A Nonparametric Panel Model for Climate Data with Seasonal and Spatial Variation
Jiti Gao (),
Oliver Linton and
Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge
In this paper, we consider a panel data model which allows for heterogeneous time trends at diï¬€erent locations. We propose a new estimation method for the panel data model before we establish an asymptotic theory for the proposed estimation method. For inferential purposes, we develop a bootstrap method for the case where weak correlation presents in both dimensions of the error terms. We examine the ï¬ niteâ€“sample properties of the proposed model and estimation method through extensive simulated studies. Finally, we use the newly proposed model and method to investigate rainfall, temperature and sunshine data of U.K. respectively. Overall, we ï¬ nd the weather of winter has changed dramatically over the past ï¬ fty years. Changes may vary with respect to locations for the other seasons.
Keywords: Bootstrap method; Interactive ï¬ xedâ€“eï¬€ect; Panel rainfall data; Time trend (search for similar items in EconPapers)
JEL-codes: C23 Q50 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-env
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Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:2239
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