No hay nada tan ruim que no puede piorar: un análisis Bayesiana de la pobreza
DOI:
https://doi.org/10.17058/redes.v25i4.12685Palabras clave:
La pobreza. Red Bayesiana. Municipios.Resumen
Este artículo pretende comprender las relaciones existentes entre diferentes formas de pobreza y, así, verificar si un determinado tipo de carencia inhibe la capacidad del individuo de superar de otras formas de privaciones. El enfoque utilizado para entender los mecanismos que rigen las relaciones entre distintos niveles de pobreza se remite a la red bayesiana. Los datos utilizados se refieren a las informaciones sobre renta, salud, educación y vivienda para 5.565 municipios brasileños entre 1970 y 2010, siendo la fuente de tales informaciones debida al Instituto Brasileño de Geografía y Estadística. Los resultados destacan la existencia de relaciones entre las facetas de la pobreza analizadas. Se observaron influencias directas de todas las privaciones sobre las condiciones de salud, indicando que precarias en salud normalmente surgen en ambientes donde otros tipos de carencias afloran. Otro hecho importante es que las privaciones educativas no son explicadas por ninguna de las ópticas tratadas y, por lo tanto, retratan un carácter exógeno. El indicador de educación también refleja información sobre la privación monetaria, siendo tal relación de carácter positivo. Por último, las carencias monetarias son responsables de limitar el acceso a una vivienda digna.Descargas
Citas
ADLER, Nancy E. Socioeconomic inequalities in health: no easy solution. Jama, v. 269, n. 24, p. 3140-3145, 1993.
ALKIRE, Sabina; FOSTER, James. Counting and multidimensional poverty measurement. Journal of public economics, v. 95, n. 7, p. 476-487, 2011.
ANGELL, Marcia. Privilege and health-what is the connection?. The New England journal of medicine, v. 329, n. 2, p. 126, 1993.
ATKINSON, A.; BOURGUIGNON, F.: The comparison of multidimensioned distributions of economic status. Review Economics Studies. 49, p.183–201, 1982.
BARRO, Robert J. Economic growth in a cross section of countries. National Bureau of Economic Research, 1991.
BIBI, Sami. Measuring poverty in a multidimensional perspective: A review of literature. 2005.
BLAU, David M. The effect of income on child development. Review of Economics and Statistics, v. 81, n. 2, p. 261-276, 1999.
BOEHM, T.; SCHLOTTMANN, A. M. Housing and wealth accumulation: Intergenerational impacts (Low-Income Homeownership Working Paper Series, LIHO-01.15). Cambridge, MA: Joint Center for Housing, Harvard University, 2001.
BOSSERT, Walter; CHAKRAVARTY, Satya R.; D'AMBROSIO, Conchita. Multidimensional poverty and material deprivation. 2009.
BOURGUIGNON, Francois; CHAKRAVARTY, Satya R. The measurement of multidimensional poverty. The Journal of Economic Inequality, v. 1, n. 1, p. 25-49, 2003.
BRACONI, Frank. Housing and Schooling. The Urban Prospect, v. 7, p. 1-4, 2001.
BRAMLEY, G.; KARLEY, N. Home Ownership, Poverty and Educational Achievement: Individual School and Neighbourhood Effects, paper to the Scottish Executive Education Department. Edinburgh: Centre for Research into Socially Inclusive Services, Heriot Watt University, 2005.
BUDDELMEYER, Hielke; CAI, Lixin. Interrelated dynamics of health and poverty in Australia. IZA Discussion Papers, 2009.
CAMERON, Stephen V.; HECKMAN, James J. The dynamics of educational attainment for black, hispanic, and white males. Journal of political Economy, v. 109, n. 3, p. 455-499, 2000.
CASE, Anne; DEATON, Angus. Health and wealth among the poor: India and South Africa compared. American Economic Review, p. 229-233, 2005.
CERIOLI, Andrea; ZANI, Sergio. A fuzzy approach to the measurement of poverty. In: Income and wealth distribution, inequality and poverty. Springer Berlin Heidelberg, 1990. p. 272-284.
CHAKRAVARTY, Satya; DEUTSCH, Joseph; SILBER, Jacques. On the Watts Multidimensional Poverty Index and its Decomposition. World Development 36(6): 1067-1077. 2008.
CHELI, Bruno; LEMMI, Achille. A" Totally" fuzzy and relative approach to the multidimensional analysis of poverty. ECONOMIC NOTES-SIENA-, p. 115-134, 1995
DUCLOS, J.; SAHN, D.; YOUNGER, E. Robust multidimensional poverty comparisons. Economic Journal, 116 (514): 943-968. 2006.
DUNCAN, G.; CHASE-LANSDALE, L. Wefare Reform and Child Well-being. Mimeo Northwestern University, 2000.
FEINSTEIN, Jonathan S. The relationship between socioeconomic status and health: a review of the literature. The Milbank Quarterly, p. 279-322, 1993.
FUCHS, Victor R. Reflections on the socio-economic correlates of health.Journal of health economics, v. 23, n. 4, p. 653-661, 2004.
GLEWWE, Paul; JACOBY, Hanan. Student achievement and schooling choice in low-income countries: Evidence from Ghana. Journal of Human Resources, p. 843-864, 1994.
GLIED, Sherry; LLERAS-MUNEY, Adriana. Health inequality, education and medical innovation. National Bureau of Economic Research, 2003.
GOLDMAN, Dana P.; SMITH, James P. Can patient self-management help explain the SES health gradient?. Proceedings of the National Academy of Sciences, v. 99, n. 16, p. 10929-10934, 2002.
GREEN, Richard K.; WHITE, Michelle J. Measuring the benefits of homeowning: Effects on children. Journal of Urban Economics, v. 41, n. 3, p. 441-461, 1997.
GROSSMAN, Michael. The demand for health: a theoretical and empirical investigation. NBER Books, 1972.
HAURIN, Donald R.; PARCEL, Toby L.; HAURIN, R. Jean. Does homeownership affect child outcomes?. Real Estate Economics, v. 30, n. 4, p. 635-666, 2002.
HUROWITZ, James C. Toward a social policy for health. The New England journal of medicine, v. 329, n. 2, p. 130-133, 1993.
KNOX, Virginia W.; MILLER, Cynthia; GENNETIAN, Lisa A. Reforming welfare and rewarding work: A summary of the final report on the Minnesota Family Investment Program. New York: Manpower Demonstration Research Corporation, 2000.
KOLM, S-Ch. Multidimensional egalitarianisms. Quartely Journal Economics. 91: 1 – 13, 1977.
LEVY, D.; DUNCAN, G. Using siblings to assess the effect of childhood family income on completed schooling. Joint Centre for Poverty Research Working Paper, North Western University, 2001.
MATTE, Thomas D.; JACOBS, David E. Housing and health—current issues and implications for research and programs. Journal of Urban Health, v. 77, n. 1, p. 7-25, 2000.
MAASOUMI, E. The Measurement and Decomposition of Multidimensional Inequality, Econometrica, 54, 771-779, 1986.
MAASOUMI, Esfandiar; LUGO, Maria Ana. The Information Basis of Multivariate Poverty Assessments. In Quantitative Approaches to Multidimensional Poverty Measurement, Kakwani and Silber (eds.), Palgrave Macmillan, 2008.
MANKIW, N. Gregory; ROMER, David; WEIL, David N. A contribution to the empirics of economic growth. National Bureau of Economic Research, 1992.
PSACHAROPOULOS, George.; PATRINOS, Harry A. Returns to investment in education: a further update. World Bank Policy Research Working Paper Series, Vol, 2002.
ROMER, Paul M. Endogenous technological change. Journal of political Economy, p. S71-S102, 1990.
RUGGIERI-LADERCHI, C.; SAITH, R.; STEWART, F. Does it matter that we do not agree on the definition of poverty? A comparison of four approaches. Oxford Development Studies, 31, 243–274. 2003.
SAEGERT, Susan C. et al. Healthy housing: a structured review of published evaluations of US interventions to improve health by modifying housing in the United States, 1990-2001. American Journal of Public Health, v. 93, n. 9, p. 1471-1477, 2003.
SÁNCHEZ, Marco V.; SBRANA, Giacomo. Determinants of education attainment and development goals in Yemen. Prepared for the Project Assessing Development Strategies to achieve the Millennium Development Goals in the Arab Region, UNDP-RBAS, UN-DESA and World Bank [downloadable from: http://www.un.org/en/development/desa/policy/capacity/yemen.shtml], 2009.
SANTOS, Anderson Moreira Aristides dos; JACINTO, Paulo de Andrade; TEJADA, Cesar Augusto Oviedo. Causalidade entre renda e saúde: uma análise através da abordagem de dados em painel com os estados do Brasil. Estudos Econômicos (São Paulo), v. 42, n. 2, p. 229-261, 2012.
SCHULTZ, T. Paul. Accounting for public expenditures on education: an international panel study. 1995.
SEN, Amartya K. Poverty: An ordinal approach to measurement. Econometrica. 44 (2): 219-231. 1976.
SHASHIDHAR, Saraswati; RAO, Chandrika; HEGDE, Radhakrishna. Factors affecting scholastic performances of adolescents. The Indian Journal of Pediatrics, v. 76, n. 5, p. 495-499, 2009.
SMITH, James P. Healthy bodies and thick wallets: the dual relation between health and economic status. The journal of economic perspectives: a journal of the American Economic Association, v. 13, n. 2, p. 144, 1999.
SOARES, R. R. The effect of longevity on schooling and fertility: evidence from the Brazilian Demographic and Health Survey. Journal of Population Economics, v.19, n.1, p. 71-97, n.1, 2006.
TILAK, Jandhyala BG. Post-elementary education, poverty and development in India y Role of post-basic education in alleviation of poverty and development.Centre of African Studies, University of Edinburgh. Disponível em : www.cas.ed.ac.uk/research/projects. html# pubs [02/05/2007], 2005.
TSUI, Kai-yuen. Multidimensional Generalizations of the Relative and Absolute Indices: the Atkinson-Kolm-Sen Approach. Journal of Economic Theory, (1995), 67, 251-265, 1995.
TSUI, Kai-yuen. Multidimensional poverty indices. Social Choice and Welfare, v. 19, n. 1, p. 69-93, 2002.
VANDIVERE, S.; HAIR, E. C.; THEOKAS, C.; CLEVELAND, K.; MCNAMARA, M.; ATIENZA, A. How housing affects child well-being. Funders' Network for Smart Growth and Livable Communities, 2006.
WILSON, Kathryn. The determinants of educational attainment: Modeling and estimating the human capital model and education production functions. Southern Economic Journal, p. 518-551, 2001.
