户籍制度扭曲及放松对经济的影响:理论与实证

户籍制度是我国劳动力流动的主要障碍.那么,当前我国的户籍扭曲程度几何?户籍制度放松对经济又会有怎样的影响?对这些问题的回答将有助于政府评估户籍制度改革的空间和经济效益.文章在Hansen和Prescott(2002)的两部门劳动力流动模型基础上,将工人分为农业和非农户口,引入户籍扭曲因子,构建两部门两类工人的户籍扭曲模型;然后,使用1984?2013年宏观经济数据度量户籍扭曲程度,并对2013年我国户籍制度逐渐放松过程中经济变量的变化进行模拟;最后,文章建立了包含"农业与非农"和"本地与外地"户籍差异的省份异质性户籍扭曲模型.研究表明:(1)经济和户籍制度改革的不同步导致了1984?2013年我国户籍扭曲程度呈现倒"U"形变化,且相较于韩国尚有较大的改善空间;(2)以韩国为参照,若2013年我国户籍制度完全放开,经济达到均衡时,农业部门和非农部门的就业人数将分别下降58.83%和上升26.92%,工资率将分别上升19.44%和下降6.77%,社会增加值将增长15.33%,这说明社会经济效率将得到提升,贫富差距将缩小.文章丰富和完善了户籍扭曲的理论模型,从减少劳动力流动摩擦的视角为政府制定相关政策提供了参考.     

Transmission of information within transnational social networks: a field experiment

Several studies have shown a relationship between the stocks of migrants and country-level investment in the home country; however the mechanism through which this relationship operates is still unexplored. We use a field experiment in which participants who are recent immigrants send information about risky decisions to others in their social network in their home country. The results demonstrate how this information influences decisions in the home country. We find that the advice given by family members and decisions made by friends significantly affects an individual’s risky decision-making.     

智能制造有利于增加企业技术创新投入吗——基于智能制造试点的准自然实验

智能制造是我国制造业转型升级的主攻方向,而如何准确客观评价智能制造的实施效果成为亟待解决的问题.从技术创新投入视角,将智能制造试点政策实施视为一次准自然实验,采用2011-2019年制造业上市企业面板数据,通过PSM-DID方法研究智能制造对企业技术创新投入的影响.研究结果表明,智能制造显著影响企业技术创新投入,即通过提升客户集成度、供应商集成度进而提高企业技术创新投入,且促进作用仅发生在民营企业和非高新技术行业中.该发现扩展了现有研究外延,同时,为解决当前国际困局和促进智能制造的持续推广提供了重要实践价值.     

Financial Instruments and Promotional Banking in the EU are Growing — But is this Justified?

Institutions and the European Investment Bank are at the forefront of EU investment policy. Their role is expanding and it is now a widely-held position that an improvement in the economy will not eliminate the need for their intervention. The proposals for the 2021–2027 MFF launch more financial instruments and present ‘InvestEU’ as a larger more powerful version of the European Fund for Strategic Investments (EFSI). However, promotional banking is often misunderstood and so is the actual size of promotional banking in Europe in which InvestEU will operate.     

Characterization of the Row Geometric Mean Ranking with a Group Consensus Axiom

An axiomatic approach is applied to the problem of extracting a ranking of the alternatives from a pairwise comparison ratio matrix. The ordering induced by row geometric mean method is proved to be uniquely determined by three independent axioms, anonymity (independence of the labelling of alternatives), responsiveness (a kind of monotonicity property) and aggregation invariance, which requires the preservation of group consensus, that is, the pairwise ranking between two alternatives should remain unchanged if unanimous individual preferences are combined by geometric mean.     

Fixed-Term Contracts and Labor Market Duality in France

The French labor market is segmented between permanent and temporary workers. The second category has difficulty in getting an open-ended contract. This paper aims at depicting workers on short-term contracts and shows the consequences on their professional career are negative and significant. A large part of the wage gap between permanent and temporary workers remains unexplained by observable characteristics. They receive less on-the-job training and their likelihood of obtaining a stable job is lower than 30% after 1 year and a half. They have also a higher probability of being the adjustment variable in case of an economic negative shock. These different findings show the importance of using public policies to encourage transitions from fixed-term to permanent employment and reducing labor-market duality.     

A New Regulatory Paradigm for the Digital Sector in Europe

The new regulatory framework in the digital sector in Europe is likely to fall short of expectations. A fragmented digital market with insuffi cient incentives for investment is the probable outcome. European regulators should abandon their approach in favour of a new and more flexible set of ideas discussed in this paper.     

Crowdsourcing-based semantic relation recognition for natural language questions over RDF data

ABSTRACT

Natural language query systems over RDF data need to rely on the semantic relations in query. First, we propose the new crowdsourcing model that used to produce semantic relations dataset. The model not only inherits completeness of the iterative model and accuracy of the parallel model, but also saves human resources. Second, we mine the rules of semantic relation recognition from the correlations between dependency structures and semantic relations. Third, we propose an algorithm of semantic relation recognition for natural language query over RDF data, and experiments demonstrate that it can recognize more semantic relations than existing methods.