房产税能否抑制实体经济"脱实向虚"——来自上海和重庆的经验分析

本文利用我国35个大中城市2006-2018年的平衡面板数据,基于上海和重庆在2011年实施的房产税试点政策,运用合成控制法检验房产税政策能否抑制实体经济"脱实向虚"发展的趋势.研究结果显示,房产税政策能够有效地遏制地区房地产业新增产值占GDP的比重的上升,促使实体企业回归主业,增加实体投资,实现促进实体经济朝着"脱虚返实"方向发展的作用.鉴于此,本文提出应加快推进房产税政策在全国范围内的实施,并在政府补贴、银行贷款等方面采取一系列配套措施鼓励实体企业进行更多的实体投资.     

Institutional dynamics and access to non-farm employment in rural China, 1950–1996

This article examines non-farm employment in the context of Chinese rural institutional change, based on evidence from discrete-time logistic models for event history analysis using the Life History and Social Change survey. We find the transition to non-farm sector rose rapidly during the Great Leap Forward and market reform, while the Cultural Revolution saw it reach the lowest ebb. While male advantage prevailed exclusively during the Cultural Revolution and early marketization, education possessed a stable positive effect in all historical periods. Although the returns to different kinds of political capital vary along with institutional dynamics, intergenerational reproduction was greatly reduced after the Cultural Revolution.     

中医药文化融入高等中医药院校意识形态工作探究

当前抓紧加强和改进高校意识形态工作具有极端重要性和现实紧迫性.中医药文化之意蕴与高校意识形态教育目标、内容价值相通,更与高校意识形态工作理念、方法内在相契.通过将中医药文化有机融入意识形态工作,进一步加强宣传阵地、实践阵地建设,协同发力,有助于实现高等中医药院校意识形态工作创新发展.     

Structural estimation of behavioral heterogeneity

We develop a behavioral asset pricing model in which agents trade in a market with information friction. Profit‐maximizing agents switch between trading strategies in response to dynamic market conditions. Owing to noisy private information about the fundamental value, the agents form different evaluations about heterogeneous strategies. We exploit a thin set—a small sub‐population—to point identify this nonlinear model, and estimate the structural parameters using extended method of moments. Based on the estimated parameters, the model produces return time series that emulate the moments of the real data. These results are robust across different sample periods and estimation methods.     

网络直播购物情境下的拟剧化营销——基于抖音直播平台的分析与诠释

网络直播购物逐渐成为一种新的网络营销与消费方式。对于该模式的剖析,有助于对网络直播购物这一新兴事物进行全景化的解构与阐释,更好地理解与把握该模式的本质与趋势。本文基于第三方立场与视角,以戈夫曼拟剧理论为基础,锚定抖音平台为实践场景,尝试诠释拟剧理论在网络直播购物情境中的新变化、新形式、新内涵。研究选择Top100网络直播主播为分析对象,采用后台运营数据、页面数据爬虫、人工观察分析等多元数据采集与分析方法,对整个网络直播购物场景进行分析。研究发现,网络直播购物呈现出鲜明的拟剧化营销特质,各类要素间存在循环强化的运行机理,消费者的购物行为有着显著的集体偏好,且主体间的协同合作机制促进了消费的延续。该发现有助于对拟剧化营销运行机制、拟剧理论的新场景及网络直播购物这一新兴商业模式进行客观辩证的思考。     

Close relationship with the supervisor may impede employee creativity by suppressing vertical task conflict

Leader‐member exchange as a form of supportive leadership is expected to foster employee creativity. However, empirical evidence suggested this relationship is complex. This study attempts to address this complexity by proposing and testing a curvilinear mechanism, which attenuates the overall positive effect of LMX on creativity by transmitting a curvilinear indirect effect via vertical task conflict. Results drawn from a sample of 276 supervisor–subordinate dyads provided support for the hypothesized curvilinear indirect effect. Specifically, LMX was found to negatively influence employee creativity by suppressing vertical task conflict for subordinates in high‐quality LMX relationships, while the indirect effect was not significant for subordinates in low‐quality LMX relationships.     

Using a dual-frame design to improve phone surveys on political attitudes: developing a weighting strategy for limited external information in Hong Kong

Quality & Quantity - In recent years, rapid increases in mobile phone ownership and decreases in landline users have led to potential biases in landline phone survey estimations. Mobile-only...     

EMPIRICAL PERFORMANCE OF GARCH MODELS WITH HEAVY‐TAILED INNOVATIONS

We introduce a new type of heavy‐tailed distribution, the normal reciprocal inverse Gaussian distribution (NRIG), to the GARCH and Glosten‐Jagannathan‐Runkle (1993) GARCH models, and compare its empirical performance with two other popular types of heavy‐tailed distribution, the Student's t distribution and the normal inverse Gaussian distribution (NIG), using a variety of asset return series. Our results illustrate that there is no overwhelmingly dominant distribution in fitting the data under the GARCH framework, although the NRIG distribution performs slightly better than the other two types of distribution. For market indexes series, it is important to introduce both GJR‐terms and the NRIG distribution to improve the models’ performance, but it is ambiguous for individual stock prices series. Our results also show the GJR‐GARCH NRIG model has practical advantages in quantitative risk management. Finally, the convergence of numerical solutions in maximum‐likelihood estimation of GARCH and GJR‐GARCH models with the three types of heavy‐tailed distribution is investigated.     

Aid for trade and the quality of exports

This article studies how aid for trade (AfT) affects the quality of recipient countries’ exports. It shows that the quality effect is most discernible for AfT for assistance in trade policy: a 50% increase in the value of AfT received in this category is associated with a 0.5–1% increase in the quality of exports to the donor and other OECD countries. On average, the actual AfT received for assistance in trade policy leads to a 2% upgrade of the recipient country in the quality ladder of all developing countries. Around half of this quality effect is driven by the quality improvement of continued products in continued markets (intensive margin), and the other half by the quality upgrading of new products in continued markets and existing products in new markets (extensive margin).     

A hybrid information approach to predict corporate credit risk

This study proposes a hybrid information approach to predict corporate credit risk. In contrast to the previous literature that debates which credit risk model is the best, we pool information from a diverse set of structural and reduced‐form models to produce a model combination based on credit risk prediction. Compared with each single model, the pooled strategies yield consistently lower average risk prediction errors over time. We also find that while the reduced‐form models contribute more in the pooled strategies for speculative‐grade names and longer maturities, the structural models have higher weights for shorter maturities and investment grade names.