Hostname: page-component-848d4c4894-nmvwc Total loading time: 0 Render date: 2024-06-29T17:06:57.920Z Has data issue: false hasContentIssue false

On Mexican poverty-trap regimes and struggling to escape them

Published online by Cambridge University Press:  12 July 2023

Edgar J. Sanchez Carrera*
Affiliation:
Department of Economics, Social Sciences, and Politics (DESP), University of Urbino Carlo Bo, Urbino, Italy CIMA UAdeC, Saltillo, Mexico
Wiston Adrián Risso
Affiliation:
Universidad de la Republica de Uruguay, Montevideo, Uruguay
*
Corresponding author: Edgar J. Sanchez Carrera; Email: edgar.sanchezcarrera@uniurb.it

Abstract

This paper deals with the phenomenon of poverty-trap regimes in Mexico, that is, self-reinforcing mechanisms in which municipalities which start poor remain poor. We develop a coordination game of poverty traps driven by strategic interactions of economic agents: people choose to complete or not their education levels since it might be excessively costly and unprofitable. A one-shot game is constructed and then converted into a system of differential equations in which strategies that perform relatively better become more abundant in the population. Applying evolutionary games and symbolic-regimes dynamics (nonparametric and nonlinear techniques), we show that Mexican regions are in poverty-trap regimes (stable and dynamically evolving low-level equilibria) characterized by incomplete education and low income since initial conditions (education and income per capita) are such (very precarious) that poverty is the stable steady-state situation. We examine scenarios to show that to overcome the high-poverty regime by the year 2030, it is necessary to reduce incomplete education by 10% in the 5-year periods 2020–2025 and 2025–2030 and increase per-capita income by 10% in both periods.

Type
Articles
Copyright
© The Author(s), 2023. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Accinelli, E. and Sanchez Carrera, E. J.. (2012) The evolutionary game of poverty traps. Manchester School 80(4), 381400.10.1111/j.1467-9957.2011.02262.xCrossRefGoogle Scholar
Agüero, J. M. and Beleche, T. (2013) Test-Mex: Estimating the effects of school year length on student performance in Mexico. Journal of Development Economics 103(C), 353361. DOI: 10.1016/j.jdeveco.2013.03.008.10.1016/j.jdeveco.2013.03.008CrossRefGoogle Scholar
Angeletos, G.-M., Hellwig, C. and Pavan, A.. (2007) Dynamic global games of regime change: Learning, multiplicity, and the timing of attacks. Econometrica 75(3), 711756.10.1111/j.1468-0262.2007.00766.xCrossRefGoogle Scholar
Angulo-Cázares, R. (2018) Problemas de agencia en la educación básica en México: Un diagnóstico institucional. Convergencia Revista de Ciencias Sociales 25(77), 149173. DOI: 10.29101/crcs.v25i77.9224.10.29101/crcs.v25i77.9224CrossRefGoogle Scholar
Antman, F. and McKenzie, D.. (2007) Poverty traps and nonlinear income dynamics with measurement error and individual heterogeneity. The Journal of Development Studies 43(6), 10571083.10.1080/00220380701466567CrossRefGoogle Scholar
Arellano, M. and Bover, O.. (1995) Another look at the instrumental variable estimation of error-components models. Journal of Econometrics 68(1), 2951.10.1016/0304-4076(94)01642-DCrossRefGoogle Scholar
Azariadis, C. (1996) The economics of poverty traps: Part one: Complete markets. Journal of Economic Growth 1(4), 449486.10.1007/BF00150197CrossRefGoogle Scholar
Bachhoff, E., Contreras, C., Hernandez, E. and Garcia, M.. (2007) Factores Escolares y Aprendizajes en México. El caso de la educación básica. México: Instituto Nacional de Evaluación de la Educación.Google Scholar
Banerjee, A. V. (2020) Field experiments and the practice of economics. American Economic Review 110(7), 19371951.10.1257/aer.110.7.1937CrossRefGoogle Scholar
Barrett, B. C. and Carter, M. R.. (2013) The economics of poverty traps and persistent poverty: Empirical and policy implications. The Journal of Development Studies 49(7), 976990. DOI: 10.1080/00220388.2013.785527.10.1080/00220388.2013.785527CrossRefGoogle Scholar
Barrios-Fernández, A. (2022) Neighbors’ effects on university enrollment. American Economic Journal: Applied Economics 14(3), 3060.Google Scholar
Basu, K. A. and Van, P. H.. (1998) The economics of child labor. American Economic Review 88, 412427.Google Scholar
Bell, A. and Jones, K.. (2015) Explaining fixed effects: Random effects modeling of time-series cross-sectional and panel data. Political Science Research and Methods 3(1), 133153.10.1017/psrm.2014.7CrossRefGoogle Scholar
Bischi, G. I., Grassetti, F. and Sanchez Carrera, E. J. (2022) On the economic growth equilibria during the Covid-19 pandemic. Communications in Nonlinear Science and Numerical Simulation 112, 106573. DOI: 10.1016/j.cnsns.2022.106573.10.1016/j.cnsns.2022.106573CrossRefGoogle ScholarPubMed
Bloom, D. E., Khoury, A., Kufenko, V. and Prettner, K.. (2021) Spurring economic growth through human development: Research results and guidance for policymakers. Population and Development Review 47(2), 377409.10.1111/padr.12389CrossRefGoogle Scholar
Blundell, R. and Bond, S.. (1998) Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics 87(1), 115143.10.1016/S0304-4076(98)00009-8CrossRefGoogle Scholar
Boehm, B. and Punzo, L. F.. (1994) Dynamics of industrial sectors and structural change in the Austrian and Italian economies. In: Boehm, B. and Punzo, L. F.. (eds.), Economic Performance. A Look at Austria and Italy. Berlin and Vienna: Physica Verlag.Google Scholar
Boehm, B. and Punzo, L. F.. (2001) Investment-productivity fluctuations and structural change. In: Boehm, B. and Punzo, L. F.. (ed.), Cycles, Growth and Structural Change. London: Routledge.Google Scholar
Bollt, E. M., Stanford, T., Lai, Y. C. and Życzkowski, K.. (2001) What symbolic dynamics do we get with a misplaced partition? On the validity of threshold crossings analysis of chaotic time-series. Physica D: Nonlinear Phenomena 154(3-4), 259286.10.1016/S0167-2789(01)00242-1CrossRefGoogle Scholar
Boltvinik, J. and Damián, A.. (2020) Medición de la pobreza de México: Análisis crítico comparativo de los diferentes métodos aplicados. Recomendaciones de buenas prácticas para la medición de la pobreza en México y América Latina. En serie Estudios y Perspectivas-Sede subregional de la CEPAL en México, N° 183 (LC/TS.2020/43-LC/MEX/TS.2020/11), Ciudad de México, Comisión Económica para América Latina y el Caribe (CEPAL).Google Scholar
Bowles, S. (1998) Endogenous preferences: The cultural consequences of markets and other economic institutions. Journal of Economic Literature 36(1), 75111.Google Scholar
Bowles, S. (2006) Institutional poverty traps. In: Bowles, S. (eds.), Poverty Traps, pp. 116138. Princeton, NJ: Princeton University Press.Google Scholar
Bowles, S. (2008) Policies designed for self-interested citizens may undermine “the moral sentiments”: Evidence from economic experiments. Science (New York, N.Y.) 320(5883), 16051609. DOI: 10.1126/science.1152110.10.1126/science.1152110CrossRefGoogle ScholarPubMed
Bowles, S., Durlauf, S. N. and Hoff, K. R. (2006) Poverty Traps. Princeton, NJ: Princeton University Press. https://press.princeton.edu/books/paperback/9780691170930/poverty-traps Google Scholar
Brida, J. G., Risso, W. A., Sánchez Carrera, E. J. and Segarra, V.. (2021) Growth and inequality in the Mexican states: Regimes, thresholds, and traps. Papers in Regional Science 100(5), 12951322.10.1111/pirs.12616CrossRefGoogle Scholar
CEPAL (Comisión Económica para América Latina y el Caribe). (2020a) Enfrentar los efectos cada vez mayores del COVID-19 para una reactivación con igualdad: nuevas proyecciones. Informe Especial número, N° 5, julio.Google Scholar
CEPAL (Comisión Económica para América Latina y el Caribe). (2020b) El desafío social en tiempos del COVID-19. Informe Especial, N°3, Santiago de Chile.Google Scholar
Ceroni, C. B. (2001) Poverty traps and human capital accumulation. Economica 68(270), pages 203219.10.1111/1468-0335.00242CrossRefGoogle Scholar
CONEVAL (Consejo Nacional de Evaluación de la Política de Desarrollo Social). (2019) Metodología para la medición multidimensional de la pobreza en México, 3era edición, junio. https://www.coneval.org.mx/InformesPublicaciones/ InformesPublicaciones/Documents/Metodologia-medicion-multidimensional-3er-edicion.pdf Google Scholar
Cooper, D. J. and Kagel, J. H.. (2016) Other-regarding preferences: A selective survey of experimental results. In: Cooper, D. J. and Kagel, J. H.. (eds.), The Handbook of Experimental Economics, Vol. 2, pp. 217275. Princeton, NJ: Princeton University Press.Google Scholar
Daw, C. S., Finney, C. E. A. and Tracy, E. R.. (2003) A review of symbolic analysis of experimental data. Review of Scientific Instruments 74(2), 915930.10.1063/1.1531823CrossRefGoogle Scholar
Durlauf, S. (1996) A theory of persistent income inequality. Journal of Economic Growth 1(1), 7593.10.1007/BF00163343CrossRefGoogle Scholar
Durlauf, S. (2001) The Memberships Theory of Poverty: The Role of Group Affiliations in Determining Socioeconomic Outcomes. Mimeo, University of Wisconsin Madison, Department of Economics.Google Scholar
Durlauf, S. N. (2003) Neighborhood Effects, Madison, University of Wisconsin, Department of Economics, SSRI Working Paper 2003-17. In: Durlauf, S. N. (eds.), Handbook of Regional and Urban Economics, Vol. 4, Cities and Geography (Handbooks in Economics 7). Amsterdam: North-Holland. DOI: 10.1016/S1574-0080(04)80007-5.Google Scholar
ECLAC - Economic Commission for Latin America and the Caribbean. (2020) Fiscal Panorama of Latin America and the Caribbean 2020 (LC/PUB.2020/6-P). Santiago. https://www.cepal.org/sites/default/files/publication/files/ 45731/S2000153_en.pdf Google Scholar
Edmond, C. (2013) Information manipulation, coordination, and regime change. Review of Economic Studies 80(4), 14221458.10.1093/restud/rdt020CrossRefGoogle Scholar
Emerson, P. M. and Souza, A. P.. (2003) Is there a child labor trap? Intergenerational persistence of child labor in Brazil. Economic Development and Cultural Change 51(2), 375398.10.1086/346003CrossRefGoogle Scholar
Fehr, E. and Schmidt, K. M.. (1999) A theory of fairness, competition and cooperation. The Quarterly Journal of Economics 114(3), 817868.10.1162/003355399556151CrossRefGoogle Scholar
Galor, O. and Zeira, J. (1993) Income distribution and macroeconomics. Review of Economic Studies 60(1), 3552. DOI: 10.2307/2297811.10.2307/2297811CrossRefGoogle Scholar
Growiec, K. and Growiec, J.. (2014) Social capital, trust, and multiple equilibria in economic performance. Macroeconomic Dynamics 18(2), 282315. DOI: 10.1017/S136510051200034X.10.1017/S136510051200034XCrossRefGoogle Scholar
Heinz, N. and Koessler, A.-K.. (2021) Other-regarding preferences and pro-environmental behaviour: An interdisciplinary review of experimental studies. Ecological Economics 184(C), 106987.10.1016/j.ecolecon.2021.106987CrossRefGoogle Scholar
Hirata, Y., Judd, K. and Kilminster, D.. (2004) Estimating a generating partition from observed time series: Symbolic shadowing. Physical Review E 70(1), 016215.10.1103/PhysRevE.70.016215CrossRefGoogle ScholarPubMed
Hirschman, A. O. (1958) The Strategy of Economic Development. Yale University Press.Google Scholar
Hofbauer, J. and Sigmund, K. (1998) Evolutionary Games and Population Dynamics. Cambridge University Press. DOI: 10.1017/CBO9781139173179.10.1017/CBO9781139173179CrossRefGoogle Scholar
INEE- Instituto Nacional para la Evaluación dela Educación. (2014) El Derecho a una Educación de Calidad. Informe 2014. México: INEE.Google Scholar
Iniguez-Montiel, A. J., Kurosaki, T. and T. (2018) Growth, inequality and poverty dynamics in Mexico. Latin American Economic Review 27(1), 12. DOI: 10.1186/s40503-018-0058-9.10.1186/s40503-018-0058-9CrossRefGoogle Scholar
Jalan, J. and Ravallion, M. (2004) Household income dynamics in rural China. In: Dercon, S. (ed.), Insurance Against Poverty, pp. 108–124. Oxford: Oxford University Press.10.1093/0199276838.003.0006CrossRefGoogle Scholar
Kraay, A. and McKenzie, D.. (2014) Do poverty traps exist? Assessing the evidence. The Journal of Economic Perspectives 28(3), 127148.10.1257/jep.28.3.127CrossRefGoogle Scholar
Kurths, J., Schwarz, U., Witt, A., Krampe, R. T. and Abel, M.. (1996) Measures of complexity in signal analysis. AIP Conference Proceedings 375(1), 3354.10.1063/1.51037CrossRefGoogle Scholar
Kuznetsov, Y. A. (2004) Elements of Applied Bifurcation Theory, Applied Mathematical Sciences, 3rd ed. New York, NY: Springer. DOI: 10.1007/978-1-4757-3978-7.10.1007/978-1-4757-3978-7CrossRefGoogle Scholar
Lustig, N. and Martínez Pabón, V.. (2021) The impact of COVID-19 on inequality and poverty in Mexico/El impacto del COVID-19 en la desigualdad y la pobreza en México. Estudios Económicos 36(1), 725.Google Scholar
Mathai, A. and Provost, S.. (1992) Quadratic Forms in Random Variables: Theory and Applications. New York: Marcel Dekker.Google Scholar
McKay, A. and Perge, E.. (2013) How strong is the evidence for the existence of poverty traps? A multicountry assessment. Journal of Development Studies 49(7), 877897.10.1080/00220388.2013.785521CrossRefGoogle Scholar
Mckinley, T. and Alarcon, D.. (1995) The prevalence of rural poverty in Mexico. World Development 23(9), 15751585.10.1016/0305-750X(95)00066-LCrossRefGoogle Scholar
Muñoz Izquierdo, C. and Silva Laya, M.. (2012) Revertir la desigualdad educativa, un paso decisivo para el desarrollo social. In: Muñoz Izquierdo, C. and Silva Laya, M.. (ed.), Políticas de educación, ciencia, tecnología y competitividad, pp. 4055. México: Juan Pablos Editor y Consejo Nacional de Universitarios.Google Scholar
Murphy, K. M., Shleifer, A. and Vishny, R. M. (1989) Industrialization and the big push. Journal of Political Economy 97(5), 10031026.10.1086/261641CrossRefGoogle Scholar
Noritomo, Y. and Takahashi, K.. (2020) Can insurance payouts prevent a poverty trap? Evidence from randomised experiments in northern Kenya. Journal of Development Studies 56(11), 20792096.10.1080/00220388.2020.1736281CrossRefGoogle Scholar
Piccardi, C. (2004) On the control of chaotic systems via symbolic time series analysis. Chaos: An Interdisciplinary Journal of Nonlinear Science 14(4), 10261034.10.1063/1.1796071CrossRefGoogle ScholarPubMed
Polterovich, V. (2008) Institutional trap. In: Polterovich, V. (eds.), The New Palgrave Dictionary of Economics. New York: Palgrave Macmillan.Google Scholar
Radosavljevic, S., Haider, L. J., Lade, S. J. and Schlüter, M.. (2021) Implications of poverty traps across levels. World Development 144(C), 105437.10.1016/j.worlddev.2021.105437CrossRefGoogle Scholar
Risso, W. A. (2014) An independence test based on symbolic time series. International Journal of Statistical Mechanics 2014, 114.10.1155/2014/809383CrossRefGoogle Scholar
Risso, W. A. (2015) A first approach on testing non-causality with symbolic time series. Economic Computation & Economic Cybernetics Studies & Research 49(3), 19.Google Scholar
Risso, W. A. (2018) Symbolic Time Series Analysis and Its Application in Social Sciences. IntechOpen.10.5772/intechopen.70826CrossRefGoogle Scholar
Risso, W. A., Punzo, L. F. and Sánchez Carrera, E. J.. (2013) Economic growth and income distribution in Mexico: A cointegration exercise. Economic Modelling 35(C), 708714.10.1016/j.econmod.2013.08.036CrossRefGoogle Scholar
Sanchez Carrera, E. (2019) Evolutionary dynamics of poverty traps. Journal of Evolutionary Economics 29(2), 611630.10.1007/s00191-018-0575-3CrossRefGoogle Scholar
Sánchez Carrera, E. (2012) Imitation and evolutionary stability of poverty traps. Journal of Bioeconomics 14(1), 120.10.1007/s10818-011-9114-0CrossRefGoogle Scholar
Tagliati, F. (2022) Welfare effects of an in-kind transfer program: Evidence from Mexico. Journal of Development Economics 154(C), 102753.10.1016/j.jdeveco.2021.102753CrossRefGoogle Scholar
Taylor, P. D. (1979) Evolutionarily stable strategies with two types of player. Journal of Applied Probability 16(1), 7683. DOI: 10.2307/3213376.10.2307/3213376CrossRefGoogle Scholar
Taylor, P. D. and Jonker, L. B. (1978) Evolutionarily stable strategies and game dynamics. Bellman Prize in Mathematical Biosciences 40, 145156.10.1016/0025-5564(78)90077-9CrossRefGoogle Scholar
Todd, P. E. and Wolpin, K. I.. (2006) Assessing the impact of a school subsidy program in Mexico: Using a social experiment to validate a dynamic behavioral model of child schooling and fertility. American Economic Review 96(5), 13841417.10.1257/aer.96.5.1384CrossRefGoogle ScholarPubMed
Weibull, J. W. (1995) Evolutionary Game Theory. Cambridge, MA: MIT Press.Google Scholar
Williams, S. G. (2004) Symbolic Dynamics and Its Applications: American Mathematical Society, Short Course, January 4-5, 2002, San Diego, California, Vol. 60. American Mathematical Society.10.1090/psapm/060CrossRefGoogle Scholar
World Bank. (2005) Mexico - Income Generation and Social Protection for the Poor: Volume 4. A Study of Rural Poverty in Mexico. Washington, DC: World Bank. https://openknowledge.worldbank.org/handle/10986/8286. License: CC BY 3.0 IGO.Google Scholar
World Bank Group. (2018) Mexico Systematic Country Diagnostic. Washington, DC: World Bank. https://openknowledge.worldbank.org/handle/10986/31130. License: CC BY 3.0 IGO.Google Scholar