La revolución empírica en economía

Contenido principal del artículo

Autores

Boris Salazar-Trujillo http://orcid.org/0000-0003-1872-7956
Daniel Otero-Robles https://orcid.org/0000-0001-8451-302X

Resumen

Este artículo intenta explicar el avance de la revolución empírica. Plantea que la búsqueda de experimentos naturales y cuasi naturales, allí donde estuvieran disponibles, para mejorar la credibilidad de los métodos de identificación, condujo a la creación y aplicación de nuevas herramientas econométricas y a su posterior propagación transversal a un número creciente de campos de la economía. La aplicación de los nuevos diseños y herramientas de investigación a la evaluación de intervenciones de política en todo el mundo, activó un potente sistema de retroalimentación que va de las intervenciones a su evaluación mediante nuevas herramientas econométricas, a la publicación de artículos académicos y a la generación de nuevas intervenciones. Usando redes de cocitación y redes semánticas de los artículos que introdujeron las nuevas herramientas, encontramos trazos de su impacto creciente sobre la práctica de los economistas, y de la emergencia de tres agrupaciones de investigadores como efecto de la irrupción del control sintético en 2003.

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Detalles del artículo

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Referencias

Abadie, A., Diamond, A. & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493–505. https://doi.org/10.1198/jasa.2009.ap08746

Abadie, A. & Gardeazabal, J. (2003). The Economic Costs of Conflict: A Case Study of the Basque Country. American Economic Review, 93(1), 113–32. https://doi.org/10.1257/000282803321455188

Angrist, J. D. 1990. Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security Administrative Records. American Economic Review 80: 313-336.

Angrist, J. D. (2004). American Education Research Changes Tack. Oxford Review of Economic Policy, 20(2), 198-212. https://doi.org/10.1093/oxrep/grh011

Angrist, J., Azoulay, P., Ellison, G., Hill, R. & Feng Lu, S. (2017). Economic Research Evolves: Fields and Styles. American Economic Review: Papers and Proceedings, 107(5), 293-297. https://doi.org/10.1257/aer.p20171117

Angrist, J. D., Imbens, G. W. & Rubin, D. B. (1996). Identification of Causal Effects Using Instrumental Variables. Journal of the American Statistical Association, 91(434), 444–55. https://doi.org/10.2307/2291629

Angrist, J. D. & Krueger, A. (2001). Instrumental Variables and the Search for Identification. Journal of Economic Perspectives, 15, 69-86.

Angrist, J. D. & Lavy, V. (1999). Using Maimonides’ Rule to Estimate Effects of Class Size on Student Achievement. Quaterly Journal of Economics, 114(2), 533-75. https://doi.org/10.3386/w5888

Angrist, J. D. & Pischke, J. S. (2010). The Credibility Revolution in Empirical Economic: 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

Arendt, H. (1960). On Revolution. New York: Penguin.

Ashenfelter, O. (1974). The Effect of Manpower Training on Earnings: Preliminary Results. Princeton, NJ: Princeton University Industrial Relations Section, Working Paper No 60.

Ashenfelter, O. (1987). The Case for Evaluating Training Programs with Randomized Trials, Economics of Education Review, 6(4): 333-338. https://doi.org/10.1016/0272-7757(87)90016-1

Ashenfelter, O. (2014). The Early History of Program Evaluation and the Department of Labor. Industry and Labor Review, 87(Suppl.), 374-377.


Ashenfelter, O. & Card, D. (2017). Introduction to “Essays in Honor of Robert J. LaLonde”. Princeton, NJ: Princeton University Industrial Relations Section, Working Paper No 610.

Ashenfelter, O. & Heckman, J. (1974). Measuring the Effect of an Antidiscrimination Program. Stanford, CA: NBER, Center of the Economic Analysis of Human Behavior and Social Institutions.

Athey, S. & 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

Backhouse, R. E. & Cherrier, B. (2017). The Age of the Applied Economist: The Transformation of Economics since 1970. History of Political Economy, 49 (Supplement): 1-33. https://doi.org/10.1215/00182702-4166239

Biagoli, M. (1993). Galileo Courtier. The Practice of Science in the Culture of Absolutism. Chicago: Chicago University Press. https://doi.org/10.1086/ahr/99.2.505

Blondel, V., Guillaume, J. L. Lambiote, R. & Lefebvre, E. (2008). Fast Unfolding of Communities in Large Networks. Journal of Statistical Mechanics: Theory and Experiment, 10 (P10008). DOI: 10.1088/1742-5468/2008/10/P10008. https://doi.org/10.1088/1742-5468/2008/10/p10008

Card, D. (1990). The Impact of the Mariel Boatlift on the Miami Labor Market. Industrial and Labor Relations Review, 43(2), 245–57. https://doi.org/10.2307/2523702

Card, D. & Krueger, A. B. (1992). Does School Quality Matter? Returns to Education and the Characteristics of Public Schools in the United States. Journal of Political Economy, 100 (1), 1-40. https://doi.org/10.1086/261805

Deaton, A. (2009). Instruments of Development: Randomization in the Tropic, and the Search for the Elusive Keys to Economic Development. Cambridge, MA: National Bureau of Economic Research Working Paper 14960. https://doi.org/10.3386/w14690

Deaton, A. & Cartwright, N. (2016). Understanding and Misunderstanding Randomized Control Trials. Durham, England: Durham University CHESS Working Paper 2016-05.

Dizikes, P. (2013, January 2). The Natural Experimenter. MIT Technology Review. Retrieved from http://www.technology review.com/article/508381/the-natural-experimenter/

Duflo, E. (2017). Richard D. Ely Lecture: The Economist as Plumber. American Economic Review Papers and Proceedings, 107(5), 1-26.

Erickson, P. (2015). The World the Game Theorists Made. Chicago: University of Chicago Press.

Griffiths, T. L. & Steyvers, M. (2002). A Probabilistic Approach to Semantic Representation. In Proceedings of the Twenty-Fourth Annual Conference of Cognitive Science Society (pp. 381-386). Hillsdale, NJ: Lawrence Erlbaum. https://doi.org/10.4324/9781315782379-102

Griffiths, T. L. & Steyvers, M. (2004). Finding Scientific Topics. PNAS, 101(1), 5228-5235.

Hammersh, D. S. (2013). Six Decades of Top Economics Publishing: Who and How? Journal of Economic Literature, 51(1), 162-172. https://doi.org/10.1257/jel.51.1.162

Heckman, J. J. & Urzúa, S. (2010). Comparing IV with Structural Methods: What Simple IV Can and Cannot Identify. Journal of Econometrics, 156(1), 27-37. https://doi.org/10.1016/j.jeconom.2009.09.006

Hendry, D. F. 1980. “Econometrics— Alchemy or Science?” Economica 47(188): 387–406. https://doi.org/10.2307/2553385

Imbens, G.W. (2010). Better LATE than Nothing: Some Comments on Heckman and Urzua (2009). Journal of Economic Literature, 48, 399-423. https://doi.org/10.1257/jel.48.2.399

Imbens, G. W. & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467–75. https://doi.org/10.2307/2951620

Imbens, G. W., D. Rubin, and B. I. Sacerdote. (2001). Estimating the Effect of Unearned Income on Labor Earnings, Savings and Consumption: Evidence from a Survey of Lottery Players. American Economic Review 91(4), 778-794. https://doi.org/10.3386/w7001

Imbens, G. W. & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. https://doi.org/10.1016/j.jeconom.2007.05.001

Jacob, B. A. & Lefgren, L. (2004). Remedial Education and Student Achievement: A Regression-Discontinuity Analysis. Review of Economics and Statistics, 86(1), 226–44. https://doi.org/10.1162/003465304323023778

Keane, M. P. (2010). A Structural Perspective on the Experimentalist School. Journal of Economic Perspectives, 24(2), 47-58. https://doi.org/10.1257/jep.24.2.47

Kleinberg, J. (1999). Authoritative Sources in a Hyperlinked Environment. JACM, 46(5), 604-632. https://doi.org/10.1145/324133.324140

Kuhn, T. S. (2000). The Road since Structure. Chicago: Chicago University Press.

LaLonde, R. J. (1986). Evaluating the Econometric Evaluation of Training Programs with Experimental Data. American Economic Review, 76(4), 604-20.

Leamer, E. E. (1983). Let’s Take the Con Out of Econometrics. American Economic Review, 73(1), 31-43.

Leamer, E. (2010). Tantalus on the Road to Asymptopia. Journal of Economic Perspectives, 34(2), 31-46. https://doi.org/10.1257/jep.24.2.31

Meyer, B. D. (1995). Natural and Quasi-Natural Experiments in Economics. Journal of Business and Economic Statistics, 13(2), 151-161. https://doi.org/10.2307/1392369

Salazar, B. & Otero, D. (2019). A Tale of Tool: The Impact of Sims’s Vector Autoregressions on Econometrics. History of Political Economy, 51(3), 557-578.

Small, H. (1973). Co-citation in the Scientific Literature: A New Measure of the Relationship Between Two Documents. Journal of the American Society for Information Science, 24(4), 265-269. https://doi.org/10.1002/asi.4630240406

Small, H. (1977). A Co-Citation of a Scientific Specialty: A Longitudinal Study of Collagen Research. Social Studies of Science, 7, 139-66.

Small, H. (1980). Co-citation Context Analysis and the Structure of Paradigms. Journal of Documentation, 36(3), 183-196. https://doi.org/10.1108/eb026695

Small, H. (1999, December/January). On the Shoulders of Giants. Bulletin of the American Society for the Information Science, 23-25.

Sims, C.A. (1980). Macroeconomics and Reality. Econometrica 48:1–48.

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