Statistical and computational tradeoff in genetic algorithm-based estimation

When a genetic algorithm (GA) is employed in a statistical problem, the result is affected by both variability due to sampling and the stochastic elements of algorithm. Both of these components should be controlled in order to obtain reliable results. In the present work we analyze parametric estimation problems tackled by GAs, and pursue two objectives: the first one is related to a formal variability analysis of final estimates, showing that it can be easily decomposed in the two sources of variability. In the second one we introduce a framework of GA estimation with fixed computational resources, which is a form of statistical and the computational tradeoff question, crucial in recent problems. In this situation the result should be optimal from both the statistical and computational point of view, considering the two sources of variability and the constraints on resources. Simulation studies will be presented for illustrating the proposed method and the statistical and computational tradeoff question.     

Comparison of predictions by kriging and spatial autoregressive models

In geostatistics, the prediction of unknown quantities at given locations is commonly made by the kriging technique. In addition to the kriging technique for modeling regular lattice spatial data, the spatial autoregressive models can also be used. In this article, the spatial autoregressive model and the kriging technique are introduced. We extend prediction method proposed by Basu and Reinsel for SAR(2,1) model. Then, using a simulation study and real data, we compare prediction accuracy of the spatial autoregressive models with that of the kriging prediction. The results of simulation study show that predictions made by the autoregressive models are good competitor for the kriging method.     

随机效应广义空间滞后半参数变系数面板模型的估计

通过构建同时包含因变量和误差项空间滞后的随机效应半参数变系数面板模型,拓展了现有模型的灵活性和适应性。采用截面极大似然估计方法得出了参数和非参数的估计,理论证明发现：在一定的正则条件下,所有估计量具有一致性和渐近正态性。数值模拟显示：估计量具有良好的小样本性质,估计精度随着样本容量的增加而增加;空间权重矩阵的选择对估计量的表现没有产生显著差异,但是在Case权重矩阵下,当样本量相同时,空间相关系数的估计偏差随着空间权重结构复杂度的增加而扩大。     

真实固定效应空间随机前沿模型的贝叶斯估计

忽略个体效应和空间效应会严重干扰效率测算,其中忽略个体效应使得技术无效率项发生偏移,忽略空间相关性导致估计量有偏且不一致。本文基于真实固定效应随机前沿模型（引入了个体效应）,引入因变量和双边误差项的空间滞后项,构建了适用性更佳的真实固定效应空间随机前沿模型。对模型进行组内变化以消除额外参数,使用贝叶斯方法（需推导未知参数的后验分布并执行MCMC抽样）估计参数和技术效率。该方法真正克服了额外参数问题,比同类方法直观、简便。数值模拟结果表明,本文方法对参数、个体截距项及技术无效率项的估计精度均较高,且增加样本容量,估计精度变优。     

考虑成分股联跳与宏观信息发布的沪深300指数已实现波动率模型研究

利用日内高频数据计算的已实现波动率较好度量了金融资产的风险,因此对其预测模型的研究具有重要意义。考虑到指数成分股的联跳可能蕴含指数跳跃所未能反映的信息,提出运用非参数方法识别指数成分股的联跳,采用自回归条件风险模型估计成分股联跳强度,并将其引入指数的已实现波动率异质自回归（HAR-RV-CJ）模型中,分析模型预测性能的改进。进一步的,考虑到宏观信息公告的发布可能对股市产生整体性影响,相应影响成分股联跳的几率;因此,在成分股联跳的自回归条件风险模型中引入居民消费价格指数、国内生产总值、贸易差额等宏观信息公告变量,并分析对联跳强度估计以及指数已实现波动率预测的影响。采用2011年1月4日至2013年7月11日沪深300指数及其成分股高频数据的实证表明,指数成分股联跳与指数跳跃具有不同的特征;用成分股联跳强度代替HAR-RV-CJ模型中的跳跃构建的HAR-RV-CI模型,较原始的HAR-RV-CJ模型,以及同时考虑指数跳跃与成分股联跳强度的HAR-RV-CJI模型,具有明显较优的样本内拟合与样本外预测性能。引入宏观信息公告变量可以改进联跳强度自回归条件风险模型的拟合效果,并提高指数已实现波动率模型的样本内拟合能力,但对于指数已实现波动率的样本外预测性能并无明显的帮助。     

存在自相关时检验和估计方法的改进——基于自回归分布滞后模型的自相关检验和参数估计

存在自相关时的自相关检验和参数估计是基础计量经济学的一个重要内容,并且存在自相关时的原模型已转化为自回归分布滞后模型。讨论存在自相关时的自相关检验和参数估计问题,提出了一种基于自回归分布滞后模型的自相关检验法,并同时给出了相应的参数估计。     

中国碳排放的环境库兹涅茨曲线分析——基于空间面板模型的实证研究

在环境库兹涅茨曲线理论的基础上,选用30个省域2000—2009年数据,运用空间面板计量经济模型研究碳排放与经济增长的关系,结果表明:利用空间相关性指标检验出经济发展与碳排放之间存在显著的空间效应;利用空间面板自回归和误差模型发现,中国碳排放与经济增长存在倒U形关系,转折点在8.167亿元至11.025亿元人均GDP之间;工业结构比重对碳减排有消极影响,而技术进步、FDI与碳排放之间存在显著的正效应,这说明通过降低工业结构比重、促进新能源技术的革新以及引进外资等能减少中国的碳排放。     

人口城市化空间路径的理论与研究及其启示

城市化的实践进程表明,一个国家的人口城市化往往遵循"城市化—郊区化—逆城市化—再城市化"或者"大城市—中等城市—小城市"的空间路径而展开。文章对"空间循环假说"、ROXY指数方法、"区域城市化"概念以及"差别城市化理论"等人口城市化空间路径理论的演绎进行了梳理,并对国内外相关研究进行了总结。结合中国人口城市化进程特点,文章认为,人口城市化空间路径理论与研究对中国城市化的道路模式、区域规划以及都市圈与城市群区域人口城市化问题的研究有启示作用。     

Extrapolative simulation of neighborhood networks based on population spatial distribution: Do they predict crime?

Objectives

Previous criminological scholarship has posited that network ties among neighborhood residents may impact crime rates, but has done little to consider the specific ways in which network structure may enhance or inhibit criminal activity. A lack of data on social ties has arguably led to this state of affairs. We propose to avoid this limitation by demonstrating a novel approach of extrapolatively simulating network ties and constructing structural network measures to assess their effect on neighborhood crime rates.

Methods

We first spatially locate the households of a city into their constituent blocks. Then, we employ spatial interaction functions based on prior empirical work and simulate a network of social ties among these residents. From this simulated network, we compute network statistics that more appropriately capture the notions of cohesion and information diffusion that underlie theories of networks and crime.

Results

We show that these network statistics are robust predictors of the levels of crime in five separate cities (above standard controls) at the very micro geographic level of blocks and block groups.

Conclusions

We conclude by considering extensions of the approach that account for homophily in the formation of network ties.     

我国医药制造业的区域差异与空间集聚

基于省际面板数据,采用区位产值指数、地区专业化指数及空间分离指数,并把2001-2010这10年分成2001-2004、2004-2007及2007-2010三个时间段,分析了中国医药制造业的区域差异和空间集聚状况。研究结果表明,东部地区总体的专业化水平高于西部地区低于中部地区,而且各地区间的专业化水平差异较大,尤其是东部各省市与中西部的比较;另外,地区专业化水平在三个时段呈现“低-高-低”的特点,十年间整个医药制造业的空间集聚程度也表现出“扩散-集聚-扩散”的规律。最后,给出了相应的政策建议。