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); 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, The Sustainable Industrial Site of the Future Based on Energy Efficiency, Renewable Energy, Artificial Intelligence, and Energy PolicyThe world’s high emissions of carbon dioxide are the primary cause of climate change and its harmful consequences, such as floods, storms, and droughts. According to the Intergovernmental Panel on Climate Change, human-induced warming reached approximately 1 °C above preindustrial levels in 2017, increasing at 0.2 °C per decade. The industrial sector contributes greatly to this global warming, as it is among the largest energy consumers. Indeed, industrial processes require a lot of energy, for example, for cooling, venting, pumping, producing steam, and hot water. This chapter focuses on industrial sites and aims to find a global solution to accelerate their transition toward sustainability. The study defines a clear and robust framework to obtain a sustainable industrial site and to keep it sustainable. Technologies (both well-proven technologies and new technologies) and policies are examples of tools used during the research. The method used is also supported by the current state-of-the-art on carbon emissions reduction and energy savings. The framework is based on four levers: energy efficiency, artificial intelligence, renewable energy, and energy policy and management. This framework can be used by any organization, stakeholders, and policymakers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Corporate Social Responsibility and Financial Performance: Evidence from Public Companies Listed on the Mexican Stock Exchange(Springer Nature Switzerland, 2026); ; The research on how corporate social responsibility (CSR) affects the financial performance (FP) of companies is limited, especially in the case of Mexico. There is a lack of studies that measure the financial impact of socially responsible strategies in Mexican companies. This study introduces an innovative approach by proposing a hybrid model that combines three quantitative methodologies: principal component analysis (PCA), cluster analysis, and an ordered logit model. The goal is to assess the impact of sustainability practices on financial performance. The study considers financial data from the past decade for 91 companies listed on the Mexican Stock Exchange. The results indicate that CSR practices have a positive effect on FP. The proposed hybrid model serves as a valuable methodological tool for evaluating the impact on FP of Mexican public companies listed on the BMV and holding the ESR seal granted by CEMEFI (Mexican Center for Philanthropy). This approach will help monitor the evolution of FP through the adoption of various CSR-related practices. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. - 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, 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, 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, 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, Machine learning models in health prevention and promotion and labor productivity: A co-word analysis(2024)Scopus© Citations 2 6 - 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, 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