At‐home meat consumption in China: an empirical study*

The remarkable economic changes occurring within China since 1978 have resulted in a striking alteration in food consumption patterns, and one marked change is the increasing consumption of meat. Given China’s large population, a small percentage change in per capita meat consumption could lead to a dramatic impact on the production and trade of agricultural products. Such changes have major implications for policy makers and food marketers. This paper concentrates on meat consumption patterns in the home in China. A censored linear approximate almost ideal demand system model was employed in the study, and major economic parameters were estimated for different meat items. Data used in this study were collected from two separate consumer surveys – one urban and one rural in 2005.     

基于迭代列消元法的线性分组码参数盲识别

针对线性分组码参数盲识别容错性能差的问题,提出基于迭代列消元法的线性分组码参数盲识别方法。首先对截获矩阵应用迭代列消元法,将其相关列对应各个窗内的转移矩阵中的列向量作为候选校验向量,再根据截获矩阵对偶码空间归一化维数来识别码字长度和同步时刻,最后将对偶码字进行初等行变换识别校验矩阵。仿真结果证明,与以往盲识别方法相比,所提方法容错性能好,适用于各种码率的线性分组码的码字长度、同步时刻和生成多项式识别。     

Spillovers in Exchange Rates and the Effects of Global Shocks on Emerging Market Currencies

This paper provides an investigation into the spillover effects of exchange rate returns and volatility for developed and emerging market currencies, using data from 1997 to 2011. The results suggest that spillovers in exchange rate returns have increased steadily over time, in moderate reaction to economic events. In contrast, spillovers in total observed volatility (measured by squared returns) react more strongly to economic events, and this transmission has remained at a relatively high level since the global financial crisis. Furthermore, over the course of time, global shocks would appear to account for a larger proportion of aggregate exchange rate volatility (and the relative importance of domestic shocks has declined). The paper also considers whether the increase in volatility spillover is due to sudden shocks, or whether it is due to changes in the stochastic trend of the underlying volatility process. The results suggests that in most cases, this increase is due to sudden shocks, however, in certain instances country‐specific events may perpetuate changes to the trend of the underlying volatility spillover.     

河南省城镇居民消费结构的比较实证分析

本文根据扩展线性支出系统模型的计算结果,通过横向和纵向比较,发现河南省城镇居民消费水平已经提高,消费结构已经得到提升,交通通信等享受性支出已经成为重点消费支出项目,但基本生存型消费仍然占较大比重,而且城镇居民收入差距对消费状况造成一定程度的影响。为此,提高河南省城镇居民收入水平是解决问题的根本途径,同时,消费信贷种类的增加,社会保障水平的提高等也是解决问题的有效方法。     

新围海涂土地利用结构优化模型及其应用

为了进一步探讨数学规划模型在新围海涂土地利用结构优化中的应用,在模型分析与实例应用相结合的基础上,选择浙江沿海新围海涂作为典型研究区,根据当地滩涂开发利用总体规划要求,结合实际开发需要,应用数学规划方法构建土地利用结构优化决策模型,对规划范围内新围海涂的土地利用结构进行优化配置。研究结论:应用数学模型对研究区内土地利用结构优化配置是可行的。但是今后需要进一步研究空间优化配置方法,实现定性、定量和定位三者的统一。     

浅谈事故路段道路的排队长度问题

通过观察参考文献视频一中各个时间段内交通事故路段输入车辆与输出车辆的数目,运用SPSS软件,建立了统计回归模型。运用回归系数,得出了统计回归模型的参数。对模型进行了评估．进而得出了交通事故所影响的路段车辆排队长度与事故横断面实际通行能力和事故持续时间之间的关系。     

Negative affectivity and workplace deviance: the moderating role of ethical climate

This study investigates (1) the relationship between employees’ trait of negative affectivity (NA) and workplace deviance and (2) the moderating role of ethical climate in the above relationship. Data was collected from 310 employees in 40 Taiwanese companies, and hierarchical linear modeling was used to test the hypotheses. Results show that NA was positively related to workplace deviance. In addition, the rules climate weakened the relationship between NA and workplace deviance, and both the instrumental climate and the caring climate strengthened the relationship between NA and workplace deviance. Managerial implications and future research directions are also discussed.     

高科技风投企业家项目考察阶段的非理性决策实证研究——基于人口统计特征分析

基于人口统计特征,采用列联表和多元线性回归的方法分析人口统计特征中有关的年龄、学历、留学经历与家庭结构等要素与高科技风投企业家非理性行为在项目考察阶段决策的相关性结果显示:国外留学经验、创业成功经验与企业家项目考察阶段的非理性决策存在着相关性。     

Non-permutation flowshop scheduling in a supply chain with sequence-dependent setup times

In this paper, we consider a flowshop scheduling problem with sequence-dependent setup times and a bicriteria objective to minimize the work-in-process inventory for the producer and to maximize the customers' service level. The use of a bicriteria objective is motivated by the fact that successful companies in today's environment not only try to minimize their own cost but also try to fulfill their customers' need. Two main approaches, permutation and non-permutation schedules, are considered in finding the optimal schedule for a flowshop. In permutation schedules the sequence of jobs remains the same on all machines whereas in non-permutation schedule, jobs can have different sequence on different machines. A linear mathematical model for solving the non-permutation flowshop is developed to comply with all of the operational constraints commonly encountered in the industry, including dynamic machine availabilities, dynamic job releases, and the possibility of jobs skipping one or more machines, should their operational requirements deem that it was necessary. As the model is shown to be NP-hard, a metasearch heuristic, employing a newly developed concept known as the Tabu search with embedded progressive perturbation (TSEPP) is developed to solve, in particular, industry-size problems efficiently. The effectiveness and efficiency of the search algorithm are assessed by comparing the search algorithmic solutions with that of the optimal solutions obtained from CPLEX in solvable small problem instances.     

The out-of-sample forecasting performance of nonlinear models of regional housing prices in the US

This article provides out-of-sample forecasts of linear and nonlinear models of US and four Census subregions’ housing prices. The forecasts include the traditional point forecasts, but also include interval and density forecasts, of the housing price distributions. The nonlinear smooth-transition autoregressive model outperforms the linear autoregressive model in point forecasts at longer horizons, but the linear autoregressive and nonlinear smooth-transition autoregressive models perform equally at short horizons. In addition, we generally do not find major differences in performance for the interval and density forecasts between the linear and nonlinear models. Finally, in a dynamic 25-step ex-ante and interval forecasting design, we, once again, do not find major differences between the linear and nonlinear models. In sum, we conclude that when forecasting regional housing prices in the United States, generally the additional costs associated with nonlinear forecasts outweigh the benefits for forecasts only a few months into the future.