Rodríguez Aguilar, Román
Main Affiliation
Preferred name
Rodríguez Aguilar, Román
Official Name
Rodríguez Aguilar, Román
ORCID
0000-0002-6496-4453
Researcher ID
AAO-6158-2020
Scopus Author ID
56717663000
98 results
Settings
Now showing 1 - 10 of 98
- Some of the metrics are blocked by yourconsent settings
Item type:Publication, Estimating Conditional Labor Productivity Penalties from Non-Communicable Diseases Using Double Machine Learning: Evidence from Mexican Household Data(MDPI AG, 2026) ;Domínguez-Miranda, Sergio Arturo; Non-communicable diseases (NCDs) represent a growing challenge for developing countries, as they are among the leading causes of morbidity and mortality within the working-age population. Beyond their effects on health outcomes, NCDs are associated with reductions in labor productivity, which may influence long-term development dynamics through human capital. This study estimates the conditional labor productivity penalty associated with Non-Communicable Diseases (NCDs) among employed workers in Mexico using an observational high-dimensional framework. By addressing high-dimensional confounding under the Conditional Independence Assumption (CIA), the analysis isolates the relationship between NCD status and hourly labor earnings. Using microdata from the Mexican National Survey of Household Income and Expenditure, labor productivity is defined as the ratio of labor income to hours worked. To obtain robust causal estimates, a Double Machine Learning (DML) framework is implemented, integrating regularized regression and machine learning algorithms to control for high-dimensional confounding factors. These covariates include socioeconomic, demographic, and health-related variables, allowing for flexible adjustment of observable heterogeneity across individuals. The empirical findings demonstrate a statistically significant conditional negative penalty of −11.44% (p = 1.03 × 10−11, 95% CI: [−14.59, −8.40]) on hourly labor earnings under the cross-fitted DML specification using XGBoost and Random Forest. To resolve an observational measurement artifact where chronic individuals report artificially inflated hourly wages due to severe hours contraction, a presenteeism adjustment factor ((Formula presented.)) was calibrated. Incorporating this presenteeism correction, the aggregate national economic burden among the employed population is estimated at approximately 496.82 billion pesos annually. The findings suggest that NCDs constitute a relevant constraint on labor productivity at the microeconomic level. The study highlights the importance of prevention-oriented health strategies, workplace health promotion, and early disease management. From a methodological perspective, the results illustrate the usefulness of Double Machine Learning for purging high-dimensional confounding in cross-sectional survey data, providing robust conditional empirical benchmarks for public health policy. © 2026 by the authors. © MPDI © Applied Sciences. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Impuestos en botanas. Su impacto en precio y consumo en México(Fondo de Cultura Económica, 2017) ;Aguilera Aburto, Nelly; ;Sansores Martínez, Diana Nicte-HáGutiérrez Delgado, CristinaAntecedentes: Para contribuir al control de la epidemia de sobrepeso y obesidad en México, se implementó, a partir de enero de 2014, una estrategia integral que incluye un impuesto a bebidas azucaradas y a un grupo de alimentos con alto contenido calórico, entre los que se encuentran las botanas. En este artículo analizamos cómo se comportan los precios de las botanas ante el incremento de los impuestos y estimamos el posible impacto del incremento en precios en el consumo.Métodos: Para el análisis de precios aplicamos un modelo de datos panel con tres escenarios y un modelo de series de tiempo interrumpidas. Para la estimación del posible impacto del incremento en precios en el consumo desarrollamos escenarios de elasticidad y tasas de impuesto. En ambos casos usamos información pública del INEGI.Resultados: Del análisis de precios, los resultados indican que la industria transfirió el impuesto al precio en las botanas en su totalidad. Asimismo muestran que el impuesto vigente de 2014 a 2016 generó una disminución moderada del consumo. Las estimaciones del impacto en el consumo indican que una mayor tasa impositiva generaría mayores disminuciones de consumo y que la medida impositiva sería más efectiva si las demandas son elásticas.Conclusiones: Los resultados proporcionan información para replantear el nivel de tasa impositiva y alertar sobre la necesidad de evaluar la estrategia en su conjunto. ©2017 Fondo de Cultura Económica, Los autores.13Scopus© Citations 9 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Preface: Intelligent Computing and Optimization : Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 (ICO2023) : Volume 4(Springer, 2023) ;Vasant, Pandian ;Weber, Gerhard-Wilhelm ;Arefin, Mohammad Shamsul; Panchenko, VladimirThe sixth edition of the International Conference on Intelligent Computing and Optimization (ICO’2023) was held during April 27–28, 2023, at G Hua Hin Resort and Mall, Hua Hin, Thailand. The objective of the international conference is to bring the global research scholars, experts and scientists in the research areas of intelligent computing and optimization from all over theworld to share their knowledge and experiences on the current research achievements in these fields. This conference provides a golden opportunity for global research community to interact and share their novel research results, findings and innovative discoveries among their colleagues and friends. The proceedings of ICO’2023 is published by SPRINGER (in the book series Lecture Notes in Networks and Systems) and indexed by SCOPUS. ©2023 Springer, ©2023 The authors.16 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Preface: Intelligent Computing and Optimization : Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 (ICO2023) : Volume 3(Springer, 2023) ;Vasant, Pandian ;Weber, Gerhard-Wilhelm ;Arefin, Mohammad Shamsul; Panchenko, VladimirThe sixth edition of the International Conference on Intelligent Computing and Optimization (ICO’2023) was held during April 27–28, 2023, at G Hua Hin Resort and Mall, Hua Hin, Thailand. The objective of the international conference is to bring the global research scholars, experts and scientists in the research areas of intelligent computing and optimization from all over theworld to share their knowledge and experiences on the current research achievements in these fields. This conference provides a golden opportunity for global research community to interact and share their novel research results, findings and innovative discoveries among their colleagues and friends. The proceedings of ICO’2023 is published by SPRINGER (in the book series Lecture Notes in Networks and Systems) and indexed by SCOPUS. ©2023 Springer, ©2023 The authors.19 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Short-term generation planning by primal and dual decomposition techniques(Universidad Nacional de Colombia, Facultad de Minas, 2015) ;Marmolejo Saucedo, José AntonioThis paper addresses the short-term generation planning (STGP) through thermoelectric units. The mathematical model is presented as a Mixed Integer Non Linear Problem (MINLP). Several works on the state of art of the problem have revealed that the computational effort of this problem grows exponentially with the number of time periods and number of thermoelectric units. Therefore, we present two alternatives to solve a STGP based on Benders’ partitioning algorithm and Lagrangian relaxation in order to reduce the computational effort. The proposal is to apply primal and dual decomposition techniques, which exploit the structure of the problem to reduce solution time by decomposing the STGP into a master problem and a subproblem. For Benders’ algorithm, the master problem is a Mixed Integer Problem (MIP) and for the subproblem, it is a Non Linear Problem (NLP). For Lagrangian relaxation, the master problem and the subproblem are MINLP. The computational experiments show the performance of both decomposition techniques applied to the STGP. These techniques allow us to save computation time when compared to some high performance commercial solvers. ©Universidad Nacional de Colombia: Facultad de Minas, Los autores.Scopus© Citations 2 29 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, El coeficiente de Hurst y el parámetro α-estable para el análisis de series financieras Aplicación al mercado cambiario mexicano(Universidad Nacional Autónoma de México, Facultad de Contaduría y Administración, 2014)Este trabajo aborda la utilidad de estimar, previo a cualquieranálisis, el parámetro de la distribución -estable y el coeficientede Hurst para una serie financiera en periodos de altavolatilidad. Mediante la estimación del coeficiente de Hurst yel parámetro se busca explorar la violación de dos grandessupuestos en la modelación de series financieras: suponer quelas series presentan una distribución normal y que los rendimientossucesivos son independientes; asimismo, se analiza elcaso del tipo de cambio Fix peso-dólar en México en el periodo1992-2011. Uno de los principales resultados es la identificaciónde características fractales y colas pesadas en la seriepara algunos periodos en magnitudes diferenciadas; dichasdiferencias se acentúan en periodos de crisis. Caracterizar laserie mediante estos parámetros a través de un índice permitirámejorar la toma de decisiones sobre el tipo de análisis que esmetodológicamente correcto aplicar en una ventana de tiempoespecífica, ya sea para valuación de activos o para la gestiónde riesgos. ©2012 Universidad Nacional Autónoma de México, Facultad de Contaduría y Administración © El autor.10 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Modeling responsible technologies using multiagent system for climate crisis and sustainability(Elsevier, 2025) ;Nanda, Pragyan ;Sahoo, Sipra; ;Marmolejo-Saucedo, José AntonioBehera, ItishreeThis chapter delves into the dynamic landscape of responsible technologies and their crucial role in addressing the climate crisis and advancing sustainability. It highlights the need to understand the intricate connections between technology adoption, environmental impact, and societal behavior across various dimensions of sustainability, including environmental, social, economic, cultural, technological, political, ethical, health, educational, and adaptive aspects. The chapter introduces the concept of responsible technologies and their key principles, emphasizing real-world experimentation limitations and simulation advantages, particularly through a multiagent system (MAS). It explores different modeling approaches, focusing on the suitability of MAS for studying responsible technologies, along with considerations in its implementation. A step-by-step guide is provided for constructing a tailored MAS model for responsible technologies, incorporating real-world data and environmental factors. Findings and insights from MAS simulations are analyzed, shedding light on the implications of responsible technology adoption across these sustainability dimensions. The chapter also underscores the pivotal role of a MAS in comprehensively modeling responsible technologies and invites further research exploration in this expansive domain, serving as a comprehensive guide for researchers, policymakers, and stakeholders committed to leveraging responsible technologies for climate change mitigation and sustainability advancement. ©The authors ©Elsevier.24 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Machine Learning Applied to the Measurement of Quality in Health Services in Mexico: The Case of the Social Protection in Health System(2018); ;Marmolejo Saucedo, José AntonioVasant, PandianTo propose a satisfaction indicator of users of health services affiliated to the Social Protection System in Health (SPSS). Identify the effect of the main factors that are directly related to the satisfaction level and perception of quality of health services. A machine-learning model based on Logistic Models and Principal Components was developed to estimate a satisfaction index. The survey data collected for the “SPSS 2014 User’s Satisfaction Study” was used, considering a sample of 28,290 users. The proposed model shows, in general, the positive perception of quality of health services (national average 0.0756). There are factors statistically significant that influence these results, the good perception of infrastructure (OR:2.12; CI 95%:1.9–2.36); the gratuity of the service provided (OR:1.98; CI 95%: 1.42–2.76); and full medicines supply (OR:1.81; CI 95%:1.91–2.36). The proposed index can be used as an indicator for improving health care quality of the population covered by the SPSS. © 2019, Springer Nature Switzerland AG.Scopus© Citations 1 1 13 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Preface: Intelligent Computing and Optimization : Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 (ICO2023) : Volume 1(Springer, 2023) ;Vasant, Pandian ;Weber, Gerhard-Wilhelm ;Arefin, Mohammad Shamsul; Panchenko, VladimirThe sixth edition of the International Conference on Intelligent Computing and Optimization (ICO’2023) was held during April 27–28, 2023, at G Hua Hin Resort and Mall, Hua Hin, Thailand. The objective of the international conference is to bring the global research scholars, experts and scientists in the research areas of intelligent computing and optimization from all over theworld to share their knowledge and experiences on the current research achievements in these fields. This conference provides a golden opportunity for global research community to interact and share their novel research results, findings and innovative discoveries among their colleagues and friends. The proceedings of ICO’2023 is published by SPRINGER (in the book series Lecture Notes in Networks and Systems) and indexed by SCOPUS. ©2023 Springer, ©2023 The authors.20 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Liberalization of the Mexican Electricity Sector: A Study of Technical Efficiency(2019); Marmolejo Saucedo, José AntonioThis article discusses the recent reform implemented in the Mexican electricity sector. As part of the structural reforms carried out in Mexico during the last 6 years (2012–2018), the opening of this sector to foreign capital, the creation of a wholesale electricity market, and the end of the monopoly of a CFE (Federal Electricity Commission, a government company) are the main changes. This study addresses an estimation of technical efficiency of power thermal units within the framework of the liberalization of the Mexican electricity market. These estimations are relevant because a single supplier, even before liberalization, must form a portfolio of the most efficient plants to be able to compete in the electricity market. The main results show the composition of a set of power thermal plants that are the most efficient of the total number of plants in operation and that could represent CFE in the wholesale electricity market. © Springer Nature Switzerland AG 2019.3 3
