Publications

 

Book:

Spatial Analysis for the Social Sciences. 2015. New York: Cambridge University Press, Analytical Methods for Social Research Series.

ThePlot blog post about this book

 

 

 

 

 

 

 

 

 

 

Articles and Book Chapters:

 

A Spatial Analysis of the Impact of West German Television on Protest Mobilization During the East German Revolution. With Charles Crabtree and Holger Kern. Journal of Peace Research 52(3): 269-284.

We examine whether West German television broadcasts served as a coordination device for anti-regime protests during the East German revolution. Our paper makes use of a detailed dataset on protest events during the revolution and exploits the fact that West German television broadcasts could not be received in all parts of East Germany. Combining a radio propagation signal model with a spatial conditional frailty gap time survival model, we find no evidence to support the widely accepted claim that West German television served as a coordination device for protests in East Germany.

Featured in the Washington Postís Monkey Cage blog.

Data

 

Bringing Together Spatial Demography and Political Science: Reexamining the Big Sort. With Ryan Strickler. Forthcoming In Recapturing Space: New Middle-Range Theory in Spatial Demography, eds. Frank M. Howell, Jeremy R. Porter, and Stephen A. Matthews, Volume 1, Spatial Demography Series. Dordrecht: Springer.

Demographers and political scientists are increasingly expressing interest in modeling the spatial dimensions of their theories. To date, however, these research agendas have progressed along separate tracks. We examine how the research interests of both sets of scholars can be brought together by reexamining a concern of scholars in both disciplines: the possible geographic sorting of partisans into Democratic and Republican locales.

 

Modeling Spatial Heterogeneity with Geographically Weighted Regressions in R. The Political Methodologist 19(2): 7-12.

Scholars are increasingly interested in modeling behavioral heterogeneity, but little of this research to date has focused on spatial heterogeneity. This article examines how scholars can modeled the spatial heterogeneity that is likely to exist in many social science applications via Geographically Weighted Regressions using the spgwr package in R. I examine the strengths and limitations of the current version of the spgwr package and provide an application to voting behavior during the New Deal realignment.

 

The Dynamics of Critical Realignments: An Analysis Across Time and Space. With Peter F. Nardulli. Political Behavior 32(2): 255-283.

Critical realignments may be produced by any of three dynamics: the conversion of active partisans, the mobilization of non-voters, or the demobilization of active voters. In this paper, we identify the dynamics responsible for all city- and county-level critical realignments in presidential voting in the United States since 1828. We find that most critical change has been produced by the conversion of active partisans, with mobilization playing an increasing role in the 20th century as the non-voting population increased. The findings are encouraging from a normative perspective, as they argue that citizens have been able to reject past partisan loyalties during periods of crisis to hold political elites accountable. We also move beyond existing studies to identify the sources of realignment dynamics. Political factors, such as the strength of state and local parties and demographic factors such as changes in the size of local immigrant populations have each favored particular realignment dynamics in American electoral history.

 

Reexamining the Calculus of Voting. Political Psychology 31(2): 149-174.

This paper applies social cognitive theory to the study of voter turnout, examining the effects of self-efficacy on citizensí decisions of whether or not to vote. Consistent with recent arguments in cognitive psychology (Fenton-O-Creevy, Nicholson, Soane, and Willman 2003, 2005), I argue that excessive perceptions of self-efficacy lead some citizens to overestimate their voteís impact in close elections and to vote as a consequence of these perceptions. Employing cross-sectional and panel data, I find that citizens with high levels of self-efficacy are more likely to be moved to vote by perceptions that an election will be close than are citizens with low levels of self-efficacy.

 

Bayesian Spatial Survival Models for Political Event Processes. American Journal of Political Science 53(1): 241-257.

In this paper, I examine random effects survival models for spatially correlated event processes. These models differ from standard frailty modeling approaches by allowing for spatially correlated random effects at neighboring locations. In this paper, I examine spatially dependent random effects models for both semiparametric Cox and parametric Weibull models and examine both individual and shared frailty models. The Bayesian approach presents an effective approach for political scientists wishing to account for spatial dependence in their models of political event processes.

Code and Data

 

The Aggregate Dynamics of Campaigns. With Janet M. Box-Steffensmeier and Christian A. Farrell. Journal of Politics 71(1): 309-323.

Studies of campaign effects confront an inherent simultaneity problem ó just as campaign expenditures may increase voter support, so also may voter support increase campaign donations. In this paper, we address this endogeneity problem by applying a vector autoregression (VAR) analysis to examine how campaign expenditures, voter support, and media coverage influenced each other on a daily basis during the 2000 presidential campaign. Our results identify the direct effects of campaign expenditures on voter support independent of any potential simultaneity bias. At the same time, they highlight the critical and interdependent roles that elites, citizens, and the media play in shaping campaign dynamics and the outcomes of elections. Recipient of the Journal of Politics Best Paper Award.

Web Appendix for The Aggregate Dynamics of Campaigns.

Data: ICPSR Study 26901

 

The Political Geography of the New Deal Realignment. American Politics Research 36(6): 934-961.

This article applies spatial analyses to examine the political geography of voting during the 1928-1936 Democratic realignment. The results challenge some of our common conceptions of this realignment. For example, Al Smith enjoyed widespread increases in Democratic support in largely rural Western locales in 1928. In 1932, higher rates of unemployment impeded shifts toward Franklin Roosevelt and the Democrats. Geographically Weighted Regressions demonstrate that the political geography of the New Deal realignment was shaped by extensive geographic variation in how political and demographic factors influenced voting across the United States.

 

Bayesian Spatial Survival Analysis in WinBUGS. The Political Methodologist 15(1): 4-8.

Two of the most positive and visible developments in political methodology in the past decade have been the increased use of Markov Chain Monte Carlo (MCMC) methods and spatial analysis by political scientists.† This article examines how scholars can link Bayesian and spatial analyses by employing the GeoBUGS module in WinBUGS. I examine the strengths and limitations of the current version of GeoBUGS and provide an application to spatial survival analysis.

 

The Political Geography of Macro-Level Turnout in American Political Development. Political Geography 25(2): 123-150.

This article examines spatial dependence in macro-level turnout from the advent of Jacksonian democracy through the contested election of 2000. Several regimes of high and low voter participation are identified for the first time, including a westward expansion of participation following the Civil War. Employing spatial econometrics, the article identifies the impact of political factors such as partisan competition and voting laws on the political geography of macro-level turnout.

 

Elite Cues and Citizen Disagreement with Expert Opinion. Political Research Quarterly 58(3): 381-395.

This article presents and tests a new evaluative standard for citizen decision making: the correspondence of citizen opinion with that of public policy experts. Employing this evaluative criterion, the article demonstrates that the political environment can either aid or hinder citizen decision making, depending upon the cues provided by political elites. I find significant partisan and source effects in cue taking: citizens are more likely to disagree with expert opinion when elites they support disagree with this opinion. Recipient of the Political Research Quarterly Best Article Award.

 

 

 

 

 

 

Contact Info:

Department of Political Science

University of South Carolina

350 Gambrell Hall

Columbia, SC 29208

Office: (803) 777-5440

darmofal@gmail.sc.edu

darmofal@mailbox.sc.edu

 

David Darmofal

Associate Professor

Political Science

University of South Carolina