ML– and semiparametric estimation in logistic models with incomplete covariate data

ML–estimation of regression parameters with incomplete covariate information usually requires a distributional assumption regarding the concerned covariates that implies a source of misspecification. Semiparametric procedures avoid such assumptions at the expense of efficiency. In this paper a simulation study with small sample size is carried out to get an idea of the performance of the ML–estimator under misspecification and to compare it with the semiparametric procedures when the former is based on a correct assumption. The results show that there is only a little gain by correct parametric assumptions, which does not justify the possibly large bias when the assumptions are not met. Additionally, a simple modification of the complete case estimator appears to be nearly semiparametric efficient.     

An effective going concern prediction model for the sustainability of enterprises and capital market development

The purpose of this study is to construct a two-stage effective and innovative going concern prediction model to predict going concern doubt for the sustainability of enterprises and capital market development. Samples of this study are the companies listed on the Taiwan Stock Exchange or the Taipei Exchange, totalling 196 companies and including 49 companies with going concern doubt and 147 normal companies (with no going concern doubt). The data are taken from the Taiwan Economic Journal (TEJ) and the Market Observation Post System during the period from 2001 to 2016 (totalling 16 years). This study adopts a two-stage way to construct the going concern prediction models. In Stage I, the traditional statistical method of stepwise regression (SR) and the data mining technique artificial neural network (ANN) are applied to select the important variables. In Stage II, two decision tree algorithms (data mining techniques): classification and regression tree (CART) and C5.0 are used to establish the prediction models. The results show that the SR + CART model has the highest going concern prediction accuracy, with an overall accuracy of 87.42%.     

股权分置改革受限股份流通次序

本文采用分量回归模型．具体研究国有股权对不同业绩水平上市公司影响程度的差异。结论表明．国有股权对公司业绩具有负面影响，且对不同业绩水平上市公司的影响程度存在明显差异．业绩越好的公司，国有股权带来的负面影响越严重。因此，基于市场承受能力的限制．从提高市场整体效率的角度出发．政府在股权分置改革第二阶段．安排受限股份上市流通时．应该考虑首先安排业绩好的上市公司的受限股份优先进入流通。实证分析结果还验证了现阶段我国市场上规模经济效应的存在。     

Bayesian assessment of dimensionality in reduced rank regression

We consider Bayesian inference about the dimensionality in the multivariate reduced rank regression framework, which encompasses several models such as MANOVA, factor analysis and cointegration models for multiple time series. The fractional Bayes approach is used to derive a closed form approximation to the posterior distribution of the dimensionality and some asymptotic properties of the approximation are proved. Finite sample properties are studied by simulation and the method is applied to growth curve data and cointegrated multivariate time series.     

中国电子商务企业生存的实证分析

本文通过Logisitc回归模型，对电子商务企业生存的影响因素进行了分析。笔者认为，电子商务企业的生存是受企业自身基因构成决定的，而电子商务企业的基因构成包括了企业家才能、资金、信息资本、人力资本、社会资本和技术资本。同时，企业的基因会随着环境的变化而不断地进行着调整和整合，以适应竞争的需要。实证分析的结果证实了笔者的判断。     

城市公交行业顾客满意度测评及其提升对策——以合肥市为例

城市公交作为城市经济运转的动脉,已经成为国内城市发展规划中的重中之重。然而,目前在城市公交行业占主体地位的国有公交企业却亟待提高营运效益,增强企业活力,以摆脱经营上的困境。立足于安徽省省会城市合肥市的公交行业,通过实证研究与规范研究相结合的方式,针对城市公交行业的顾客满意度测评及其提升对策问题进行了较为深入的探讨。     

A Semiparametric Method for Valuing Residential Locations: Application to Automated Valuation

This paper is motivated by automated valuation systems, which would benefit from an ability to estimate spatial variation in location value. It develops theory for the local regression model (LRM), a semiparametric approach to estimating a location value surface. There are two parts to the LRM: (1) an ordinary least square (OLS) model to hold constant for interior square footage, land area, bathrooms, and other structural characteristics; and (2) a non-parametric smoother (local polynomial regression, LPR) which calculates location value as a function of latitude and longitude. Several methods are used to consistently estimate both parts of the model. The LRM was fit to geocoded hedonic sales data for six towns in the suburbs of Boston, MA. The estimates yield substantial, significant and plausible spatial patterns in location values. Using the LRM as an exploratory tool, local peaks and valleys in location value identified by the model are close to points identified by the tax assessor, and they are shown to add to the explanatory power of an OLS model. Out-of-sample MSE shows that the LRM with a first-degree polynomial (local linear smoothing) is somewhat better than polynomials of degree zero or degree two. Future applications might use degree zero (the well-known NW estimator) because this is available in popular commercial software. The optimized LRM reduces MSE from the OLS model by between 5 percent and 11 percent while adding information on statistically significant variations in location value.     

关系型借贷与中小企业融资的实证分析

本文通过一个计量经济学模型来检验企业贷款是否存在关系型借贷,结果发现:大型企业的确存在关系型借贷行为,且对企业的贷款量有显著性影响;中小企业关系型借贷对于贷款量的影响较小,且并不明显。原因可能是商业银行在审批中小企业贷款时,注重对“硬”信息的考察,同时中小企业并没有同某一家或几家商业银行保持长期关系。为改善中小企业融资状况,商业银行应建立起一套完整的信用记录体系,并实现信息共享,在贷款过程中增强对“软”信息的考察,积极培育一批资质较好的中小企业客户并建立密切的联系;中小企业则应该规范财务制度并增强财务信息的透明度,同银行建立长期关系。     

我国商业银行业公司治理结构与经营绩效的实证研究

通过对8家股份制商业银行的公司治理结构与经营绩效的关系做回归分析,结果显示:经营绩效与董事会规模正相关;与第一大股东持股比例负相关;与前5大股东控制权分散度正相关。因此,国有商业银行应当适度增大董事会规模、明晰产权关系、强化监事会职能、加强管理层激励与信息透明度。     

基于VAR模型的山东省经济增长波动分析

本文通过建立向量自回归模型,运用脉冲响应函数和预测方差分解的方法对山东省经济增长的波动情况进行了实证分析。研究结果表明:各变量对山东经济增长的影响均不太明显。这说明山东经济一直保持稳定快速发展的势头。