En el contexto investigativo actual resulta relevante conocer los principales paradigmas y métodos que guían la investigación científica en diversas disciplinas. Esta obra ofrece una visión crítica y detallada de los paradigmas que dan origen a los enfoques cualitativos, cuantitativos y mixtos, explorando las características distintivas de cada uno y sus aplicaciones en la práctica investigativa. A lo largo del libro, se destacan las bases epistemológicas que sustentan estos enfoques, mostrando cómo los investigadores seleccionan el paradigma más adecuado según la naturaleza de sus preguntas de investigación y los objetivos que persiguen. Además, se exploran las corrientes y representantes de estos paradigmas con sus diferencias y explicación de su propia naturaleza. El libro se convierte en una guía valiosa para académicos, estudiantes y profesionales interesados en comprender y aplicar metodologías de investigación de manera rigurosa y fundamentada.

The objective of this research was to analyze the effect of education on monetary poverty in the regions of Peru. As a source of information, the SIRTOD database of the National Institute of Statistics and Informatics was used for the period 2007 to 2016. The study is based on the framework of human capital theory and consumer microeconomic theory. Therefore, the study is considered as hypothetico-deductive. Education was approached through the percentage of the economically active population by educational levels; primary, secondary, non-university education and university education, and poverty by the percentage of the population that have less expenditure than the monetary poverty line. The main hypothesis of the study is that the higher level of education has a positive effect in the reduction of monetary poverty, through the mechanism of productivity and income improvement. The estimation methodology was the panel data model; fixed and random effects. The research results show that from the beginning of secondary education monetary poverty is reduced in the regions of Peru; that is, the population educated by educational levels increases by 10%, this would lead to a reduction of poverty in the regions by 1.07%, 1.68% and 0.83% respectively. Finally, public policy is that the regions and the central government close gaps in access to education, especially in secondary education and non-university education, which have the greatest effect.

This study examines the direct and indirect effects of mining activities on key socioeconomic indicators such as per capita income, the Human Development Index (HDI), and education in the Puno region of Peru, comparing short-term (2015–2019) and long-term (2003–2029) impacts. Using a random effects panel data model and incorporating spatial autocorrelation, the study analyzes data from 2003 to 2019 to assess the effects of mining on both mining and non-mining districts. The results show that in the short term, family income per capita in mining districts increased by PEN 65.03, while non-mining districts saw an indirect increase of PEN 80.59. In the long term, the direct impact on mining districts grew to PEN 239.44, with the indirect impact on non-mining districts reaching PEN 352.30. In education, mining districts experienced a 6.74 percentage point increase in secondary education for 18-year-olds in the short term, and non-mining districts had a 5.19 percentage point increase, with both showing positive impacts. Long-term effects showed a smaller increase, with mining districts at 12.27 percentage points and non-mining districts at 9.71 percentage points. Regarding the HDI, the direct impact in mining districts in the short term was an increase of 0.02 points, with a total impact of 0.03 points, while the indirect impact on non-mining districts was minimal. In the long term, the direct impact on mining districts grew to 0.09 points, with the total impact reaching 0.10 points, while non-mining districts showed an increase of 0.10 points as well. The study concludes that mining has significant short-term impacts, particularly on income and education, but the long-term effects are more pronounced, especially for income and the HDI, with substantial indirect benefits for non-mining districts, especially in terms of income. Educational improvements stabilize over time, and mining’s overall impact on the HDI increases as its economic and social effects deepen.

Out-of-pocket health care spending is an inefficient and inequitable financing mechanism, as it reduces household well-being and can push families into poverty. This study estimates the impoverishment associated with out-of-pocket health care expenditures in Peru between 2010 and 2021 and identifies the factors associated with such impoverishment. Using microdata from the National Household Survey and a multivariate logit model, the study assesses the probability of falling into poverty related to such direct spending. The results show that 2,7% of non-poor households became impoverished during the period analyzed, a percentage that increased to 4,5% during the COVID-19 pandemic. This pattern was more pronounced in rural areas, especially in the highlands and the rainforest. Regarding associated factors, it was found that years of education, per capita income, health insurance coverage, and visits to health facilities are significantly associated with a lower probability of falling into poverty due to out-of-pocket expenditures. In contrast, the presence of chronic diseases, disability, a higher economic dependency ratio, pregnancy, the presence of young children, unmet basic needs, lack of sanitation services, and the use of solid fuels for cooking are associated with a higher probability of this risk. Health insurance coverage, while essential, remains insufficient if it is not accompanied by substantive improvements in the social determinants of health.

Economic literature has shown that out-of-pocket healthcare spending is the most unequal and inefficient way to finance medical care. It harms household welfare; as it increases family expenses and decreases consumption of basic goods like food. In situations of health "shock", these further aggravate and impoverish households. This study analyzes the impoverishment due to out-of-pocket healthcare spending in Peruvian households during the period 2015-2020. It followed the methodology of the World Health Organization and used the logit model to estimate the determining factors of such impoverishment. The results show that out-of-pocket health spending impoverished, on average, 2.6% of non-poor households, with greater impoverishment during the COVID-19 pandemic in 2020, at 3.53%. It was found that the factors determining impoverishment due to health spending were per capita household income, schooling, presence of chronic discomfort, disability of a household member, unmet basic needs such as inadequate housing, overcrowding and lack of sanitary facilities, low school attendance, and high economic dependency, health insurance. Finally, it was found that non-poor urban households become impoverished to a greater extent compared to rural households.