Firm-Level TFP Growth in the Chinese Automobile Industry

China has been the world’s largest automobile producer since 2009,but it still lags behind other countries in terms of productivity. Based on theNational Bureau of Statistics of China (NBSC) firm-level data and the improvedapproach proposed by Ackerberg et al. (2015), this paper investigates thecontribution of total factor productivity (TFP) growth to the Chinese automobileindustry and evaluates the impact of firm entry and exit on TFP growth. Theempirical results show that the TFP of the Chinese automobile industry grows at10.7% per year. Joint venture and foreign-owned firms have a significantly higherTFP growth rate than others. Large-scale firms have a higher TFP growth rate thando small-scale firms, but the latter have caught up after 2004. Moreover, the entryof new firms and exit of old firms significantly improve the aggregate TFP growthrate.     

基于自回归移动平均模型的国际金融危机对四川经济的影响分析研究

2008年发生的美国次贷危机引发的全球金融危机给世界各国的经济特别是金融行业带来了强烈的冲击.金融危机主要通过投资渠道、贸易渠道、汇率渠道以及预期渠道直接或间接影响四川经济.为估算这种影响,文章基于自回归移动平均模型(ARIMA)的特殊性,选取了2000～2008年的样本数据,运用时间序列建模技术,从直接影响和间接影响两个维度7项指标所描述的经济发展指标上,详尽分析研究了国际金融危机对四川经济的影响.文章克服了实际工作部门在测算该种影响时,不考虑经济序列长期发展趋势的不足,并就其对我国经济和四川经济发展的影响作了探讨,在此基础上,提出四川省市应对经济危机的措施,以供相关部门决策时参考.     

On the use of the Box–Cox transformation on conditional variance models

We investigate the effects of using the Box–Cox transformation on conditional variance specifications. By deriving its autocorrelation functions, we infer “rich” autocorrelation structures due to the existence of the specification parameter in this non-linear transformation. To illustrate transformation's effects on conditional variance models, we first generate its theoretical autocorrelation function and then investigate model's fit using real financial time-series data.     

基于聚合通道特征下的探地雷达对地下管网建模

本论文提出一种利用探地雷达检测数据建立地下管网GIS模型的方法。该方法应用聚合通道特征(ACF)自动分析地下管网的探地雷达数据并生成地理参考线,并通过实地实验验证了该方法的有效性。     

CBOC调制方式及其性能分析

Galileo卫星导航系统在E1频段使用CBOC(6,1,1/11)调制方式取 代原计划的BOC(1,1)调制方式。介绍了CBOC(6,1,1/11)的频谱、实现方式及其相关函数 ,并通过仿真计算,对比分析了CBOC(6,1,1/11)和BOC(1,1)调制方式在谱分离系数、根均方 带宽和多径误差包络的差别。结果表明： CBOC(6,1,1/11)和BOC(1,1)频谱相近,但增加了 部分高频分量, 且CBOC(6,1,1/11)不同的实现方式相关函数上有一定的差别; CBOC(6,1,1/ 11)在与同频段其它服务信号间的谱分离系数整体上小于BOC(1,1),降低了系统内和系统间 的干扰; CBOC(6,1,1/11)根均方带宽大于BOC(1,1), 减小了跟踪抖动; CBOC(6,1,1/11)的 多径误差包络整体上小于BOC(1,1),提高了系统的抗多径能力。     

基于计算实验金融方法的决策偏好比较研究

风险决策偏好表征着个体在面对不确定条件或具有风险时的决策态度,不同的偏好特征以效用函数为载体,外在地表现为个体具体所运用的投资策略。风险决策机制的深入理解以及基于不同决策偏好的策略比较分析对投资者的投资决策具有重要意义。通过运用计算实验金融方法对传统决策偏好以及前景理论进行多角度的比较分析,研究发现基于前景理论构造的投资策略相比传统决策偏好具有较大的优势,对于投资者本身来说是一个最佳的策略选择。     

Multi-population mortality projection: The augmented common factor model with structural breaks

Multi-population mortality forecasting has become an increasingly important area in actuarial science and demography, as a means to avoid long-run divergence in mortality projections. This paper aims to establish a unified state-space Bayesian framework to model, estimate, and forecast mortality rates in a multi-population context. In this regard, we reformulate the augmented common factor model to account for structural/trend changes in the mortality indexes. We conduct a Bayesian analysis to make inferences and generate forecasts so that process and parameter uncertainties can be considered simultaneously and appropriately. We illustrate the efficiency of our methodology through two case studies. Both point and probabilistic forecast evaluations are considered in the empirical analysis. The derived results support the fact that the incorporation of stochastic drifts mitigates the impact of the structural changes in the time indexes on mortality projections.