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什么是经济发展新动能指数（图）
统计检测 经济指标 统计知识
2024/11/26
2015年以来，国家陆续出台加快实施《促进大数据发展行动纲要》《关于积极推进“互联网 +”行动的指导意见》《国家创新驱动发展战略纲要》等重大政策措施，激发创新活力，加快培育经济发展新动能，主动适应和引领经济发展新常态，实现我国经济提质增效和转型升级。创新驱动 , 培育新动能，发展壮大新产业、新业态、新商业模式（简称“三新”），是新常态下经济发展的空间和潜力， 也是推动新旧动能转换的动力源泉。
浙江省2019、2020年度跨省跨区电源新建机组调试差额资金分配测算表详情见附件
西北大学经济管理学院经济统计学专业本科人才培养方案和指导性教学计划
西北大学经济管理学院 经济统计学 人才培养
2023/2/17
2010年陕西省教育厅下发《关于陕西省普通高等学校2011年度增设本科专业的批复》（陕教高[2010]27号）文件，“统计学”专业获准增设，所属于应用经济学科，后于2013年更名为经济统计学专业。本专业将经济学与统计学两个学科的知识交叉融合，形成包含基本理论、基本方法、基本工具、应用实践的培养体系。
动态能力演化是组织与环境的互动匹配过程，注重从微观层面分析动态能力产生与演变机制的现有研究，忽视了动态能力在全球价值链升级的宏观环境中不断演化的事实；而基于GVC治理范式的全球价值链升级研究则相对忽略了企业层面能力形成、开发的内生互动过程。本文通过对Sanmina公司的案例研究，揭示了全球价值链升级与重构过程中企业动态能力协同演化的内在机制，并进一步细致刻画了升级不同阶段中动态能力的阶跃过程。研究...
股票价格与宏观经济联动关系研究——政策预期视角
股票价格 宏观经济信息 政策预期
2019/4/23
经济预测机构对经济数据的预测与发布使得宏观经济信息宣布对金融市场和投资者而言已非全新信息，与之相对应的传统资产价格与宏观经济政策之间传递溢出效应的估计也因此而有失偏颇。本文以政策预期为视角，通过构建改进的C-GARCH模型，在特别设计区分宏观经济信息的预见与未预见部分的基础上，分别从政策异质性与行业差异性层面细致分析了我国股票价格波动与宏观经济变量的关联互动，并借助扩展的T-GARCH模型进行了稳...
Enhancing Estimation for Interest Rate Diffusion Models with Bond Prices
Interest Rate Models Affine Term Structure Bond Prices Market Price of Risk Combined Estimation Parameter Estimation
2016/1/26
We consider improving estimating parameters of diffusion processes for interest rates by incorporating information in bond prices. This is designed to improve the estimation of the drift parameters, w...
Law of large numbers for branching symmetric Hunt processes with measure-valued branching rates
Law of large numbers branching Hunt processes spine approach h-transform spectral gap
2016/1/26
We establish weak and strong law of large numbers for a class of branching symmetric Hunt processes with the branching rate being a smooth measure with respect to the underlying Hunt process, and the ...
Strong law of large numbers for supercritical superprocesses under second moment condition
superprocess scaling limit theorem Hunt process spec- tral gap h-transform martingale measure
2016/1/26
Strong law of large numbers for supercritical superprocesses under second moment condition.
Bias Correction for Fixed Effects Spatial Panel Data Models
Bootstrap Spatial Panel Individual Fixed Effects Time Fixed Effects
2016/1/26
This paper examines the finite sample properties of the quasi maximum likelihood (QML) esti-mators of the fixed effects spatial panel data (FE-SPD) models of Lee and Yu (2010). Following the general b...
Spatial Weights Matrix Selection and Model Averaging for Spatial Autoregressive Models
Model Selection Model Averaging Spatial Econometrics Spatial Autoregressive
2016/1/26
Spatial econometrics relies on spatial weights matrix to specify the cross sectional depen-dence, which might not be unique. This paper proposes a model selection procedure to choose an optimal weight...
High Dimensional Generalized Empirical Likelihood for Moment Restrictions with Dependent Data
Generalized empirical likelihood High dimensionality Penalized likelihood Variable selec- tion
2016/1/26
This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on parameters identified by high dimensional moment restrictions with weakly dependent data when the di...
FUNCTIONAL COEFFICIENT MOVING AVERAGE MODEL WITH APPLICATIONS TO FORECASTING CHINESE CPI
Moving Average model functional coefficient model fore- casting Consumer Price Index
2016/1/26
This article establishes the functional coefficient moving average mod-el (FMA), which allows the coefficient of the classical moving average model to adapt with a covariate. The functional coefficien...
Functional central limit theorems for supercritical superprocesses
Functional central limit theorem supercritical superprocess excursion measures of superprocesses
2016/1/26
In this paper, we establish some functional central limit theorems for a large class of general supercritical superprocesses with spatially dependent branching mechanisms satisfying a second moment co...
Estimating Mixture of Gaussian Processes by Kernel Smoothing
Identifiability EM algorithm Kernel regression Gaussian process Functional principal component analysis
2016/1/26
When the functional data are not homogeneous, e.g., there exist multiple classes of func-tional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimati...