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Toward Sustainable Economic Growth: A Spatial Panel Data Analysis of Regional Income Convergence in US BEA Economic Areas

机译:迈向可持续的经济增长:美国BEA经济区区域收入趋同的空间面板数据分析

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A question fundamental to sustainable economic growth is whether a poor region tends to grow faster than a rich one, such that the poor region catches up with the rich region in terms of the level of per capita income. In this article, we apply the spatial panel data approach to the analysis of regional income convergence across 177 economic areas in the contiguous US states over the period from 1969 to 2009. Using data on per capita incomes in the functionally defined economic areas, we find that the absolute value of the estimated coefficient of the initial per capita income decreases in the spatial and time-period fixed effects spatial lag model and increases in the spatial and time-period fixed effects spatial error model. This result implies that the growth rate in a specific economic area will be not only directly affected by an exogenous shock introduced into that economic area but also be impacted more by both the indirect effects of the first-order neighboring economic areas and the induced effects of the higher-order neighboring economic areas. This gives helpful hints on the issue of spatial interaction and regional policy coordination to start a virtuous circle of sustainable economic growth.
机译:可持续经济增长的一个基本问题是,贫困地区的增长速度是否往往快于富裕地区,从而使贫困地区的人均收入水平赶上了富裕地区。在本文中,我们使用空间面板数据方法来分析1969年至2009年期间美国毗连州177个经济区的区域收入趋同。使用功能定义的经济区的人均收入数据,我们发现初始人均收入估计系数的绝对值在空间和时间固定效应空间滞后模型中减小,在空间和时间固定效应空间误差模型中增大。这一结果表明,特定经济区的增长率不仅将受到引入该经济区的外来冲击的直接影响,而且还将受到一阶邻近经济区的间接影响和经济活动的诱发影响的更大影响。高阶邻近经济区。这为空间互动和区域政策协调问题提供了有益的提示,从而开始了可持续经济增长的良性循环。

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