Decisionmetrics: A decision-based approach to econometric modelling

An approach to developing a possibly misspecified econometric model that will be used as the beliefs of an expected utility maximiser is proposed. This approach builds on a novel objective function that measures the value of predictive distributions in decision-making and is used in model estimation, selection and evaluation. The methods proposed also provide an econometric approach for developing arbitrary parametric action rules such as technical trading rules. The approach is compared in detail with existing methods and is applied in the context of a CARA investor's decision problem where analytical and empirical results suggest it is very effective.     

The synergistic effect of insurance and banking sector activities on economic growth in Africa

It is widely understood that the insurance and banking sectors of every economy perform some functions in driving economic growth. What is not yet well documented is whether their roles are complimentary or substitutive. With the aid of the dynamic panel generalized method of moments (GMM) estimation technique, this paper evaluates the synergistic effect of both sectors on economic growth in a panel of 10 African countries that are responsible for most of the activities in the continent’s financial sector. The insurance-banking-growth nexus was also examined through bootstrap panel causality tests. The results show that the life insurance market and the banking sector, as well as the non-life insurance market and the banking sector, are complimentary. We find that, overall, the relationship between the insurance and banking sectors in Africa is a complimentary one and that their synergistic impact on economic growth is positive. The feedback hypothesis was also confirmed in the relationship between the insurance sector and economic growth and between the banking sector and economic growth.     

短期生产决策理论下学生党支部最优规模分析

高校学生党支部是高校最重要的基层党组织团队之一。本文利用微观经济学短期生产决策理论,设置支部产出,构建数学模型,利用调查数据进行分析,对高校学生党支部这一特殊团队的规模最优进行了研究。     

Intra- and inter-country bank branch assessment using DEA

Increasingly globalized financial markets with considerable activity in the multinational sector have created the need to understand inter-country bank branch performance. This topic is relatively unstudied, primarily due to the immense difficulty encountered in gathering reliable data. Fortunately, we have been able to obtain data on a group of banks operating in one geographical market area, but in different countries. In this paper we critically assess bank branch profitability and productivity in seven national branch networks owned and operated by a multi-national financial services corporation. The corporate head office (owner) imposes its management philosophy equally on all of its subsidiaries, thus removing executive managerial and corporate disparity. Results suggest that countries in which branch performance is quite consistent amongst domestic branches are less productive and less profitable when compared to other countries that have more disparity in their efficiency scores. In addition, we discovered that, surprisingly, branches do not have to be productive in order to be profitable and this led us to somewhat of a major breakthrough in inter-country branch analysis. Significant managerial advice may be derived from these results vis-à-vis trans-national benchmarking and opportunity for performance improvements both at the branch level and nationally as well.

Empirical labor search: A survey

This paper surveys the existing empirical research that uses search theory to empirically analyze labor supply questions in a structural framework, using data on individual labor market transitions and durations, wages, and individual characteristics. The starting points of the literature are the Mincerian earnings function, Heckman's classic selection model, and dynamic optimization theory. We develop a general framework for the labor market where the search for a job involves dynamic decision making under uncertainty. It can be specialized to be in agreement with most published research using labor search models. We discuss estimation, policy evaluation with the estimated model, equilibrium model versions, and the decomposition of wage variation into factors due to heterogeneity of various model determinants as well as search frictions themselves. We summarize the main empirical conclusions.     

National versus supranational bank regulation: Gains and losses of joining a banking union

We ask how the structure of international banking affects the decision of a national regulator to join a banking union and to transfer regulatory powers to the supranational level. The focus is on bank supervision and bank resolution. A national regulator ignores possible gains or losses, which accrue to other jurisdictions if banks are internationally active. A supranational regulator takes these regulatory external effects into account. While supranational regulation improves total welfare, this is not necessarily the case for welfare in single countries. By analyzing the size and determinants of spillover effects we show how they constrain a country’s willingness to participate in a banking union. Our results may explain why some member states of the European Union currently hesitate to join the European Banking Union.     

关于加强支部班子建设的思考

支部班子建设是一个单位工作的基础,是全面贯彻执行党的路线、方针、政策和团结带领群众全面建设小康社会的前沿阵地。支部班子建设的好坏,直接关系着党和政府在人民群众中的威望,那么如何加强支部班子建设,提高支部班子的凝聚力、号召力、战斗力,笔者谈些拙见。     

Structural changes,competition and bank stability in Malaysia’s dual banking system

This paper assesses Malaysia’s competition landscape and its risk implications subsequent to conventional banking consolidation and Islamic banking penetration in the aftermath of the 1997/1998 Asian financial crisis. Employing a panel sample of conventional and Islamic commercial banks, it arrives at the following conclusions. First, the consolidation exercise, which has led to a significant reduction in the number of domestic commercial banks, has not stifled banking competition. Second, the paper provides empirical support for the competition-stability relationship, particularly for the conventional banking sector. Islamic banking sector risk appears to be neutral to market competition or market power, although there is limited evidence that it increases with overall market concentration. Finally, the analysis uncovers the risk-increasing effect of the Islamic banking market structure on the conventional banking sector. By contrast, conventional banking market concentration tends to reduce the credit risk of Islamic banks.     

Explaining greater test use for selection: the role of HR professionals in a world of expanding regulation

In recent decades there has been a well‐documented increase in organisations' use of formal tests for selection purposes. This article investigates whether tests' technical qualities and predictive validity are the critical determinants of take‐up, or whether other organisational and contextual factors are more important. Case studies of organisations were used to identify the factors driving change and Workplace Employee Relations Survey data were analysed to determine the consistency of the findings with national data. The single most important factor appears to be the regulatory environment, with tests used as a precautionary measure to protect selection decisions from challenge. The growing formal professionalisation of HR departments is also important, and the influence of both factors is consistent with current theories of organisational decision‐making. Continued growth in test use is likely, but the implications for efficiency in selection are less clear.     

Automated web service composition supporting conditional branch structures

The creation of value-added services by automatic composition of existing ones is gaining a significant momentum as the potential silver bullet in service-oriented architecture. However, service composition faces two aspects of difficulties. First, users' needs present such characteristics as diversity, uncertainty and personalisation; second, the existing services run in a real-world environment that is highly complex and dynamically changing. These difficulties may cause the emergence of nondeterministic choices in the process of service composition, which has gone beyond what the existing automated service composition techniques can handle. According to most of the existing methods, the process model of composite service includes sequence constructs only. This article presents a method to introduce conditional branch structures into the process model of composite service when needed, in order to satisfy users' diverse and personalised needs and adapt to the dynamic changes of real-world environment. UML activity diagrams are used to represent dependencies in composite service. Two types of user preferences are considered in this article, which have been ignored by the previous work and a simple programming language style expression is adopted to describe them. Two different algorithms are presented to deal with different situations. A real-life case is provided to illustrate the proposed concepts and methods.     

GMADM-based attributes selection method in developing prediction model

Attribute Selection is an important issue for developing a prediction model, however, how to determine an effective attribute selection algorithm is an important but difficult issue. Attribute selection can effectively delete the irrelevant and redundant attributes to increase the prediction accuracy, and evaluating attribute selection methods usually need to consider several criteria such as accuracy, type I error, and type II error. In this paper, the selected attribute process is modeled as a group multiple attributes decision making (GMADM) problem. In evaluating different GMACD methods, the most results usually are consistently, But there are some situations where the evaluated outcomes have different results. The GMADM method is useful tool for evaluating attribute selection algorithms, and the TOPSIS is capable of identifying a compromised solution when different GMADM method result in conflicting rankings. Therefore, this paper proposes an objective (persuasive) GMADM-based attributes selection method to solve this disagreement and help decision makers pick the most suitable method. After verification, the proposed model is more persuasive to evaluate the attributes selection methods for developing prediction model.     

群体决策复合准则在供应商选择中的应用

供应商多属性的本质是供应商选择问题复杂性的主要原因之一,特别是属性为描述性质的模糊数时,有限理性的个体在决策制定过程中受到很大的局限。实际操作过程中,专家评分法运用广泛,在此基础上,文中将其与群决策理论相结合,首先指出了对供应商进行评价时常出现的平局问题,将群体决策复合准则引入到供应商选择过程中,然后建立模型,对其求解,最后结合算例,说明该方法的有效性。     

Sequential conditional correlations: Inference and evaluation

This paper presents a new approach to the modeling of conditional correlation matrices within the multivariate GARCH framework. The procedure, which consists of breaking the matrix into the product of a sequence of matrices with desirable characteristics, in effect converts a highly dimensional and intractable optimization problem into a series of simple and feasible estimations. This in turn allows for richer parameterizations and complex functional forms for the single components. An empirical application involving the conditional second moments of 69 selected stocks from the NASDAQ100 shows how the new procedure results in strikingly accurate measures of the conditional correlations.     

Statistical treatment choice based on asymmetric minimax regret criteria

This paper studies the problem of treatment choice between a status quo treatment with a known outcome distribution and an innovation whose outcomes are observed only in a finite sample. I evaluate statistical decision rules, which are functions that map sample outcomes into the planner’s treatment choice for the population, based on regret, which is the expected welfare loss due to assigning inferior treatments. I extend previous work started by Manski (2004) that applied the minimax regret criterion to treatment choice problems by considering decision criteria that asymmetrically treat Type I regret (due to mistakenly choosing an inferior new treatment) and Type II regret (due to mistakenly rejecting a superior innovation) and derive exact finite sample solutions to these problems for experiments with normal, Bernoulli and bounded distributions of outcomes. The paper also evaluates the properties of treatment choice and sample size selection based on classical hypothesis tests and power calculations in terms of regret.     

基于多粒度二元语义的供应商选择方法

供应商选择是一个多属性决策问题,既包括定性的因素也包括定量的因素。把成本、质量、服务水平、供应商的能力和外部因素作为供应商选择的标准,并将基于多粒度二元语义信息处理的群决策方法应用于供应商的选择,给出了基于二元语义信息处理的群决策的步骤,最后给出了一个算例。     

Bayesian hypothesis testing in latent variable models

Hypothesis testing using Bayes factors (BFs) is known not to be well defined under the improper prior. In the context of latent variable models, an additional problem with BFs is that they are difficult to compute. In this paper, a new Bayesian method, based on the decision theory and the EM algorithm, is introduced to test a point hypothesis in latent variable models. The new statistic is a by-product of the Bayesian MCMC output and, hence, easy to compute. It is shown that the new statistic is appropriately defined under improper priors because the method employs a continuous loss function. In addition, it is easy to interpret. The method is illustrated using a one-factor asset pricing model and a stochastic volatility model with jumps.     

Mean-variance portfolio selection of cointegrated assets

This paper considers the continuous-time mean-variance portfolio selection problem in a financial market in which asset prices are cointegrated. The asset price dynamics are then postulated as the diffusion limit of the corresponding discrete-time error-correction model of cointegrated time series. The problem is completely solved in the sense that solutions of the continuous-time portfolio policy and the efficient frontier are obtained as explicit and closed-form formulas. The analytical results are applied to pairs trading using cointegration techniques. Numerical examples show that identifying a cointegrated pair with a high mean-reversion rate can generate significant statistical arbitrage profits once the current state of the economy sufficiently departs from the long-term equilibrium. We propose an index to simultaneously measure the departure level of a cointegrated pair from equilibrium and the mean-reversion speed based on the mean-variance paradigm. An empirical example is given to illustrate the use of the theory in practice.     

Optimal statistical decisions about some alternative financial models

We study Neyman–Pearson testing and Bayesian decision making based on observations of the price dynamics (_Xt:t∈[0,T])$(X_t:t\in [0,T])$ of a financial asset, when the hypothesis is the classical geometric Brownian motion with a given constant growth rate and the alternative is a different random diffusion process with a given, possibly price-dependent, growth rate. Examples of asset price observations are introduced and used throughout the paper to demonstrate the applicability of the theory. By a rigorous mathematical approach, we obtain exact formulae and bounds for the most common statistical characteristics of testing and decision making, such as the power of test (type II error probability), the Bayes factor and its moments (power divergences), and the Bayes risk or Bayes error. These bounds can be much more easily evaluated than the exact formulae themselves and, consequently, they are useful for practical applications. An important theoretical conclusion of this paper is that for the class of alternatives considered   neither the risk nor the errors converge to zero faster than exponentially in the observation time T$T$. We illustrate in concrete decision situations that the actual rate of convergence is well approximated by the bounds given in the paper.     

A conceptual framework for R&D strategic alliance assessment for Taiwan’s biotechnology industry

With the rapid development of technology, technology advancement is harder and harder with more and more risks in technology innovation, thus enterprises can’t carry out technology innovation program alone. The development of the emergence of the biotechnology industries provides valuable insights into the role of strategic alliances and networking that shaped the synergy between both industries. This paper provides a step by step methodology to evaluate R&D strategic alliances problem in Taiwan biotechnology Industry. The purpose of this paper is to formalize the choice of R&D strategic alliance modes for an individual multinational enterprise among Joint Venture, Franchise agreement, Licensing Agreement, Subcontract and Merger/acquisition. An illustrative example is presented to demonstrate the applicability of the proposed methodology. The proposed approach also provides a relatively simple and well suited decision making tool for this type of strategic decision making problem. This evaluation mode was identified as a workable method.     

Green supplier selection: a new genetic/immune strategy with industrial application

With the onset of the ‘climate change movement’, organisations are striving to include environmental criteria into the supplier selection process. This article hybridises a Green Data Envelopment Analysis (GDEA)-based approach with a new Genetic/Immune Strategy for Data Envelopment Analysis (GIS-DEA). A GIS-DEA approach provides a different view to solving multi-criteria decision making problems using data envelopment analysis (DEA) by considering DEA as a multi-objective optimisation problem with efficiency as one objective and proximity of solution to decision makers’ preferences as the other objective. The hybrid approach called GIS-GDEA is applied here to a well-known automobile spare parts manufacturer in India and the results presented. User validation developed based on specific set of criteria suggests that the supplier selection process with GIS-GDEA is more practical than other approaches in a current industrial scenario with multiple decision makers.