Looking for regular statistical trends of relations in schools, we constructed 42 independent weighted directed networks of simultaneous friendship and animosity from surveys we made in the Mexico City Metropolitan area in classrooms with students of different ages and levels by asking them to nominate and order five friends and five foes. However, the data show that older students nominated fewer than the five required five foes. Although each classroom was independent of the others, we found several general trends involving students of different ages and grade levels. In all classrooms, friendship entropy was found to be higher than enmity entropy, indicating that fewer students received enmity links than received friendship nominations. Popular agents exhibited more reciprocal nominations among themselves than less popular agents, and opposite-sex friendships increased with age.

En este artículo analizamos el impacto heterogéneo de un incremento de los costos de las remuneraciones a los trabajadores sobre el nivel de precios general y sectorial de la economía mexicana. Mediante un modelo de precios de insumo producto con funciones de costos flexibles, simulamos escenarios considerando un aumento de 10% en las remuneraciones a los trabajadores. Encontramos que el aumento de precios a nivel de sectores económicos es heterogéneo y depende tanto de su estructura de costos como de cuán flexibles sean dichos sectores para sustituir. A nivel global, para costos fijos un aumento del 10% tiene un efecto sobre la inflación de 2.2%, mientras para costos flexibles de 1.98%. La originalidad de este trabajo consiste en el hallazgo de impactos heterogéneos, dando pie a la propuesta de políticas públicas focalizadas por sector. Naturalmente, el modelo está limitado por los propios supuestos del modelo de insumo producto.

We analyze the three most recent Mexican input–output production networks at the national industry level (6-digit classification), focusing on the statistical characterization of degree, strength, and local entropy. Using these metrics, we develop a multi-centrality index to identify key industries and track their positional changes over time. The results show that the in-degree distribution follows a bimodal pattern, where agricultural industries exhibit lower mean values than the rest of the economy. Conversely, the out-degree distribution evolves toward a beta-like form with parameters 1.42 < a < 2.09 and 0.155 < b < 0.219. Edge weights display a dual structure: low and medium values follow a stretched exponential (0.199 < β < 0.233), while the tail follows a power law with exponents around 2.3. Strength distributions also show a dual pattern, combining stretched exponential or lognormal behavior for small and medium values and power-law tails with 2 < α < 2.5. Local entropy distributions are well fitted by compressed exponentials, with 6.6 < β < 7.5 for in-entropy and 3.3 < β < 3.6 for out-entropy. Finally, the top 50 industries ranked by the out-multi-centrality index remain stable across periods, while the in-multi-centrality index shows greater variability. Sectorally, construction and manufacturing dominate the in-direction in 2008, whereas public administration, educational services, health care and nonresidential construction occupy the highest ranks in 2013 and 2018. These findings reveal a structural shift in Mexico’s production network, highlighting the growing relevance of service-based activities and state-driven sectors in recent years.