Trust Erosion During Industry-Wide Crises: The Central Role of Consumer Legitimacy Judgement

Journal of Business Ethics - Widespread unethical corporate misconduct in an industry triggers industry-wide crises. This research investigates how industry misconduct affects consumers’...     

土地市场扭曲如何影响制造业出口产品质量升级*——基于土地市场交易数据和制造业企业数据的实证分析

地方政府“以地谋发展”的策略在促进各地区制造业大规模集聚和出口贸易快速增长的同时，也势必会给企业出口产品质量带来深刻影响。本文综合利用中国土地市场网城市土地交易数据、中国工业企业数据、中国海关进出口产品数据和中国城市面板数据，实证检验了土地市场扭曲对企业出口产品质量升级的影响，并对其内在机制进行了探讨。研究发现：中国城市建设用地配置存在明显的工业偏向性，进而导致工业用地价格被低估，产生工业用地应得收益大于实际价格的反向扭曲问题。这种反向扭曲可通过抑制技术进步、阻碍产业结构高级化、弱化集聚经济效应等机制显著降低制造业企业出口产品质量。土地市场扭曲对企业出口产品质量升级的影响具有明显的异质性特征。具体而言，土地市场扭曲不利于一般贸易企业与混合贸易企业出口产品质量提升，但对加工贸易企业出口产品质量提升具有促进作用。土地市场扭曲对企业出口产品质量升级的抑制作用由东到西依次递增。土地市场扭曲不利于外资企业和国有企业出口产品质量提升，对集体企业及民营企业的影响不显著。     

Farm Capital Investment and Deviations from the Optimal Path

We identify farms’ optimal investment path in capital assets and compare it with their actual investment to assess the direction and extent of deviation from the optimal investment. A probit model is further used to investigate the determinants of the probability that a farmer over‐ or under‐invests in capital assets. We use a panel dataset of Dutch dairy farms over the period 2003–2013, and find that most farms under‐invest in capital assets during the study period. Although the number of farms that had over‐invested in capital assets is relatively small, these farms account for the biggest share of total investment in capital assets. The probit results show that liquidity, agricultural support payments, age, land tenure and standard output size are important variables explaining the likelihood of over‐and under‐investment.     

Improving forecasting performance using covariate-dependent copula models

Copulas provide an attractive approach to the construction of multivariate distributions with flexible marginal distributions and different forms of dependences. Of particular importance in many areas is the possibility of forecasting the tail-dependences explicitly. Most of the available approaches are only able to estimate tail-dependences and correlations via nuisance parameters, and cannot be used for either interpretation or forecasting. We propose a general Bayesian approach for modeling and forecasting tail-dependences and correlations as explicit functions of covariates, with the aim of improving the copula forecasting performance. The proposed covariate-dependent copula model also allows for Bayesian variable selection from among the covariates of the marginal models, as well as the copula density. The copulas that we study include the Joe-Clayton copula, the Clayton copula, the Gumbel copula and the Student’s $t$-copula. Posterior inference is carried out using an efficient MCMC simulation method. Our approach is applied to both simulated data and the S&P 100 and S&P 600 stock indices. The forecasting performance of the proposed approach is compared with those of other modeling strategies based on log predictive scores. A value-at-risk evaluation is also performed for the model comparisons.     

长三角港口腹地动态演变及耦合协调度研究

明确港口腹地演变趋势、分析港腹耦合协调度,对长三角地区港腹联动发展具有重要意义。量化港口系统—腹地系统综合指标评价体系,运用高斯烟羽模型在2006、2011、2016年3个时间节点上测算长三角地区主要港口影响强度,并对腹地范围进行划分,利用耦合协调模型定量分析港口系统和直接腹地经济系统耦合协调度。研究结果表明:长三角地区港口呈现"一超多强"的格局,以上海港为中心,各港口多极发展;港口腹地范围整体稳定,局部波动,上海港的边缘腹地不断缩减;港口与腹地的耦合协调度处于上升态势,宁波—舟山港腹耦合协调度最高。     

去库存及建筑总量控制政策对三四线城市能源消耗的影响效应研究

近十年来房地产开发迅猛,在满足人们居住需求的同时也伴随着大量泡沫的涌现。中央提出的供给侧改革、去库存和能效提升给建筑部门指明了发展方向,有效地实施供给侧改革是建筑部门一项重要工作。拟通过开展去库存及建筑总量控制对三四线城市能源消耗的影响研究,为建筑部门的供给侧改革提供建议和参考。站在建筑部门宏观视角,通过文献调查,分析总结了建筑终端能耗影响因素及其影响效应,梳理了中国建筑总量、库存量及建筑领域能源消耗量总体情况,论述了三四线城市去库存、进行建筑总量控制的重要性;在此基础上,根据分析结果、三四线城市特点及数据可获得性,选定自变量和因变量及量化指标,运用岭回归方法,以6个城市的数据为例进行三四线城市建筑总量控制、去库存政策对城市能耗影响效果的定量分析;最后基于彼此间关系及研究过程中发现的问题对建筑部门的供给侧改革工作提出建议。     

Noise traders,firm-specific uncertainty and technical trading effectiveness

This is the first study to document evidence of technical trading effectiveness at firm level in the Chinese A-share market by investigating the relationship between excess profits of technical trading rules and firm-specific characteristics. Our results reveal that firms with higher excess profits from technical trading have more noise traders and higher institutional ownership and that those firms tend to be growth firms with lower liquidity and higher firm-specific uncertainty. Further analysis shows that the profitability of technical trading rules is unsustainable and the excess profits of the highest technical trading profit quintile portfolio disappear in the following year.     

Chinese tourists' views of nature and natural landscape interpretation: a generational perspective

This study investigates Chinese tourists’ views of nature, interest in animal experiences and their preferred natural landscape interpretation content from a generational perspective. Eight hundred and eight self-administered questionnaires were collected at Wulingyuan, a UNESCO World Natural Heritage Site, in China. It suggests that overall Chinese traditional cultural values and beliefs, notably the thinking of tian ren he yi (oneness of nature with humans), still have considerable impacts on Chinese tourists. They were found to have a strong sense of connection with nature and a preference for cultural interpretations of natural landscapes. Meanwhile, Chinese might be reaching a point of convergence in terms of attitude towards nature and animals with their Western counterparts, as reflected by their weak anthropocentric view, and strong ethical and aesthetic appreciation of animals, regardless of generation cohorts. Yet, the study shows significant generational gaps: older generations have a stronger connection with nature, are more concerned about environmental issues and show more support for the Western approach towards nature protection; the younger generations hold weaker anthropocentrism, and are more interested in animals, yet are less likely to learn about nature through tourism interpretation.     

Competing with complementors: An empirical look at Amazon.com

Research Summary : Platform owners sometimes enter complementors' product spaces and compete against them. Using data from Amazon.com to study Amazon's entry pattern into third‐party sellers' product spaces, we find that Amazon is more likely to target successful product spaces. We also find that Amazon is less likely to enter product spaces that require greater seller efforts to grow, suggesting that complementors' platform‐specific investments influence platform owners' entry decisions. While Amazon's entry discourages affected third‐party sellers from subsequently pursuing growth on the platform, it increases product demand and reduces shipping costs for consumers. We consider the implications of these findings for complementors in platform‐based markets. Managerial Summary : Platform owners can exert considerable influence over their complementors' welfare. Many complementors with successful products are pushed out of markets because platform owners enter their product spaces and compete directly with them. To mitigate such risks, complementors could build their businesses by aggregating nonblockbuster products or focusing on products requiring significant platform‐specific investments to grow. They should also develop capabilities in new product discovery so that they could continually bring innovative products to their platforms.     

Volatility forecasting: long memory,regime switching and heteroscedasticity

In this article, we account for the first time for long memory, regime switching and the conditional time-varying volatility of volatility (heteroscedasticity) to model and forecast market volatility using the heterogeneous autoregressive model of realized volatility (HAR-RV) and its extensions. We present several interesting and notable findings. First, existing models exhibit significant nonlinearity and clustering, which provide empirical evidence on the benefit of introducing regime switching and heteroscedasticity. Second, out-of-sample results indicate that combining regime switching and heteroscedasticity can substantially improve predictive power from a statistical viewpoint. More specifically, our proposed models generally exhibit higher forecasting accuracy. Third, these results are widely consistent across a variety of robustness tests such as different forecasting windows, forecasting models, realized measures, and stock markets. Consequently, this study sheds new light on forecasting future volatility.