References
Anselin, Luc. 1988. Spatial Econometrics:
Methods and Models. Studies in
Operational Regional Science. Dordrecht:
Kluwer.
———. 1995. “Local Indicators of Spatial
Association-LISA.” Geographical Analysis 27 (2):
93–115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x.
———. 2003. “Spatial Externalities, Spatial
Multipliers, and Spatial Econometrics.”
International Regional Science Review 26 (2): 153–66. https://doi.org/10.1177/0160017602250972.
Anselin, Luc, and Anil K. Bera. 1998. “Spatial
Dependence in Linear Regression Models with an
Introduction to Spatial Econometrics.”
In Handbook of Applied Economic Statistics, edited
by Aman Ullah and David E. A. Giles, 237–89. New York:
Dekker.
Anselin, Luc, Anil K. Bera, Raymond Florax, and Mann J. Yoon. 1996.
“Simple Diagnostic Tests for Spatial
Dependence.” Regional Science and Urban Economics
26 (1): 77–104. https://doi.org/10.1016/0166-0462(95)02111-6.
Beron, Kurt J., and Wim P. M. Vijverberg. 2004. “Probit in a
Spatial Context: A Monte Carlo
Analysis.” In Advances in Spatial
Econometrics: Methodology, Tools and
Applications, edited by Luc Anselin, Florax, Raymond
J. G. M, and Sergio J. Rey, 169–95. Berlin, Heidelberg:
Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-05617-2‗
8.
Betz, Timm, Scott J. Cook, and Florian M. Hollenbach. 2020.
“Spatial Interdependence and Instrumental Variable Models.”
Political Science Research and Methods 8 (4): 646–61. https://doi.org/10.1017/psrm.2018.61.
Bivand, Roger S., and Colin Rudel. 2018. “Rgeos:
Interface to Geometry Engine - Open
Source (’GEOS’).”
Bivand, Roger, Giovanni Millo, and Gianfranco Piras. 2021. “A
Review of Software for Spatial
Econometrics in R.” Mathematics 9
(11): 1276. https://doi.org/10.3390/math9111276.
Bivand, Roger, and David W. S. Wong. 2018. “Comparing
Implementations of Global and Local Indicators of Spatial
Association.” TEST 27 (3): 716–48. https://doi.org/10.1007/s11749-018-0599-x.
Brunsdon, Chris, A. Stewart Fotheringham, and Martin E. Charlton. 1996.
“Geographically Weighted Regression: A
Method for Exploring Spatial
Nonstationarity.” Geographical Analysis 28 (4):
281–98. https://doi.org/10.1111/j.1538-4632.1996.tb00936.x.
Cliff, Andrew, and Keith Ord. 1972. “Testing for Spatial
Autocorrelation Among Regression Residuals.”
Geographical Analysis 4 (3): 267–84. https://doi.org/10.1111/j.1538-4632.1972.tb00475.x.
Cook, Scott J., Jude C. Hays, and Robert J. Franzese. 2020. “Model
Specification and Spatial
Interdependence.” In The Sage Handbook of
Research Methods in Political Science and International Relations,
edited by Luigi Curini and Robert Franzese, 1st ed, 730–47.
Thousand Oaks: SAGE Inc.
Drukker, David M., Peter Egger, and Ingmar R. Prucha. 2013. “On
Two-Step Estimation of a Spatial Autoregressive
Model with Autoregressive Disturbances and
Endogenous Regressors.” Econometric Reviews
32 (5-6): 686–733. https://doi.org/10.1080/07474938.2013.741020.
Franzese, Robert J., and Jude C. Hays. 2007. “Spatial
Econometric Models of Cross-Sectional
Interdependence in Political Science Panel and
Time-Series-Cross-Section Data.” Political
Analysis 15 (2): 140–64. https://doi.org/10.1093/pan/mpm005.
Franzese, Robert J., Jude C. Hays, and Scott J. Cook. 2016.
“Spatial- and Spatiotemporal-Autoregressive Probit
Models of Interdependent Binary Outcomes.”
Political Science Research and Methods 4 (01): 151–73. https://doi.org/10.1017/psrm.2015.14.
Gibbons, Steve, and Henry G. Overman. 2012. “Mostly
Pointless Spatial Econometrics?” Journal of
Regional Science 52 (2): 172–91. https://doi.org/10.1111/j.1467-9787.2012.00760.x.
Gollini, Isabella, Binbin Lu, Martin Charlton, Christopher Brunsdon, and
Paul Harris. 2015. “GWmodel : An R
Package for Exploring Spatial Heterogeneity Using
Geographically Weighted Models.” Journal of
Statistical Software 63 (17). https://doi.org/10.18637/jss.v063.i17.
Halleck Vega, Solmaria, and J. Paul Elhorst. 2015. “The SLX
Model.” Journal of Regional Science 55 (3):
339–63. https://doi.org/10.1111/jors.12188.
Kelejian, Harry H., and Gianfranco Piras. 2017. Spatial
Econometrics. Elsevier. https://doi.org/10.1016/C2016-0-04332-2.
Kelejian, Harry H., and Ingmar R. Prucha. 1998. “A
Generalized Spatial Two-Stage Least Squares Procedure for
Estimating a Spatial Autoregressive Model with
Autoregressive Disturbances.” The Journal of
Real Estate Finance and Economics 17 (1): 99–121. https://doi.org/10.1023/A:1007707430416.
———. 1999. “A Generalized Moments Estimator for the
Autoregressive Parameter in a Spatial
Model.” International Economic Review 40 (2):
509–33. https://doi.org/10.1111/1468-2354.00027.
———. 2010. “Specification and Estimation of
Spatial Autoregressive Models with
Autoregressive and Heteroskedastic
Disturbances.” Journal of Econometrics 157 (1):
53–67. https://doi.org/10.1016/j.jeconom.2009.10.025.
Kelejian, Harry H., Ingmar R. Prucha, and Yevgeny Yuzefovich. 2004.
“Instrumental Variable Estimation of a Spatial
Autoregressive Model with Autoregressive
Disturbances: Large and Small Sample
Results.” In Spatial and Spatiotemporal
Econometrics, edited by James P. LeSage and R. Kelley Pace,
163–98. Advances in Econometrics. Amsterdam and
Boston: Elsevier.
Klier, Thomas, and Daniel P. McMillen. 2008. “Clustering of
Auto Supplier Plants in the United States:
Generalized Method of Moments Spatial Logit
for Large Samples.” Journal of Business &
Economic Statistics 26 (4): 460–71.
Lacombe, Donald J., and James P. LeSage. 2018. “Use and
Interpretation of Spatial Autoregressive Probit Models.” The
Annals of Regional Science 60 (1): 1–24. https://doi.org/10.1007/s00168-015-0705-x.
Lee, Lung-fei. 2004. “Asymptotic Distributions of
Quasi-Maximum Likelihood Estimators for Spatial
Autoregressive Models.” Econometrica 72 (6):
1899–1925.
LeSage, James P. 2014. “What Regional Scientists Need
to Know about Spatial Econometrics.”
The Review of Regional Studies 44 (1): 13–32.
https://doi.org/https://dx.doi.org/10.2139/ssrn.2420725.
LeSage, James P., and R. Kelley Pace. 2009. Introduction to
Spatial Econometrics. Statistics,
Textbooks and Monographs. Boca
Raton: CRC Press.
———. 2014. “The Biggest Myth in Spatial
Econometrics.” Econometrics 2 (4): 217–49. https://doi.org/10.3390/econometrics2040217.
Lovelace, Robin, Jakub Nowosad, and Jannes Muenchow. 2019.
Geocomputation with R. 1st ed. Chapman &
Hall/CRC the R Series. Boca
Raton: Chapman & Hall/CRC.
McMillen, Daniel P. 1992. “Probit with Spatial
Autocorrelation.” Journal of Regional Science 32
(3): 335–48. https://doi.org/10.1111/j.1467-9787.1992.tb00190.x.
Moran, P. A. P. 1950. “Notes on Continuous Stochastic
Phenomena.” Biometrika 37 (1/2): 17. https://doi.org/10.2307/2332142.
Neumayer, Eric, and Thomas Plümper. 2016. “W.”
Political Science Research and Methods 4 (01): 175–93. https://doi.org/10.1017/psrm.2014.40.
Ord, John Keith. 1975. “Estimation Methods for
Models of Spatial Interaction.”
Journal of the American Statistical Association 70 (349):
120–26. https://doi.org/10.2307/2285387.
Pace, R. Kelley, and James P. LeSage. 2010. “Omitted
Variable Biases of OLS and Spatial Lag
Models.” In Progress in Spatial
Analysis, edited by Antonio Páez, Julie Gallo, Ron N.
Buliung, and Sandy Dall’erba, 17–28. Berlin and Heidelberg:
Springer.
Pebesma, Edzer, and Roger Bivand. 2023. Spatial Data
Science: With Applications in R.
First. Boca Raton: Chapman and Hall/CRC. https://doi.org/10.1201/9780429459016.
Rüttenauer, Tobias. 2022. “Spatial Regression Models:
A Systematic Comparison of Different Model
Specifications Using Monte Carlo Experiments.”
Sociological Methods & Research 51 (2): 728–59. https://doi.org/10.1177/0049124119882467.
Sarrias, Mauricio. 2023. Intermediate Spatial
Econometrics with Applications in
R.
Tobler, Waldo R. 1970. “A Computer Movie Simulating Urban
Growth in the Detroit Region.” Economic
Geography 46: 234–40. https://doi.org/10.2307/143141.
Wimpy, Cameron, Guy D. Whitten, and Laron K. Williams. 2021. “X
Marks the Spot: Unlocking the
Treasure of Spatial-X Models.” The
Journal of Politics 83 (2): 722–39. https://doi.org/10.1086/710089.
Wooldridge, Jeffrey M. 2010. Econometric Analysis of
Cross Section and Panel Data.
Cambridge, Mass.: MIT Press.