Advertising a second-price auction

This study examines a symmetric private-value second-price auction model in which the seller solicits bidders at a cost, sets a reserve price, and receives a payoff which is a convex combination of revenue and welfare. The bidder’s valuations are drawn from a distribution with a decreasing hazard rate and non-decreasing virtual valuations. We find that at equilibrium the seller adopts an advertising policy which minimizes the uncertainty over the number of participants, and sets a reserve price which only depends on the distribution of valuations and the weight on revenue in the objective function. A welfare-maximizing seller is shown to advertise more than a revenue-maximizing seller, and a ceteris paribus increase in the advertising level is proved to increase the expected winner’s rent.     

Uncertain equilibria and incomplete preferences

This paper studies the tendency for incomplete preference structures to be associated with equilibrium price indeterminacies in an Arrow–Debreu–McKenzie state-contingent setting. It is shown that the presence of a sufficiently smooth stochastic production technology is inconsistent with equilibrium price indeterminacies even if all individuals have incomplete preference structures. A particularly convenient characterization of Paretian equilibria in the presence of incomplete preferences, which allows Paretian equilibrium to be characterized using simple principles of convex optimization and (sub)differential analysis, is also developed.     

Urban housing with discrete structures

Competitive equilibrium in an urban housing model with structures that cannot be readily aggregated or subdivided is analyzed in this paper. The price and quantity of services forthcoming from each dwelling occupied by a household is determined by the equality of competitive supply and demand. A stack algorithm is then developed to ensure households are assigned to dwellings so that they would not prefer to live in any other dwelling with an equilibrium price less than the one they would pay if they lived there. Using the Urban Institute Housing Model as an example, the results of this algorithm are compared with those of the algorithm developed by de Leeuw and Struyk (D-S). The stack algorithm yields greater price discounting of existing dwellings below the price of a new dwelling than does the D-S algorithm and, thus, a greater potential for housing prices to be increased by a demand subsidy such as a housing allowance.     

On the demand generated by a smooth and concavifiable preference ordering

It is shown that if a consumer's preference ordering is strictly convex and is representable by means of a concave, twice continuously differentiable utility function, then the partial derivative of a demanded commodity with respect to its price is bounded from above in a neighborhood of a price vector at which the demand fails to be differentiable. In the case of two commodities, if the demand does not possess finite derivatives with respect to prices at a certain point, then the partial ‘derivative’ of a commodity with respect to its price is equal to minus infinity. The same result holds for n commodities under ‘almost every’ choice of coordinates in the commodity space. If preferences are weakly convex but the same representation assumption holds, demand may not be single-valued but own-price difference quotients are still bounded from above.     

Is Giffen behaviour compatible with the axioms of consumer theory?

A family of direct utility functions is constructed which exhibit the characteristic of Giffenity, while satisfying the axioms of convexity and monotonicity. The approach starts by specifying a price offer curve, C₀, with a required backward-bending segment. Then a set of convex indifference curves is constructed having price offer curve arbitrarily close to C₀.     

一种算法改进的模糊神经网络及其性能分析

将T-S模糊模型与前馈神经网络相融合构造了一种新型的模糊神经网络,该模型采用基于梯度下降法和算法相结合的混合学习方法,其中梯度下降法用来训练高斯型隶属度函数的非线性参数,而算法用来训练线性参数,即权值。从理论上,证明了该模型对非线性函数的万能逼近能力。仿真实验表明,该模糊神经网络用于非线性动态系统辨识的有效性。     

REGIONAL AND SECTORAL DISAGGREGATION OF MULTI-REGIONAL INPUT–OUTPUT TABLES – A FLEXIBLE ALGORITHM

A common shortcoming of available multi-regional input–output (MRIO) data sets is their lack of regional and sectoral detail required for many research questions (e.g. in the field of disaster impact analysis). We present a simple algorithm to refine MRIO tables regionally and/or sectorally. By the use of proxy data, each MRIO flow in question is disaggregated into the corresponding sub-flows. This downscaling procedure is complemented by an adjustment rule ensuring that the sub-flows match the superordinate flow in sum. The approximation improves along several iteration steps. The algorithm unfolds its strength through the flexible combination of multiple, possibly incomplete proxy data sources. It is also flexible in a sense that any target sector and region resolution can be chosen. As an exemplary case we apply the algorithm to a regional and sectoral refinement of the Eora MRIO database.     

Link-save trading

Transaction costs involved while trading several assets may be described using bid-ask spread of the asset prices. We assume that the prices of several assets may be linked, so that transactions involving several assets have prices that are not necessarily equal to the sums of (bid or ask) prices of the individual assets. The family of possible price combinations forms a convex (random) set which changes in time and is called the set-valued price process. It is shown that the necessary and sufficient condition for no-arbitrage is the existence of a martingale selection, i.e. a martingale that takes values in the set-valued price process. Examples and applications to option pricing are discussed.     

Successive Sampling to Estimate Quantiles with P-Auxiliary Variables

The successive sampling is a known technique that can be used in longitudinal surveys to estimate population parameters and measurements of difference or change of a study variable. The paper discusses the estimation of quantiles for the current occasion based on sampling in two successive occasions and using p-auxiliary variables obtained of the previous occasion. A multivariate ratio estimator from the matched portion is used to provide the optimum estimate of a quantile by weighting the estimates inversely to derived optimum weights. Its properties are studied under large–sample approximation and the expressions of the variances are established. The behavior of these asymptotic variances is analyzed on the basis of data from natural populations. A simulation study is also used to measure the precision of the proposed estimator.     

Tacit Collusion in a One‐Shot Game of Price Competition with Soft Capacity Constraints

This paper analyzes price competition in the case of two firms operating under constant returns to scale with more than one production factor. Factors are chosen sequentially in a two‐stage game generating a soft capacity constraint and implying a convex short‐term cost function in the second stage of the game. We show that tacit collusion is the only predictable result of the whole game, that is, the unique payoff‐dominant pure strategy Nash equilibrium. Technically, this paper bridges the capacity constraint literature on price competition and that of the convex cost function.     

The spatial price equilibrium problem with path variables

Most of the recent literature dealing with the solution of the spatial price equilibrium model has dealt with the arc variable formulation; that is, the situation where the flows on the paths connecting an origin-destination pair in a network with trans-shipment nodes are not explicitly considered. This paper presents a clarification of the main assumption underlying this arc formulation and presents an argument for the need for using a model with path variables in certain applications. After this discussion, a new solution algorithm for the model with path variables is stated and compared against the linear approximation algorithm first proposed by Florian and Los [1] for this problem. Numerical examples are presented which illustrate the features of this new algorithm.     

Incentive pay and rent in oligopoly

Our purpose is to examine strategic delegation in nonlinear Cournot oligopoly. The findings generalize earlier results and show that managerial contracts reward sales under the condition of a fixed input price. Alternatively, under a variable input price, owners might punish sales even when goods are strategic substitutes. We conclude that optimal strategic motivation depends critically on the input price. For example, motivation that supports positive owner profit under a fixed input price nullifies owner-profit if an upstream monopolist with convex costs sets the input price. In a vertical relationship between a duopoly and an upstream monopolist, strategic delegation punishes sales.     

基于特征价格模型的住宅需求价格弹性分析——深圳住宅市场实证研究

基于特征价格模型(hedonic model)分析住宅价格包络函数曲线形态,边际价格增长速度随着特定特征值递增从呈现下降趋势转为呈上升趋势,即均衡价格曲线从凹向特征值轴转为凸向特征值轴.通过对深圳经济特区内外的两个住宅交易子样本进行hedonic分析,结果表明,均衡价格的增长速度随着特征变量面积的变化呈现由凹变凸的趋势...     

改进的蚁群算法在TSP中的应用

介绍了蚁群算法的特点,提出了基于蚁群算法的TSP问题的求解方法,并分别建立基本蚁群算法及MAX-MIN蚁群算法模型,并引入“三步走”法确定模型参数的最优组合,还结合了交叉局部优化相关的求凸壳顶点的算法进行预处理,进行仿真分析比较。实验结果表明基于MMAS模型相对于基本蚁群算法模型,有比较好最短路径选择能力及良好的可扩展性能,能够较好地适应物流配送系统的要求。     

改进BP神经网络在预测房地产价格指数中的应用

要对非线性趋势房地产价格指数进行预测,就必须利用模拟非线性的模型,采用BP人工神经网络的改进算法,建立了基于BP神经网络的房地产价格指数预测模型。结果表明:该模型预测精度较高,能较好地反映房地产价格指数内在变化规律。     

Pricing currency options with scheduled and unscheduled announcement effects on volatility

It is well documented that exchange rate volatility is time-varying and that it can be affected by scheduled events such as money supply announcements and unscheduled ones such as spot market interventions and interest rate changes. This study provides a European event model (E model) for currency call options that explicitly addresses the volatility effects of these two classes of events. Managers who are concerned with hedging in an environment of changing volatility may find the E model useful. The E and modified Black-Scholes (MBS) models have similar average errors in predicting option price changes across event windows and do better than a naive no-change prediction. The E model tends to reduce the underpricing of convex, short-term out-of-the-money options and the mispricing of most classes of convex options.     

The lag structure of option price

The price of common stock warrants do not adjust immediately to changes in common stock prices. This lag is inconsistent with the ‘efficient market’ hypothesis. Based on daily closing prices this lag was measured and found to be a combination of the adjustment to stock price and to the adjustment of ‘other’ variables, i.e., positive serially correlated disturbance terms. A single equation model simultaneously estimating the parameters of the serial correlation and the coefficients of the lagged stock price indicate a substantial deviation from efficiency. Various simple strategies designed to exploit this lag are then tested.     

Estimating farmers’ productive and marketing inefficiency: an application to vegetable producers in Benin

This paper estimates the technical and marketing inefficiency of a sample of urban vegetable producers in Benin. Marketing inefficiency is defined as the failure of farmers to achieve better marketing output and is reflected in lower output price indices. The study proposes a Russell-type measure of inefficiency using a directional distance function that accounts simultaneously for the expansion of outputs and price indices and the contraction of variable inputs. A truncated bootstrap regression is used in the second stage to consistently analyze factors that underlie differences in inefficiency. The first-stage results suggest that vegetable producers are more inefficient with respect to marketing than production. The second-stage results indicate that technical inefficiency is affected by the production environment and private extension services. Marketing inefficiency is affected by the type of marketing arrangements.     

Equal risk pricing under convex trading constraints

In an incomplete market model where convex trading constraints are imposed upon the underlying assets, it is no longer possible to obtain unique arbitrage-free prices for derivatives using standard replication arguments. Most existing derivative pricing approaches involve the selection of a suitable martingale measure or the optimisation of utility functions as well as risk measures from the perspective of a single trader.We propose a new and effective derivative pricing method, referred to as the equal risk pricing approach, for markets with convex trading constraints. The approach analyses the risk exposure of both the buyer and seller of the derivative, and seeks an equal risk price which evenly distributes the expected loss for both parties under optimal hedging. The existence and uniqueness of the equal risk price are established for both European and American options. Furthermore, if the trading constraints are removed, the equal risk price agrees with the standard arbitrage-free price.Finally, the equal risk pricing approach is applied to a constrained Black–Scholes market model where short-selling is banned. In particular, simple pricing formulas are derived for European calls, European puts and American puts.