arXiv · 2207.04082
Spatial Econometrics for Misaligned Data
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.
Explore related subjects
Keep this discovery
Guillaume Allaire Pouliot. 2022-07-08. Spatial Econometrics for Misaligned Data. https://arxiv.org/abs/2207.04082
Cite the original work for its findings. Save a collection to share your selection of sources.