基于中国经济转轨实践的分析方法研究——兼作对“北京共识”合理逻辑的一种解释

与中东欧有意识设计的转轨模式不同,中国经济转轨的实践动因源于如何更好地解决民生问题。这一动因也成为推动和评价转轨绩效的线索,并贯穿始终。迄今的转轨实践证明,转轨必然是一个渐进的制度形成过程,转轨过程、绩效与预期目标之间并不存在一元线性关系。因此,针对转轨过程的分析方法具有十分重要的政策指导作用。本文试图以中国转轨实践为研究对象,通过引入适应能力、路径选择、创新能力等指标,解释中国成功实践中的某种合理逻辑。这样做的意义在于尝试从中国的成功中总结可用于分析的一般性方法,同时也作为对“北京共识”的一种系统阐述。希望这项研究能使“中国模式”更具普世意义。     

An empirical investigation of technology acceptance in a field sales force setting

Gaining technology acceptance by salespeople is critical in modern organizations. Sales technology is an integral tool for enhancing customer-related information management and knowledge development. Knowledgeable salespeople are able to use the information and knowledge to practice adaptive selling, improve performance, and enhance their firm's competitive advantage in the marketplace. This study proposes and tests a model linking technology acceptance to adaptive selling and job performance of field salespeople. The results provide evidence that behavioral intentions to use technology positively affect salesperson performance through enhanced propensity to practice adaptive selling. Implications of the study for managers and researchers are discussed.     

自适应数字回波抵消

本文阐述了解决通信系统中回波问题而提出的一种较完善的数据驱动自适应回波抵消器的结构及性能。分析了相位抖动、频率漂移及偏值等问题对抵消器性能的影响。     

机动目标自适应高斯模型与跟踪算法

提出了一种描述机动目标运动状态的自适应高斯模型，在这种模型中，机动目标的加速度被认为是具有非零均值、时间相关的随机过程，并假定其概率密度函数服从高斯分布。指出了机动目标运动模型的均值和方差与目标机动加速度最佳当前估计值之间的关系，在此基础上，提出了相应的自适应卡尔曼滤波算法。仿真结果表明，该算法对机动目标在不同机动方式下的位置、速度和加速度均有良好的跟踪效果，且所需计算量小。     

Adaptation analysis for environmental change in coastal communities

Small islands and coastal communities around the world are particularly vulnerable to climate change impacts, mainly from storm surge attributed to more frequent and severe coastal storms, and mounting sea-level rise. Coastal hazards including inundation, salinisation of the water supply, and land erosion all threaten vital infrastructure that support coastal communities. This research, part of the International Community-University Research Alliance (ICURA) C-Change project “Managing Adaptation to Environmental Change in Coastal Communities: Canada and the Caribbean”, develops and applies a multicriteria decision evaluation and support system for evaluating adaptation options for coastal communities. The paper estimates vulnerability, resilience, and adaptive capacity measures associated with adaptation strategies in coastal communities with respect to their environmental, economic, social, and cultural dimensions. Results are determined using a multi-participant formulation of the Analytical Hierarchy Process (AHP) for identifying multicriteria decisions as adaptation strategies in a specific coastal context. The application of the framework is conducted for the coastal community of Little Anse on Isle Madame, Nova Scotia. Specifically, the state of the Little Anse breakwater is analysed and adaptation options for protecting, accommodating, and retreating are presented and evaluated in the face of predicted storm scenarios. The results indicate that, in the case of Little Anse, the strategic decision to protect the community by a new breakwater arm provides preferred measures for resilience and adaptive capacity.     

Is central bank conservatism desirable under learning?

In a New Keynesian model, we consider the delegation problem of the government when the central bank optimally sets discretionary monetary policy taking account of private expectations formed through adaptive learning. Learning gives rise to an incentive for the central bank to accommodate less the effect of inflation expectations and cost-push shocks on inflation and induces thus a deviation from rational expectations equilibrium. However, discretionary monetary policy under learning suffers from an excessively low stabilization bias. To improve the social welfare, the government should appoint a liberal central banker, i.e., set a negative optimal inflation penalty that decreases with the value of learning coefficient. The main conclusions are valid under both constant- and decreasing-gain learning.     

Government debt,learning and the term structure

Does a change in the public׳s holdings of government debt affect the term structure of interest rates? Empirical analysis using a VAR model indicates that a rise in these holdings of the real debt-to-GDP ratio increases both the three-month and ten-year U.S. nominal yields in a statistically significant manner. The maturity composition of debt is also found to matter: innovations in holdings of long-term debt affect the term structure, while increases in short-term debt affect inflation expectations. These effects of changes in holdings of debt on the yield curve can be derived in a general equilibrium model in which the government issues exponentially-maturing riskless debt, financed by lump-sum taxes, and the optimizing agents are adaptive learners. On calibrating the average maturity of debt in the model to match that of U.S. Treasury debt since the 1980s, I find that positive innovations in government debt lead to increases in asset yields. This is because agents do not learn the principle of Ricardian equivalence exactly, and perceive increases in holdings of government bonds as a rise in their net wealth. Imposing rational expectations on the agents eliminates this channel, and changes in holdings of government debt have no effect on yields. The learning model also implies that as the real debt-to-GDP ratio increases, and the average maturity of debt becomes longer, the agents become less likely to learn that Ricardian equivalence holds.     

Projections of maize yield vulnerability to droughts and adaptation options in Uganda

Sub-Saharan Africa is likely going to experience more intense and frequent droughts with high parallel possibilities of ramifications on maize yields. While there is a lot of scholarship dwelling on the ramifications of droughts on maize yields at the level of Africa, little has been researched at lower scales. This study presents past (1960–2014) vulnerability of maize yields to droughts based on a previous study (Epule et al., 2017) and projects the future vulnerability of maize yields to droughts by calculating the sensitivity, exposure and adaptive capacity of maize yields to droughts for the period 2015–2050. The results show that maize yields are more vulnerable in the north of Uganda for the period 1960–2014. However, adaptive capacity is higher in the south. Maize yields also record higher levels of sensitivity and exposure in the north with the latter patterns explained by variations in precipitation, temperature, rich volcanic soils, access to rivers and lakes. In terms of future vulnerability for the period 2015–2050, this study shows that the level of vulnerability of maize yields to droughts in Uganda will increase to levels higher than what currently obtains. For example, the vulnerability index will increase from 0.54 under the 1.5 °C to 0.70 under the 2.0 °C and to 1.54 under the 2.5 °C scenario. Sensitivity is also likely to increase while exposure and adaptive capacity are most likely to remain the same. Overall, it can be said that the future of maize production in Uganda under present and future circumstances remains very bleak without concrete actions. As a way forward, land use policy designers will have to integrate water management, agroforestry, climatic information diffusion, training and indigenous knowledge into land use planning decisions in the context of agriculture.     

Learning from Doing Participatory Rural Research: Lessons from the Peak District National Park

Understanding the socio‐economic and environmental implications of rural change requires the active participation of many research disciplines and stakeholders. However, it remains unclear how to best integrate participatory and biophysical research to provide information useful to land managers and policy makers. This paper presents findings of a RELU scoping study that has formulated and applied a research framework based on stakeholder participation and adaptive learning to model rural change in the Peak District National Park in the north of England. The paper describes a learning process that integrates different types of knowledge to produce future scenarios that describe possible economic and environmental changes due to a national review of burning practices on heather moorland and blanket bogs. We stress the need for using social network analysis to structure stakeholder engagement and outline how a range of participatory approaches can facilitate more inclusive environmental planning and policy development.