Replication Data for: Sleeping with the Enemy: Effective Representation Under Dynamic Electoral Competitiondoi:10.7910/DVN/LFLCMAHarvard Dataverse2021-10-081Frey, Anderson; Lopez-Moctezuma, Gabriel; Montero, Sergio, 2021, "Replication Data for: Sleeping with the Enemy: Effective Representation Under Dynamic Electoral Competition", https://doi.org/10.7910/DVN/LFLCMA, Harvard Dataverse, V1, UNF:6:TRYrJb+wJrhFYbZE+jUKbQ== [fileUNF]Replication Data for: Sleeping with the Enemy: Effective Representation Under Dynamic Electoral Competitiondoi:10.7910/DVN/LFLCMAFrey, AndersonLopez-Moctezuma, GabrielMontero, SergioMontero, SergioHarvard DataverseFrey, AndersonLopez-Moctezuma, GabrielMontero, SergioMontero, Sergio2021-06-10Social SciencesElectoral coalitionsEntrenched incumbencyDynamic electoral competitionRegression discontinuity designStructural estimationElectoral coalitions between ideologically incompatible parties---among other unconventional electoral strategies---may seem to threaten effective representation, signaling a breakdown of programmatic politics. However, this perspective overlooks parties' and voters' dynamic considerations. We propose and estimate a model of dynamic electoral competition in which a short-term ideology compromise, via an electoral coalition, offers opposition parties (and voters) the opportunity to remove an entrenched incumbent party from office, thus leveling the playing field in the future. This tradeoff provides a previously unrecognized rationale for coalition formation in elections. We take our model to data from Mexican municipal elections between 1995-2016 and show that coalitions between parties on opposite ends of the ideology spectrum have served as an instrument of democratic consolidation.This dataset underwent an independent verification process that replicated the tables and figures in the primary article. For the supplementary materials, verification was performed solely for the successful execution of code. The verification process was carried out by the Odum Institute for Research in Social Science at the University of North Carolina at Chapel Hill. <br></br> The associated article has been awarded Open Materials and Open Data Badges. Learn more about the Open Practice Badges from the <a href="https://osf.io/tvyxz/wiki/home/" target="_blank">Center for Open Science</a>.<br></br> <img src="https://odum.unc.edu/files/2020/03/OpenData_PR-1.png" alt="Open Data Badge" height="77" width="80"> <img src="https://odum.unc.edu/files/2020/03/OpenMaterials_PR-1.png" alt="Open Materials Badge" height="77" width="80">INEGI2, State and Municipal Public Finances. 1989-2018. Municipal budget breakdown. https://en.www.inegi.org.mx/programas/finanzas/ [Retrieved March 1, 2017]. Additional instructions: (1) Go to "Open Data" and select the desired year to download the files under "annual municipal"; (2) From each file, aggregate by municipality the total expenses (EGRESOS), and the social spending (INVERSIÓN PÚBLICA or Public works and social actions); (3) aggregate all municipality-year data in one file.<br></br> TSE, Repositório de Dados Eleitorais. 2000-2016. Election results for all municipal elections in Brazil. http://www.tse.jus.br/eleicoes/estatisticas/repositorio-de-dados-eleitorais-1/repositorio-de-dados-eleitorais [Retrieved March 1, 2019]. Additional instructions: (1) Use the left-side menu. For results click on "Resultados"; (2) Select the election year, (3) Download the files. For results: "Votação nominal por município e zona". The files in the replication dataset only include the variables that were relevant for the empirical exercise.<br></br> CONAPO http://www.conapo.gob.mx/es/CONAPO/Datos_Abiertos_del_Indice_de_Marginacion [Retrieved February 1, 2017]. Additional instructions: Select "Índice de marginación por municipio 1990 - 2015"<br></br> SNIM http://www.http://www.snim.rami.gob.mx [Retrieved February 1, 2017]. Additional instructions: The raw data is in "Base de Datos: Poblacion".<br></br> INE https://portal.ine.mx/voto-y-elecciones/procesos-electorales-anteriores [Retrieved February 1, 2017].Additional instructions: Electoral returns at the municipal level are computed based on original data from INE and from local state electoral authorities. Electoral coalition data was handcoded from coalition agreements submittted to the state electoral authorities and obtained via freedom of information requests.The <i>American Journal of Political Science</i> and the Odum Institute for Research in Social Science are not responsible for the accuracy or quality of data uploaded within the <i>AJPS</i> Dataverse, for the use of those data, or for interpretations or conclusions based on their use.This dataset is made available with limited information on how it can be used. You may wish to communicate with the Contact(s) specified before use.Frey, Anderson, Gabriel Lopez-Moctezuma, and Sergio Montero. [date]. “Sleeping with the Enemy: Effective Representation Under Dynamic Electoral Competition.” <i>American Journal of Political Science</i> Forthcoming. <a href="http://ajps.org/" target="_blank">http://ajps.org/</a>Frey, Anderson, Gabriel Lopez-Moctezuma, and Sergio Montero. [date]. “Sleeping with the Enemy: Effective Representation Under Dynamic Electoral Competition.” <i>American Journal of Political Science</i> Forthcoming. <a href="http://ajps.org/" 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