Titulo:
Probabilidad e incertidumbre en Keynes. Una revisión de tipo bayesiano
.
Sumario:
Este articulo analiza el concepto de probabilidad en la obra de Keynes y propone un metodo para formalizar la nocion de la incertidumbre en la Teoría general utilizando el teorema de Bayes y el principio de maxima entropia. Una de las principales conclusiones es que, a pesar de compartir su rechazo del enfoque frecuentista de la estadistica, es poco razonable pensar que no se pueden determinar probabilidades numericas, aunque se cumpla algun criterio de objetividad.
Guardado en:
0124-5996
2346-2450
23
2021-07-01
137
162
Juan Esteban Jacobo - 2021
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
info:eu-repo/semantics/openAccess
http://purl.org/coar/access_right/c_abf2
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Probabilidad e incertidumbre en Keynes. Una revisión de tipo bayesiano Uncertainty and probability in Keynes. A Bayesian-type review Este articulo analiza el concepto de probabilidad en la obra de Keynes y propone un metodo para formalizar la nocion de la incertidumbre en la Teoría general utilizando el teorema de Bayes y el principio de maxima entropia. Una de las principales conclusiones es que, a pesar de compartir su rechazo del enfoque frecuentista de la estadistica, es poco razonable pensar que no se pueden determinar probabilidades numericas, aunque se cumpla algun criterio de objetividad. This paper analyzes the concept of probability in Keynes’ work and proposes a method for formalizing the notion of uncertainty in the General Theory using Bayes’ theorem and the principle of maximum entropy. One of the main conclusions is that, despite sharing his rejection of the frequentist approach to statistics, it is unreasonable to think that numerical probabilities cannot be determined, even if some criterion of objectivity is met. Jacobo, Juan Esteban entropy, Bayes’ theorem, uncertainty, Keynes B16, B31, C11 entropia, teorema de Bayes, incertidumbre, Keynes B16, B31, C11 entropia, teorema de Bayes, incerteza, Keynes B16, B31, C11 23 45 Núm. 45 , Año 2021 : Julio-diciembre Artículo de revista Journal article 2021-07-01T07:01:15Z 2021-07-01T07:01:15Z 2021-07-01 application/pdf text/html text/xml Universidad Externado de Colombia Revista de Economía Institucional 0124-5996 2346-2450 https://revistas.uexternado.edu.co/index.php/ecoins/article/view/7338 10.18601/01245996.v23n45.07 https://doi.org/10.18601/01245996.v23n45.07 spa http://creativecommons.org/licenses/by-nc-sa/4.0 Juan Esteban Jacobo - 2021 Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0. 137 162 <p>Bateman, B. (1987). Keynes’s changing conception of probability. Economics and Philosophy, 3(1), 97-119.<br>Bauwens, L., Lubrano, M. y Richard, J.-F. (2000). Bayesian inference in dynamic econometric models. Oxford: Oxford University Press.<br>Carabelli, A. (1988). On Keynes’s method. Nueva York: Palgrave Macmillan.<br>Cover, T. y Thomas, J. (2006). Elements of information theory. Hoboken: Wiley & Sons.<br>Cox, R. (1961). The algebra of probable inference. Baltimore: The John Hopkins Press.<br>Feduzi, A. (2007). On the relationship between Keynes’s conception of evidential weight and the Ellsberg Paradox. Journal of Economic Psychology, 28(5), 545-565.<br>Feduzi, A., Runde, J. y Zappia, C. (2013). De Finetti on Uncertainty. Cambridge Journal of Economics, 38(1), 1-21.<br>Jaynes, E. (1957). Information theory and statistical mechanics. The Physical Review, 106(4), 620-630.<br>Jaynes, E. (2003). Probability theory: The logic of science. Cambridge: Cambridge University Press.<br>Keynes, J. M. (1921). A treatise on probability. En E. Johnson y D. Moggridge (eds.), The collected writings of John Maynard Keynes, v. VIII. Cambridge: Cambridge University Press for the Royal Society.<br>Keynes, J. M. (1933). Essays in biography En E. Johnson y D. Moggridge (eds.), The collected writings of John Maynard Keynes, v. X. Cambridge: Cambridge University Press for the Royal Society.<br>Keynes, J. M. (1936). The general theory. En E. Johnson y D. Moggridge (eds.), The collected writings of John Maynard Keynes (vol. VII). Cambridge: Cambridge University Press for the Royal Society.<br>Keynes, J. M. (1973). The general theory and after: Part II. Defence and development. En E. Johnson y D. Moggridge (eds.), The collected writings of John Maynard Keynes, v. XIV. Cambridge: Cambridge University Press for the Royal Society.<br>Lindley, D. (1987). Using expert advice on a skew judgmental distribution. Operations Research, 35(5), 716-721.<br>Lindley, D. (2000). The philosophy of statistics. Journal of the Royal Society. Series D, 49(3), 293-337.<br>O’Donnel, R. (1989). Keynes: Philosophy, economics and politics. Nueva York: Palgrave Macmillan.<br>Patinkin, D. (1976). Keynes and econometrics: On the interaction between the macroeconomic revolutions of the interwar period. Econometrica, 44(6), 1091-1123.<br>Ramsey, F. (1960). Truth and probability [1926]. En R. Braithwaite, The foundations of mathematics and other logical essays. Londres: Littlefield, Adams & Co.<br>Roncaglia, A. (2009). Keynes and probability: An assessment. The European Journal of the History of Economic Thought, 16(3), 489-510.<br>Samuelson, P. (1946). Lord Keynes and the General Theory. Econometrica, 14(3), 187-200.<br>Zellner, A. (1971). An introduction to Bayesian inference in econometrics. Nueva York: Wiley.<br>Zellner, A. (1991). Bayesian methods and entropy in economics and econometrics. En W. Grandy e I. Shick, Maximum entropy and Bayesian methods. Fundamental theories of physics. Dordrecht: Springer.</p> https://revistas.uexternado.edu.co/index.php/ecoins/article/download/7338/10065 https://revistas.uexternado.edu.co/index.php/ecoins/article/download/7338/13167 https://revistas.uexternado.edu.co/index.php/ecoins/article/download/7338/13267 info:eu-repo/semantics/article http://purl.org/coar/resource_type/c_6501 http://purl.org/redcol/resource_type/ARTREF info:eu-repo/semantics/publishedVersion http://purl.org/coar/version/c_970fb48d4fbd8a85 info:eu-repo/semantics/openAccess http://purl.org/coar/access_right/c_abf2 Text Publication |
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UNIVERSIDAD EXTERNADO DE COLOMBIA |
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Revista de Economía Institucional |
| title |
Probabilidad e incertidumbre en Keynes. Una revisión de tipo bayesiano |
| spellingShingle |
Probabilidad e incertidumbre en Keynes. Una revisión de tipo bayesiano Jacobo, Juan Esteban entropy, Bayes’ theorem, uncertainty, Keynes B16, B31, C11 entropia, teorema de Bayes, incertidumbre, Keynes B16, B31, C11 entropia, teorema de Bayes, incerteza, Keynes B16, B31, C11 |
| title_short |
Probabilidad e incertidumbre en Keynes. Una revisión de tipo bayesiano |
| title_full |
Probabilidad e incertidumbre en Keynes. Una revisión de tipo bayesiano |
| title_fullStr |
Probabilidad e incertidumbre en Keynes. Una revisión de tipo bayesiano |
| title_full_unstemmed |
Probabilidad e incertidumbre en Keynes. Una revisión de tipo bayesiano |
| title_sort |
probabilidad e incertidumbre en keynes. una revisión de tipo bayesiano |
| title_eng |
Uncertainty and probability in Keynes. A Bayesian-type review |
| description |
Este articulo analiza el concepto de probabilidad en la obra de Keynes y propone un metodo para formalizar la nocion de la incertidumbre en la Teoría general utilizando el teorema de Bayes y el principio de maxima entropia. Una de las principales conclusiones es que, a pesar de compartir su rechazo del enfoque frecuentista de la estadistica, es poco razonable pensar que no se pueden determinar probabilidades numericas, aunque se cumpla algun criterio de objetividad.
|
| description_eng |
This paper analyzes the concept of probability in Keynes’ work and proposes a method for formalizing the notion of uncertainty in the General Theory using Bayes’ theorem and the principle of maximum entropy. One of the main conclusions is that, despite sharing his rejection of the frequentist approach to statistics, it is unreasonable to think that numerical probabilities cannot be determined, even if some criterion of objectivity is met.
|
| author |
Jacobo, Juan Esteban |
| author_facet |
Jacobo, Juan Esteban |
| topic |
entropy, Bayes’ theorem, uncertainty, Keynes B16, B31, C11 entropia, teorema de Bayes, incertidumbre, Keynes B16, B31, C11 entropia, teorema de Bayes, incerteza, Keynes B16, B31, C11 |
| topic_facet |
entropy, Bayes’ theorem, uncertainty, Keynes B16, B31, C11 entropia, teorema de Bayes, incertidumbre, Keynes B16, B31, C11 entropia, teorema de Bayes, incerteza, Keynes B16, B31, C11 |
| topicspa_str_mv |
entropia, teorema de Bayes, incertidumbre, Keynes B16, B31, C11 entropia, teorema de Bayes, incerteza, Keynes B16, B31, C11 |
| citationvolume |
23 |
| citationissue |
45 |
| citationedition |
Núm. 45 , Año 2021 : Julio-diciembre |
| publisher |
Universidad Externado de Colombia |
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Revista de Economía Institucional |
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https://revistas.uexternado.edu.co/index.php/ecoins/article/view/7338 |
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spa |
| format |
Article |
| rights |
http://creativecommons.org/licenses/by-nc-sa/4.0 Juan Esteban Jacobo - 2021 Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0. info:eu-repo/semantics/openAccess http://purl.org/coar/access_right/c_abf2 |
| references |
<p>Bateman, B. (1987). Keynes’s changing conception of probability. Economics and Philosophy, 3(1), 97-119.<br>Bauwens, L., Lubrano, M. y Richard, J.-F. (2000). Bayesian inference in dynamic econometric models. Oxford: Oxford University Press.<br>Carabelli, A. (1988). On Keynes’s method. Nueva York: Palgrave Macmillan.<br>Cover, T. y Thomas, J. (2006). Elements of information theory. Hoboken: Wiley & Sons.<br>Cox, R. (1961). The algebra of probable inference. Baltimore: The John Hopkins Press.<br>Feduzi, A. (2007). On the relationship between Keynes’s conception of evidential weight and the Ellsberg Paradox. Journal of Economic Psychology, 28(5), 545-565.<br>Feduzi, A., Runde, J. y Zappia, C. (2013). De Finetti on Uncertainty. Cambridge Journal of Economics, 38(1), 1-21.<br>Jaynes, E. (1957). Information theory and statistical mechanics. The Physical Review, 106(4), 620-630.<br>Jaynes, E. (2003). Probability theory: The logic of science. Cambridge: Cambridge University Press.<br>Keynes, J. M. (1921). A treatise on probability. En E. Johnson y D. Moggridge (eds.), The collected writings of John Maynard Keynes, v. VIII. Cambridge: Cambridge University Press for the Royal Society.<br>Keynes, J. M. (1933). Essays in biography En E. Johnson y D. Moggridge (eds.), The collected writings of John Maynard Keynes, v. X. Cambridge: Cambridge University Press for the Royal Society.<br>Keynes, J. M. (1936). The general theory. En E. Johnson y D. Moggridge (eds.), The collected writings of John Maynard Keynes (vol. VII). Cambridge: Cambridge University Press for the Royal Society.<br>Keynes, J. M. (1973). The general theory and after: Part II. Defence and development. En E. Johnson y D. Moggridge (eds.), The collected writings of John Maynard Keynes, v. XIV. Cambridge: Cambridge University Press for the Royal Society.<br>Lindley, D. (1987). Using expert advice on a skew judgmental distribution. Operations Research, 35(5), 716-721.<br>Lindley, D. (2000). The philosophy of statistics. Journal of the Royal Society. Series D, 49(3), 293-337.<br>O’Donnel, R. (1989). Keynes: Philosophy, economics and politics. Nueva York: Palgrave Macmillan.<br>Patinkin, D. (1976). Keynes and econometrics: On the interaction between the macroeconomic revolutions of the interwar period. Econometrica, 44(6), 1091-1123.<br>Ramsey, F. (1960). Truth and probability [1926]. En R. Braithwaite, The foundations of mathematics and other logical essays. Londres: Littlefield, Adams & Co.<br>Roncaglia, A. (2009). Keynes and probability: An assessment. The European Journal of the History of Economic Thought, 16(3), 489-510.<br>Samuelson, P. (1946). Lord Keynes and the General Theory. Econometrica, 14(3), 187-200.<br>Zellner, A. (1971). An introduction to Bayesian inference in econometrics. Nueva York: Wiley.<br>Zellner, A. (1991). Bayesian methods and entropy in economics and econometrics. En W. Grandy e I. Shick, Maximum entropy and Bayesian methods. Fundamental theories of physics. Dordrecht: Springer.</p> |
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