中国建筑业能源经济效率与能源环境效率研究——基于SBM模型和面板Tobit模型的两阶段分析

定义建筑业的能源经济效率和能源环境效率,对中国各省建筑业在2004-2011年期间的能源经济效率、能源环境效率及其分解指数进行测算分析,检验各种外部环境因素对能源效率的影响.研究结果表明:中国东部、中部和西部三大地区建筑业能源效率呈逐年上升的趋势,建筑业能源纯技术效率较低是制约我国建筑业能源效率上升的主要原因.中国应通过进一步规范建筑业市场、加大节能减排领域的技术创新力度、提高电力等清洁型能源的消费比重等措施来提高建筑业能源效率.     

Monte carlo evidence on the robustness of conditional moment tests in tobit and probit models

This paper numerically examines the size robustness of various conditional moment tests in misspecified tobit and probit models. The misspecifications considered include the incorrect exclusion of regressors, ignored heteroskedasticity and false distributional assumptions. An important feature of the experimental design is that it is based on an existing empirical study and is more realistic than many simulation studies. The tests are seen to have mixed performance depending on both the original null hypothesis being tested and type of misspecification encountered.     

On a tobit–Birnbaum–Saunders model with an application to medical data

The tobit model allows a censored response variable to be described by covariates. Its applications cover different areas such as economics, engineering, environment and medicine. A strong assumption of the standard tobit model is that its errors follow a normal distribution. However, not all applications are well modeled by this distribution. Some efforts have relaxed the normality assumption by considering more flexible distributions. Nevertheless, the presence of asymmetry could not be well described by these flexible distributions. A real-world data application of measles vaccine in Haiti is explored, which confirms this asymmetry. We propose a tobit model with errors following a Birnbaum–Saunders (BS) distribution, which is asymmetrical and has shown to be a good alternative for describing medical data. Inference based on the maximum likelihood method and a type of residual are derived for the tobit–BS model. We perform global and local influence diagnostics to assess the sensitivity of the maximum likelihood estimators to atypical cases. A Monte Carlo simulation study is carried out to empirically evaluate the performance of these estimators. We conduct a data analysis for the mentioned application of measles vaccine based on the proposed model with the help of the R software. The results show the good performance of the tobit–BS model.     

基于效率分解视角的林业专业合作社提质增效研究

提高林业专业合作社运行效率是实现林业高质量发展的重要途径。林业专业合作社运行效率包括经济效率、社会效率和交易效率。采用DEA-Tobit模型对林业专业合作社运行效率进行实证分析,研究发现:(1)林业专业合作社整体运行效率较低,这是规模效率和纯技术效率共同作用的结果。林业专业合作社的经济、社会与交易的效率值处于[0.25~0.35],纯技术效率值处于[0.55~0.75],规模效率值处于[0.35~0.45]。(2)外部环境因素对林业专业合作社运行效率具有显著影响。用外部环境变量对投入指标的松弛变量进行SFA回归,发现外部环境变量对不同类型林业专业合作社运行效率影响和作用路径差异显著。(3)林业专业合作社运行效率内部改进存在冲突,即组织资产总额、合作社股权制衡度、财务信息公开次数等指标对林业专业合作社运行效率内部改进存在冲突。因此,林业专业合作社要通过提高全要素生产率,统筹国际国内生产与分工格局,营造林业专业合作社良好的发展环境,利用双循环发展机遇提升林业专业合作社运行效率等措施来提质增效。     

改革开放以来中国服务业生产率实证分析

本文使用DEA-Malmquist生产率指数法测算了1978-2007年中国27个省份服务业全要素生产率(TFP)的变动。结果表明:中国服务业TFP总体呈下降态势,这主要源于技术进步率的倒退;与1978-1992年相比,1993-2007年服务业TFP的下降幅度增大;西部地区的下降幅度小于中、东部地区。服务业TFP不存在σ收敛,而存在绝对和条件β收敛,1992年后β收敛速度快于1992年之前的收敛速度。Tobit回归表明,城市化、消费需求和市场化对服务业TFP的提高有促进作用,而对外开放对其影响不显著。     

高端装备制造业技术创新资源配置效率及影响因素研究——基于两阶段StoNED和Tobit模型的实证分析

新常态下,高端装备制造业在推动国民经济稳定增长、加快传统工业转型升级、提升产业链核心竞争力的过程中,先导性和战略性作用日益凸出,但其技术创新资源配置的合理性和有效性却成为产业持续发展的主要瓶颈。本文从投入产出角度出发,基于价值链理论,将技术创新活动分为技术研发和技术转化两个阶段,并构建两阶段StoNED模型,采用2011-2014年的行业面板数据作为样本数据,对高端装备制造业技术创新资源配置效率进行测度和比较;以产业组织为视角,利用Tobit模型分析影响效率的关键因素。实证研究表明,我国高端装备制造业技术创新资源配置的整体和阶段效率在子行业间存在不同程度的波动和差异,技术研发阶段效率偏低制约着整体效率的最优化;甄别影响因素发现,企业规模对技术研发阶段效率具有负向作用,对整体和技术转化阶段效率具有正向作用;市场垄断不利于整体和技术转化阶段效率的提升;政府支持对整体和两阶段效率均具有负面影响。在此基础上,进一步提出应对产业技术创新资源配置现状的对策建议。     

Efficient Semiparametric Estimation of Censored and Truncated Regressions via a Smoothed Self‐Consistency Equation

An asymptotically efficient likelihood‐based semiparametric estimator is derived for the censored regression (tobit) model, based on a new approach for estimating the density function of the residuals in a partially observed regression. Smoothing the self‐consistency equation for the nonparametric maximum likelihood estimator of the distribution of the residuals yields an integral equation, which in some cases can be solved explicitly. The resulting estimated density is smooth enough to be used in a practical implementation of the profile likelihood estimator, but is sufficiently close to the nonparametric maximum likelihood estimator to allow estimation of the semiparametric efficient score. The parameter estimates obtained by solving the estimated score equations are then asymptotically efficient. A summary of analogous results for truncated regression is also given.     

Asymptotic properties of a quast-maximum likelihood estimator in truncated regression model with serial correlation

Robinson (1982a) presented a general approach to serial correlation in limited dependent variable models and proved the strong consistency and asymptotic normality of the quasi-maximum likelihood estimator (QMLE) for the Tobit model with serial correlation, obtained under the assumption of independent errors. This paper proves the strong consistency and asymptotic normality of the QMLE based on independent errors for the truncated regression model with serial correlation and gives consistent estimators for the limiting covariance matrix of the QMLE.     

环境约束下城市全要素能源效率的变动分解——基于三阶段DEA-malmquist指数的实证分析

中国城市全要素能源效率在考虑环境因素前后具有明显的差异,调整后的malmquist指数普遍低于调整前的值;环境约束下的城市全要素能源效率增量具有沿海城市上升、内陆城市下降的特征;收敛性分析表明沿海城市趋于增强,内陆城市趋于恶化.     

The Monte Carlo EM method for estimating multivariate tobit latent variable models

We propose a multivariate tobit (MT) latent variable model that is defined by a confirmatory factor analysis with covariates for analysing the mixed type data, which is inherently non-negative and sometimes has a large proportion of zeros. Some useful MT models are special cases of our proposed model. To obtain maximum likelihood estimates, we use the expectation maximum algorithm with its E-step via the Gibbs sampler made feasible by Monte Carlo simulation and its M-step greatly simplified by a sequence of conditional maximization. Standard errors are evaluated by inverting a Monte Carlo approximation of the information matrix using Louis's method. The methodology is illustrated with a simulation study and a real example.