区域知识产权保护发展的空间格局及结构体系研究

以我国各省知识产权保护制度为研究对象，创新性地将探索性空间数据分析方法与社会网络分析方法相结合，基于地理邻近视角，验证了区域知识产权保护的空间相关性、空间集聚特征和空间溢出效应。同时，突破地理近邻效应的局限，解析区域知识产权保护的空间关联特征。结果表明：我国各省知识产权保护具有全局自相关性，相似地区间存在空间集聚效应，不同发展程度地区的空间关联性质不同；网络化后的区域知识产权保护各节点间联系紧密、网络结构稳定，并且可以确定核心行动者和边缘行动者角色；长三角、珠三角、环渤海等较发达地区与其它地区之间存在较多溢出关系。     

Operational risk quantified with spectral risk measures: a refined closed-form approximation

The quantification of operational risk has become an important issue as a result of the new capital charges required by the Basel Capital Accord (Basel II) to cover the potential losses of this type of risk. In this paper, we investigate second-order approximation of operational risk quantified with spectral risk measures (OpSRMs) within the theory of second-order regular variation (2RV) and second-order subexponentiality. The result shows that asymptotically two cases (the fast convergence case and the slow convergence) arise depending on the range of the second-order parameter. We also show that the second-order approximation under 2RV is asymptotically equivalent to the slow convergence case. A number of Monte Carlo simulations for a range of empirically relevant frequency and severity distributions are employed to illustrate the performance of our second-order results. The simulation results indicate that our second-order approximations tend to reduce the estimation errors to a great degree, especially for the fast convergence case, and are able to capture the sub-extremal behavior of OpSRMs better than the first-order approximation. Our asymptotic results have implications for the regulation of financial institutions, and may provide further insights into the measurement and management of operational risk.     

东部地区农业结构变动与政策变量之间的相关性研究

本文通过农民收入变量、农民受教育程度、农村人均固定资产投资额、政府用于农村人均文教娱乐用品及服务支出和政府用于农村财政支出等政策变量与东部地区农业结构变动的相关性分析,再根据未来若干年我国及东部地区农业政策变化趋势,从而预测未来我国东部地区农业结构的变化趋势。     

Modelling exchange of probabilistic opinions

Summary. This paper studies how communication or exchange of opinions influences correlation of beliefs. The paper focuses on a situation in which agents communicate with each other infinitely many times without observing data. It is an extension to the ‘Expert Problem’ in Bayesian theory, where the informational flow is asymmetric. Moreover, this paper generalizes the existing literature of communication that employs the common prior assumption (CPA) by allowing for heterogeneous beliefs. Some basic convergence results are shown in contrast with the results obtained under the CPA. Furthermore, several economic implications of the basic results are provided. Received: August 27, 2001; revised version: April 16, 2002 RID="*" ID="*" The results presented in this paper are taken from my Ph.D. thesis at Stanford University. I gratefully acknowledge the inspiration obtained from innumerable discussions with Mordecai Kurz about this subject. Also, I appreciate comments from Kenneth J. Arrow, Peter J. Hammond, Maurizio Motolese, Carsten K. Nielsen, Ho-Mou Wu and the anonymous referee.     

基于谱分析的连续加工过程检验批量的确定

在连续加工过程中 ,合理地确定检验批量 ,不仅可以反映加工过程的稳定性 ,而且也是确定抽样检验方案及检验频次的基础。本文主要利用时间序列的谱分析方法对连续加工过程的质量检测数据进行周期划分 ,从而确定抽样检验的批量 ,并根据周期分析结果 ,指出了导致加工质量产生波动的一些原因。     

欧盟REACH法令对中国化工产品出口的影响分析

欧盟REACH法令的实施将促进我国化学工业的发展,但在短期内会导致我国出口欧盟化工产品和进口化工产品成本上升,降低出口产品竞争力,部分产品甚至退出欧盟市场,其他国家可能纷纷效仿欧盟,引起连锁反应。应对该种技术性壁垒,我国政府和行业协会应加大宣传REACH法令的力度,加快国内相关立法,推进国内实验室的GLP认证工作。另外,化学品生产企业应提高自身产品质量,做好化学品注册的可行性分析和预注册工作。     

Correlated daily time series and forecasting in the M4 competition

We participated in the M4 competition for time series forecasting and here describe our methods for forecasting daily time series. We used an ensemble of five statistical forecasting methods and a method that we refer to as the correlator. Our retrospective analysis using the ground truth values published by the M4 organisers after the competition demonstrates that the correlator was responsible for most of our gains over the naïve constant forecasting method. We identify data leakage as one reason for its success, due partly to test data selected from different time intervals, and partly to quality issues with the original time series. We suggest that future forecasting competitions should provide actual dates for the time series so that some of these leakages could be avoided by participants.     

Business Cycles Synchronisation and Symmetries in the Transition to East African Monetary Union

Our paper explores the prospects for the proposed East African Monetary Union (EAMU) by employing rigorous empirical tools to analyse business cycles synchronisation, structural cross-correlations, spectral decomposition and regional clusters to identify different cyclical episodes, periodicities and characterise the economic cycles of East African countries. We find that cyclical movements reflect various idiosyncratic, common, historical and external shocks in the region. Secondly, all countries appear to be structurally correlated with each other except for South Sudan and Burundi. Our results also observe that the contemporaneous co-movements of East African Community (EAC) cycles with those of Kenya and Tanzaniaare procyclical with coincidental path shift, while the same EAC cycles appear to be acyclical with those of Burundi. Additionally, from the spectral decomposition, Kenyan cycles take 10 years to complete, while those of Tanzania and Rwanda take 8 years. Ugandan and Burundian cycles take approximately 5 years, while the cyclical frequency for South Sudan corresponds to 3.3 years. Finally, the cluster characterisation of countries reveals that South Sudan, Burundi and Rwanda form a group, while Kenya and Tanzania from a group distinct from the rest. We urge the member countries to prioritise policies on regional risk-sharing and adjustment mechanisms, in addition to establishing credible institutional infrastructure that ensures surveillance and enforcement of convergence conditions adopted in EAMU protocol.     

Probabilistic assessment of fleet-level noise impacts of projected technology improvements

Demand projections for civil aviation have forecast increases in operations in future decades. Increases in demand are beneficial to the growth and advancement of the aviation industry, but also come with the threat of significant increase in environmental impacts. In response, the industry is focusing on programs to develop technologies for reductions in fuel burn, NO_x emissions, and noise. While aircraft-level impacts are an obvious metric of success, it is difficult to make informed robust technology investment decisions with respect to noise without understanding the fleet-level impacts. Fleet-level predictions of noise for technology explorations are especially complicated because it is computationally expensive, highly combinatorial, and airport-specific. Recently, rapid automated airport noise models have been developed, which can be simulated using Design of Experiments (DOE). The results of these simulations are used to generate surrogate models for airport noise contour area, which can be summed to yield a fleet-level impact. These models make use of simplifying assumptions to provide estimates of airport-level noise that are substantially cheaper to compute. They can be used to perform parametric trade-off analyses in conjunction with the equivalency assumption. Equivalency asserts that environmental impacts of a technology infused aircraft can be represented by scaled operations of the baseline aircraft in the same class. This simple assumption allows for the modeling of technology and market penetration factors under the same units: operations. This research uses surrogate models in conjunction with the equivalency assumption to examine two potential technology scenarios in a target forecast year, simulating technology and market performance factors to identify vehicle classes that could have the greatest impact in reducing contour area. Results show that technology and market performance of future notional Small Single Aisle and Large Single Aisle vehicle aircraft have the highest positive correlations with potential reductions in contour area.     

Flight-to-quality and correlation between currency and stock returns

We document that capital flows in and out of emerging or developed markets are sensitive to global equity market conditions. Capital tends to move out of emerging into developed countries in global down markets, leading to depreciation (appreciation) of emerging (developed) currencies. This generates a positive (negative) correlation between currency and equity in emerging (developed) markets which is amplified by the magnitude of the capital movement. We also verify that hedging currency risks may undo the natural hedge and increase the total return volatility under negative correlation.