知识密集型服务业集聚对经济增长的影响研究

文章在计算区位熵指数(Location Quotient)的基础上,根据经济增长理论和经济地理理论构建面板数据模型,运用广义矩估计(GMM)方法实证分析了中国2004-2012年24个省市的知识密集型服务业(KIBS)集聚对于经济增长的作用.实证结果显示:知识密集型服务业集聚与经济增长之间呈现出倒U型曲线关系,说明集聚能对经济增长产生正效应,但是集聚不适度时会对经济增长产生负效应.基于上述结论,提出了相应的政策建议.     

地方政府竞争对环境污染影响效应的实证研究

基于中国1998—2012年省际动态面板数据和通过改进后熵值法计算得到的环境污染综合指数,运用系统广义矩估计(GMM)实证地方政府竞争对环境污染的影响效应。结果表明:地方政府竞争对环境污染呈显著的正向影响,即地方政府竞争显著增加了地区污染排放,降低了区域环境质量。而经济发展水平、资本存量与环境污染均呈倒“U”形关系,经济发展短期会带来环境污染,长远则有助于环境质量的改善;资本存量决定了一个地方的投资能力,投资速度过猛或滞后均会给环境造成影响。认为,应从改革传统政绩考核办法、确立地方政府环境责任制度等方面优化地方政府竞争机制;并进一步加大地方政府环境治理投资力度,着力解决环境污染问题,从而提高环境质量。     

资源的跨区域错置和区域内错置——基于中国工业企业数据的实证研究

纠正资源的跨区域错置和区域内错置,提高配置效率,是促进区域经济快速、协调发展的重要课题。中国的资源错置主要表现为区域内错置,区域之间的配置相对区域内的配置更有效率。纠正各省内部的错置可使中国的TFP提高124%-164%,纠正各省之间的错置可使中国的TFP提高4%-18%。金融市场的发育、国有企业的改革能显著促进区域内资源配置的改善,政府干预市场、市场分割能显著提高资源错置程度,而劳动力流动性、FDI和进出口对区域内资源配置的改善作用并不显著。     

Estimation of Sparse Structural Parameters with Many Endogenous Variables

We apply the generalized method of moments–least absolute shinkage and selection operator (GMM-Lasso) (Caner, 2009) to a linear structural model with many endogenous regressors. If the true parameter is sufficiently sparse, we can establish a new oracle inequality, which implies that GMM-Lasso performs almost as well as if we knew a priori the identities of the relevant variables. Sparsity, meaning that most of the true coefficients are too small to matter, naturally arises in econometric applications where the model can be derived from economic theory. In addition, we propose to use a modified version of AIC or BIC to select the tuning parameter in practical implementation. Simulations provide supportive evidence concerning the finite sample properties of the GMM-Lasso.     

Does economic policy uncertainty affect bank earnings opacity? Evidence from China

Uncertainty about economic policy (EPU) in today's interconnected world and its impact worldwide is more significant than ever before. Thus, this study examines EPU's impact on the bank's earnings opacity of the Chinese banking industry, using the two-step system GMM estimator and the time covering 2011–2018. Our finding shows a negative and statistically significant relationship between EPU and bank earnings opacity, implying that the Chinese banking sector decreases earnings opacity in times of high EPU to earn trust and show good banks’ financial image. Moreover, our finding reveals that the effect of EPU on earnings opacity relies on the banks’ financial strength. This study recommends that a policy to reduce earnings opacity should be in place and also the supervisory capability and financial regulation should be strengthened. Moreover, the regulators should be more vigilant while making economic policies during high economic uncertainties.     

货币政策非对称性与惰性区域的识别和检验

在对货币当局政策偏好分析的基础上,构建更为一般的货币政策反应模型,用于识别名义利率对通胀缺口和产出缺口的非线性和非对称调整特征以及货币政策对通货膨胀和产出变化的惰性属性。采用7天期银行间同业拆借加权平均利率作为名义利率的代理变量,对上述货币政策反应模型进行广义矩估计,并对参数进行约束检验。研究结果表明,中国货币政策对通货膨胀的调整存在明显的惰性区域,即当通货膨胀率在目标通货膨胀率的较小范围内波动时,利率并未针对通货膨胀与目标通货膨胀率的偏离做出调整,而当通货膨胀率与目标通货膨胀率的偏离(即通胀缺口)超过惰性区域时,货币当局开始针对通胀缺口调整利率,并且随着通胀缺口的增大,利率对通货膨胀的反应越来越强烈,存在明显的非线性调整特征。     

国际贸易、产业结构对环境污染的影响——基于面板数据动态GMM模型

基于2000-2010年我国29个省级区域的面板数据,采用动态面板模型GMM估计方法,分析了国际贸易和产业结构对工业二氧化硫、工业废水、工业烟尘、工业粉尘等四类污染物的排放量的影响.实证结果显示,国际贸易程度的增加与工业二氧化硫、工业烟尘、工业粉尘三类污染物排放存在较强的正向影响而且都很显著,而有助于降低工业废水的排放但在统计结果上不显著.产业结构对四类污染物排放的影响都很显著,其中对工业二氧化硫和工业粉尘的排放起到了很好的抑制作用,而对工业废水和工业废气的排放起到了推动的作用.FDI与四类污染物存在明显的负相关,说明FDI有利于抑制污染物的排放,起到了降低环境污染的作用.另一方面,从弹性值来看,产业结构的弹性系数要大于国际贸易和FDI的系数,这说明国际贸易、FDI对环境的影响较小,而产业结构对环境的影响普遍较大.同时,加入收入这个控制变量显示环境Kuznets曲线在我国具有一定的适用性.     

农村金融区域发展差异及其影响因素

以全国29个省(市、自治区)2002—2011年的数据为基础,利用泰尔指数方法衡量了我国东、中、西三大区域的农村金融发展差异,并在此基础上运用面板数据模型,从区位发展因素、经济发展因素、政治因素和市场因素四个方面定量分析了影响差异形成的因素。研究表明:我国农村金融发展程度的地区差异显著,且区域内差异对总差异贡献较大;地区教育水平、地区商品交易效率、地区信息化水平、地区政策支持和金融市场交易效率对金融相关比率均有显著的正向影响,受农业的弱质性和农业资金外流的影响,地区经济发展水平对金融发展有微弱的反向作用;上一期的农村金融发展水平对本期的农村金融发展影响非常显著,这表明农村金融区域发展差异存在扩大的迹象。     

B-CAPM模型的GMM估计和检验

作为资本资产定价模型（CAPM）的发展之一,B-CAPM模型更适合于复杂多变的现实资本市场。本文首先分析从CAPM到B-CAPM的模型转化及其理论含义,然后迭代求出B-CAPM模型的零贝塔期望收益的极大似然估计值（MLE）,最后通过案例,实证运用GMM方法构建B-CAPM的估计和检验。结果表明,B-CAPM模型适用于证券市场收益和风险的度量以及有效性检验,GMM方法更符合实际。     

Adaptive Elastic Net for Generalized Methods of Moments

Model selection and estimation are crucial parts of econometrics. This article introduces a new technique that can simultaneously estimate and select the model in generalized method of moments (GMM) context. The GMM is particularly powerful for analyzing complex datasets such as longitudinal and panel data, and it has wide applications in econometrics. This article extends the least squares based adaptive elastic net estimator by Zou and Zhang to nonlinear equation systems with endogenous variables. The extension is not trivial and involves a new proof technique due to estimators’ lack of closed-form solutions. Compared to Bridge-GMM by Caner, we allow for the number of parameters to diverge to infinity as well as collinearity among a large number of variables; also, the redundant parameters are set to zero via a data-dependent technique. This method has the oracle property, meaning that we can estimate nonzero parameters with their standard limit and the redundant parameters are dropped from the equations simultaneously. Numerical examples are used to illustrate the performance of the new method.