Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-27T21:24:09.380Z Has data issue: false hasContentIssue false
  • English
  • Français

Interpretation: the final spatial frontier

Published online by Cambridge University Press:  18 June 2019

Guy D. Whitten ,
Laron K. Williams  and
Cameron Wimpy Open the ORCID record for Cameron Wimpy [Opens in a new window]
Guy D. Whitten
Affiliation:
Department of Political Science, Texas A&M University, 4348 TAMU College Station, TX77843, US
Laron K. Williams
Affiliation:
Department of Political Science, University of Missouri, 103 Professional Building, Columbia, MO, 65211, US
Cameron Wimpy*
Affiliation:
Department of Political Science, Massachusetts Institute of Technology, 77 Massachusetts AVE. E53–449 Cambridge, MA02139, US
*
*Corresponding author. E-mail: cwimpy@astate.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

The use of spatial econometric models in political science has steadily risen in recent years. However, the interpretation of these models has generally ignored the important substantive, and even spatial, nature of the estimated effects. This leaves many papers with a (non-spatial) interpretation of coefficients on the covariates and a brief discussion of the sign and strength of the spatial parameter. We introduce a general approach to interpreting spatial models and provide several avenues for an exposition of substantive spatial effects. Our approach can be generalized to most models in the spatial econometric taxonomy. Building on the example of the diffusion of democracy, we elucidate how our approach can be applied to modern political science problems.

Keywords

Spatial methods
Type
Original Article
Information
Political Science Research and Methods , Volume 9 , Issue 1 , January 2021 , pp. 140 - 156
Copyright
Copyright © The European Political Science Association 2019

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Beck, N, Gleditsch, KS and Beardsley, K (2006) Space is more than geography: using spatial econometrics in the study of political economy. International Studies Quarterly 50, 27–44.CrossRefGoogle Scholar
Brinks, D and Coppedge, M (2006) Diffusion is no illusion: neighbor emulation in the third wave of democracy. Comparative Political Studies 39, 463–489.CrossRefGoogle Scholar
Carsey, TM and Harden, JJ (2014) Monte Carlo Simulations and Resampling Methods for Social Science. Thousand Oaks, CA: Sage Publications.CrossRefGoogle Scholar
Cook, SJ, Hays, JC and Franzese, RJ (2015) Model specification and spatial interdependence. Paper presented at the 2015 Annual Meeting of POLMETH, In APSA Conference Paper. Available at http://www.sas.rochester.edu/psc/polmeth/papers/Cook\_Hays\_Franzese.pdf.Google Scholar
Darmofal, D (2015) Spatial Analysis for the Social Sciences. New York: Cambridge University Press.CrossRefGoogle Scholar
Elkins, Z and Simmons, B (2005) On waves, clusters, and diffusion: a conceptual framework. Annals of the American Academy of Political and Social Science 598, 33–51.CrossRefGoogle Scholar
Fortunato, D, Swift, CS and Williams, LK (2018) All economics is local: spatial aggregations of economic information. Political Science Research and Methods 6, 467–487.CrossRefGoogle Scholar
Franzese, RJ and Hays, JC (2006) Strategic interaction among EU governments in active labor market policy-making: subsidiarity and policy coordination under the European employment strategy. European Union Politics 7, 167–189.CrossRefGoogle Scholar
Franzese, RJ and Hays, JC (2007) Spatial econometric models of cross-sectional interdependence in political science panel and time-series-cross-section data. Political Analysis 15, 140–164.CrossRefGoogle Scholar
Garcia, BE and Wimpy, C (2016) Does information lead to emulation? Spatial dependence in anti-government violence. Political Science Research and Methods 4, 27–46.CrossRefGoogle Scholar
Gibbons, S and Overman, HG (2012) Mostly pointless spatial econometrics. Journal of Regional Science 52, 172–191.CrossRefGoogle Scholar
Gleditsch, KS and Ward, MD (2006) Diffusion and the international context of democratization. International Organization 60, 911–933.CrossRefGoogle Scholar
Halleck Vega, S and Elhorst, JP (2015) The SLX model. Journal of Regional Science 55, 339–363.CrossRefGoogle Scholar
Huntington, SP (1991) The Third Wave: Democratization in the Late Twentieth Century. Norman, OK: University of Oklahoma Press.Google Scholar
King, G, Tomz, M and Wittenberg, J (2000) Making the most of statistical analyses: improving interpretation and presentation. American Journal of Political Science 44, 347–361.CrossRefGoogle Scholar
LeSage, JP and Pace, RK (2009) Introduction to Spatial Econometrics. Boca Raton: Chapman & Hall/CRC.CrossRefGoogle Scholar
Morgan, SL and Winship, C (2007) Counterfactuals and Causal Inference: Methods and Principles for Social Research. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Neumayer, E and Plümper, T (2016) W. Political Science Research and Methods 4, 175–193.CrossRefGoogle Scholar
Pierskalla, JH and Hollenbach, FM (2013) Technology and collective action: the effect of cell phone coverage on political violence in Africa. American Political Science Review 107, 207–224.CrossRefGoogle Scholar
Plümper, T and Neumayer, E (2010) Model specification in the analysis of spatial dependence. European Journal of Political Research 49, 418–442.CrossRefGoogle Scholar
Shipan, CR and Volden, C (2008) The mechanisms of policy diffusion. American Journal of Political Science 52, 840–857.CrossRefGoogle Scholar
Ward, MD and Gleditsch, KS (2008) Spatial Regression Models, vol. 155, Thousand Oaks: Sage.CrossRefGoogle Scholar
Williams, LK (2015) It's all relative: spatial positioning of parties and ideological shifts. European Journal of Political Research 54, 141–159.CrossRefGoogle Scholar
Williams, LK, Seki, K and Whitten, GD (2016) You've got some explaining to do: the influence of economic conditions and spatial competition on party strategy. Political Science Research and Methods 4, 47–63.CrossRefGoogle Scholar
Supplementary material: Link

Whitten et al. Dataset

Dataset

https://doi.org/10.7910/DVN/RGDEET
Link
Supplementary material: PDF

Whitten et al. supplementary material

Whitten et al. supplementary material 1

Download Whitten et al. supplementary material(PDF)
PDF 157 KB