ante-natal care in Scotland. The results are discussed and conclusions made concerning the use of the CE WTP instrument for valuing health goods.

Valuing International Tourism Benefits from Natural Areas

Tourism involves intensive utilization of environmental assets and natural resources. Valuing these assets may be relevant for policy purposes. This paper presents results from a contingent valuation study of the benefits experienced by tourist visitors to natural areas in Gran Canaria (Canary Islands). Construct validity is approached by investigating question format effects. The open-ended format is compared with dichotomous choice methods using a general parametric testing procedure. In general, the single-bounded method does produce larger estimates of consumer surplus than the open-ended method, but these divergences were not significant for German and Italian tourists. In addition, the double-bounded method converges to open-ended results, especially for UK tourists. The former method is also robust with respect to the choice of the bid vector design. The assessed benefits highlight the economic contribution of these assets to the tourism industry.

On the Choice of Funtional Form for Hedonic Price Functions

This study examines how errors in measuring marginal attribute pric es vary with the form of the hedonic price function. In simulations, consumers with known utility functions bid for houses with given attributes. Various forms of the hedonic function are estimated using equilibrium housing prices. Errors in estimating marginal attribute prices are calculated by comparing each consumer's equilibrium marginal bid vector with the gradient of the hedonic function. When all attributes are observed, linear and quadratic Box-Cox forms produce lowest mean percentage errors; however, when some attributes are unobserved or are replaced by proxies, linear and linear Box-Cox functions perform best. Copyright 1988 by MIT Press.