Velázquez-Salazar, Marisol
Main Affiliation
Preferred name
Velázquez-Salazar, Marisol
Official Name
Velázquez Salazar, Marisol
ORCID
0000-0002-2434-8760
Researcher ID
HPD-6060-2023
Scopus Author ID
57221855410
17 results
Now showing 1 - 10 of 17
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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, Financial education and internal governance on short food supply chains: evidence from vulnerable rural communities in Latin America(Springer Science and Business Media LLC, 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, Global Value Chains in the Coffee Sector: A Comparative Analysis Between El Salvador and MexicoThe objective of this chapter is to compare the coffee chains in Mexico and El Salvador under the theoretical framework of Global Value Chains (GVC) proposed by Gereffi, highlighting the dimensions of governance in the original version related to the control or dominance of the chain (Gereffi, Commodity chains and global capitalism, Praeger, 1994), linkage governance (2005), and governance by regulation (2014, 2018). It is also discussed around the institutional framework to observe similarities and differences, establishing some recommendations of good practice for both countries under the interest of enhancing the product and improving the socioeconomic conditions of the producers of each of them. The comparison methodology combines quantitative and qualitative analysis and deepens through case studies. The results show that apart from geography and the size of production, there are few differences between the two countries regarding the conditions of the coffee chain. However, we found coincidences in the input-output, institutional framework, and governance dimensions. © 2024 Springer Nature.36Scopus© Citations 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Cultural preservation and economic inclusion in small-scale food production: the case of Latino Farms in Ohio(Springer Science and Business Media LLC, 2025); Scopus© Citations 1 19 2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Evaluating the Financial Performance of CSR Strategies and Sustainable Operations in Mexican Companies: An Explainable Machine Learning ApproachResearch on how corporate social responsibility (CSR) practices linked to sustainable operations (SO) affect corporate financial performance (FP) is still limited. This study presents a novel methodological proposal to measure the individual impact of such practices on the profitability of companies listed on the Mexican Stock Exchange. The method employed consists of a Random Forest (RF) model complemented by Explainable Machine Learning (XML) techniques, namely Individual Conditional Expectation (ICE), Partial Dependence Plots (PDPs) and SHapley Additive exPlanations (SHAP), to calculate the individualized marginal effect in the return on assets (RoA), return on equity (RoE) and return on investment capital (ROIC) for each company, explained by the environmental, social, and governance scores provided by Bloomberg (Bloomberg Finance, L.P., New York, NY, USA), such as the market capitalization, debt-to-equity ratio, sales growth, and years since listing. The novelty of this model lies in the application of RF and XML, which offers a comprehensive and interpretable perspective on the CSR–FP relationship and the use of lagged explanatory variables to avoid endogeneity problems, overcoming the limitations of traditional analyses. The results indicate that environmental scores exhibit the most consistent contribution to FP, whereas social and governance effects are highly metric-dependent. The SHAP analysis reveals substantial heterogeneity in the drivers of firm FP, highlighting the relevance of XML methods. © The authors © MDPI41 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Sustainability and Quality of Life in Marginalized Areas: An Impact Evaluation of a Community Center in Santa Fe, MexicoThe aim of this paper is to present the results of an impact evaluation of a community center in health, capacity building, and digital access, which form an approximation of quality of life, in the population of Santa Fe town in Mexico City, from 2022 to 2024. The methodology is quantitative, using an impact index and the differences in differences (DD) technique. The data were obtained from primary sources with surveys undertaken via questionnaires. The center is operated by a private university and funded by private firms. The results show a positive impact of 0.287127 out of 1 on the weighted impact index, which allows us to consider this program successful in improving the quality of life of the target population. Through impact evaluation, the effectiveness of interventions and opportunities for improvement are identified, fostering collaboration among local actors, including community members, state-run public programs, and community centers. This collaborative effort improves the quality of life, creating a sustainable community wherein each actor addresses specific needs. Impact evaluation plays a crucial role in measuring sustainability because it is a continuous improvement process that, when combined with other actions, enhances the community’s overall well-being. ©2024 MDPI, The authors.Scopus© Citations 2 27 18 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Small Coffee Companies and the Impact of Geographical Indications as Productive Innovation in Mexico in the New Reality(2021); Pérez Akaki, PabloThis paper analyzes the Protected Designation of Origin (PDO) as a factor of innovation in the Coffee Pluma geographical region in Oaxaca, Mexico, a vital tool to solve the problem of the actual crisis in the chain and for the new context of business and markets in the post-COVID 19 era due to the need for new marketing methods. Two case studies are presented under the Global Value Chain (GVC) methodology proposed by Gereffi et al. (1994, 2005, 2018) with a contribution from the conceptual framework of Geographical Indications (GI) used by Belletti et al. (2017) to analyze the PDO as an innovation. The first are small-size producers and the second are medium-size producers, both considered as small companies by the number of people employed. Even on a small scale, the coffee sector, through the appellation of origin, has the potential to generate economic benefits in the place of origin by promoting the development of two other economic sectors such as tourism and retail marketing. Likewise, it gives a comprehensive answer considering the business economic field and incorporating, as required by the current reality, other capitals such as social, cultural and environmental. The aim of this chapter is to evaluate the benefits that coffee sector, will obtain and generate through this sectorial and territorial development tool, considering that the G.I. emerges as an option to improve production by acquiring the exclusivity of producing coffee within that region to achieve sustainable development faced with the new reality. © Springer1 34Scopus© Citations 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Modeling the Relation Between Non-Communicable Diseases and the Health Habits of the Mexican Working Population: A Hybrid Modeling Approach(MDPI AG, 2025); The impact that Non-Communicable Diseases (NCDs) have on the health status of the population has generated the need for an in-depth analysis of health habits and NCDs. In addition to its significant impact on population health, this phenomenon also translates into substantial economic consequences for countries. This study delves into the analysis of the relationship between health habits and NCDs among the economically active population of Mexico. Through a hybrid approach that integrates the use of machine learning (ML) models and a structural equation model (SEM), we seek to quantify the direct and indirect causal effects between health habits and NCDs. For this study, information from the 2022 National Health and Nutrition Survey carried out in Mexico for the working-age population is used. According to the results obtained in the first stage of analysis using ML, the most relevant variables (health habits) that impact the probability of individuals presenting with NCDs were identified (random forest precision of 78.66% and Lasso with 71.27%). The second stage of analysis through SEM using the most relevant variables, which were selected through ML, allowed us to measure the direct and indirect causal effect of health habits on NCDs. The SEM model was statistically significant (Chi-square: 449.186; p-value = 0.0000) and revealed that negative health habits, such as a poor diet, physical inactivity, smoking and alcohol consumption, significantly increase the risk of NCDs in the working-age population in Mexico (0.23), while vigorous physical activity and salary has a negative impact (−0.17 and −0.23, respectively) on the presence of NCDs. This study highlights the ability of machine learning and SEM approaches to model the impact of health habits on NCDs for the economically active population in Mexico. ©The authors © Mathematics ©MDPI.20 114 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Thematic mapping of artificial intelligence in management: A bibliometric approach using co-word analysis (2015–2024)(Pro-Metrics, 2025); Objective: The objective of this study was twofold: first, to map the main themes in the literature on artificial intelligence in management, and second, to explore the relationships between these themes. Design/Methodology/Approach: A co-word analysis was performed on 15,835 articles indexed in Scopus (2015–2024), with the author’s keywords in the field of administration constituting the unit of analysis. The semantic network under consideration was constructed using the 50 most frequent terms, applying normalization by association and the Walktrap algorithm for cluster detection. Results/Discussion: The results of the analysis indicated that the extant literature was organized around three thematic groups. The first of these focused on conversational interfaces, the second on digital transformation, and the third adopted a computational approach. The thematic structure identified reflected a field in the process of consolidation, with a predominance of technical approaches and limited functional specialization. Conclusion: Contemporary research endeavors prioritized methodological development over strategic implementation in particular organizational contexts. These findings underscored the necessity for more comprehensive approaches that articulated technology, management, and governance. Moreover, they called for a future agenda that was oriented toward its adoption from sociotechnical perspectives. ©The authors ©Iberoamerican Journal of Science Measurement and Communication (Revista Iberoamericana de Medición y Comunicación de la Ciencia) ©Pro Metrics.22 66