Nonlinear autoregressive leading indicator models of output in G‐7 countries

This paper studies linear and nonlinear autoregressive leading indicator models of business cycles in G‐7 countries. Our models use the spread between short‐term and long‐term interest rates as leading indicators for GDP. We examine data admissibility by determining whether these models have the ability to produce time series with classical cycles that resemble the observed classical cycles in the data, and then we ask whether this data admissibility lends itself to better predictions of the probability of recession. Copyright © 2007 John Wiley & Sons, Ltd.     

Necessary conditions for admissibility of matrix linear estimators in a multivariate linear model

This article provides necessary conditions for the admissibility of matrix linear estimators of an estimable parameter matrix linear function under two kinds of quadratic matrix loss functions in a multivariate linear model following a family of matrix normal distributions, where the covariance matrix associated is completely unknown. Further it is demonstrated that if a more concrete condition supplied for one of the subdivided conditions is satisfied, then the special condition concerning the Stein problem is necessary for the admissibility of the kind of estimators under each of the loss functions.     

On universal admissibility of scale parameter estimators

A characterization result of Kushary (1998) regarding universal admissibility of equivariant estimators in the one parameter gamma distribution is generalized to a scale family of distributions with monotone likelihood ratio. New examples are given, among them the F-distribution with a scale parameter. In particular, universal admissibility is characterized within the class of location-scale equivariant estimators of the ratio of the variances of two normal distributions with unknown means. In this context the maximum likelihood estimator is shown to be universally inadmissible by virtue of a general sufficient condition for universal inadmissibility of a scale equivariant estimator. Received: January 2000     

Stepwise Bayes distributional inference for a finite population

Stepwise Bayes arguments can be used to derive various decision rules. Admissibility of such rules follows if additional conditions are satisfied. We show that in complete generality almost admissibility is in place. A uniform distribution example is used to demonstrate how stepwise Bayes arguments can be used when the support of the observation distribution depends on the unknown parameter. We then discuss distributional inference and show that weighted Polya posterior distributions provide admissible distributional inference for finite population problems when strictly proper loss functions are used.     

On an admissibility problem involving the moment generating function of the lognormal distribution

A new location invariant loss function is considered and the best invariant estimator of normal mean is obtained. This estimator is a function of the moment generating function of the lognormal distribution. The admissibility is studied of a class of linear estimators of the form cX+d, where X~N(/,C²), with / unknown and C² known. This yields the admissibility of the best invariant estimator of /.     

Admissibility Considerations in the Finite State Compound and Empirical Bayes Decision Problems*

In the compound decision problem the same decision problem. called the component decision problem, occurs repeatedly. Data from all repetitions are used to reach decisions concerning the parameter values in each component; such rules are called compound decision rules. The compound risk is the average risk across all component decisions. In the analogous empirical Bayes problem the parameters are taken to be independent and identically distributed with unknown distribution. This paper explores the relationship between compound risk admissibility and component risk admissibility in these problems. The definitions are general and the results are fairly obvious and proved for the finite parameter set component only.     

Potential games with incomplete preferences

This paper studies potential games allowing the possibility that players have incomplete preferences and empty best-response sets. We define four notions of potential games, ordinal, generalized ordinal, best-response, and generalized best-response potential games, and characterize them using cycle conditions. We study Nash equilibria of potential games and show that the set of Nash equilibria remains the same when every player’s preferences are replaced with the smallest generalized (best-response) potential relation or a completion of it. Similar results are established about strict Nash equilibria of ordinal and best-response potential games. Lastly, we examine the relations among the four notions of potential games as well as pseudo-potential games.     

Admissible unbiased variance estimation in finite population sampling under randomized response

LetP be the proportion of units in a finite population possessing a sensitive attribute. We prove the admissibility of (i) an unbiased estimator of the variance of a general homogeneous linear unbiased estimator ofP and (ii) an unbiased estimator of the population varianceP(1−P), based on an arbitrary but fixed sampling design, under the randomized response plans due to Warner (1965) and Eriksson (1973). Admissibility of an unbiased strategy for estimating the population variance is also established.     

GB2760—2011《食品安全国家标准食品添加剂使用标准》的几点思索

食品安全备受瞩目的今天,食品添加剂使用标准的修订与完善显得尤为重要。怎样使得标准更加严谨,更加完善,更加科学,是我们大家都关心的,也是我们应该关注和探讨的大事。     

基于树模型的XML查询

文章首先将XML数据查询定义为一个有序的带标记树而数据库是一个有序的带标记树集合,对于查询的回答是一个或几个从查询树结点到数据库结点的同态映射;其次,对一般意义下的XML树模型进行了形式化改造,并且基于改造后的XML树模型构造了查询;最后,阐述了这一工作的意义。     

Generalized coalitions and bargaining sets

We introduce new notions of bargaining set for mixed economies which rest on the idea of generalized coalitions (Aubin, 1979) to define objections and counter-objections. We show that the bargaining set defined through generalized coalitions coincides with competitive allocations under assumptions which are weak and natural in the mixed market literature. As a further result, we identify some additional properties that a generalized coalition must satisfy to object an allocation.     

Propensity for hedging and ambiguity aversion

We study ambiguity aversion by introducing some new notions of propensity for hedging that are less general than convexity of preferences. We therefore characterize the corresponding properties of the capacity and Choquet functional, and link them with actual observed behaviors under uncertainty (Fox et al., 1996; Tversky and Wakker, 1995).     

Universal Pareto dominance and welfare for plausible utility functions

We study Pareto efficiency in a setting that involves two kinds of uncertainty: Uncertainty over the possible outcomes is modeled using lotteries whereas uncertainty over the agents’ preferences over lotteries is modeled using sets of plausible utility functions. A lottery is universally Pareto undominated if there is no other lottery that Pareto dominates it for all plausible utility functions. We show that, under fairly general conditions, a lottery is universally Pareto undominated iff it is Pareto efficient for some vector of plausible utility functions, which in turn is equivalent to affine welfare maximization for this vector. In contrast to previous work on linear utility functions, we use the significantly more general framework of skew-symmetric bilinear (SSB) utility functions as introduced by Fishburn (1982). Our main theorem generalizes a theorem by Carroll (2010) and implies the ordinal efficiency welfare theorem. We discuss three natural classes of plausible utility functions, which lead to three notions of ordinal efficiency, including stochastic dominance efficiency, and conclude with a detailed investigation of the geometric and computational properties of these notions.     

La quasi-ammissibilitá nella teoria generale delle decisioni

In questo lavoro, la nozione di quasi-ammissibilità, come ampliamento della nozione di ammissibilità, viene formalizzata esplicitando una topologia sullo spazio funzionale in cui sono immerse le funzioni di perdita corrispondenti alla classe di decisioni del problema. Per questa via è possibile analizzare il concetto di quasi-ammissibilità senza restrizioni sullo spazio degli stati di natura. Si verifica poi, che le nozioni già note di ε-ammissibilità costituiscono casi particolari del-l’impostazione più generale qui proposta.

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It is known that in Decision Theory under Uncertainty the notion of admissibility and almost-admissibility plays an important role since it does not depend properly on the chosen optimality criterion. The main goal of the known notions of ε-admissibility is to conveniently enlarge the class of the admissible decision rules, which for some problems can be empty. Once observed that the notion of ε-equivalence between two decision rules is based on the fact that the decision are “close” each other, it is then natural to study the notion of ε-equivalence in a topological context. Here the functional space of the loss functions associated to the class of the decision rules is equipped with the product topology which the functional space is naturally endoved of. It this framework it is possible to study the notion of almost-admissibility independently of the characteristics of the states space. The known definitions of ε-admissibility are then reduced to particular cases of this more general approach.

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Lavoro eseguito nell’ambito del Gruppo Nazionale per l’Analisi Funzionale e le sue Applicazioni del C.N.R.     

Core and equilibria in coalitional asymmetric information economies

We study coalitional economies under uncertainty and asymmetric information, assuming a finitely additive measure space of agents and finitely many possible states of nature. We introduce a suitable core notion showing that it is equivalent to Walrasian expectations equilibria. The finitely additive approach proposed in the paper permits also asymmetric information economy with countably many agents, rather than requiring only a continuum. Moreover, it allows us to overcome well-known criticisms related to the interpretation of individual private core notions.     

试论会计信息失真的治理与防范

会计信息失真是我国当前经济生活中较为普遍的现象和十分突出的问题。防止会计信息失真,提高会计信息质量,必须进一步完善会计法律法规体系,建立健全内部控制制度和内部审计制度,建立完善的外部监督体系,提高财会人员整体素质。     

Diversification preferences in the theory of choice

Diversification represents the idea of choosing variety over uniformity. Within the theory of choice, desirability of diversification is axiomatized as preference for a convex combination of choices that are equivalently ranked. This corresponds to the notion of risk aversion when one assumes the von Neumann–Morgenstern expected utility model, but the equivalence fails to hold in other models. This paper analyzes axiomatizations of the concept of diversification and their relationship to the related notions of risk aversion and convex preferences within different choice theoretic models. Implications of these notions on portfolio choice are discussed. We cover model-independent diversification preferences, preferences within models of choice under risk, including expected utility theory and the more general rank-dependent expected utility theory, as well as models of choice under uncertainty axiomatized via Choquet expected utility theory. Remarks on interpretations of diversification preferences within models of behavioral choice are given in the conclusion.     

A class of statistical models to weaken independence in two-way contingency tables

In this paper we study a new class of statistical models for contingency tables. We define this class of models through a subset of the binomial equations of the classical independence model. We prove that they are log-linear and we use some notions from Algebraic Statistics to compute their sufficient statistic and their parametric representation. Moreover, we show how to compute maximum likelihood estimates and to perform exact inference through the Diaconis-Sturmfels algorithm. Examples show that these models can be useful in a wide range of applications.     

On estimating the mean of the selected normal population under the LINEX loss function

Following Parsian and Farsipour (1999), we consider the problem of estimating the mean of the selected normal population, from two normal populations with unknown means and common known variance, under the LINEX loss function. Some admissibility results for a subclass of equivariant estimators are derived and a sufficient condition for the inadmissibility of an arbitrary equivariant estimator is provided. As a consequence, several of the estimators proposed by Parsian and Farsipour (1999) are shown to be inadmissible and better estimators are obtained. Received January 2001/Revised May 2002