spuR

spuR implements diagnostics and correction methods for spatial unit roots developed by Müller & Watson 2024 in R.

This package implements low-frequency spatial unit root tests and spatial transformations for cross-sectional data as developed by Müller & Watson 2024. A practical guide to these methods can be found in Becker, Boll and Voth 2026.

Installation

Install from GitHub:

# install.packages("remotes")
remotes::install_github("spatial-spur/scpcR@v0.1.3")
remotes::install_github("spatial-spur/spuR@v0.1.2")

GitHub installation does not guarantee the declared scpcR version is updated, so make sure both versions are up to date by installing the tagged version explicitly.

Usage

library(spuR)
data(spur_example)

# Spatial I(0) test
spurtest_i0(am ~ 1, data = spur_example, lon = "lon", lat = "lat", seed = 42)

# Spatial I(1) test
spurtest_i1(am ~ 1, data = spur_example, lon = "lon", lat = "lat", seed = 42)

# Residual-based I(0) test
spurtest_i0resid(am ~ gini, data = spur_example, lon = "lon", lat = "lat", seed = 42)

# Half-life confidence interval
spurhalflife(am ~ 1, data = spur_example, lon = "lon", lat = "lat", seed = 42)

# Spatial transformation — pass your analysis formula to transform all variables
out <- spurtransform(am ~ gini + fracblack, data = spur_example,
                     lon = "lon", lat = "lat", transformation = "lbmgls")
head(out[, c("h_am", "h_gini", "h_fracblack")])

Documentation

Please refer to the package documentation for detailed information and other (R, Python, Stata) packages.

Citation

If you use this package, please cite Becker, Boll and Voth 2026 and Müller & Watson 2024. See CITATION.bib for the BibTeX entries.

References

Mueller, U. K. and Watson, M. W. (2024). Spatial Unit Roots and Spurious Regression. Econometrica, 92(5), 1661-1695. doi: 10.3982/ECTA21654