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Temporal and spatial homogeneity in air pollutants panel EKC estimations: Two nonparametric tests applied to Spanish provinces

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Abstract

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 (CH4, CO, CO2 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 timeseries 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.

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File URL: http://mpra.ub.uni-muenchen.de/5043/1/MPRA_paper_5043.pdf
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Bibliographic Info

Paper provided by IRENE Institute of Economic Research in its series IRENE Working Papers with number 07-01.

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Length: 31 pages
Date of creation: Aug 2007
Date of revision:
Handle: RePEc:irn:wpaper:07-01

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Keywords: Environmental Kuznets Curve; Air pollutants; Non/Semiparametric estimations; Poolability tests;

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Cited by:
  1. Ian Christensen & Fuchun Li, 2013. "A Semiparametric Early Warning Model of Financial Stress Events," Working Papers 13-13, Bank of Canada.

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