我国住房保障制度研究态势评述

本文研究目的,回顾和总结我国住房保障制度的一般理论研究,提出进一步的研究方向。研究结论,研究中存在的问题主要有,经验性研究较多,就事论事现象明显;理论性研究较少,基础理论研究较薄弱,理论体系有待建立。研究方法上存在缺陷与不足,应用研究缺乏理论指导,解决实际问题能力差。研究工作缺乏必要的协调,研究力量分散,存在低水平重复等问题。未来将要重点研究的内容包括,住房保障制度的科学理论构建;住房保障的体制和机制研究;住房保障制度中具体标准、模式以及理论体系研究。     

近10年我国运动生物力学发展历程分析

以第10-15届全国运动生物力学学术交流大会所收录的研究论文为研究对象,对运动生物力学的三个主要研究领域(基础理论研究、实践应用研究、方法技术研究)的研究数量、研究主题的分布和研究方法进行分析,总结概括出近10年我国运动生物力学研究的历程,并在此基础上发现问题,提出今后运动生物力学研究应该重点关注的方向,为提高运动生物力学研究的水平,促进运动生物力学学科发展提供借鉴。     

我国住房保障制度研究态势评述

本文研究目的,回顾和总结我国住房保障制度的一般理论研究,提出进一步的研究方向。研究结论,研究中存在的问题主要有,经验性研究较多,就事论事现象明显;理论性研究较少,基础理论研究较薄弱,理论体系有待建立。研究方法上存在缺陷与不足,应用研究缺乏理论指导,解决实际问题能力差。研究工作缺乏必要的协调,研究力量分散,存在低水平重复等问题。未来将要重点研究的内容包括,住房保障制度的科学理论构建;住房保障的体制和机制研究;住房保障制度中具体标准、模式以及理论体系研究。     

规范会计研究与实证会计研究评析

在我国会计研究历史上,按照研究方法可分为规范会计研究即传统的会计研究和实证会计研究。规范会计研究始于二十世纪三十年代的美国,到二十世纪六、七十年代占据西方国家会计研究的主导地位。然而随着会计研究的发展,规范会计研究中的问题逐渐暴露,实证研究开始被引入会计研究领域,这促进了实证学在会计研究中的作用。规范会计研究和实证会计研究之间相辅相成,既有区别又有着密不可分的联系。对此,本文将做出评析。     

企业家学习研究方法现状评述与展望

企业家能力的成长和学习型组织的兴起使企业家学习成为企业管理领域的一个研究重点。通过搜索相关数据库对国内外企业家学习的相关文献与书籍的分析,本研究总结归纳了国内外研究企业家学习的研究方法。国外对于企业家学习的研究已经逐步趋向成熟,研究的方法多种多样而且非常规范,包括规范研究和实证研究;相对而言,国内的研究方法比较单一而且不够规范。国外对于企业家学习的研究定性分析居多．而国内则定量研究较定性研究多。因此,对于企业家学习的研究方法,除了多样性与规范性之外,定量研究和多学科交叉方法都为未来的研究提供了借鉴。     

化解省属高校贷款债务政策研究

从对高校贷款债务的研究方式来看,现有的研究方式显得比较单一.研究方法多属于理论研究,缺乏实证研究,研究的成果往往不容易转化为实践.正因如此,进一步推动高校贷款的理论研究和实证研究的充分结合就显得十分必要.应该增加运用实证研究方法的比重,保证研究的客观性和规范性,本文试图从政府角度研究解决高校贷款问题,提出具体的方案和对应的实施细则,对高校如何控制贷款的风险和多大程度上控制贷款风险提供可操作性的办法,为国家和政府如何调整高校贷款政策、规范高校贷款行为提供必要的参考和借鉴.     

前瞻我国企业文化的走向

中国企业文化研究要想适应实践的需要,就应遵循以下原则:理论研究与应用研究相结合,定性研究与定量研究相结合,宏观研究与微观研究相结合,本土化研究与全球化研究相结合.     

基于EVA的企业绩效管理创新研究综述

文章通过文献计量和内容分析,回顾了国内学者关于EVA导向的企业绩效管理创新的研究历程,概括了研究的阶段性特征、主要研究视角、研究方法和研究所取得的进展等,展望了未来的研究趋势,认为"过程研究"、跨案例研究等将会显著增多,基于中国管理情境的EVA实施模式的研究,将会成为研究主题之一。     

经济学理论对会计学研究的渗透

在现代会计研究领域,会计学研究与经济学理论的连接越来越密切。从经济学角度解释会计目标和全面收益理论、用经济学观点研究会计准则、以经济学立场剖析会计诚信缺失以及将经济学的实证方法用于会计学研究等等,经济学对会计学研究的支持加深了会计学研究的深度,会计学研究对经济学的应用拓宽了会计研究的广度。正确处理会计学研究与经济学理论的关系,有助于进一步提升和推进会计理论研究,更好地为会计实务服务。     

“致堵” “治堵”——城市交通治堵研究述评

在评述国内外城市交通“致堵”和“治堵”研究的基础上,指出城市交通拥堵治理研究中,偏重于制度研究,缺乏定量研究,缺乏与其他城市问题的综合治理研究,缺乏人本关怀,并阐述未来研究走向.     

Locating a Biorefinery in Northern Spain: Decision Making and Economic Consequences

Biofuels are emerging as a prominent renewable and sustainable energy sources in developed countries. In this sense, this paper presents a case study in which a biorefinery has to be sited in Northern Spain. Thus, the strategic decision of locating such a facility is deeply investigated through strategic policy evaluation. Then, tactical decisions ranging from purchasing and transportation policies to storage protocols are carried out. Only local and limited biomass can be harvested for supplying the biorefinery through a heterogeneous vehicle fleet. Moreover two different and mutually exclusive storage strategies are evaluated: direct supply from crops to biorefinery and using intermediate-collectors. Additionally, crop exploitation factors and biorefinery sizes are used to generate several scenarios in which the strategic decision of location as well as all the tactic decisions are made. Some mixed integer linear programming models are proposed to figure out all relevant decision problems.The results suggest that the Northwest study area as the best option to locate the biorefinery and recommend the intermediate-collector storage strategy. Moreover, the key information about critical biomass, crops and times are also provided.     

Productivity Growth, Efficiency and Outsourcing in Manufacturing and Service Industries

This paper is a survey of recent contributions to, and developments of, the relationship between outsourcing, efficiency and productivity growth in manufacturing and services. The objective is to provide a thorough and up–to–date survey that provides a significant discussion on data, as well as on the core methods of measuring efficiency and productivity. First, the readers are introduced to the measurement of partial and total factor productivity growth. Different parametric and non–parametric approaches to the productivity measurement in the context of static, dynamic and firm–specific modelling are discussed. Second, we survey the econometric approach to efficiency analysis. The issues of modelling, distributional assumptions and estimation methods are discussed assuming that cross–sectional or panel data are available. Third, the relationship between outsourcing and productivity growth in manufacturing and services is discussed. The correspondence between a number of hypotheses and empirical findings are examined. Examples of varieties of relevant empirical applications, their findings and implications are presented. Fourth, measurement of inputs and outputs in manufacturing and services are discussed. Finally, to promote useful research, a number of factors important to the analysis of outsourcing, efficiency and productivity growth in the service sector are summarised.     

A general method for addressing forecasting uncertainty in inventory models

In practice, inventory decisions depend heavily on demand forecasts, but the literature typically assumes that demand distributions are known. This means that estimates are substituted directly for the unknown parameters, leading to insufficient safety stocks, stock-outs, low service, and high costs. We propose a framework for addressing this estimation uncertainty that is applicable to any inventory model, demand distribution, and parameter estimator. The estimation errors are modeled and a predictive lead time demand distribution obtained, which is then substituted into the inventory model. We illustrate this framework for several different demand models. When the estimates are based on ten observations, the relative savings are typically between 10% and 30% for mean-stationary demand. However, the savings are larger when the estimates are based on fewer observations, when backorders are costlier, or when the lead time is longer. In the presence of a trend, the savings are between 50% and 80% for several scenarios.     

Varying Coefficient Regression Models: A Review and New Developments

Varying coefficient regression models are known to be very useful tools for analysing the relation between a response and a group of covariates. Their structure and interpretability are similar to those for the traditional linear regression model, but they are more flexible because of the infinite dimensionality of the corresponding parameter spaces. The aims of this paper are to give an overview on the existing methodological and theoretical developments for varying coefficient models and to discuss their extensions with some new developments. The new developments enable us to use different amount of smoothing for estimating different component functions in the models. They are for a flexible form of varying coefficient models that requires smoothing across different covariates' spaces and are based on the smooth backfitting technique that is admitted as a powerful technique for fitting structural regression models and is also known to free us from the curse of dimensionality.     

Semiparametric econometric estimators for a truncated regression model: a review with an extension

Econometric estimators for a truncated regression model are reviewed. For each estimator, the motivations, the key assumptions, the asymptotic distribution and estimates for the asymptotic variance matrix are presented; also a new estimator is suggested. We select five practical estimators among those, and compare them through a Monte Carlo study where the response variable is simulated but the covariates are drawn from a real data set. Some practical and computational issues are addressed as well.     

Computer‐Aided Statistical Instruction—Multi‐Mediocre Techno‐Trash?

The very soul of statistics are data, but few students actually collect data as part of their statistical journey. The impediments to real data collection exercises are very real—they are logistically difficult to set up, expensive, and may not work because of extraneous events outside the control of the instructor. Computer‐aided laboratories are a way to bring many of the benefits of actual data collection to students at a fraction of the cost and can be easily controlled by the instructor. There are many computer‐aided modules available—indeed a search on Google gave over 1 million hits. Some modules are good but many are mediocre. What separates the gems from the trash?     

Forecasting returns in the VIX futures market

This paper introduces a new forecasting model for VIX futures returns. The model is structural in nature and parsimonious, and contains parameters that are relatively easy to estimate. The forecasts of next day VIX futures returns based on this model are superior to those produced by a linear forecasting model that uses the same set of predictors. Moreover, the profits to a market-timing model based on the proposed forecasts are statistically and economically significant, and are robust to both the method used for adjusting for risk and transaction costs (up to around 15 basis points). In contrast, the forecasts generated by the linear forecasting model are not.     

Data transforms with exponential smoothing methods of forecasting

In this paper, transforms are used with exponential smoothing, in the quest for better forecasts. Two types of transforms are explored: those which are applied to a time series directly, and those which are applied indirectly to the prediction errors. The various transforms are tested on a large number of time series from the M3 competition, and ANOVA is applied to the results. We find that the non-transformed time series is significantly worse than some transforms on the monthly data, and on a distribution-based performance measure for both annual and quarterly data.     

CEO optimism,CEO selection,compensation, and corporate investment decision: The case of CEOs who were rehired as CEOs by another firms after turnover

What happens to CEOs after they are let go by their firm? This study is designed to investigate CEOs who are rehired as CEOs by another firms after turnover. CEOs defined as “moderately optimistic” and those who left voluntarily from their departing firms, are younger, have better prior performance, and work in larger firms are found to have a greater likelihood of being rehired as a CEO by another employer. Moreover, new-hire firms with higher growth opportunity and higher R&D expenditures are found to be significantly more willing to hire overconfident CEOs. Furthermore, more-optimistic CEOs are found to receive higher total compensation from their new-hire firms than CEOs who are less optimistic. Finally, overconfident CEOs working in firms with high growth opportunity and higher R&D show a significantly greater tendency toward increasing firm investment.     

Linear and nonlinear regression with stable errors

In this paper we describe methods and evaluate programs for linear regression by maximum likelihood when the errors have a heavy tailed stable distribution. The asymptotic Fisher information matrix for both the regression coefficients and the error distribution parameters are derived, giving large sample confidence intervals for all parameters. Simulated examples are shown where the errors are stably distributed and also where the errors are heavy tailed but are not stable, as well as a real example using financial data. The results are then extended to nonlinear models and to non-homogeneous error terms.