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.     

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.     

禽流感危机下肉鸡产业市场状态分析*——基于互联网大数据和MS-VAR模型

[目的]为了有效应对禽流感冲击、维持肉鸡产业稳定健康发展。[方法]基于互联网大数据构建了禽流感舆情指数,选取2012年1月至2017年3月周度数据,通过MS-VAR模型分析了禽流感危机下肉鸡市场状态的转换特征以及不同市场状态下产业链价格传导关系。[结果]2012年以来可将肉鸡产业市场状态划分为危机状态和正常状态,肉鸡产业市场在两个市场状态下转换频繁;肉鸡产业危机市场状态和正常市场状态平均持续期分别为4.65周和9.05周;肉鸡市场在区制转移概率上存在明显的非对称特征;肉雏鸡、活鸡和白条鸡价格之间在危机状态下相关性小于正常市场状态下相关性;不同市场状态下肉鸡产业链价格传导存在差异;肉鸡产业市场在危机状态下不稳定程度明显增加。[结论]提出了加大对禽流感疫情的监测以及疫情处理能力,密切关注公众禽流感舆情动态变动情况,做好舆情引导,加强禽流感疫情科学知识的宣传,增强公众对禽流感的认知等对策建议。     

基于均方差法的郑州市土地综合承载力评价

［目的］开展土地综合承载力评价是科学编制国土空间发展战略的基础。通过构建包含水土资源承载力、经济承载力和生态承载力3个维度土地综合承载力评价指标体系，定量刻画郑州市城市土地综合承载力的特征与轨迹。［方法］运用均方差法，选取2010—2016年郑州市城市土地综合承载力评价指标，分析其土地综合承载力特征。［结果］（1）总体上，郑州市城市土地综合承载力不断增强，水土资源承载力呈现先升—降—升的动态演变特征； 经济承载力持续增长，这源于郑州市土地经济效益的大幅提升； 生态承载力呈现波动性增强的演变特征。（2）郑州市城市土地综合承载力经历了较低—中等—较高发展历程，但土地综合承载力处于低层次的较高阶段，仍有较大提升空间。（3）为提高郑州市城市土地综合承载力，应加快“多规合一”规划的编制，科学划定城市增长边界和“三生”空间，转变城市发展理念，优化发展发展路径，提升城市土地综合承载力水平。［结论］郑州市城市土地综合承载力仍有较大提升空间，应加快建立土地综合承载力扩容的有效机制。     

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...     

Resource Dependence and Network Relations: A Test of Venture Capital Investment Termination in China

This study examines how venture capital (VC) firms terminate investments in an emerging economy context. We contend that due to the weak institutional environment, it is appropriate to draw on insights from power and social relation perspectives for a better understanding of the phenomenon. Specifically, we argue that a termination decision hinges on not only the dependence relationship between a VC firm and its portfolio companies, but also the social relationships among VC firms. Event history analyses of approximately 12,000 VC deals made in China between 2001 and 2012 reveal that when a VC firm has a greater number of investments in an industry, it is more likely to terminate investments on a portfolio company in that industry. Moreover, such effect on termination is moderated by the focal VC's embeddedness with its syndicate partners and collaboration opportunities with other VC firms outside the immediate access of the syndicate partners. Our study sheds light on research on VC decision making in emerging markets by integrating insights from resource dependence relationships and interorganizational network characteristics.     

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).     

Impulse response function analysis of the impacts of land value-added tax policy on government performance

In this study, an epsilon-based network data envelopment analysis is employed to construct assessment mechanisms for government performance. Moreover, performance indicators of two dimensions of tax collection efficiency and financial effectiveness are measured. We propose a vector autoregression model in which all economic variables are regarded as dependent variables to address the disadvantages of traditional regression model. The conclusions are as follows: (a) measures of tax collection efficiency deteriorated, whereas those of financial effectiveness improved. (b) In an impulse response analysis of the model, an increase in government-published land values produced significantly increased tax collection efficiency.     

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.