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
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Item type:Publication, Estimating Conditional Labor Productivity Penalties from Non-Communicable Diseases Using Double Machine Learning: Evidence from Mexican Household Data(MDPI AG, 2026); 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, Short-term generation planning by primal and dual decomposition techniques(Universidad Nacional de Colombia, Facultad de Minas, 2015)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, Preface: Intelligent Computing and Optimization : Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 (ICO2023) : Volume 3(Springer, 2023); 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, Preface: Intelligent Computing and Optimization : Proceedings of the 6th International Conference on Intelligent Computing and Optimization 2023 (ICO2023) : Volume 4(Springer, 2023); 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, Impuestos en botanas. Su impacto en precio y consumo en México(Fondo de Cultura Económica, 2017); 13Scopus© Citations 9 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Machine learning models in health prevention and promotion and labor productivity: A co-word analysis(2024)6Scopus© 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 1(Springer, 2023); 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, Development of a Digital Twin Driven by a Deep Learning Model for Fault Diagnosis of Electro-Hydrostatic ActuatorsThe first quarter of the 21st century has witnessed many technological innovations in various sectors. Likewise, the COVID-19 pandemic triggered the acceleration of digital transformation in organizations driven by artificial intelligence and communication technologies in Industry 4.0 and Industry 5.0. Aiming at the construction of digital twins, virtual representations of a physical system allow real-time bidirectional communication. This will allow the monitoring of operations, identification of possible failures, and decision making based on technical evidence. In this study, a fault diagnosis solution is proposed, based on the construction of a digital twin, for a cloud-based Industrial Internet of Things (IIoT) system contemplating the control of electro-hydrostatic actuators (EHAs). The system was supported by a deep learning model using Long Short-Term Memory (LSTM) networks for an effective diagnostic approach. The implemented study considers data preparation and integration and system development and application to evaluate the performance against the fault diagnosis problem. According to the results obtained, positive results are shown in the construction of the digital twin using a deep learning model for the fault diagnosis problem of an active EHA-IIoT configuration. ©The authors ©MDPI.22Scopus© Citations 12 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A Timetabling Application for the Assignment of School Classrooms(2019)1 11Scopus© Citations 1