Therefore, this paper introduces environment tax variable to utility function and makes experiential analysis by building a panel data model in the coastal area in Jiangsu province.
对此，将环境税收引入效用函数进行数理分析，并以江苏沿海区域为例，构建面板数据模型进行实证研究。
This paper builds a conditional two-factor measure model, and proves the efficiency of this model using panel data regression skill. The samples are 54 Chinese close-end funds.
基于此，本文构建了条件双因子评价模型，并且以中国全部54只封闭式基金为样本采用面板数据回归技巧验证了该模型的有效性。
It also calculates the conditional convergence speed of the province by applying Solow-Swan model with panel data, and finds that a slow but steady catch-up does exist in the province.
利用斯旺-索洛模型，借助面板数据，对福建省各地区经济增长条件收敛进行分析，估算条件收敛速度，揭示了福建省落后地区以较低速度实现对发达地区的赶超的事实。
Considering spatial spillover effects of outputs and inputs, a modified knowledge production spatial panel data model is established.
在综合考虑知识产出和投入空间溢出效应的基础上，构建了改进的知识生产空间面板数据模型。
As a kind of economics model, the panel data can be viewed as the two-way design of co-variables.
平行数据模型是一类线性经济模型，这些模型可以看作协变量的双向设计。
Panel data model is a roper method for investigating the influencing factor and driving mechanism of spatial pattern change of grain production.
面板数据模型是探讨粮食生产空间格局变化的影响因素与驱动机制的适宜方法。
The model may be used by the adorner panel as a data binding target.
可供装饰器面板用作数据绑定目标的模型。
Finally it establishes a fixed effect variable intercept model to check financial structure differences with panel data of 11 cities in Zhejiang.
最后采用浙江省11市的面板数据，建立固定效应变截距模型检验各市金融结构与经济增长的关系。
This paper constructs a dynamic adjustment model of capital structure and employs the dynamic panel data methodology to make empirical study of Chinese-listed companies.
本文引入调整成本这一概念，构建了资本结构的动态调整模型。
Therefore, the identification of outliers in panel data model is a very important work.
因此该面板数据模型异常值的识别问题是一项重要的研究工作。
Through panel data model, we find that the impacts of real interest rates is negative, inflation volatility has a significant negative impact on debt maturity structure.
面板数据模型研究表明，实际利率的影响是负的，通胀波动性对债务期限结构有显著的负影响。
Also, the paper use an individual-time fixed panel data model to build a more real acts equation than the cross section data model, and compare with traditional factors.
运用个体时点固定效应的面板数据模型，构建比横截面数据模型更为真实的行为方程，并与传统的区位因素进行比较分析。
Also, the paper use an individual-time fixed panel data model to build a more real acts equation than the cross section data model, and compare with traditional factors.
运用个体时点固定效应的面板数据模型，构建比横截面数据模型更为真实的行为方程，并与传统的区位因素进行比较分析。
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