Spatial Econometrics for Misaligned Data
Econometrics
2022-07-12 v1 Methodology
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.
Keywords
Cite
@article{arxiv.2207.04082,
title = {Spatial Econometrics for Misaligned Data},
author = {Guillaume Allaire Pouliot},
journal= {arXiv preprint arXiv:2207.04082},
year = {2022}
}