The return to education and its distribution in urban China: evidence from quantile regression analysis

Based on Chinese Households Income Projects in 2002, this paper discusses the relationship between the return to education and the quantiles of income distribution. The findings in this paper show that the return to education is lower for the higher quantiles, while the estimators also depend on the choice of control variables. The methodology of the quantile regression might be helpful in adjusting the ability bias in the estimation on return to education. The policy implications of the paper highlight the impact of the education expansion in boosting the income growth for those in lower quantiles.     

Choosing propensity score matching over regression adjustment for causal inference: when,why and how it makes sense

Summary

This study identified when regression adjustment fails to adjust adequately for differences in observed covariates and where propensity score matching is the only alternative.

Multivariate analysis might fail to adjust for observed confounders if:

• 1. The means of the propensity scores in the two groups are more than one-half a standard deviation apart unless distributions of the covariates in both groups are nearly symmetric, sample sizes of the two groups are approximately the same and distributions of the covariates in the two groups have similar variances;

• 2. The ratio of the propensity score variances in the two groups is significantly different from one;

• 3. The ratio of residual variances in the two groups after adjusting for the propensity score is significantly different from one.

Conducted retrospective analysis showed that the treatment effect would be an estimated $305 (or 26%) less if the misspecified outcome model had been chosen.     

Anonymous social influence

We study a stochastic model of influence where agents have “yes” or “no” inclinations on some issue, and opinions may change due to mutual influence among the agents. Each agent independently aggregates the opinions of the other agents and possibly herself. We study influence processes modeled by ordered weighted averaging operators, which are anonymous: they only depend on how many agents share an opinion. For instance, this allows to study situations where the influence process is based on majorities, which are not covered by the classical approach of weighted averaging aggregation. We find a necessary and sufficient condition for convergence to consensus and characterize outcomes where the society ends up polarized. Our results can also be used to understand more general situations, where ordered weighted averages are only used to some extent. Furthermore, we apply our results to fuzzy linguistic quantifiers, i.e., expressions like “most” or “at least a few”.     

Entrepreneurial innovativeness and growth ambitions in thick vs. thin regional innovation systems

Research in economic geography has paid increasing attention to regional innovation systems (RISs) as a potential vehicle for growth and development. Yet despite an increasing amount of research studying RISs in particular and economic regions in general, we have limited knowledge about their influence on entrepreneurs and entrepreneurship. We respond to this knowledge gap and study if entrepreneurs’ localization in thick vs. thin RISs affects their innovativeness and growth ambitions. Thick RISs are predominately urbanized spaces that include organizations of higher-level education, R&D intensive milieus, and an ample industry sector, while thin RISs to a lesser degree encompass these features. Empirically, we analyse 870–917 entrepreneurial firms in Agder of Southern Norway. Based on trade and labour markets, as defined by the EU’s classification of local administrative units (LAU1), we identify two thick and six thin RISs in Agder. Econometric analyses show that entrepreneurs located in thick RISs are more innovative than entrepreneurs located in thin RISs, but there are no significant differences concerning entrepreneurs’ growth ambitions. In light of our findings, we discuss the potential agency role played by entrepreneurial firms at a micro level on path dependent features of RISs at a macro level.     

中国技术进步对能源效率影响的空间计量分析

利用探索性空间数据方法,运用空间滞后模型和空间误差模型对全域能源效率的影响因素进行估计,运用地理加权回归模型对局域能源效率的影响因素进行估计。结果表明:中国省域能源效率存在显著的空间相关性,全域层面的人力资本投入和外资技术溢出是促进能源效率提高的主要因素;从局域层面看,东北经济区的人力资本投入和产业结构调整对能源效率提高的贡献较大,而广东等南部地区省份的外商投资带来的技术溢出对能源效率提高的贡献最大。     

基于方差分解法的中国股市泡沫检验问题研究

基于理性投机泡沫理论,采用方差分解法对2005年5月到2012年9月上证综指是否存在泡沫以及泡沫的严重程度进行实证检验,并将检验结果同动态自回归法得到的结果进行比较。研究发现该方法能更有效地检测出我国股市中存在的严重投机性泡沫。     

安徽省主要城市工业用电效率及影响因素分析--基于DEA及Tobit两阶段模型

随着节约型社会的构建,安徽省不断加大对能源使用效率的监督和管理力度,为了明确安徽省近年来工业用电效率及其影响因素,采用数据包络及托宾回归模型对2004-2011年安徽省17个主要城市工业用电效率进行评价和分析。研究结果表明：（1）自2004年以来,安徽省主要城市工业用电效率一直处在上升阶段,但是与最优水平仍存在一定差距,同时还发现工业增加值与用电效率之间并不存在显著关系;（2）工业经济发达城市唯有依靠技术效率来提升用电效率,工业经济欠发达城市则需通过规模经济来实现用电效率的改善。（3）对外开放水平、节电意识、科技水平以及政府支出对工业用电效率有正向影响。     

考虑违约距离的上市公司危机预警模型研究

在上市公司财务危机预警中,违约距离起着重要的不可替代的作用,仅考虑财务指标并不足以完全解释企业财务危机发生的原因.文章应用Merton模型对2002～2004年ST公司和相应配对公司的危机发生之前的违约距离进行了研究,发现危机公司违约距离在危机发生前第三年明显低于正常公司的相应值,违约距离比传统财务指标能更早地预警到企业财务危机的发生.结合违约距离因素的危机预警模型能更明显地提高模型的危机判断正确率.     

服务业发展与人均收入的关系:基于分位数回归的实证研究

利用118个国家和地区1980-2005年服务业发展和人均收入的非平衡面板数据,采用分量回归的方法,在Fuchs的基础上对两者的关系进行研究。结果发现,服务业就业比重和人均GDP之间存在着显著并且稳定的正相关关系,服务业就业比重随着人均GDP的增加逐渐提高,这与Fuchs研究结论相同;与Fuchs不同的是,本文通过分位数回归还可以看出人均GDP的需求效应在服务业发展的不同阶段的影响程度的变化。在服务业发展的较低阶段,人均GDP的需求效应对服务业发展的作用较大;在服务业发展的较高阶段,人均GDP的需求效应对服务业发展的作用相对较小。     

中国股市波动与成交量动态关系研究——基于分位数回归的角度

研究股市波动与成交量之间的动态关系对于了解股市的信息传导机制与微观结构有重要意义.本文基于广义混合分布假说理论,利用分位数回归方法对中国股市上证综指1994年1月至2007年12月的资料进行实证研究,结果发现:中国股市波动具有长期的持续性,负向消息对股市波动的影响大于正向消息;成交量与股市波动之间呈现显著的正向关系,即较大(小)的波动伴随着较大(小)的交易量,且这种关系随着波动增加而逐渐增强,同时具有不对称的特点.相对于传统实证方法,分位数回归对二者的动态关系提供了更完整的描述,能够弥补以往研究的不足.