Cuando el método redefine el problema: identificación causal y límites del análisis del desarrollo en América Latina
DOI:
https://doi.org/10.35319/lajed.202645625Palabras clave:
Credibilidad Empírica, economía del desarrollo, identificación causal, procesos estructurales, América LatinaResumen
Este artículo examina cómo la literatura económica ha abordado los problemas estructurales del desarrollo en América Latina en el contexto de la consolidación de estándares de evidencia empírica, centrados en la validez interna y la identificación causal. A partir de una revisión sistemática, el estudio analiza cómo estas orientaciones han condicionado la formulación de los problemas de investigación, la delimitación de fenómenos empíricamente abordables y el tratamiento de cuestiones como la generalización de resultados y la validez externa. Los resultados indican que, si bien estos avances elevaron de manera sustantiva el rigor empírico de la investigación aplicada, también favorecieron una fragmentación analítica de los procesos estructurales del desarrollo, desplazando explicaciones integradas de largo plazo. El artículo discute las implicaciones de este desplazamiento y subraya la necesidad de enfoques pluralistas y sensibles al contexto institucional para el análisis del desarrollo latinoamericano.
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Andrews, I., Gentzkow, M. y Shapiro, J. M. (2017). Measuring the sensitivity of parameter estimates to estimation moments. Quarterly Journal of Economics, 132(4), 1553-1592. https://doi.org/10.1093/qje/qjx0232 .
Angrist, J. D. y Pischke, J.-S. (2010). The credibility revolution in empirical economics: How better research design is taking the con out of econometrics. Journal of Economic Perspectives, 24(2), 3-30. https://doi.org/10.1257/jep.24.2.3
Angrist, J. D. y Pischke, J.-S. (2017). Undergraduate econometrics instruction: Through our classes, darkly. Journal of Economic Perspectives, 31(2), 125-144. https://doi.org/10.1257/jep.31.2.125
Athey, S. (2018). The impact of machine learning on economics. The Economics of Artificial Intelligence. University of Chicago Press. https://doi.org/10.7208/chicago/9780226613475.003.0021
Athey, S. e Imbens, G. W. (2017). The state of applied econometrics: Causality and policy evaluation. Journal of Economic Perspectives, 31(2), 3-32. https://doi.org/10.1257/jep.31.2.3
---------- (2019). Machine learning methods that economists should know about. Annual Review of Economics, 11, 685-725. https://doi.org/10.1146/annureveconomics-080217-053433
Backhouse, R. E. y Cherrier, B. (2017). The age of the applied economist. History of Political Economy, 49 (Supplement), 1-33. https://doi.org/10.1215/00182702-4166239
Banerjee, A. V. y Duflo, E. (2008). The Experimental Approach to Development Economics, NBER Working Paper N° 14467. https://doi.org/10.3386/w14467
Bold, T., Kimenyi, M., Mwabu, G., Ng’ang’a, A. y Sandefur, J. (2018). Experimental evidence on scaling up education reforms in Kenya. Journal of Public Economics, 168, 1-20. https://doi.org/10.1016/j.jpubeco.2018.08.007
Busso, M., Fazio, M. V. y Levy, S. (2012). (In)formal and (un)productive: the productivity costs of excessive informality in Mexico. Inter-American Development Bank. http://dx.doi.org/10.18235/0011401
Deaton, A. (2020). Randomization in the tropics revisited. En Bédécarrats, F., Guérin, I. y Roubaud, F. (Eds.), Randomized control trials in the field of development: a critical perspective. Oxford University Press. https://doi.org/10.1093/oso/9780198865360.003.0002
---------- (2024). Rethinking my economics. F y D Magazine https://www.imf.org/en/publications/fandd/issues/2024/03/symposium-rethinking-economics-angus-deaton
Deaton, A. y Cartwright, N. (2018). Understanding and misunderstanding randomized controlled trials. Social Science & Medicine, 210, 2-21. https://doi.org/10.1016/j.socscimed.2017.12.005
Ferraz, C. y Finan, F. (2008). Exposing corrupt politicians: the effects of Brazil’s publicly released audits on electoral outcomes. The Quarterly Journal of Economics, 123(2), 703- 745. https://doi.org/10.1162/qjec.2008.123.2.703
Finan, F., Olken, B. y Pande, R. (2017). The personnel economics of the developing state. Handbook of Economic Field Experiments, 2, 467-514. https://doi.org/10.1016/bs.hefe.2016.08.001
Gelman, A. e Imbens, G. (2013). Why ask why? Forward causal inference and reverse causal questions. NBER Working Paper N° 19614. https://doi.org/10.3386/w19614
Grant, M. J. y Booth, A. (2009). A typology of reviews: an analysis of 14 review types and associated methodologies. Health Information & Libraries Journal, 26(2), 91-108. https://doi.org/10.1111/j.1471-1842.2009.00848.x
Heckman, J. J. (2010). Building bridges between structural and program evaluation approaches to evaluating policy. Journal of Economic Literature, 48(2), 356-398. https://doi.org/10.1257/jel.48.2.356
Heckman, J. J. y Pinto, R. (2015). Econometric mediation analyses: Identifying the sources of treatment effects from experimentally estimated production technologies with unmeasured and mismeasured inputs. Econometric Reviews, 34(1-2), 6-31. https://doi.org/10.1080/07474938.2014.944466
Imbens, G. W. (2020). Potential outcome and directed acyclic graph approaches to causality: Relevance for empirical practice in economics. Journal of Economic Literature, 58(4), 1129-1179. https://doi.org/10.1257/jel.20191597
Ioannidis, J. P. A., Stanley, T. D. y Doucouliagos, H. (2017). The power of bias in economics research. Economic Journal, 127(605), F236-F265. https://doi.org/10.1111/ecoj.12461
Leamer, E. E. (2010). Tantalus on the road to asymptopia. Journal of Economic Perspectives, 24(2), 31-46. https://doi.org/10.1257/jep.24.2.31
Levy, S. y Schady, N. (2013). Latin America’s social policy challenge: education, social insurance, redistribution. Journal of Economic Perspectives, 27(2), 193-218. https://doi.org/10.1257/jep.27.2.193
Mazzuca, S. (2021). Latecomer state formation: political geography and capacity failure in Latin America. EEUU: Yale University Press.
Mazzuca, S. L. y Munck, G. L. (2014). State or democracy first? Alternative perspectives on the state-democracy nexus. Democratization, 21, 1221-1243. https://doi.org/10.1080/13510347.2014.960209
Paré, G., Trudel, M.-C., Jaana, M. y Kitsiou, S. (2015). Synthesizing information systems knowledge: A typology of literature reviews. Information & Management, 52(2), 183-199. https://doi.org/10.1016/j.im.2014.08.008
Petticrew, M. y Roberts, H. (2006). Systematic reviews in the social sciences: A practical guide. Blackwell Publishing.
Piketty, T., Saez, E. y Zucman, G. (2018). Distributional national accounts: Methods and estimates for the United States. Quarterly Journal of Economics, 133(2), 553-609. https://doi.org/10.1093/qje/qjx043
Pritchett, L., Woolcock, M. y Andrews, M. (2013). Looking like a state: techniques of persistent failure in state capability for implementation. Journal of Development Studies, 49(1), 1-18. https://doi.org/10.1080/00220388.2012.709614
Ravallion, M. (2020). Should the randomistas (continue to) rule? In Bédécarrats, F., Guérin, I. y Roubaud, F. (Eds.), Randomized control trials in the field of development: A critical perspective. Oxford University Press. https://doi.org/10.1093/oso/9780198865360.003.0003
Rodrik, D. (2008). Second-best institutions. American Economic Review, 98(2), 100-104. https://doi.org/10.1257/aer.98.2.100
---------- (2014). When ideas trump interests: Preferences, worldviews, and policy innovations. Journal of Economic Perspectives, 28(1), 189-208. https://doi.org/10.1257/jep.28.1.189
Vivalt, E. (2020). How much can we generalize from impact evaluations? Journal of the European Economic Association, 18(6), 3045-3089. https://doi.org/10.1093/jeea/jvaa019
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