基于DEA和SFA方法的中国省区灌溉用水效率比较研究

文章利用1997～2006年31个省区的面板数据,采用随机前沿分析(SFA)和数据包络分析(DEA)方法对中国宏观层面的灌溉用水效率进行了测度;在此基础上利用配对样本t检验和Spearman相关检验比较分析两类方法的效率估计得分。结果表明了虽然规模收益不变假设下的DEA效率值显著小于SFA效率估计值,但两种方法所测算的灌溉用水效率排名具有显著一致性。     

中国商业银行技术效率实证分析

目前国际上流行的测定商业银行效率的方法包括随机边界方法(SFA)、自由分布法(DFA)、厚边界方法(TFA)、数据包络分析(DEA)、自由可置壳(FDH).在国外针对研究商业银行效率所使用方法的一项统计中,在120多篇文章中,使用SFA方法的文章大约有20篇.本文拟应用SFA方法依据我国14家商业银行2000 2003年的面板数据进行极大似然估计,测定了14家商业银行的技术效率,并对影响商业银行效率的因素进行了分析.     

考虑外部环境与异质性前沿面的三阶段Window-DEA模型研究

三阶段DEA模型是一种效率度量方法,因其可以剔除环境因素和随机因素对效率测度的影响,得到越来越多学者的应用.由于跨期异质性前沿面的存在,传统三阶段DEA模型分析面板数据的结论值得商榷.文章通过引入Window-DEA模型和面板SFA模型,构建了同时考虑外部环境和异质性前沿面的三阶段Window-DEA模型.案例分析表明,该模型具有较强的可操作性,能够为准确的测度决策单元生产效率以及考察效率的时间演变特征提供方法工具.     

双效应面板ELES模型的构建与实证研究

本文在拓展ELES模型传统假设的基础上,将ELES模型推广到面板数据模型。构建同时包含时间效应和个体效应的双效应面板ELES模型,提出实证研究中模型形式的识别检验流程,并利用面板ELES模型实证研究了2002-2012年期间我国城镇居民消费结构的变动特征。     

空间动态面板模型的时间滞后效应检验

空间面板数据模型由于考虑了经济变量间的空间相关性,其优势日益凸显,已成为计量经济学的热点研究领域。将空间相关性与动态模式同时扩展到面板模型中的空间动态面板模型,不仅考虑了经济变量之间的空间相关性,还考虑了时间上的滞后性,是空间面板模型的发展,增强了模型的解释力。考虑一种带固定个体效应、因变量的时间滞后项、因变量与随机误差项均存在空间自相关性的空间动态面板回归模型,提出了在个体数n和时间数T都很大,且T相对地大于n的条件下空间动态面板模型中时间滞后效应存在性的LM和LR检验方法,其检验方法包括联合检验、一维及二维的边际和条件检验;推导出这些检验在零假设下的极限分布;其极限分布均服从卡方分布。通过模拟试验研究检验统计量的小样本性质,结果显示其具有优良的统计性质。     

基于SFA和DEA的中国低碳企业生产效率的比较

文章以2003～2009年37家低碳企业上市公司面板数据为基础,分别采用数据包络分析(DEA)和随机前沿分析(SFA)方法对中国低碳企业生产效率进行了测度;在此基础上利用配对样本T检验和Spearman相关检验对两种方法测度出的低碳企业生产效率值进行了对比分析,结果表明,两种方法测度出的低碳企业生产效率在数值有显著差异,DEA方法测算的生产效率均值明显低于SFA方法测算的生产效率均值,且在生产效率排序上也不具有显著的一致性。     

中国区域物流发展效率实证分析

文章借助随机前沿分析(SFA)的框架,采用First-difference面板数据建模技术,对不同区域的物流效率进行测度,对所得的各省市自治区的物流效率结果进行了横向和纵向的全面分析。结果表明,我国地区间的物流差距仍然较大,制约了我国整体物流水平的提高,但随着时间的推移,各省份物流效率差距在逐年缩小。     

基于SFA的我国企业集团财务公司成本效率评价

文章运用随机前沿分析(SFA)方法对我国企业集团财务公司成本效率进行了评价研究。结果表明:随机前沿模型适用于进行财务公司成本效率的测算,利用SFA模型进行财务公司成本效率测度更能反映实际情况。     

中国区域生产效率与经济发展差距研究

利用1998-2007年的省级面板数据,通过SFA模型利用超越对数函数估算了中国各省市区和三大区域历年的资本和劳动产出弹性、全要素生产率（TFP）水平及其效率变化,研究发现,东中西部的资本产出弹性大于劳动产出弹性。在此基础上对各省市区历年的全要素生产率水平进行了分析,结果表明,在1998-2007年间,东部的TFP增长率最高,中部地区高于西部地区。以上研究表明,TFP是造成区域社会经济发展差距扩大的主要因素之一。提高中西部全要素生产率生产效率和国家增加对中西部的投资可以缩小中国区域经济发展差异。     

面板数据双因素误差回归模型序列相关和随机效应的联合LM检验

对面板数据双因素误差回归模型构造了检验序列相关和随机效应的一种联合LM检验,发现该LM统计量也是检验联合假设H0：σμ^2=λ=0的Baltagi-Li LM统计量和检验假设H0：σv^2=λ=0的Breusch-Pagan-LM统计量之和。当面板数据的个体数N充分大时,该联合LM统计量的渐近分布是χ^2（3）分布;无论双因素误差面板数据回归模型的剩余误差项是AR（1）过程还是MA（1）过程,联合LM检验是相同的,即对随机效应和一阶序列相关的联合LM检验是独立于序列相关的形式。     

技术进步对中国能源利用效率影响机制研究

由于"回弹效应"的存在,对技术进步是否必然提高能源利用效率存在争议。本文在DEA-Tobit两阶段分析框架下研究技术进步对地区能源利用效率的影响。以中国29个省级行政单位为研究对象,采用DEA-Malmquist生产率法将技术进步分解为前沿型技术进步与追随型技术进步两类,通过构建面板数据的Tobit回归模型对技术进步在能源利用效率提升过程中的影响机制进行较为细致的研究,发现追随型技术进步对中国各地区能源利用效率施加了显著正向影响,而前沿型技术进步作用并不明显;影响中国地区能源利用效率的诸因素,其正向作用力度呈现出由东向西逐渐递减的态势。     

基于SFA的中国银行业成本效率实证研究

本文基于随机边界模型,假定成本误差项服从截断正态分布的前提下,估算我国18家银行2001-2007年的成本效率。结果显示我国商业银行成本效率总体偏低,经营绩效落后于美国银行业,且在观测期内没有明显改善;样本银行成本效率与资产规模等因素没有显著联系,国有银行平均效率水平与股份制银行大致持平,均低于合资银行;各银行成本效率随时间推移而趋同,集中化趋势明显。     

Testing for homogeneity in cross-lagged panel studies

Panel studies are statistical studies in which two or more variables are observed for two or more subjects at two or more points In time. Cross- lagged panel studies are those studies in which the variables are continuous and divide naturally into two effects or impacts of each set of variables on the other. If a regression approach is taken5 a regression structure Is formulated for the cross-lagged models This structure may assume that the regression parameters are homogeneous across waves and across subpopulations. Under such assumptions the methods of multivariate regression analysis can be adapted to make inferences about the parameters. These inferences are limited to the degree that homogeneity of the parameters Is 'supported b}T the data. We consider the problem of testing the hypotheses of homogeneity and consider the problem of making statistical inferences about the cross-effects should there be evidence against one of the homogeneity assumptions. We demonstrate the methods developed by applying then to two panel data sets.     

技术采纳对农业生产技术效率的影响效应分析——基于随机前沿分析与分位数回归分解

使用随机前沿分析方法研究了中国农业生产的技术效率,利用OLS和分位数回归及分解方法分析了技术采纳对中国农业生产技术效率的影响。结果发现:中国农业生产呈现出规模报酬递增的状态,但土地利用效率仍具提升空间;技术采纳对农业生产技术效率有一定的改善,而改善空间却局限于农业生产的规模;技术采纳所带来的农业生产技术效率提升作用会随着农业生产技术效率增加而逐渐被耗散,农业产出与技术采纳之间具有"刺猬效应"。     

中国全要素生产率重估——ACF模型中弹性估计改进和实证

索洛余额法、随机前沿生产函数法以及数据包络分析方法都没有解决函数的内生性和模型参数的时变性问题，ACF方法克服了这些局限性，对全要素生产率的测度更加准确。本文推导了参数的内生性和时变性问题，基于ACF模型提出了我国的时变参数估计方法，并对我国1990－2017年28个省份的全要素生产率进行重估。研究结果表明，ACF方法对全要素生产率的测度更加准确。从全国来看，资本投入增长对经济增长的贡献度最大，TFP增长对我国经济增长的贡献度正在逐渐下降，劳动投入对经济增长的贡献度相对较弱且波动大。分地区来看，各地区的TFP平均水平有所回落，近年来东北地区的TFP增长率水平最低，2012－2017年均为负值。同时，东北地区的劳动力流失情况较为严重。     

Estimating DEA confidence intervals with statistical panel data analysis

This paper describes a statistical method for estimating data envelopment analysis (DEA) score confidence intervals for individual organizations or other entities. This method applies statistical panel data analysis, which provides proven and powerful methodologies for diagnostic testing and for estimation of confidence intervals. DEA scores are tested for violations of the standard statistical assumptions including contemporaneous correlation, serial correlation, heteroskedasticity and the absence of a normal distribution. Generalized least squares statistical models are used to adjust for violations that are present and to estimate valid confidence intervals within which the true efficiency of each individual decision-making unit occurs. This method is illustrated with two sets of panel data, one from large US urban transit systems and the other from a group of US hospital pharmacies.     

Semiparametric Smooth Coefficient Stochastic Frontier Model With Panel Data

ABSTRACT

We investigate the semiparametric smooth coefficient stochastic frontier model for panel data in which the distribution of the composite error term is assumed to be of known form but depends on some environmental variables. We propose multi-step estimators for the smooth coefficient functions as well as the parameters of the distribution of the composite error term and obtain their asymptotic properties. The Monte Carlo study demonstrates that the proposed estimators perform well in finite samples. We also consider an application and perform model specification test, construct confidence intervals, and estimate efficiency scores that depend on some environmental variables. The application uses a panel data on 451 large U.S. firms to explore the effects of computerization on productivity. Results show that two popular parametric models used in the stochastic frontier literature are likely to be misspecified. Compared with the parametric estimates, our semiparametric model shows a positive and larger overall effect of computer capital on the productivity. The efficiency levels, however, were not much different among the models. Supplementary materials for this article are available online.     

Distribution of cost inefficiency in stochastic frontier approach: evidence from Spanish banking

The aim of the paper is to demonstrate the appropriateness of an a priori analysis to determine the distributional assumption of the inefficiency term in a stochastic frontier model. To this end, theoretical distributions of estimated inefficiency were obtained when the inefficiency term is assumed to be distributed as a half normal and an exponential in a cost frontier model. Comparisons of such theoretical distributions with the respective cost inefficiency estimators using the goodness of fit test allow selecting the most appropriate distributional assumption. The application on three data sets of Spanish banking system in 2009 demonstrated the relevance of the research question. First, the results of estimated cost inefficiency with a half normal assumption are larger than with an exponential distribution significantly. Besides, half normal assumption was rejected and exponential was not rejected as the most appropriate distribution of inefficiency term in Spanish banking data set. However, the adjustment of saving banks data had been better with the former distribution than the latter. In the case of banks, any distribution results appropriate. To sum up, this work demonstrate that the distributional assumption on inefficiency term in Stochastic Frontier Approach must be established in a justified way, as it can significantly bias the results of estimated inefficiency and therefore, influences improving policies and strategies in the Spanish banking sector.     

Models, assumptions and model checking in ecological regressions

Ecological regression is based on assumptions that are untestable from aggregate data. However, these assumptions seem more questionable in some applications than in others. There has been some research on implicit models of individual data underlying aggregate ecological regression modelling. We discuss ways in which these implicit models can be checked from aggregate data. We also explore the differences in applications of ecological regressions in two examples: estimating the effect of radon on lung cancer in the United States and estimating voting patterns for different ethnic groups in New York City.