Uniform Inference in Autoregressive Models

The purpose of this paper is to provide theoretical justification for some existing methods for constructing confidence intervals for the sum of coefficients in autoregressive models. We show that the methods of Stock (1991), Andrews (1993), and Hansen (1999) provide asymptotically valid confidence intervals, whereas the subsampling method of Romano and Wolf (2001) does not. In addition, we generalize the three valid methods to a larger class of statistics. We also clarify the difference between uniform and pointwise asymptotic approximations, and show that a pointwise convergence of coverage probabilities for all values of the parameter does not guarantee the validity of the confidence set.     

How Should a Firm Manage Deteriorating Inventory?

Firms selling goods whose quality level deteriorates over time often face difficult decisions when unsold inventory remains. Since the leftover product is often perceived to be of lower quality than the new product, carrying it over offers the firm a second selling opportunity, a product line extension to new and unsold units, and the ability to price discriminate. By doing so, however, the firm subjects sales of its new product to competition from the leftover product. We present a two period model that captures the effect of this competition on the firm's production and pricing decisions. We characterize the firm's optimal strategy and find conditions under which the firm is better off carrying all, some, or none of its leftover inventory. We also show that, compared to a firm that acts myopically in the first period, a firm that takes into account the effect of first period decisions on second period profits will price its new product higher and stock more of it in the first period. Thus, the benefit of having a second selling opportunity dominates the detrimental effect of cannibalizing sales of the second period new product.     

Games and Mechanism Design in Machine Scheduling—An Introduction

We survey different models, techniques, and some recent results to tackle machine scheduling problems within a distributed setting. In traditional optimization, a central authority is asked to solve a (computationally hard) optimization problem. In contrast, in distributed settings there are several agents, possibly equipped with private information that is not publicly known, and these agents must interact to derive a solution to the problem. Usually the agents have their individual preferences, which induces them to behave strategically to manipulate the resulting solution. Nevertheless, one is often interested in the global performance of such systems. The analysis of such distributed settings requires techniques from classical optimization, game theory, and economic theory. The paper therefore briefly introduces the most important of the underlying concepts and gives a selection of typical research questions and recent results, focusing on applications to machine scheduling problems. This includes the study of the so‐called price of anarchy for settings where the agents do not possess private information, as well as the design and analysis of (truthful) mechanisms in settings where the agents do possess private information.     

On Pricing and Composition of Bundles

This paper addresses the problem of how to determine the composition and price of a bundle so as to maximize the total expected profit. To motivate the problem, we use as a setting a high‐tech manufacturing company that operates in a competitive environment, is not a leader in the industry, and is constantly reacting to bundles introduced by the leader. Bundles are sets of components that must meet technical constraints. The company's objective is to build a bundle and offer it in a market where it will compete with other bundles. Consumers purchase the bundle that maximizes their utility after examining all available bundles. The company selection of the bundle's components and its price is made in light of the bundles against which it will be competing and the uncertainty in the consumer choice process. The optimal decision could be found by solving a nonlinear mixed integer program, which is difficult to solve. Instead, we propose an efficient solution procedure to determine the optimal composition of the bundle and the price at which it should be offered. The paper concludes with a brief discussion of extensions of the research to cases that consider multiple segments of customers and/or multiple bundles.     

我国天然气价格管理体制及定价模式研究

从我国目前的天然气价格管理体制存在问题出发,从分析长输管道行业特点入手,运用垄断竞争市场定价模式及市场供求关系对价格影响的理论,剖析并提出我国天然气价格管理体制改革思路,通过具体分析“西气东输”工程的天然气价格,来规范我国长输管道天然气的定价模式及新时期的价格水平。     

跳跃分形过程下欧式汇率期权的定价

假设汇率变化过程服从带跳跃的分形布朗运动,建立跳跃分形的汇率期权市场模型,利用分形Girsanov公式和自融资策略,推导出跳跃分形汇率市场中欧式未定权益在任意时刻的定价公式。然后,根据汇率期权定价原理得出跳跃分形过程下欧式汇率期权的定价公式。最后选取欧元/美元汇率期权进行实证分析,通过比较不同定价模型的结果说明了汇率市场兼具跳跃和分形的特性。     

股票联系票据研究

股票联系票据(EquityLinkedNotes)作为一种新型的金融创新产品在发达国家受到众多投资者的青睐,特别是进入20世纪90年代,股票联系票据在发行规模、品种创新和交易手段等方面取得了突飞猛进的发展,而目前国内尚未出现这类证券品种,投资者对股票联系票据还不熟悉,相关的理论研究还较为欠缺,基于这种情况,本文对股票联系票据进行深入的经济学分析,研究该投资工具的风险收益特征和定价原理,并提出我国发展股票联系票据市场的政策建议。     

基于消费者策略行为的高新技术产品定价模型研究

随着技术更新速度的加快和市场竞争的加剧,厂商经常会采取降价促销的手段刺激高新技术产品的销售.久而久之,消费者自然形成一种等待厂商进一步降价的习惯.文章主要考虑基于消费者策略行为下,厂商实施的动态定价策略.讨论在需求不确定的条件下,厂商在面对消费者策略行为时,如何决定最优价格策略,以获得最大化利润.     

内生区位与独占厂商空间定价策略分析

在有关独占厂商空间定价的研究中,许多文献假定市场范围外生给定。为在可变市场范围假定下,得到更为一般性的结论,放松买者固定概率分布假定,研究需求型态和买者分布型态与定价策略优劣的关系。研究发现,当市场范围内生决定时,厂商利润大小,与需求函数型态有关,而与买者分布无关,拓展了有关研究;消费者剩余和社会福利在FOB定价下恒大于CIF定价,与需求型态和买者分布均无关,与以往文献不同。     

村规民约略论

通过对村规民约在中国不同历史时期的表现分析,指出村规民约作为特定时期的历史产物,其存在与发展都与社会当时的具体环境,特别是政治需要及权力运行模式密切相关。作为乡村社会“小共同体”“私的法律秩序”,村规民约与国家“公的法律秩序”存在不可调和的冲突和矛盾。提出为保证中国法制统一,学界不应过高渲染村规民约的功能作用。村规民约作为一种文化遗产,伦理价值和道德教化的作用和意义是主要的。