Spatial Econometrics for Misaligned Data

Guillaume Allaire Pouliot

Papers from arXiv.org

Abstract: We produce methodology for regression analysis when the geographic locations of the independent and dependent variables do not coincide, in which case we speak of misaligned data. We develop and investigate two complementary methods for regression analysis with misaligned data that circumvent the need to estimate or specify the covariance of the regression errors. We carry out a detailed reanalysis of Maccini and Yang (2009) and find economically significant quantitative differences but sustain most qualitative conclusions.

Date: 2022-07
New Economics Papers: this item is included in nep-ecm, nep-geo and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2207.04082

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