战略匹配对合资企业绩效的影响研究——基于中美合资企业的实证研究

关于合资企业的研究从不同学者分别论述了合资企业的战略、组织和文化的匹配性对合资企业绩效的影响。本文通过研究合资企业在合资运营之前战略匹配对中外合资企业四类绩效指标的影响研究。研究结果发现,目标一致(战略匹配)对合资企业满意度和总体竞争力有显著影响,而资源互补(战略匹配)对合资企业绩效无显著影响。     

Deeds or words? The local influence of anti-immigrant parties on foreigners’ flows

We investigate the influence of anti-immigrant parties on foreigners' location choices. Considering Italian municipal elections from 2000 to 2018, we create a comprehensive database that includes a classification of the anti-/pro-immigration axis of leading political parties based on specialists' assessments. Adopting a bias-corrected regression discontinuity design, we find that the election of a mayor supported by an anti-immigrant coalition significantly affects immigrants' location choices only when considering the most recent years. This finding is not driven by the enactment of policies against immigrants but by an ‘inhospitality effect’, which has become stronger over time due to the exacerbation of political propaganda. Therefore, foreigners' flows are influenced by the local political environment only when immigration is central to the political debate.     

中国家庭住房产权类型分化研究

本文基于CFPS2010年基线调查的微观数据,利用Logistic模型探讨住房类型分化的产生原因,测算各个阶层在获取住房的途径和机会上的差异。结果表明：户口状况、城乡类别对产权类型的影响存在差异;年龄对租房和亲友提供住房产生影响;收入、是否是党员、婚姻状况、对教育重要程度的认知情况、职业类别等不同程度地影响产权类型;乡村住房自有率高于城市。     

政府规模、政府支出增长与经济增长关系的非线性研究

本文运用面板平滑转换回归模型(PSTR),在非线性的框架下对政府规模与经济增长关系的渐进演变展开深入研究,并对可能引发两者关系结构性转变的警戒政府规模进行有效估算。研究结果表明,政府规模与经济增长之间存在着非线性关系,即随着政府规模的逐步增大,由于税负增加等因素的影响,使得政府支出增加所产生的负效应影响逐步凸显,而政府规模进一步扩大并超过警戒水平时,过度拥挤的政府支出对经济增长将由促进作用转变为阻碍作用。研究还发现,尽管我国政府支出增长与经济增长的关系参数值有所下降,但由于基础设施落后,公共物品与公共服务供给仍然相对不足,政府支出的增加仍有助于促进经济的进一步发展。     

带未知异方差与半线性结构Tobit模型的半参数估计

本文将Tobit模型扩展至同时带未知条件异方差与半线性结构回归函数的场合,并提出一种计算简便的半参数二步估计法。该方法的关键之处在于连续两次施以成对相减变换,并先后消去第一步所得被解释变量非参数条件分位函数中的两类非线性冗余成分(非线性回归函数部分与未知异方差结构)。文章证明了估计量的n-一致性与渐近正态性,并通过Monte Carlo模拟研究了分位点对的选择、扰动项分布类型与样本删尾程度等因素对估计量小样本性质的影响。最后通过国内居民医疗服务利用不平等的实例验证了本文所提的方法。     

房价影响因素的实证分析——以青岛市为例

运用SPSS软件,以人口、人均GDP、住房销售面积和房地产开发投资为自变量,采用2000～2009年10年的数据,建立了多元线性回归模型,对青岛市房价这一因变量进行了模拟分析。模型通过各种检验,得出了影响青岛市住房价格最重要的因素是市区人口这一结论,说明青岛市有效的需求增大,是抬高住房价格十分重要的因素,这在一定层面上说明了青岛的住宅市场的价格是比较正常的价格。     

科技基础设施建设投入与高科技产值的回归分析——以镇江市发展科技基础设施建设为视角

本文利用线性回归方法研究了R&D投入对高科技产业产值的影响,使用SPSS统计软件通过建立了回归方程,结合镇江市的实际进行了实证分析。研究表明R&D投入水平对高科技产业发展是正相关作用,且关系显著。在此基础上,提出了进一步加快发展科技基础设施建设的一系列建议。     

武汉市城市化进程中的环境效应分析

本文根据武汉市1989～2008年相关数据,选取非农人口比重(即城市化率)作为城市化指标;废水排放量、废气排放量、工业固体废弃物产生量等作为环境污染指标,运用回归模型对城市化率和环境污染指标分别进行耦合分析并建模,探究城市化进程对城市环境的影响,并基于研究结果分析,提出了促进武汉市城市经济与环境协调发展的对策建议.     

Mixture Models of Missing Data

This paper proposes a general framework for the analysis of survey data with missing observations. The approach presented here treats missing data as an unavoidable feature of any survey of the human population and aims at incorporating the unobserved part of the data into the analysis rather than trying to avoid it or make up for it. To handle coverage error and unit non-response, the true distribution is modeled as a mixture of an observable and of an unobservable component. Generally, for the unobserved component, its relative size (the no-observation rate) and its distribution are not known. It is assumed that the goal of the analysis is to assess the fit of a statistical model, and for this purpose the mixture index of fit is used. The mixture index of fit does not postulate that the statistical model of interest is able to account for the entire population rather, that it may only describe a fraction of it. This leads to another mixture representation of the true distribution, with one component from the statistical model of interest and another unrestricted one. Inference with respect to the fit of the model, with missing data taken into account, is obtained by equating these two mixtures and asking, for different no-observation rates, what is the largest fraction of the population where the statistical model may hold. A statistical model is deemed relevant for the population, if it may account for a large enough fraction of the population, assuming the true (if known) or a sufficiently small or a realistic no-observation rate.     

A refined parametric model for short term load forecasting

We present a refined parametric model for forecasting electricity demand which performed particularly well in the recent Global Energy Forecasting Competition (GEFCom 2012). We begin by motivating and presenting a simple parametric model, treating the electricity demand as a function of the temperature and day of the data. We then set out a series of refinements of the model, explaining the rationale for each, and using the competition scores to demonstrate that each successive refinement step increases the accuracy of the model’s predictions. These refinements include combining models from multiple weather stations, removing outliers from the historical data, and special treatments of public holidays.