Fragilidad institucional y sostenibilidad fiscal en Centroamérica un enfoque cuántico y contrafactual estructural
Contenido principal del artículo
Resumen
El estudio analiza la fragilidad institucional y la sostenibilidad fiscal en los países del Sistema de la Integración Centroamericana (SICA) mediante un enfoque cuántico y contrafactual. Se desarrolla un modelo funcional basado en la teoría cuántica de campos para estimar trayectorias metaestables de fragilidad soberana e identificar transiciones críticas entre regímenes de estabilidad. Además, se construye un índice ESG soberano mediante análisis factorial y se aplica el control sintético extendido para evaluar el impacto de reformas institucionales y eventos relevantes durante 2008–2023. Los resultados muestran que la calidad de la gobernanza, el control de la corrupción y la cohesión social reducen la vulnerabilidad fiscal, mientras que las debilidades institucionales amplifican los efectos de choques externos. En conjunto, el modelo propuesto constituye una herramienta empírica para anticipar escenarios de fragilidad estructural y orientar políticas de sostenibilidad macroinstitucional en Centroamérica.
Descargas
Detalles del artículo

Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
Los autores afirman reconocer que la Revista de Fomento Social asume como suyos los derechos de propiedad intelectual sobre sus trabajos y otorgan a la revista los permisos de distribución y comunicación pública de los mismos establecidos en las declaraciones de Berlin, Bethesda y Budapest; razón por la cual aceptan que el trabajo que se presenta sea distribuido en acceso abierto, resguardando los derechos de autor bajo una licencia “Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0 (CC BY-NC-ND).
Se puede copiar, usar, difundir, transmitir y exponer públicamente siempre que:
Citen la autoría del trabajo, la publicación en Revista de Fomento Social, número, año y las páginas en la que encontraron la información.
No se puede obtener ningún beneficio comercial.
Se anima a los autores a difundir el artículo vía electrónica (Revista de Fomento Social, número, año, paginación, ISSN, DOI, etc.), para favorecer su circulación y difusión, aumentar en su citación y alcance entre la comunidad académica.
La información de la revista se facilitará a Dulcinea
Citas
Abadie, A. (2021). Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects. Journal of Economic Literature, 59(2), 391–425. https://doi.org/10.1257/jel.20191450
Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493–505. https://doi.org/10.1198/jasa.2009.ap08746
Abadie, A., & Gardeazabal, J. (2003). The Economic Costs of Conflict: A Case Study of the Basque Country. American Economic Review, 93(1), 113–132. https://doi.org/10.1257/000282803321455188
Adhikari, B. (2022). A Guide to Using the Synthetic Control Method to Quantify the Effects of Shocks, Policies, and Shocking Policies. The American Economist, 67(1), 46–63. https://doi.org/10.1177/05694345211019714
Alaminos, D., Salas, M. B., & Fernández-Gámez, M. A. (2024). GLOBAL PATTERNS AND EXTREME EVENTS IN SOVEREIGN RISK PREMIA: A FUZZY S DEEP LEARNING COMPARATIVE. Technological and Economic Development of Economy, 30(3), 753–782. https://doi.org/10.3846/tede.2024.20488
Allison, P. D. (2009). Missing data. The SAGE Handbook of Quantitative Methods in Psychology, 23, 72–89.
Anand, A., Vanpée, R., & Lončarski, I. (2023). Sustainability and sovereign credit risk. International Review of Financial Analysis, 86, 102494. https://doi.org/10.1016/j.irfa.2023.102494
Ando, T., Greenwood-Nimmo, M., & Shin, Y. (2022). Quantile Connectedness: Modeling Tail Behavior in the Topology of Financial Networks. Management Science, 68(4), 2401–2431. https://doi.org/10.1287/mnsc.2021.3984
Andriyanov, N., Tashlinsky, A., & Dementiev, V. (2021). Detailed Clustering Based on Gaussian Mixture Models (pp. 437–448). https://doi.org/10.1007/978-3-030-55187-2_34
Baaquie, B. E. (2007). Quantum finance: Path integrals and Hamiltonians for options and interest rates. Cambridge University Press.
Barbier, E. B., & Burgess, J. C. (2021). Institutional Quality, Governance and Progress towards the SDGs. Sustainability, 13(21), 11798. https://doi.org/10.3390/su132111798
Barro, R. J., & Lee, J. W. (2013). A new data set of educational attainment in the world, 1950–2010. Journal of Development Economics, 104, 184–198. https://doi.org/10.1016/j.jdeveco.2012.10.001
Birlan, I., Davidescu, A. A., Tita, C.-E., & Nae, T. M. (2025). Modeling Regional ESG Performance in the European Union: A Partial Least Squares Approach to Sustainable Economic Systems. Mathematics, 13(15), 2337. https://doi.org/10.3390/math13152337
Boiciuc, I., & Orțan, D. (2020). Estimating the effects of fiscal policy on GDP growth in Romania in 2015-2017 using the synthetic control method. Post-Communist Economies, 32(6), 749–770. https://doi.org/10.1080/14631377.2020.1745559
Boitan, I. A. (2023). Fiscal sustainability in times of climate challenges: a multidimensional approach of the interlinkages between climate change and sovereign debt. Current Opinion in Environmental Sustainability, 65, 101387. https://doi.org/10.1016/j.cosust.2023.101387
Bonesini, O., Callegaro, G., & Jacquier, A. (2023). Functional quantization of rough volatility and applications to volatility derivatives. Quantitative Finance, 23(12), 1769–1792. https://doi.org/10.1080/14697688.2023.2273414
Bova, E., & Klyviene, V. (2020). Macroeconomic responses to fiscal shocks in Portugal. Journal of Economic Studies, 47(5), 1051–1069. https://doi.org/10.1108/JES-12-2018-0454
Capelle-Blancard, G., & Petit, A. (2019). Every Little Helps? ESG News and Stock Market Reaction. Journal of Business Ethics, 157(2), 543–565. https://doi.org/10.1007/s10551-017-3667-3
Cavallo, E., Galiani, S., Noy, I., & Pantano, J. (2013). Catastrophic Natural Disasters and Economic Growth. The Review of Economics and Statistics, 95(5), 1549–1561. https://doi.org/10.1162/REST_a_00413
Chari, A., Garcés, F., Martínez, J. F., & Valenzuela, P. (2024). Sovereign credit spreads, banking fragility, and global factors. Journal of Financial Stability, 72, 101235. https://doi.org/10.1016/j.jfs.2024.101235
Enders, C. K. (2022). Applied missing data analysis. Guilford Publications.
Ferman, B., & Pinto, C. (2021). Synthetic controls with imperfect pretreatment fit. Quantitative Economics, 12(4), 1197–1221. https://doi.org/10.3982/QE1596
Friede, G., Busch, T., & Bassen, A. (2015). ESG and financial performance: aggregated evidence from more than 2000 empirical studies. Journal of Sustainable Finance & Investment, 5(4), 210–233. https://doi.org/10.1080/20430795.2015.1118917
Gnimassoun, B., & Do Santos, I. (2021). Robust structural determinants of public deficits in developing countries. Applied Economics, 53(9), 1052–1076. https://doi.org/10.1080/00036846.2020.1824063
Gratcheva, E. (2024). Sovereign Environmental, Social, and Governance (ESG) Investing: Chasing Elusive Sustainability. IMF Working Papers, 2024(102), 1. https://doi.org/10.5089/9798400277054.001
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective (P. P. Hall, Ed.).
Haven, E., & Khrennikov, A. I. (2013). Quantum social science. Cambridge University Press.
Leung, C. K., Ko, J., & Chen, X. (2025). Economic crises and the erosion of sustainability: A global analysis of ESG performance in 100 countries (1990–2019). Innovation and Green Development, 4(2), 100226. https://doi.org/10.1016/j.igd.2025.100226
Little, R. J. A., & Rubin, D. B. (2019). Statistical analysis with missing data. John Wiley & Sons.
Little, R., & Rubin, D. (1987). Multiple imputation for nonresponse in surveys. Wiley, 10, 9780470316696.
Liu, Z., Cai, Z., Fang, Y., & Lin, M. (2020). Statistical Analysis and Evaluation of Macroeconomic Policies: A Selective Review. Applied Mathematics-A Journal of Chinese Universities, 35(1), 57–83. https://doi.org/10.1007/s11766-020-3775-1
Lozano, M. B., & Martínez-Ferrero, J. (2022). Do emerging and developed countries differ in terms of sustainable performance? Analysis of board, ownership and country-level factors. Research in International Business and Finance, 62, 101688. https://doi.org/10.1016/j.ribaf.2022.101688
Makridis, C. (2025). Toward a Quantum Model of Macroeconomic Stability: Tokenized Assets, Digital Twins, and Reduced Inflation. https://doi.org/10.2139/ssrn.5269697
Marín-Rodríguez, N. J., Gonzalez-Ruiz, J. D., & Botero, S. (2023). Assessing Fiscal Sustainability in the Landscape of Economics Research. Economies, 11(12), 300. https://doi.org/10.3390/economies11120300
Nagel, M. (2025). From vulnerability to stability? Latin American strategies to govern financial subordination. Competition & Change, 29(2), 163–182. https://doi.org/10.1177/10245294241313003
Nguyen, T. A. N., & Luong, T. T. H. (2021). Fiscal Policy, Institutional Quality, and Public Debt: Evidence from Transition Countries. Sustainability, 13(19), 10706. https://doi.org/10.3390/su131910706
Pascoal, F. B., Juwana, H., Karuniasa, M., & Djojokusumo, H. H. (2023). Sovereign ESG Integration: A Bibliometric and Systematic Literature Review. Studies in Business and Economics, 18(1), 231–260. https://doi.org/10.2478/sbe-2023-0013
Rahman, L., Rosten, J., Monroy, P., & Huang, S. (2021). Does ESG Matter for Sovereign Debt Investing? The Journal of Fixed Income, 31(1), 51–64. https://doi.org/10.3905/jfi.2021.1.112
Ramirez, A. G., Monsalve, J., González-Ruiz, J. D., Almonacid, P., & Peña, A. (2022). Relationship between the Cost of Capital and Environmental, Social, and Governance Scores: Evidence from Latin America. Sustainability, 14(9), 5012. https://doi.org/10.3390/su14095012
Schafer, J. L. (1997). Analysis of incomplete multivariate data. CRC press.
Segura, L. D., van Zeijl‐Rozema, A., & Martens, P. (2022). Climate change adaptation in Central America: A review of the national policy efforts. Latin American Policy, 13(2), 276–327. https://doi.org/10.1111/lamp.12277
Semet, R., Roncalli, T., & Stagnol, L. (2021). ESG and Sovereign Risk: What is Priced in by the Bond Market and Credit Rating Agencies? SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3940945
Skavysh, V., Priazhkina, S., Guala, D., & Bromley, T. R. (2023). Quantum monte carlo for economics: Stress testing and macroeconomic deep learning. Journal of Economic Dynamics and Control, 153, 104680. https://doi.org/10.1016/j.jedc.2023.104680
Sorokina, N., Booth, D. E., & Thornton, J. H. (2021). Robust Methods in Event Studies: Empirical Evidence and Theoretical Implications. Journal of Data Science, 11(3), 575–606. https://doi.org/10.6339/JDS.2013.11(3).1166
Williams, C. F. (2025). Diagnosing Strategic Fragility: A Causal Simulation Approach to Value Flow Disruption. https://doi.org/10.2139/ssrn.5277550
Xafa, M. (2023). Sovereign Debt Restructuring: The Way Forward. Journal of Globalization and Development, 13(2), 435–474. https://doi.org/10.1515/jgd-2021-0070
