This paper aims to identify the presence of energy poverty in Ecuador. Three indicators proposed by the European Union Energy Poverty Observatory (EPOV) are used to construct a multidimensional energy poverty index (MEPI) based on measure conditions associated with energy poverty, in areas related to delays in the payment of electricity bills, disproportionate expenses, hidden energy poverty, and the 10% Boardman (1991) rule. The information comes from the Ecuatorian Life Conditions Survey. The results show that energy poverty is present in Ecuadorian households, at the national level, and just as these indicators have restrictions, advantages and disadvantages, which demand decisions about the choice of their use.

El envejecimiento de las personas origina cambios en el ámbito económico y demográfico de la población, provocando que un alto porcentaje de adultos mayores permanezcan en el mercado laboral. Para buscar bibliografía referente a esta problemática se realizó un análisis bibliométrico de la evolución y estado actual del tema. Como resultado, se encontró un interés creciente en la temática a nivel mundial, sobre todo en países de Europa, Asia, Oceanía y Norteamérica, registrándose una nula participación de estudios similares en el Ecuador, evidenciando una ventana de oportunidad en el ámbito de la economía plata.

Climatic variability can modify milk production through direct and indirect pathways, yet monthly farm time series also exhibit temporal dependence. A longitudinal, observational, single-case study was conducted in the San Francisco dairy system, Carchi, Ecuador, from March 2019 to December 2024. Of 70 calendar months, 64 had complete analytical information, and 58 were eligible for two-lag models. Ten model specifications were compared based on model fit, information criteria, residual diagnostics, seasonality assessment, and temporal validation. Mean daily milk production was 233.49 ± 47.90 L day⁻¹. The selected model was a second-order autoregressive model with a calendar trend and mean temperature at t − 2 (adjusted R2 = 0.827; Akaike information criterion = 519.52; Bayesian information criterion = 529.83; root mean squared error = 19.56 L day⁻¹). The temperature coefficient was 10.844 L day⁻¹ °C⁻¹ (p < 0.001 with robust standard errors). Annual harmonic terms did not improve model fit, and precipitation at t − 1 yielded only marginal improvement. The number of cows in production varied across 54 months (26.02 ± 4.11; range: 18–37). The observed temperature association should be interpreted at the system level; it does not demonstrate direct causality or individual cow productivity and requires external validation.