对林业税费的经济学分析

该文运用经济学的基本工具———供给和需求曲线 ,以商品林为研究对象 ,探讨了林业税费的作用机理和内涵。该文认为商品林生产具有正的外部性 ,市场失灵使生产者将不能提供社会真正所需要的商品林数量。在封闭的市场条件下 ,林业税费会直接成为价格的一部分 ,商品林生产者应当能够获得正常利润 ,与税费高低无关 ,但会使一部分林地退出生产。林业补贴是一种负的林业税收。在开放市场经济条件下 ,国内商品林供应量低于没有林业税收时的商品林供应量 ,更低于考虑社会生态需求时的商品林供应量 ,造成巨大的社会福利损失 ,应减免林业税费、增加林业扶持、取消价格管制。该文进一步研究了与林业税费密切相关的森林采伐限额政策 ,认为对商品林应该完全取消采伐限额政策     

The Establishment and Application of a Labor Quality Index: The Case of Taiwan’s Manufacturing Industry

The labor quality index (LQI) not only serves as an important reference for monitoring the progress of the sustainable development of a country, but it can also serve as an important parameter for economic analysis. To compile such an index for Taiwan, we conducted two large-scale surveys of 1000 major enterprises and 844 union leaders, respectively, to determine the appropriate weights for each key factor. We also searched for all the relevant statistics that were used to calculate the weighted sum of the 25 sub-indexes, in order to compile a LQI for Taiwan’s manufacturing industries covering the period from 1990-2000. Our calculations show that this LQI rose from 80.2 in 1990 to 117.5 in 2000, which reflected an impressive 37.3% increase in just one decade. This rate of growth has, however, been slowing down since 1997. Our results indicate that the LQI provides a valuable indicator for monitoring the enhancement of labor quality in this society.     

论工程量清单计价模式

分析了传统定额计价模式与市场经济不相适应之处,其主要表现为它不能反映企业的技术、管理水平等企业整体实力。在此基础上讨论了我国实行工程量清单计价模式的优点,这种计价模式要求企业自主报价、由市场交易形成建筑产品的价格,是一种新的市场定价计价模式,能适应市场经济发展的要求。但这种模式与国际通行的清单计价还存在很大差异,还没有完全脱离定额计价的思路,最后提出了改进和完善工程量清单计价模式的措施,为保证其顺利实施提供参考依据。     

教育服务产出核算分析

教育服务是服务核算中的一个重要部分。本文讨论教育服务的定义和服务产出的数量单位。研究教育服务的核算范围和计算教育服务产出价值的方法,以及教育服务的质量调整问题。最后,举例使用产出指标方法计算教育产出。     

地方高校重点学科建设绩效评价指标体系的验证性检验

对地方高校重点学科建设绩效评价指标体系进行验证性研究,检验其信效度和结构性.结果表明:指标体系咨询专家的积极系数、合理结构系数、权威系数都较高,肯德尔w系数为0.893,保证了研究较好的信效度;经聚类分析和非参数检验验证,各指标均能独立反映评价的不同信息,体现了较好的结构性.     

Asymptotic Theory of Outlier Detection Algorithms for Linear Time Series Regression Models

Outlier detection algorithms are intimately connected with robust statistics that down‐weight some observations to zero. We define a number of outlier detection algorithms related to the Huber‐skip and least trimmed squares estimators, including the one‐step Huber‐skip estimator and the forward search. Next, we review a recently developed asymptotic theory of these. Finally, we analyse the gauge, the fraction of wrongly detected outliers, for a number of outlier detection algorithms and establish an asymptotic normal and a Poisson theory for the gauge.     

Constructing a strategy map for banking institutions with key performance indicators of the balanced scorecard

This study presents a structural evaluation methodology to link key performance indicators (KPIs) into a strategy map of the balanced scorecard (BSC) for banking institutions. Corresponding with the four BSC perspectives (finance, customer, internal business process, and learning and growth), the most important evaluation indicators of banking performance are synthesized from the relevant literature and screened by a committee of experts. The Decision Making Trial and Evaluation Laboratory (DEMATEL) method, a multiple criteria analysis tool, is then employed to determine the causal relationships between the KPIs, to identify the critical central and influential factors, and to establish a visualized strategy map with logical links to improve banking performance. An empirical application is provided as an example. According to the expert evaluations, the three most essential KPIs for banking performance are customer satisfaction, sales performance, and customer retention rate. The DEMATEL results demonstrate a clear road map to assist management in prioritizing the performance indicators and in focusing attention on the strategy-related activities of the crucial indicators. According to the constructed strategy map, management could better invest limited resources in the areas that need improvement most. Although these strategy maps of the BSC are not universal, the research results show that the presented approach is an objective and feasible way to construct strategy maps more justifiably. The proposed framework can be applicable to institutions in other industries as well.     

基于熵理论的河北省可持续发展水平评价研究

根据2000—2009年国家统计年鉴中河北省的有关数据，选取有代表性的指标，构造评价可持续发展水平的指标体系，并采用熵理论确定各指标的权重，以观察近10年来河北省经济社会可持续发展的具体情况。实证研究结果表明：河北省正逐渐迈向可持续发展的道路,但任重道远。根据省际具体情况，在实证研究的基础上，就河北省经济社会的长期可持续发展提出了若干建议。     

Comparing the effectiveness of respondent-driven sampling and quota sampling in migration research

We evaluate the effectiveness in empirical migration research of the respondent-driven sampling (RDS) and the quota sampling with regard to four criteria: quality of the data; sociometric diversity of the sample; geographic coverage of the sample; and cost-effectiveness. We review two surveys of ex-USSR migrants, conducted simultaneously in the Warsaw metropolitan area, each undertaken with the use of one of the two sampling methods. We find that although the RDS was considerably costlier, it enabled faster data collection and posed a lower risk of underestimating the cost of the survey. We also find that the RDS generated higher-quality data, and that it was more successful in surveying short-term circular migrants. This comparative evaluation contributes to the literature on social research methods in that it links the sampling methods with the quality and character of the data, and helps assess the usefulness and applicability of RDS in empirical migration studies.     

A Bayesian model for multiple change point to extremes,with application to environmental and financial data

Abrupt changes often occur for environmental and financial time series. Most often, these changes are due to human intervention. Change point analysis is a statistical tool used to analyze sudden changes in observations along the time series. In this paper, we propose a Bayesian model for extreme values for environmental and economic datasets that present a typical change point behavior. The model proposed in this paper addresses the situation in which more than one change point can occur in a time series. By analyzing maxima, the distribution of each regime is a generalized extreme value distribution. In this model, the change points are unknown and considered parameters to be estimated. Simulations of extremes with two change points showed that the proposed algorithm can recover the true values of the parameters, in addition to detecting the true change points in different configurations. Also, the number of change points was a problem to be considered, and the Bayesian estimation can correctly identify the correct number of change points for each application. Environmental and financial data were analyzed and results showed the importance of considering the change point in the data and revealed that this change of regime brought about an increase in the return levels, increasing the number of floods in cities around the rivers. Stock market levels showed the necessity of a model with three different regimes.