A new energy model to capture the behavior of energy price processes

Owing to the vague fluctuation of energy prices from time to time, a new energy model, which considers both the mean-reverting behavior and the long memory property, is proposed in this paper. Since the problem of estimating parameters, in discrete time for this model, plays a central role in forecast inference, the problem of estimating the unknown parameters has been dealt with for the fractional Ornstein–Uhlenbeck process observed discretely. The asymptotic properties of these estimates are also provided. The numerical simulation results confirm the theoretical analysis and show that our method is effective. To show how to apply our approach in realistic contexts, an empirical study of energy in China, namely Daqing crude oil, is presented. The empirical results seem reasonable when compared to the real data.     

A solution to the random assignment problem on the full preference domain

We consider the problem of allocating a set of indivisible objects to agents in a fair and efficient manner. In a recent paper, Bogomolnaia and Moulin consider the case in which all agents have strict preferences, and propose the probabilistic serial (PS) mechanism; they define a new notion of efficiency, called ordinal efficiency, and prove that the probabilistic serial mechanism finds an envy-free ordinally efficient assignment. However, the restrictive assumption of strict preferences is critical to their algorithm. Our main contribution is an analogous algorithm for the full preference domain in which agents are allowed to be indifferent between objects. Our algorithm is based on a reinterpretation of the PS mechanism as an iterative algorithm to compute a “flow” in an associated network. In addition we show that on the full preference domain it is impossible for even a weak strategyproof mechanism to find a random assignment that is both ordinally efficient and envy-free.     

Joint estimation of technology choice and technical efficiency: an application to organic and conventional dairy farming

This paper proposes an econometric framework for joint estimation of technology and technology choice/adoption decision. The procedure takes into account the endogeneity of technology choice, which is likely to depend on inefficiency. Similarly, output from each technology depends on inefficiency. The effect of the dual role of inefficiency is estimated using a single-step maximum likelihood method. The proposed model is applied to a sample of conventional and organic dairy farms in Finland. The main findings are: the conventional technology is more productive, ceteris paribus; organic farms are, on average, less efficient technically than conventional farms; both efficiency and subsidy are found to be driving forces behind adoption of organic technology.     

A new clustering methodology for the analysis of sorted or categorized stimuli

This paper introduces a new stochastic clustering methodology devised for the analysis of categorized or sorted data. The methodology reveals consumers' common category knowledge as well as individual differences in using this knowledge for classifying brands in a designated product class. A small study involving the categorization of 28 brands of U.S. automobiles is presented where the results of the proposed methodology are compared with those obtained from KMEANS clustering. Finally, directions for future research are discussed. Wayne S. DeSarbo is the S. S. Kresge Distinguished Professor of Marketing and Statistics, and Michael D. Johnson is Associate Professor of Marketing, both at the University of Michigan's School of Business Administration. Kamel Jedidi is Assistant Professor of Marketing at Columbia University's Graduate School of Business. The authors gratefully acknowledge DuPont Incorporated for providing financial support for this research.     

Efficient parameter estimation for independent and INAR(1) negative binomial samples

We consider moment based estimation methods for estimating parameters of the negative binomial distribution that are almost as efficient as maximum likelihood estimation and far superior to the celebrated zero term method and the standard method of moments estimator. Maximum likelihood estimators are difficult to compute for dependent samples such as samples generated from the negative binomial first-order autoregressive integer-valued processes. The power method of estimation is suggested as an alternative to maximum likelihood estimation for such samples and a comparison is made of the asymptotic normalized variance between the power method, method of moments and zero term method estimators.     

The optimal bid/ask spread in a Specialist System

In this work we propose a simple market model where some features of the Specialist System are analyzed. In particular, the specialist's obligation to display bid/ask quotes on the book within the bounds imposed by the Exchange is considered. The proposed model allows to analyze the effects of the specialist's interventions on the short term dynamics of bid/ask prices and address a relevant market design issue, that is determination and analysis of the optimal endogenous upper bound that - according to economic conditions - should be imposed by Stock Exchange on the quoted bid/ask spread. The institutional details are summarized in a few structural parameters and the focus is on the aggregate effects of excess demand/supply.     

盈余管理:动因及后果——兼与利润操纵的比较

盈余管理的动因有终极动因和中介动因,其根本目的是实现自身效用或公司市场价值最大化,其经济后果有弊也有利.而利润操纵完全是为了谋取私利,且不惜牺牲其他相关人的利益,故它是百害而无一利的.为促进资本市场的理性发展,应当完善相关的法律法规以对二者进行规避.