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首页> 外文期刊>Environmental & Resource Economics >Temporal and Spatial Homogeneity in Air Pollutants Panel EKC Estimations Two Nonparametric Tests Applied to Spanish Provinces
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Temporal and Spatial Homogeneity in Air Pollutants Panel EKC Estimations Two Nonparametric Tests Applied to Spanish Provinces

机译：空气污染物面板中的时空同质性EKC估计应用于西班牙省份的两个非参数检验

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Although panel data have been used intensively by a wealth of studies investigating the GDP-pollution relationship, the poolability assumption used to model these data is almost never addressed. This paper applies a strategy to test the poolability assumption with methods robust to functional misspecification. Nonparametric poolability tests are performed to check the temporal and spatial homogeneity of the panel and their results are compared with the conventional F-tests for a balanced panel of 48 Spanish provinces on four air pollutant emissions (CH_4, CO, CO_2 and NMVOC) over the 1990-2002 period. We show that temporal homogeneity may allow the pooling of the data and drive to well-defined nonparametric and parametric cross-sectional U-inverted shapes for all air pollutants. However, the presence of spatial heterogeneity makes this shape compatible with different time-series patterns in every province-mainly increasing or decreasing depending on the pollutant. These results highlight the extreme sensitivity of the income-pollution relationship to region- or country-specific factors.
机译：尽管许多调查GDP污染关系的研究都大量使用了面板数据，但几乎从未解决用于建模这些数据的可合并性假设。本文采用一种策略来测试可合并性假设，并采用对功能错误指定具有鲁棒性的方法。进行非参数可汇集性测试以检查面板的时间和空间均一性，并将其结果与常规F检验进行比较，该F检验针对48个西班牙省的平衡面板，对四个空气污染物排放量（CH_4，CO，CO_2和NMVOC）进行了分析。 1990年至2002年。我们表明，时间均匀性可以允许汇总数据并驱动所有空气污染物的定义明确的非参数和参数横截面U形。但是，空间异质性的存在使该形状与每个省的不同时间序列模式兼容-主要取决于污染物的增加或减少。这些结果凸显了收入-污染关系对特定地区或特定国家因素的极端敏感性。

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