La mobilitat electoral en les eleccions de 2019 a la Comunitat Valenciana
DOI:
https://doi.org/10.28939/iam.debats.134-1.3Paraules clau:
transició de vot, inferència ecològica, eleccions espanyoles.Resum
La fragmentació política derivada de la crisi econòmica, social, política i institucional que va viure Espanya durant la Gran Recessió ha generat un panorama electoral en què l'oferta partidista, tant a a dretes com a esquerres, ha crescut de manera significativa. El número efectiu de partits parlamentaris és el més gran de la història, tant al Congrés dels Diputats com a les Corts Valencianes. Els electors disposen de més alternatives de vot i canvien la seua opció electoral amb més freqüència. En aquest escenari, aquest treball estima i analitza, a través de les matrius de transferència de vot, els moviments electorals que es van produir en les eleccions europees, generals, autonòmiques i locals celebrades durant 2019 en l'àmbit de la Comunitat Valenciana. Com a resultat més rellevant, s'hi constata la presència de continus moviments dins de cada bloc ideològic. En la dreta, els moviments s'han intensificat pel sorgiment de VOX, i en l'esquerra, s'han caracteritzat per una situació pràcticament líquida, de vasos comunicants, entre els electorats d'UP i Compromís, en què UP aglutinà una part rellevant de l'electorat conjunt en processos nacionals i Compromís quasi s’empassà UP en processos autonòmics i locals.
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Referències
Antentas, J. M. (2017). Spain: From the Indignados Rebellion to Regime Crisis (2011-2016). Labor History, 58(1), 106-131. DOI: 10.1080/0023656X.2016.1239875
Bacharach, M. (1970). Biproportional Matrices and Input-Output Change. Cambridge: Cambridge University Press. DOI: 10.1080/0953531042000219259
Becker, S., Fetzer, T., Novy, D. (2017). Who Voted for Brexit? A Comprehensive District-level Analysis. Economic Policy, 32(92), 601-650. DOI: 10.1093/epolic/eix017
Benedicto, J. y Ramos, M. (2018). Young People’s Critical Politicization in Spain in the Great Recession: A GenerationalReconfiguration? Societies, 8(89), 1-30. DOI: 10.3390/soc8030089
Biemer, P. P. (2010). Total Survey Error. Design, Implementation and Evaluation. Public Opinion Quarterly, 74, 817-848. DOI: 10.1093/poq/nfq058
Brown, P. J. y Payne, C. D. (1986). Aggregate Data, Ecological Regression and Voting Transitions. Journal of the American Statistical Association, 81, 453-460. DOI: 10.1007/978-3-642-11363-5_54
Cho, W. K. T. (1998). Iff the Assumption Fits…: A Comment on the King Ecological Inference Solution. Political Analysis, 7, 143-163. DOI: 10.1093/pan/7.1.143
CIS (2019a). Estudio n. 3.242. Macrobarómetro de marzo 2019. Preelectoral Elecciones Generales 2019. Nota metodológica. Modelos CIS V108.
CIS (2019b). Estudio n. 3.244. Preelectoral Elecciones Autonómicas 2019. Comunidad Valenciana. Nota metodológica. Modelos CIS V41.
CIS (2019c) Estudio n. 3.245. Macrobarómetro de abril 2019. Preelectoral Elecciones al Parlamento Europeo, Autonómicas y Municipales 2019.
Corominas A., Lusa, A., Valvet M. D. (2015). Computing Voter Transitions: The Elections for the Catalan Parliament, from 2010 to 2012. Journal of Industrial Engineering and Management, 8(1), 122-136. DOI: 10.1080/00207543.2018.1530477
Couperus, S. y Tortola. P. D. (2019). Right-wing Populism’s (Ab)use of the Past in Italy and the Netherlands. Debats. Journal on Culture, Power and Society, 4, 105-118.
Duncan, O. y Davis, B. (1953). An Alternative to Ecological Correlation. American Sociological Review, 18, 665-666. DOI: 10.1177/0193841X9101500602
Forcina, A. y Marchetti, G. M. (2011). The Brown and Payne Model of Voter Transition Revisited. En S. Ingrassia, R. Rocci, y M. Vichi (ed.), New Perspectives in Statistical Modeling and Data Analysis: Studies in Classification, Data Analysis, and Knowledge Organization. Berlín: Springer. DOI: 10.1007/978-3-642-11363-5_1
Füle, E. (1994). Estimating Voter Transitions by Ecological Regression. Electoral Studies, 13, 313-330.
DOI: 10.1016/0261-3794(94)90043-4.
Goodman, L. A. (1953). Ecological Regressions and the Behaviour of Individuals. American Sociological Review, 18, 663-666. DOI: 10.2307/2088122
Goodman, L. A. (1959). Some Alternatives to Ecological Correlation. American Journal of Sociology, 64(6), 610-625.
Greiner, D. y Quinn, K. M. (2010). Exit Polling and Racial Bloc Voting: Combining Individual-level and RxC Ecological Data. The Annals of Applied Statistics, 4, 1.774-1.796. DOI: 10.1214/10-AOAS353
Haunberger, S. (2010). The Effects of Interviewer, Respondent and Area Characteristics on Cooperation in Panel Surveys: a Multilevel Approach. Quality & Quantity, 44, 957-969. DOI:10.1007/s11135-009-9248-5
Hawkes, A. G. (1969). An Approach to the Analysis of Electoral Swing. Journal of the Royal Statistical Society, Series A, 132, 68-79. DOI: 10.2307/2343756
Hunter, W. y Power, T. J. (2019). Bolsonaro and Brazil’s Illiberal Backlash. Journal of Democracy, 30(1), 68-82.
King, G. (1997). A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data. Princeton, Nueva Jersey: Princeton University Press. DOI: 10.2307/2585686
King, G., Rosen, O., Tanner, M. A. (1999). Binomial-beta Hierarchical Models for Ecological Inference. Sociological Methods & Research, 28, 61-90. DOI: 10.1177/0049124199028001004
King, G., Rosen, O., Tanner, M. A. (ed.) (2004). Ecological Inference: New Methodological Strategies. Nueva York: Cambridge University Press.
Klima, A., Thurner, P. W., Molnar, C., Schlesinger, T., Küchenhoff, H. (2016). Estimation of Voter Transitions Based on Ecological Inference: An Empirical Assessment of Different Approaches. AStA — Advances in Statistical Analysis, 100, 133-159. DOI: 10.1007/s10182-015-0254-8
Klima, A., Schlesinger, T., Thurner, P. W., Küchenhoff, H. (2019). Combining Aggregate Data and Exit Polls for the Estimation of Voter Transitions. Sociological Methods & Research, 48(2), 296-325. DOI: 10.1177/0049124117701477
Krumpal, I. (2013). Determinants of Social Desirability Bias in Sensitive Surveys: A Literature Review. Quality & Quantity, 47, 2.025-2.047. DOI: 10.1007/s11135-011-9640-9
Laakso, M. y Taagepera, R. (1979). Effective Number of Parties: A Measure with Application to West Europe. Comparative Political Studies, 12, 3-27. DOI: 10.1177/001041407901200101
Martín-Cubas, J., Bodoque, A., Pavía, J.M., Tasa, V., Veres-Ferrer, E. (2019). The ‘Big Bang’ of the Populist Parties in the European Union. The 2014 European Parliament Election. Innovation —The European Journal of Social Science Research, 32(2), 168-190. DOI: 10.1080/13511610.2018.1523711
McCarthy, C., Ryan, T. M. (1977). Estimates of Voter Transition Probabilities from the British General Elections of 1974. Journal of the Royal Statistical Society. Series A, 140, 78-85. DOI: 10.2307/2344516
Miller, W. L. (1972). Measures of Electoral Change Using Aggregate Data. Journal of the Royal Statistical Society, Series A, 135, 122-142. DOI: 10.1111/rssb.12318
Orriols, L. y Cordero, G. (2016). The Breakdown of the Spanish Two-Party System: The Upsurge of Podemos and Ciudadanos in the 2015 General Election. South European Society and Politics, 21(4), 469-492. DOI: 10.1080/13608746.20 16.1151127
Park, W. (2008). Ecological Inference and Aggregate Analysis of Elections. (Tesis doctoral, Universidad de Michigan, Estados Unidos).
Pavía-Miralles, J. M. (2005). Forecasts from Non-Random Samples: The Election Night Case. Journal of the American Statistical Association, 100, 1.113-1.122. DOI: 10.1198/016214504000001835
Pavía, J. M. (2010). Improving Predictive Accuracy of Exit Polls. International Journal of Forecasting, 26, 68-81. DOI: 10.1016/j.ijforecast.2009.05.001
Pavía, J. M. (2016). Transferencia*Electoral, software registrado en la Universitat de València, número 9382. Fecha: 01/02/2016.
Pavía, J. M. y Aybar, C. (2018). Field Rules and Bias in Random Surveys with Quota Samples: An Assessment of CIS Surveys. SORT (Statistics and Operations Research Transactions), 42(2), 183-206. DOI: 10.2436/20.8080.02.74
Pavía, J. M. y Cantarino, I. (2017). Dasymetric Distribution of Votes in a Dense City. Applied Geography, 86, 22-31. DOI: 10.1016/j.apgeog.2017.06.021
Pavía, J. M. y López-Quilez, A. (2013). Spatial Vote Redistribution in Redrawn Polling Units. Journal of the Royal Statistical Society, Series A – Statistics in Society 176(3), 655-678. DOI: 10.1111/j.1467-985X.2012.01055.x
Pavía, J. M. y Veres Ferrer, E. J. (2016a). Un nuevo estimador para disgregar totales poblacionales: El caso de los nuevos electores. Anales de Economía Aplicada, XXX, 817-826.
Pavía Miralles, J. M. y Veres Ferrer, E. J. (2016b). Desagregando estadísticas de población. En J. M. Herrerías y J. Callejón (ed.), Investigaciones en métodos cuantitativos para la economía y la empresa (p. 543-555). Granada: Editorial Universidad de Granada.
Pavía, J. M., Badal, E., García-Cárceles, B. (2016). Spanish Exit Polls: Sampling Error or Nonresponse Bias? Revista Internacional de Sociología, 74(3), e043. DOI: 10.3989/ris.2016.74.3.043
Pavía, J. M., Bodoque, A., Martín, J. (2016). The Birth of a New Party: Podemos, a Hurricane in the Spanish Crisis of Trust. Open Journal of Social Sciences, 4, 67-86. DOI: 10.4236/jss.2016.49008
Pavía, J. M., Cabrer, B., Sala, R. (2009). Updating Input-Output Matrices: Assessing Alternatives through Simulation. Journal of Statistical Computation and Simulation, 79, 1.467-1.498. DOI: 10.1080/00949650802415154
Pavía, J. M., Gil-Carceller, I., Rubio-Mataix, A., Coll, V., Alvarez-Jareño, J. A., Aybar, C., Carrasco-Arroyo, S. (2019). The Formation of Aggregate Expectations: Wisdom of the Crowds or Media Influence? Contemporary Social Science, 14(1), 132-143. DOI: 10.1080/21582041.2017.1367831
Payne, C., Brown, P., Hanna, V. (1986). By-election Exit Polls. Electoral Studies, 5, 277-287. DOI: 10.1016/0261-3794(86)90015-6
Plescia, C. y De Sio, L. (2018). An Evaluation of the Performance and Suitability of R×C Methods for Ecological Inference with Known True Values. Quality & Quantity, 52(2), 669-683. DOI: 10.1007/s11135-017-0481-z
Puig, X. y Ginebra, J. (2015). Ecological Inference and Spatial Variation of Individual Behavior: National Divide and Elections in Catalonia. Geographical Analysis, 47(3), 262-283. DOI: 10.1111/gean.12056
Rama Caamaño, J. (2016). Ciclos electorales y sistema de partidos en España. Revista Jurídica Universidad Autónoma de Madrid, 34(II), 241-266. DOI: 10.1177/1354068815601347
Robinson, W. S. (1950). Ecological Correlations and the Behavior of Individuals. American Sociological Review, 15(3), 351-357. DOI: 10.2307/2087175
Romero, R. (2014). Un modelo matemático para estimar el trasvase de votos entre partidos. Revista Digital de la Real Academia de Cultura Valenciana, 3-23.
Romero, R. (2015). Trasvase de votos entre partidos en las elecciones autonómicas catalanas del 27 de septiembre de 2015. Revista Digital de la Real Academia de Cultura Valenciana, 3-15.
Romero, R. (2016). Movilidad electoral entre las elecciones del 20D y del 26J en las comunidades autónomas valenciana, madrileña y andaluza. Revista Digital de la Real Academia de Cultura Valenciana. Segunda época, 1,1-25.
Romero, R., Pavía, J. M., Martín, J., Romero, G. (2019). Assessing Uncertainty of Voter Transitions Estimated from Aggregated Data: Application to 2017 French Presidential Elections, en revisión.
Rosen, O., Jiang, W., King, G., Tanner, M. A. (2001). Bayesian and Frequentist Inference for Ecological Inference: The RxC Case. Statistica Neerlandica, 55, 134-56. DOI: 10.1111/1467-9574.00162
Royo, S. (2014). Institutional Degeneration and the Economic Crisis in Spain. American Behavioral Scientist, 58(12), 1.568-1.591. DOI: 10.1177/0002764214534664
Skonieczny, A. (2018). Emotions and Political Narratives: Populism, Trump and Trade. Politics and Governance, 6(4), 62-72. DOI: 10.17645/pag.v6i4.1574
Torcal, M. (2014). The Decline of Political Trust in Spain and Portugal: Economic Performance or Political Responsiveness? American Behavioral Scientist, 58(12), 1.542-1.567. DOI: 10.1177/0002764214534662
Wakefield, J. (2004). Ecological Inference for 2x2 Tables (with discussion). Journal of Royal Statistical Society, Series A, 167, 385-445. DOI: 10.1111/j.1467-985x.2004.02046
Bacharach, M. (1970). Biproportional Matrices and Input-Output Change. Cambridge: Cambridge University Press. DOI: 10.1080/0953531042000219259
Becker, S., Fetzer, T., Novy, D. (2017). Who Voted for Brexit? A Comprehensive District-level Analysis. Economic Policy, 32(92), 601-650. DOI: 10.1093/epolic/eix017
Benedicto, J. y Ramos, M. (2018). Young People’s Critical Politicization in Spain in the Great Recession: A GenerationalReconfiguration? Societies, 8(89), 1-30. DOI: 10.3390/soc8030089
Biemer, P. P. (2010). Total Survey Error. Design, Implementation and Evaluation. Public Opinion Quarterly, 74, 817-848. DOI: 10.1093/poq/nfq058
Brown, P. J. y Payne, C. D. (1986). Aggregate Data, Ecological Regression and Voting Transitions. Journal of the American Statistical Association, 81, 453-460. DOI: 10.1007/978-3-642-11363-5_54
Cho, W. K. T. (1998). Iff the Assumption Fits…: A Comment on the King Ecological Inference Solution. Political Analysis, 7, 143-163. DOI: 10.1093/pan/7.1.143
CIS (2019a). Estudio n. 3.242. Macrobarómetro de marzo 2019. Preelectoral Elecciones Generales 2019. Nota metodológica. Modelos CIS V108.
CIS (2019b). Estudio n. 3.244. Preelectoral Elecciones Autonómicas 2019. Comunidad Valenciana. Nota metodológica. Modelos CIS V41.
CIS (2019c) Estudio n. 3.245. Macrobarómetro de abril 2019. Preelectoral Elecciones al Parlamento Europeo, Autonómicas y Municipales 2019.
Corominas A., Lusa, A., Valvet M. D. (2015). Computing Voter Transitions: The Elections for the Catalan Parliament, from 2010 to 2012. Journal of Industrial Engineering and Management, 8(1), 122-136. DOI: 10.1080/00207543.2018.1530477
Couperus, S. y Tortola. P. D. (2019). Right-wing Populism’s (Ab)use of the Past in Italy and the Netherlands. Debats. Journal on Culture, Power and Society, 4, 105-118.
Duncan, O. y Davis, B. (1953). An Alternative to Ecological Correlation. American Sociological Review, 18, 665-666. DOI: 10.1177/0193841X9101500602
Forcina, A. y Marchetti, G. M. (2011). The Brown and Payne Model of Voter Transition Revisited. En S. Ingrassia, R. Rocci, y M. Vichi (ed.), New Perspectives in Statistical Modeling and Data Analysis: Studies in Classification, Data Analysis, and Knowledge Organization. Berlín: Springer. DOI: 10.1007/978-3-642-11363-5_1
Füle, E. (1994). Estimating Voter Transitions by Ecological Regression. Electoral Studies, 13, 313-330.
DOI: 10.1016/0261-3794(94)90043-4.
Goodman, L. A. (1953). Ecological Regressions and the Behaviour of Individuals. American Sociological Review, 18, 663-666. DOI: 10.2307/2088122
Goodman, L. A. (1959). Some Alternatives to Ecological Correlation. American Journal of Sociology, 64(6), 610-625.
Greiner, D. y Quinn, K. M. (2010). Exit Polling and Racial Bloc Voting: Combining Individual-level and RxC Ecological Data. The Annals of Applied Statistics, 4, 1.774-1.796. DOI: 10.1214/10-AOAS353
Haunberger, S. (2010). The Effects of Interviewer, Respondent and Area Characteristics on Cooperation in Panel Surveys: a Multilevel Approach. Quality & Quantity, 44, 957-969. DOI:10.1007/s11135-009-9248-5
Hawkes, A. G. (1969). An Approach to the Analysis of Electoral Swing. Journal of the Royal Statistical Society, Series A, 132, 68-79. DOI: 10.2307/2343756
Hunter, W. y Power, T. J. (2019). Bolsonaro and Brazil’s Illiberal Backlash. Journal of Democracy, 30(1), 68-82.
King, G. (1997). A Solution to the Ecological Inference Problem: Reconstructing Individual Behavior from Aggregate Data. Princeton, Nueva Jersey: Princeton University Press. DOI: 10.2307/2585686
King, G., Rosen, O., Tanner, M. A. (1999). Binomial-beta Hierarchical Models for Ecological Inference. Sociological Methods & Research, 28, 61-90. DOI: 10.1177/0049124199028001004
King, G., Rosen, O., Tanner, M. A. (ed.) (2004). Ecological Inference: New Methodological Strategies. Nueva York: Cambridge University Press.
Klima, A., Thurner, P. W., Molnar, C., Schlesinger, T., Küchenhoff, H. (2016). Estimation of Voter Transitions Based on Ecological Inference: An Empirical Assessment of Different Approaches. AStA — Advances in Statistical Analysis, 100, 133-159. DOI: 10.1007/s10182-015-0254-8
Klima, A., Schlesinger, T., Thurner, P. W., Küchenhoff, H. (2019). Combining Aggregate Data and Exit Polls for the Estimation of Voter Transitions. Sociological Methods & Research, 48(2), 296-325. DOI: 10.1177/0049124117701477
Krumpal, I. (2013). Determinants of Social Desirability Bias in Sensitive Surveys: A Literature Review. Quality & Quantity, 47, 2.025-2.047. DOI: 10.1007/s11135-011-9640-9
Laakso, M. y Taagepera, R. (1979). Effective Number of Parties: A Measure with Application to West Europe. Comparative Political Studies, 12, 3-27. DOI: 10.1177/001041407901200101
Martín-Cubas, J., Bodoque, A., Pavía, J.M., Tasa, V., Veres-Ferrer, E. (2019). The ‘Big Bang’ of the Populist Parties in the European Union. The 2014 European Parliament Election. Innovation —The European Journal of Social Science Research, 32(2), 168-190. DOI: 10.1080/13511610.2018.1523711
McCarthy, C., Ryan, T. M. (1977). Estimates of Voter Transition Probabilities from the British General Elections of 1974. Journal of the Royal Statistical Society. Series A, 140, 78-85. DOI: 10.2307/2344516
Miller, W. L. (1972). Measures of Electoral Change Using Aggregate Data. Journal of the Royal Statistical Society, Series A, 135, 122-142. DOI: 10.1111/rssb.12318
Orriols, L. y Cordero, G. (2016). The Breakdown of the Spanish Two-Party System: The Upsurge of Podemos and Ciudadanos in the 2015 General Election. South European Society and Politics, 21(4), 469-492. DOI: 10.1080/13608746.20 16.1151127
Park, W. (2008). Ecological Inference and Aggregate Analysis of Elections. (Tesis doctoral, Universidad de Michigan, Estados Unidos).
Pavía-Miralles, J. M. (2005). Forecasts from Non-Random Samples: The Election Night Case. Journal of the American Statistical Association, 100, 1.113-1.122. DOI: 10.1198/016214504000001835
Pavía, J. M. (2010). Improving Predictive Accuracy of Exit Polls. International Journal of Forecasting, 26, 68-81. DOI: 10.1016/j.ijforecast.2009.05.001
Pavía, J. M. (2016). Transferencia*Electoral, software registrado en la Universitat de València, número 9382. Fecha: 01/02/2016.
Pavía, J. M. y Aybar, C. (2018). Field Rules and Bias in Random Surveys with Quota Samples: An Assessment of CIS Surveys. SORT (Statistics and Operations Research Transactions), 42(2), 183-206. DOI: 10.2436/20.8080.02.74
Pavía, J. M. y Cantarino, I. (2017). Dasymetric Distribution of Votes in a Dense City. Applied Geography, 86, 22-31. DOI: 10.1016/j.apgeog.2017.06.021
Pavía, J. M. y López-Quilez, A. (2013). Spatial Vote Redistribution in Redrawn Polling Units. Journal of the Royal Statistical Society, Series A – Statistics in Society 176(3), 655-678. DOI: 10.1111/j.1467-985X.2012.01055.x
Pavía, J. M. y Veres Ferrer, E. J. (2016a). Un nuevo estimador para disgregar totales poblacionales: El caso de los nuevos electores. Anales de Economía Aplicada, XXX, 817-826.
Pavía Miralles, J. M. y Veres Ferrer, E. J. (2016b). Desagregando estadísticas de población. En J. M. Herrerías y J. Callejón (ed.), Investigaciones en métodos cuantitativos para la economía y la empresa (p. 543-555). Granada: Editorial Universidad de Granada.
Pavía, J. M., Badal, E., García-Cárceles, B. (2016). Spanish Exit Polls: Sampling Error or Nonresponse Bias? Revista Internacional de Sociología, 74(3), e043. DOI: 10.3989/ris.2016.74.3.043
Pavía, J. M., Bodoque, A., Martín, J. (2016). The Birth of a New Party: Podemos, a Hurricane in the Spanish Crisis of Trust. Open Journal of Social Sciences, 4, 67-86. DOI: 10.4236/jss.2016.49008
Pavía, J. M., Cabrer, B., Sala, R. (2009). Updating Input-Output Matrices: Assessing Alternatives through Simulation. Journal of Statistical Computation and Simulation, 79, 1.467-1.498. DOI: 10.1080/00949650802415154
Pavía, J. M., Gil-Carceller, I., Rubio-Mataix, A., Coll, V., Alvarez-Jareño, J. A., Aybar, C., Carrasco-Arroyo, S. (2019). The Formation of Aggregate Expectations: Wisdom of the Crowds or Media Influence? Contemporary Social Science, 14(1), 132-143. DOI: 10.1080/21582041.2017.1367831
Payne, C., Brown, P., Hanna, V. (1986). By-election Exit Polls. Electoral Studies, 5, 277-287. DOI: 10.1016/0261-3794(86)90015-6
Plescia, C. y De Sio, L. (2018). An Evaluation of the Performance and Suitability of R×C Methods for Ecological Inference with Known True Values. Quality & Quantity, 52(2), 669-683. DOI: 10.1007/s11135-017-0481-z
Puig, X. y Ginebra, J. (2015). Ecological Inference and Spatial Variation of Individual Behavior: National Divide and Elections in Catalonia. Geographical Analysis, 47(3), 262-283. DOI: 10.1111/gean.12056
Rama Caamaño, J. (2016). Ciclos electorales y sistema de partidos en España. Revista Jurídica Universidad Autónoma de Madrid, 34(II), 241-266. DOI: 10.1177/1354068815601347
Robinson, W. S. (1950). Ecological Correlations and the Behavior of Individuals. American Sociological Review, 15(3), 351-357. DOI: 10.2307/2087175
Romero, R. (2014). Un modelo matemático para estimar el trasvase de votos entre partidos. Revista Digital de la Real Academia de Cultura Valenciana, 3-23.
Romero, R. (2015). Trasvase de votos entre partidos en las elecciones autonómicas catalanas del 27 de septiembre de 2015. Revista Digital de la Real Academia de Cultura Valenciana, 3-15.
Romero, R. (2016). Movilidad electoral entre las elecciones del 20D y del 26J en las comunidades autónomas valenciana, madrileña y andaluza. Revista Digital de la Real Academia de Cultura Valenciana. Segunda época, 1,1-25.
Romero, R., Pavía, J. M., Martín, J., Romero, G. (2019). Assessing Uncertainty of Voter Transitions Estimated from Aggregated Data: Application to 2017 French Presidential Elections, en revisión.
Rosen, O., Jiang, W., King, G., Tanner, M. A. (2001). Bayesian and Frequentist Inference for Ecological Inference: The RxC Case. Statistica Neerlandica, 55, 134-56. DOI: 10.1111/1467-9574.00162
Royo, S. (2014). Institutional Degeneration and the Economic Crisis in Spain. American Behavioral Scientist, 58(12), 1.568-1.591. DOI: 10.1177/0002764214534664
Skonieczny, A. (2018). Emotions and Political Narratives: Populism, Trump and Trade. Politics and Governance, 6(4), 62-72. DOI: 10.17645/pag.v6i4.1574
Torcal, M. (2014). The Decline of Political Trust in Spain and Portugal: Economic Performance or Political Responsiveness? American Behavioral Scientist, 58(12), 1.542-1.567. DOI: 10.1177/0002764214534662
Wakefield, J. (2004). Ecological Inference for 2x2 Tables (with discussion). Journal of Royal Statistical Society, Series A, 167, 385-445. DOI: 10.1111/j.1467-985x.2004.02046
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2020-05-29
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Pavia, J. M. and Aybar, C. (2020) “La mobilitat electoral en les eleccions de 2019 a la Comunitat Valenciana”, Debats. Revista de cultura, poder i societat, 134(1), pp. 27–51. doi: 10.28939/iam.debats.134-1.3.
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