能源化工产业高级化与经济增长——兼论能源化工产业最优匹配

能源化工产业是重要的基础性产业，现阶段对能源化工产业高级化及其对经济增长影响研究的成果还较少。文章首先将能源化工产业分为能源开采业、能源加工业和化工产业三大产业，测算能源化工产业高级化水平，结果表明能源资源禀赋导致了能源化工高级化水平的“低端锁定”，能源富集区能源产业高级化水平远远低于非能源富集省份，能源化工产业空间错配现象突出。其次，实证检验能源化工产业高级化对经济增长的影响，结果表明提高能源化工高级化水平能够显著促进经济增长，且不同产业规模的能源化工产业高级化对经济增长的影响存在差异性。再次，采用滚动回归方法检验随着能源化工产业高级化水平和产业结构变动，能源化工产业高级化水平对经济增长影响的变动状况，探讨能源化工产业内部最优匹配问题，结果表明能源化工产业高级化水平在1.05-1.15之间、能源开采业占能源化工产业比重在0.20-0.40之间，能源化工产业高级化对经济增长的促进效应最大。最后提出优化能源富集区能源化工产业匹配度、促进化工产业富集区新产品和新技术研发以及缓解能源化工产业空间错配等方面的政策建议。     

养老保险可携带性、农村劳动力流动与农村反贫困

本文在三部门经济框架下拓展了Harris和Todaro(1970)关于劳动力流动及其经济与社会影响的H-T模型,对养老保险可携带性影响农村劳动力流动的收入增长效应和贫富调节机制开展了理论及实证研究。结果显示:经济发展水平和产业层级在地区之间的梯度分化与城乡之间高达1.9~2.6倍的收入差距,是农村劳动力向城镇流动以及在不同城镇之间跨区流动的根本原因。养老保险可携带性是通过改变流动成本和流动收益影响农村劳动力的流动效率和流动方向,具有显著的收入增长效应和贫富调节作用。提高养老保险可携带性在2000—2019年间可使农村劳动力收入提高 35%以上,并可使城乡劳动 力收入差距减少15%~34%。有力地验证了《城镇企业职工基本养老保险关系转移接续暂行办法》在城乡协同发展、增加农民收入和缩小城乡贫富差距中的积极作用及其进一步完善的必要性和方向。     

我国男女两性老龄人口死亡率联合建模与预测

老龄人口死亡率建模和预测是长寿风险度量和养老金风险管理的基础。在我国,退休年龄及以上老龄人口死亡数据稀少,随机波动大,构建能够捕捉老龄人口死亡率随性别、年龄和时间变动的动态预测模型成为难题。本文采用Logistic两人口死亡率模型研究我国老龄人口死亡率的建模与预测。首先,运用死亡率数据质量较好的我国台湾地区数据,对模型结构进行选择,并检验模型的稳健性和预测性能。其次,基于我国大陆地区死亡率数据对模型结构进行二次验证和选择,应用所选模型对大 陆地区老龄死亡率进行建模和预测。结果显示,对于我国男女老龄死亡率的拟合和预测,Logistic 两人口模型均优于单人口CBD模型。最后,运用Logistic两人口死亡率模型对死亡率在年龄和时间两个维度上外推和预测,计算出时期和队列老龄人口分年龄的预期余寿,为养老金精算评估和长寿风险分析提供更准确的数据支持。     

中国区域经济差异空间分异特征及其机理研究

运用全局空间自相关指数、局部空间自相关指数和空间回归模型,从空间依赖性和异质性的角度分析中国区域经济差异空间分异的过程。研究发现:中国经济发达地区和欠发达地区空间集聚格局日趋显著,且东部和中西部区域分别演变成为经济发达地区和欠发达地区的相对集聚区。造成这一分异现象的成因是各种内生因子和宏观经济环境因子的区域间差异及其循环累积作用、空间自相关性的空间近邻效应及极化——涓滴效应。     

The combined dynamically weighted modified maximum likelihood estimators of the location and scale parameters

In this study, two new types of estimators of the location and scale parameters are proposed having high efficiency and robustness; the dynamically weighted modified maximum likelihood (DWMML) and the combined dynamically weighted modified maximum likelihood (CDWMML) estimators. Three pairs of the DWMML and two pairs of the CDWMML estimators of the location and scale parameters are produced, namely, the DWMML1, the DWMML2 and the DWMML3, and the CDWMML1 and the CDWMML2 estimators, respectively. Based on the simulation results, the DWMML1 estimators of the location and scale parameters are almost fully efficient (under normality) and robust at the same time. The DWMML3 estimators are asymptotically fully efficient and more robust than the M-estimators. The DWMML2 estimators are a compromise between efficiency and robustness. The CDWMML1 and CDWMML2 estimators are jointly very efficient and robust. Particularly, the CDWMML1 and CDWMML2 estimators of the scale parameter are superior compared to the other estimators of the scale parameter.     

京津冀产业转型升级测度及其经济效应研究

文章基于2004—2017年京津冀时间序列数据,采用超前系数、Moore值和Lilien指数等指标对京津冀产业结构变化进行测度,在此基础上运用Shift-Share模型从要素生产率中分解出产业结构变化,以衡量产业转型升级的经济效应。结果表明:(1)京津冀地区第一、二产业滞后发展,第三产业超前发展,整体处于产业转型升级过程中。(2)京津冀地区产业转型升级速度排序为北京市>天津市>河北省,三大区域内部差异较大。(3)北京市TS值呈逐年攀升状态,而天津市和河北省的TS值自2014年后才缓慢上升,北京市产业转型升级高级化明显优于天津市和河北省。(4)北京市劳动生产率增长率的提高不同于天津市和河北省,北京市总结构效应是促进劳动生产率增长的主要因素,而天津市和河北省的劳动生产率增长率的推动力是内增长效应。     

中国科技活动核算体系的范式设计及理论阐释

科技活动、科技创新是社会进步、经济发展的重要动力,构建中国科技活动核算体系（CSSTAA）,对国家科技活动状况和成果进行测度分析,有重要的理论意义和实践意义。中国科技活动核算体系的理论基础是统计学理论方法、经济合作与发展组织（OECD）发布的《弗拉斯卡蒂手册2015》（FM2015）。本文讨论了中国科技活动核算体系的重要概念和范畴,设计了其账户和核算表谱系的一般式,提出要要在核算中加强分析指标体系和核算方法的设计,加强对创新活动的测度评价,要建立科技活动统计数据库,对接中国新国民经济核算体系。     

中国省域创新创业环境评价指标体系的构建研究——对全国31个省级单位的测评

围绕创新创业环境的内涵,梳理了影响创新创业环境的六类主要因素,归纳潜在指标;对各潜在指标进行"聚类—因子—权重"综合分析,提炼影响创新创业环境的主要因子,构建出以6个一级指标和20个二级指标为核心的创新创业环境评价指标体系,并建立评价模型。以中国各省为样本,对全国31个省级单位的创新创业环境在2014年的状况进行测评排序。依据各省创新创业环境综合得分情况,得出全国31省2014年创新创业环境的地理空间分布图。分地区评价结果显示,东部地区创新创业环境具有明显优势,中部、东北和西部地区发展空间较大。从准则层指出各个地区优化创新创业环境的着力点。     

制造业与生产性服务业耦合能否促进空间协调——基于285个城市数据的检验

产业空间协调发展兼有产业关联与空间关联的特征,空间集聚与空间转移具有实现产业协调与区域协调的二重协调作用。本文基于中国285城市2003—2016年数据,采用耦合协调度模型和空间面板杜宾模型验证制造业与生产性服务业协调发展所带来的空间协调发展问题。耦合协调度模型得到年度制造业与生产性服务业处于良好协调发展区间,城市制造业与生产性服务业耦合协调度较低,67.37%的城市处于濒临失调衰退区间与勉强协调发展区间。空间面板杜宾模型得到制造业与生产性服务业协调发展的正向溢出作用促进了区域协调发展,空间集聚与空间转移的作用机制具有非线性特征,对本地产业协调发展具有先弱化后增强的作用,但对相邻地区产业协调发展具有一定的虹吸效应。因此,建议增强产业与空间的系统性,强化产业空间集聚与空间转移的资源配置能力,发挥产业耦合协调作用促进空间协调发展。     

Central composite designs for estimating the optimum conditions for a second-order model

Central composite designs which maximize both the precision and the accuracy of estimates of the extremal point of a second-order response surface for fixed values of the model parameters are constructed. Two optimality criteria are developed, the one relating to precision and based on the sum of the first-order approximations to the asymptotic variances and the other to accuracy and based on the sum of squares of the second-order approximations to the asymptotic biases of the estimates of the coordinates of the extremal point. Exact and continuous central composite designs are introduced and in particular designs which place no restriction on the pattern of the weights, termed benchmark designs, and designs which comprise equally weighted factorial and equally weighted axial points, termed axial-factorial designs, are explored. Algebraic results proved somewhat elusive and the requisite designs are obtained by a mix of algebra and numeric calculation or simply numerically. An illustrative example is presented and some interesting features which emerge from that example are discussed.     

IG-symmetry and R-symmetry: Interrelations and applications to the inverse Gaussian theory

The two parameter inverse Gaussian (IG) distribution is often more appropriate and convenient for modelling and analysis of nonnegative right skewed data than the better known and now ubiquitous Gaussian distribution. Its convenience stems from its analytic simplicity and the striking similarities of its methodologies with those employed with the normal theory models. These, known as the G–IG analogies, include the concepts and measures of IG-symmetry, IG-skewness and IG-kurtosis, the IG-analogues of the corresponding classical notions and measures. The new IG-associated entities, although well defined and mathematically transparent, are intuitively and conceptually opaque. In this paper, we first elaborate the importance of the IG distribution and of the G–IG analogies. Then we consider the IG-related root-reciprocal IG (RRIG) distribution and introduce a physically transparent, conceptually clear notion of reciprocal symmetry (R-symmetry) and use it to explain the IG-symmetry. We study the moments and mixture properties of the R-symmetric distributions and the relationship of R-symmetry with IG-symmetry and note that RRIG distribution provides a link, in addition to Tweedie's Laplace transform link, between the Gaussian and inverse Gaussian distributions. We also give a structural characterization of the unimodal R-symmetric distributions. This work further expands the long list of G–IG analogies. Several applications including product convolution, monotonicity of power functions, peakedness and monotone limit theorems of R-symmetry are outlined.     

On the finite sample performance of exogeneity tests of revankar, revankar and hartley and wu-hausman

In this paper we compare the performance of the exogeneity tests of Revankar, Revankar and Hartley and Wu-Hausman for the cases of two and three included endogenous variables. The distribution and power functions are evaluated using the conditional distributions given in Kariya and Hodoshima. Our results indicate that the Revankar's test is the most powerful for large values of the concentration parameter and the Revankar and Hartley test is the most powerful for small values of the concentration parameter.     

计量经济学和统计学视角下的线性回归模型——再议线性回归模型的设定

从属性、构建方法及意义等方面,分析研究线性回归模型在计量经济学和统计学两学科视角下的差异,并根据这种差异进一步提出回归模型的基本设定思路。研究表明:识别这种差异是完成模型设定工作的基础性和必要性举措,有助于实现线性回归模型的正确设定。以经典例证对计量经济学和统计学回归模型在应用中的区别以及模型设定问题进行进一步展示和分析。     

中国区域嵌入全球价值链的碳排放转移效应研究

本文将区域投入产出表嵌入全球投入产出表并构建相应的碳排放账户,利用投入产出模型和结构分解分析方法,试图从价值链渠道、区域（国别）流向、部门结构和影响因素等角度解释中国各区域国内-外贸易的增加值排放转移效应。结果表明,国内贸易的增加值排放转入主要通过国内价值链实现并且以中间品贸易为主,而国际价值链对于对外贸易增加值排放转入的贡献程度更大;国内增加值排放转入主要流向沿海地区和中部地区,国外增加值排放转入主要流向美国、欧盟、日本等发达经济体;入世后,碳排放强度和增加值系数的下降有助于降低国内-外贸易增加值排放转入,而需求结构和需求规模的变动效应则相反。本文结论对于如何协调国内-国际分工、调整国内产业和减排布局,有效促进区域间平衡发展和外贸发展方式转型升级具有重要的政策启示。     

中国国家价值链：区域关联特征与增加值收益变化

本研究通过1997、2002、2007、2012年中国区域间投入产出表,从中间品关联、增加值关联、投入产出关联三方面的视角度考察了中国8大区域间的国家价值链（NVC）现状及其演变趋势,并测算了不同地区参与NVC的增加值收益变化。研究发现,无论是中间品关联,还是增加值关联,中国8大区域间的关联程度总体呈现上升趋势,当然,不同地区也呈现分化现象：西北、京津、中部地区的国内中间品关联指数更高一些,而东北与东南沿海地区的该指数更低一些;京津、西北地区的增加值后向关联指数较大,而中部地区与北部沿海地区的增加值前向关联指数较大。从投入产出关联视角看,中国8大区域的上游度指数与下游度指数在1997年时均超过2,而且1997-2012年间,更多地区的上、下游度指数呈现上升态势。当然,从区域的角度考察,中国国内价值链不具有明显的“微笑曲线”特征。从参与NVC的增加值获益率上看,则是内陆地区普遍高于沿海地区,但随着参与GVC程度的增加,各地区从参与NVC的增加值获益率有下降的趋势。     

Statistical analysis of firm interdependence using duration data—parametric approach

A pioneer first enters the market as the monopolist and later experiences the competition when a similar product is brought to the market by the competitor. In 2012, Wang and Xie suggested to decompose the pioneer survival to “monopoly” and “competition” durations and estimate the two survivals of the pioneer individually with the competitor's survival via regression analysis. In their article, several regression analyses were performed to study the effect of order entry to the pioneer and the later entrant in different market status. Using the same datasets from their study, our main interest is to investigate the interdependent relationship between two competitive firms and study whether the market pioneer and the later entrant can benefit from the competition. The major contribution of this article is that the interdependence between two competitive firms is explicitly expressed and three survival durations can be estimated in one model. The proposed method relates the survival times of two competitive firms to pioneer's monopoly time and some observable covariates via proportional hazard model, and incorporates frailty variables to capture the interdependence in the competition. This article demonstrates a new method that formulates the interdependence between competitive firms and shows data analyses in the industries of newspapers and high technology.     

联合均值与方差模型的统计诊断

研究了联合均值与方差模型,考虑了基于数据删除模型的参数估计和统计诊断,比较删除模型与未删除模型相应统计量之间的差异。首次提出了基于联合均值与方差模型的诊断统计量和局部影响分析。通过模拟研究和实例分析,给出了不同的诊断统计量来判别异常点或强影响点,研究表明提出的理论和方法是有用和有效的。     

中国商业银行盈利能力的实证分析

商业银行盈利能力的大小是衡量其效率高低的主要指标。近年来,理论界从商业银行的规模经济、成本效率来研究中国商业银行效率的文献较多,而对中国商业银行盈利能力的研究则较少。对中国14家商业银行1994-2003年期间的盈利能力进行财务指标对比分析,发现中国四大国有商业银行的ROE、ROA明显低于10家股份制商业银行;利用计量经济学方法对中国商业银行的盈利能力与市场结构、银行产权性质关系进行回归分析,结果发现中国商业银行的盈利能力与其存款市场份额、存款资产比之间存在负相关关系,与其银行产权性质存在正相关关系。因此,建立和完善中国商业银行法人治理结构是提高其盈利能力的关键。     

A comparative study for robust canonical correlation methods

The aim of this study is to obtain robust canonical vectors and correlation coefficients based on the percentage bend correlation and winsorized correlation in the correlation matrix and fast consistent high breakdown (FCH), reweighted fast consistent high breakdown (RFCH), and reweighted multivariate normal (RMVN) estimators to estimate the covariance matrix and then compare these estimators with the existing estimators. In the correlation matrix of canonical correlation analysis (CCA), we present an approach that substitutes the percentage bend correlation and the winsorized correlation in place of the widely employed the Pearson correlation. Moreover, we employ the FCH, RFCH, and RMVN estimators to estimate the covariance matrix in the CCA. We conduct a simulation study and employ real data with the objective of comparing the performance of the different estimators for canonical vectors and correlation with that of our proposed approaches. The breakdown plots and independent tests are employed as differentiating criteria of the robustness and performance of the estimators. Based on our computational and real data studies, we propose suggestions and guidelines on the practical implications of our findings.     

Some state space models of hiv epidemic and its applications for the estimation of hiv infection and incubation

In this paper we have developed some state space models for the HIV epidemic for populations at risk for AIDS. By using these state space models, we have developed a general Bayesian procedure for estimating simultaneously the unknown parameters and the state variables. The unknown parameters include the immigration and recruitment rates, the death and retirement rates, the incidence of HIV infection ( and hence the HIV infection distribution ) and the incidence of HIV incubation ( and hence the HIV incubation distribution). The state variables are the numbers of susceptible people (S people), HIV-infected people (I people) and AIDS incidence over time. The basic approach is through multi-level Gibbs sampler combined with the weighted bootstrap method. We have applied the methods to the Swiss AIDS homosexual and IV drug data to estimate simultaneously the unknown parameters and the state variables. Our results show that in both populations, both the HIV infection and HIV incubation have multi-peaks indicating the mixture nature of these distributions. Our results have also shown that the estimates of the death and retirement rates for I people are greater than those of S people, suggesting that the infection by HIV may have increased the death and retirement rates of the individuals.