POVERTY AND FERTILITY IN ECUADOR, PERIOD 2020
DOI:
https://doi.org/10.37135/kai.03.12.06Keywords:
Human capital, living conditions, education, income, populationAbstract
The research focuses on analyzing the relationship between poverty and fertility in Ecuador during the year 2020. This relationship is studied by applying a binary logistic regression model -logit-, and whose measurement instrument was the statistical birth registration survey. still alive and fetal deaths in 2020. The results show that fertility has a positive and significant impact on poverty: the greater the number of children, the greater the probability of falling into a situation of poverty. In addition, when fertility is analyzed based on other conditions, such as the mother's low level of education, ethnicity, and marital status, there is more depth to explain the poverty rates
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Bazán, A., Quintero, M. y Hernández, A. (2011). Evolución del concepto de pobreza y el enfoque multidimensional para su estudio. Quivera. Revista de Estudios Territoriales, 13(1), 207–219. https://www.redalyc.org/articulo.oa?id=40118420013
Becker, G. (1960). An economic analysis of fertility, En Universities-National Bureau, Demographic and economic change in developed countries (pp. 209-240). Princeton University Press. https://www.nber.org/chapters/c2387
Becker, G. y Lewis, H. (1973). On the interaction between quantity and quality of children. The journal of political economy, 81(2, Part 2), S279-288. https://doi.org/10.1086/260166
Birdsall, N. y Griffin, C. (1988). Fertility and poverty in developing countries. Journal of Policy Modeling, 10(1), 29-55. https://doi.org/10.1016/0161-8938(88)90034-8
Britt, C., y Weisburd, D. (2010). Logistic regression models for categorical outcome variables. Handbook of quantitative criminology, 649-682. https://doi.org/10.1007/978-0-387-77650-7_31.
Comisión Económica para América Latina y el Caribe [CEPAL]. (2003). Hacia el objetivo del milenio de reducir la pobreza en América Latina y el Caribe. https://www.cepal.org/es/publicaciones/2348-objetivo-milenio-reducir-la-pobreza-america-latina-caribe
Datta, N. y Dubey, A. (2003). Poverty and Fertility. An Instrumental Variables Analysis on Indian Micro Data. Department of Economics. Aarhus School of Business, Department of Economics. https://pure.au.dk/ws/files/295/0003137.pdf
Dubin, J., y Rivers, D. (1989). Selection bias in linear regression, logit and probit models. Sociological Methods & Research, 18(2-3), 360-390. https://doi.org/10.1177/0049124189018002006.
Durán, M. (2012). El trabajo no remunerado en la economía global. (1ra ed.). Fundación BBVA. https://www.fbbva.es/wp-content/uploads/2017/05/dat/DE_2012_trabajo_no_remunerado.pdf
Easterlin, R. (1975). An Economic Framework for Fertility Analysis. Studies in Family Planning, 6(3), 54-63. https://doi.org/10.2307/1964934
Eloundou, P., Giroux, S. y Tenikue, M. (2017). African Transitions and Fer-tility Inequality: A Demographic Kuznets Hypothesis: African transitions and fertility inequality. Population and Development Review, 43(51), 59–83. https://doi.org/10.1111/padr.12034
Enríquez, R. (2009). El crisol de la pobreza: mujeres, subjetividades, emociones y redes sociales. Guadalajara: ITESO.
Eryong, X., y Xiuping, Z. (2018). Education and anti-poverty: Policy theory and strategy of poverty alleviation through education in China. Educational philosophy and theory, 50(12), 1101-1112. https://doi.org/10.1080/00131857.2018.1438889
Fiuza, M. y Rodríguez, J. (2000). La regresión logística: una herramienta versátil. Nefrologia: publicacion oficial de la Sociedad Espanola Nefrologia, 20(6), 495–500. https://www.revistanefrologia.com/es-la-regresion-logistica-una-herramienta-articulo-X0211699500035664
Frías, S. (2011). Hostigamiento, acoso sexual y discriminación laboral por embarazo en México. Revista mexicana de sociología, 73(2), 329-365. https://www.scielo.org.mx/scielo.php?pid=S0188-25032011000200005&script=sci_abstract&tlng=pt.
Gaona, J. y Macas, M. (2020). Índice de Pobreza Multidimensional para Ecuador, período 2009-2019. Revista Científica Cultura, Comunicación y Desarrollo, 5(1), 17-22. https://rccd.ucf.edu.cu/index.php/aes/article/view/213
Henao, J. (2017). Fertilidad y pobreza: Una aproximación desde la descomposición de datos binarios de Fairlie al caso de la ciudad de Medellín. Science of Human Action, 2(2), 292-301. https://doi.org/10.21501/2500-669x.2476
Hirschman, C. (1994). Why Fertility Changes. Annual Review of Sociology, 20(1), 203–233. https://doi.org/10.1146/annurev.so.20.080194.001223
Hsiao, C. (1996). Logit and probit models. The Econometrics of Panel Data: A Handbook of the Theory with Applications, 410-428. https://doi.org/10.1007/978-94-009-0137-7_16.
Instituto Nacional de Estadística y Censos [INEC]. (2019). Encuesta Nacional de Salud y Nutrición 2018. https://www.ecuadorencifras.gob.ec/documentos/web-inec/Estadisticas_Sociales/ENSANUT/ENSANUT_2018/Boletin%20ENSANUT%2028_12.pdf.
Lanchimba, C. y Diaz, J. (2017). Efectos de los ingresos del hogar, educación de la mujer y participación laboral femenina sobre la fecundidad ecuatoriana. Revista de análisis económico, 32(1),47-67. https://doi.org/10.4067/s0718-88702017000100047
Libois, F. y Somville, V. (2017). Fertility, household size and poverty in Nepal. World Development, 103, 311–322. https://doi.org/10.1016/j.worlddev.2017.11.005
Malthus, T. (2016). Primer ensayo sobre la población. Alianza Editorial. https://www.alianzaeditorial.es/libro/ciencias-sociales/primer-ensayo-sobre-la-poblacion-thomas-robert-malthus-9788491045458/
Martinez, E. (2008). Logit Model con modelo de elección discreta: origen y evolución. Anuario jurídico y económico escurialense, 41, pp. 469-484. https://dialnet.unirioja.es/descarga/articulo/2652092.pdf
Matthews, R. (1969). Why growth rates differ. Economic journal (London, England), 79(314), 261. https://doi.org/10.2307/2230167
Mincer, J. (1974). Schooling, Experience and Earnings. NBER, New York. http://www.nber.org/chapters/c3693
Ministerio de Salud Pùblica (2015). Control Prenatal: Guía de Práctica Clínica (GPC). Recuperado de: https://www.salud.gob.ec/wp-content/uploads/2014/05/GPC-CPN-final-mayo-2016-DNN.pdf.
Odwe, G. (2015). Fertility and household poverty in Kenya: a comparative analysis of coast and western provinces. African Population Studies, 29(2), 1785-1802. https://doi.org/10.11564/29-2-751
Powers, D. (2020). Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation. arXiv preprint.
https://doi.org/10.48550/arXiv.2010.16061.
Pucutay, F. (2002). Los modelos Logit y Probit en la investigación social. El caso de la pobreza en Perú 2001. Lima: Centro de investigación y desarrollo del instituto Nacional de estadísticas e información (INEI). https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib0515/Libro.pdf
Recinos, E. (2018). Desnutrición materna, bajo peso al nacer, pobreza y sociedad. Revista Naturaleza, Sociedad y Ambiente, 5(1), 41-49. https://doi.org/10.37533/cunsurori.v5i1.30.
Rodríguez, D. (2013). Female Fertility: A Conceptual and Dimensional Analysis. Journal of Midwifery & Women’s Health, 58(2), 182-188. https://doi.org/10.1111/j.1542-2011.2012.00234.x
Rodríguez, J. (2017). Deseabilidad y planificación de la fecundidad adolescente en América Latina y el Caribe: tendencias y patrones emergentes. Notas de Población, 44(104), 119-144. https://hdl.handle.net/11362/41963
Schultz, T. (1961). Investment in human capital. American Economic Review, 51(1), pp. 1–17. http://www.jstor.org/stable/1818907
Sen, A. (1981). Poverty and Famines: An essay on Entitlement and Deprivation. Population and development review, 8(2), 418. https://doi.org/10.2307/1973011
Valdés, M. (2012). Conocimiento de los indicadores de fertilidad y embarazo. III Congreso Internacional en Reconocimiento de la Fertilidad, Universidad de Piura, Lima, Perú. http://www.reconocimientodelafertilidad.com/wp-content/uploads/2013/03/26-Comunicaciones_Revista_actasp.pdf
Velázquez, N., Masud, J., y Ávila, R. (2004). Recién nacidos con bajo peso; causas, problemas y perspectivas a futuro. Boletín médico del Hospital Infantil de México, 61(1), 73-86. http://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S1665-11462004000100010&lng=es&nrm=is.
Wietzke, F. (2020). Poverty, inequality, and fertility: the contribution of demographic change to global poverty reduction: Frank-Borge wietzke. Population and Development Review, 46(1), 65-99. https://doi.org/10.1111/padr.12317
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