统筹城乡发展:理论演进与财税政策

新中国成立以来,非均衡发展的战略使我国形成了以二元户籍制度为核心的城乡分割的二元经济、社会体制。本文对二元经济理论的演进路径进行了梳理,提出我国财税政策要从保障城乡公民基本权利、促进劳动力自由流动、提高农业劳动生产率、加快农村专业化水平与分工等方面支持统筹城乡发展,并对财税体制进行相应变革。     

内蒙古入境旅游市场特征分析与预测

在分析内蒙古入境旅游市场发展总体特征的基础上,根据内蒙古1980-2009年入境旅游人数和入境旅游收入数据,利用Logistic模型对＂十二五＂期间内蒙古入境旅游业的发展进行了预测与分析,得到的结果能够帮助我们把握＂十二五＂期间入境旅游业的变动趋势,并寻求最佳的调控办法。     

技术生命周期视域下领域介入方向与时机研究 ——以图像处理技术领域为例

从专利文献数据出发,以Logistic曲线模型为研究方法,实证分析图像处理领域的整体技术发展及分支技术生命周期进程。研究发现,图像分割、图像识别技术方向及生物识别应用领域处于成长期,图像增强、图像去噪、图像重建、图像融合技术方向处于技术成熟期,而图像复原、图像编码技术及通信、医疗、交通、工业及遥感应用领域已经进入技术饱和期。结合图像处理领域分支技术方向及技术生命周期进展,可为相关创新主体介入领域的方向及时机提供参考信息。     

陕西农户奶牛保险支付意愿的实证分析

陕西省于2007年7月在泾阳县实施了奶牛政策性农业保险的试点。本文按照条件价值评估方法,于2007年11月在泾阳县以支付卡式问卷调查对127户奶牛养殖户进行了实地调查,以调查数据为依据,测算了当地养殖户奶牛保险费用支付意愿,并运用Logistic回归模型分析了影响农户奶牛保险支付意愿的主要因素。结论认为,泾阳县奶牛保险试点中对畜龄2～8周岁奶牛实际征收保费标准低于养殖户平均支付意愿,是否接受保费、是否了解补贴、养殖户个体特征即受教育年限、养殖经验、年龄等是影响其保险支付意愿的主要因素。     

Basket trading under co-integration with the logistic mixture autoregressive model

In this paper, we propose a co-integration model with a logistic mixture auto-regressive equilibrium error (co-integrated LMAR), in which the equilibrium relationship among cumulative returns of different financial assets is modelled by a logistic mixture autoregressive time series model. The traditional autoregression (AR) based unit root test (ADF test), used in testing co-integration, cannot give a sound explanation when a time series passes the ADF test. However, its largest root in the AR polynomial is extremely close to, but less than, one, which is most likely the result of a mixture of random-walk and mean-reverting processes in the time series data. With this background, we put an LMAR model into the co-integration framework to identify baskets that have a large spread but are still well co-integrated. A sufficient condition for the stationarity of the LMAR model is given and proved using a Markovian approach. A two-step estimating procedure, combining least-squares estimation and the Expectation-Maximization (EM) algorithm, is given. The Bayesian information criterion (BIC) is used in model selection. The co-integrated LMAR model is applied to basket trading, which is a widely used tool for arbitrage. We use simulation to assess the model in basket trading strategies with the statistical arbitrage feature in equity markets. Data from several sectors of the Hong Kong Hang Seng Index are used in a simulation study on basket trading. Empirical results show that a portfolio using the co-integrated LMAR model has a higher return than portfolios selected by traditional methods. Although the volatility in the return increases, the Sharpe ratio also increases in most cases. This risk–return profile can be explained by the shorter converging period in the co-integrated LMAR model and the larger volatility in the ‘mean-reverting’ regime.     

Tourist market segmentation with linear and non-linear techniques

The need for in-depth knowledge of tourist market segments and the need to overcome the limitations of using linear techniques to analyse non-linear relationships requires a re-assessment of generally used approaches such as cluster analysis and multiple linear regression. The objectives of the research are (1) to consider the use of self-organising (SOM) neural networks for segmenting tourist markets and (2) to analyse the predictive ability of backpropagation (BP) neural networks for classifying tourists from follow-up surveys by using the output provided by a SOM neural network. The findings of the SOM neural network modelling indicate three natural clusters. In addition, the predictive ability of the BP neural network model appears to be superior to that of MLR static filter and logistic regression models. The BP neural network model developed for this application appears suitable for deployment (i.e. classification of tourists from follow-up surveys).     

高校教师对延迟退休年龄意愿的实证研究——基于成都市高校教师的调查

通过PPS抽样从成都市随机抽取了九所高校,并就其专任教师对延迟退休年龄的意愿进行了问卷调查,得到影响成都市高校教师退休意愿影响因素的数据,建立了二维选择logistic回归模型。是否延迟退休年龄的主要影响因素为性别、收入、和身体健康状况。对赞成延迟退休教师的意愿退休年龄进行了分布检验,发现其服从正态分布,并预测出赞成延迟退休的男教师意愿退休年龄为64-65岁,女教师的意愿退休年龄为61-62岁。     

两类农村居民点整治模式下农户整治意愿影响因素比较研究

研究目的：比较在宅基地置换和村庄归并两类农村居民点整治模式下农户整治意愿影响因素的异同,为制定差别化的农村居民点整治政策提供支持。研究方法：比较分析法,农户调查法,Logistic回归分析法。研究结果：宅基地置换模式下,年龄、人口数、房屋建筑年代、喜好房屋类型、政策认知状况以及对生活成本的接受程度是显著影响农户整治意愿的因素;村庄归并模式下,农业收入占比、宅基地面积、生态环境满意度、补偿方式和对生活成本的接受程度是显著影响农户整治意愿的因素;两类模式下,除对生活成本的接受程度是共同显著影响因素外,其他影响因素存在着较大的差别。研究结论：不同区域、不同经济发展水平下,不同农户的居民点整治意愿影响因素存在差异,新时期农村居民点整治的政策应着眼于各区域的客观实际,分区、分类推进,体现出差别化。     

Output Expectations and Forecasting of UK Manufacturing

This paper analyses both quarterly data from the Confederation of British Industry (CBI) Survey on respondents’ expectations of recent and forthcoming manufacturing output and monthly Office of National Statistics (ONS) figures on actual manufacturing output within the UK. Quarterly output expectations of the CBI manufacturers are explained from the monthly ONS observations using a bounded rationality approach. The logistic formulation models the diffusion process across respondents. There is a backward-looking CBI Survey perspective, explained by past ONS observations, and a forward-looking perspective, explained from future ONS statistics. Also, the forecasting of monthly manufacturing output from earlier values, along with the quarterly CBI Survey information, is examined and tested against the alternative Pesaran/Thomas method. The study provides econometric evidence for the validity of the logistic model and shows that bounded rationality can explain the formation of predictions among business managers in the UK manufacturing sector. The emerging consensus from the literature, supported by this paper, is that the logistic format is a superior approximation to the true data generating process compared with the earlier standard Anderson/Pesaran/Thomas approach. An adjustment to the Survey is used, which achieves perfect symmetry with up and down versions of the data. The benefits of this adjustment are tested in the forecasting section.

基于logistic回归的上市公司财务危机预警模型

国内外所有关于财务危机预警问题的研究,主要涉及到两个方面的问题：一是财务危机概念的界定;二是预测变量（判别指标）的选择和预警模型的建立（企业财务危机是一个连续的动态过程,并直接表现为绩效指标的恶化,因此,可通过一定的财务指标来构造企业的财务预警模型）。运用中国上市公司的财务指标数据及因子分析和Logistic回归等方法构建基于上市公司的财务危机预警的Logistic模型,经过检验,具有一定的实际应用价值。