Algunas lecturas para este fin de semana: (son lecturas más académicas sobre el debate macro)
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La columna en el NYT de Mankiw que aparece mañana. If You Have the Answers, Tell Me. Señala las limitaciones que enfrentamos los macroeconomistas, y en este marco apunta tres temas que son una incógnita para él. El tema de la recuperación; el anclaje de las expectativas inflacionarias y el comportamiento del mercado de bonos.
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En esta segunda Lectura, Economics in Crisis, Brad De Long elabora sobre una respuesta que Summers le dio a Martin Wolf en un evento reciente en Bretton Woods en donde cuestionaba el por qué los economistas no vieron ni entendieron bien lo que sucedió en la reciente crisis. Summers fue crítico con el contenido de los enseñado actualmente en los programas doctorales y DeLong elabora en este sentido:
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...It is the scale of the catastrophe that astonishes me. But what astonishes me even more is the apparent failure of academic economics to take steps to prepare itself for the future. “We need to change our hiring patterns,” I expected to hear economics departments around the world say in the wake of the crisis.
The fact is that we need fewer efficient-markets theorists and more people who work on microstructure, limits to arbitrage, and cognitive biases. We need fewer equilibrium business-cycle theorists and more old-fashioned Keynesians and monetarists. We need more monetary historians and historians of economic thought and fewer model-builders. We need more Eichengreens, Shillers, Akerlofs, Reinharts, and Rogoffs – not to mention a Kindleberger, Minsky, or Bagehot....
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Finalmente, un interesante post en un Blog de un estudiante de doctorado en Economía en Wisconsin, pero que su formación es de físico y cuestiona lo que aprendió en sus cursos de macro en el doctorado. En ese mismo post se encuentra la liga para la primera parte. Vale la pena leerlo. Cabe mencionar que esta reflexión ha sido comentada por otros profesores en sus blogs...
What I learned in econ grad school, Part 2
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There were two other big conclusions I drew from that course.
The first was that the DSGE framework is a straitjacket that is strangling the field. It's very costly in terms of time and computing resources to solve a model with more than one or two "frictions" (i.e. realistic elements), with more than a few structural parameters, with hysteresis, or with heterogeneity, etc. This means that what ends up getting published are the very simplest models - the basic RBC model, for example. (Incidentally, that also biases the field toward models in which markets are close to efficient, and in which government policy thus plays only a small role.)
Worse, all of the mathematical formalism and kludgy numerical solutions of DSGE give you basically zero forecasting ability (and, in almost all cases, no better than an SVAR). All you get from using DSGE, it seems, is the opportunity to puff up your chest and say "Well, MY model is fully microfounded, and contains only 'deep structural' parameters like tastes and technology!"...Well, that, and a shot at publication in a top journal.
Finally, my field course taught me what a bad deal the whole neoclassical paradigm was. When people like Jordi Gali found that RBC models didn't square with the evidence, it did not give any discernible pause to the multitudes of researchers who assume that technology shocks cause recessions. The aforementioned paper by Basu, Fernald and Kimball uses RBC's own framework to show its internal contradictions - it jumps through all the hoops set up by Lucas and Prescott - but I don't exactly expect it to derail the neoclassical program any more than did Gali.
.
La columna en el NYT de Mankiw que aparece mañana. If You Have the Answers, Tell Me. Señala las limitaciones que enfrentamos los macroeconomistas, y en este marco apunta tres temas que son una incógnita para él. El tema de la recuperación; el anclaje de las expectativas inflacionarias y el comportamiento del mercado de bonos.
.
En esta segunda Lectura, Economics in Crisis, Brad De Long elabora sobre una respuesta que Summers le dio a Martin Wolf en un evento reciente en Bretton Woods en donde cuestionaba el por qué los economistas no vieron ni entendieron bien lo que sucedió en la reciente crisis. Summers fue crítico con el contenido de los enseñado actualmente en los programas doctorales y DeLong elabora en este sentido:
.
...It is the scale of the catastrophe that astonishes me. But what astonishes me even more is the apparent failure of academic economics to take steps to prepare itself for the future. “We need to change our hiring patterns,” I expected to hear economics departments around the world say in the wake of the crisis.
The fact is that we need fewer efficient-markets theorists and more people who work on microstructure, limits to arbitrage, and cognitive biases. We need fewer equilibrium business-cycle theorists and more old-fashioned Keynesians and monetarists. We need more monetary historians and historians of economic thought and fewer model-builders. We need more Eichengreens, Shillers, Akerlofs, Reinharts, and Rogoffs – not to mention a Kindleberger, Minsky, or Bagehot....
.
Finalmente, un interesante post en un Blog de un estudiante de doctorado en Economía en Wisconsin, pero que su formación es de físico y cuestiona lo que aprendió en sus cursos de macro en el doctorado. En ese mismo post se encuentra la liga para la primera parte. Vale la pena leerlo. Cabe mencionar que esta reflexión ha sido comentada por otros profesores en sus blogs...
What I learned in econ grad school, Part 2
.
There were two other big conclusions I drew from that course.
The first was that the DSGE framework is a straitjacket that is strangling the field. It's very costly in terms of time and computing resources to solve a model with more than one or two "frictions" (i.e. realistic elements), with more than a few structural parameters, with hysteresis, or with heterogeneity, etc. This means that what ends up getting published are the very simplest models - the basic RBC model, for example. (Incidentally, that also biases the field toward models in which markets are close to efficient, and in which government policy thus plays only a small role.)
Worse, all of the mathematical formalism and kludgy numerical solutions of DSGE give you basically zero forecasting ability (and, in almost all cases, no better than an SVAR). All you get from using DSGE, it seems, is the opportunity to puff up your chest and say "Well, MY model is fully microfounded, and contains only 'deep structural' parameters like tastes and technology!"...Well, that, and a shot at publication in a top journal.
Finally, my field course taught me what a bad deal the whole neoclassical paradigm was. When people like Jordi Gali found that RBC models didn't square with the evidence, it did not give any discernible pause to the multitudes of researchers who assume that technology shocks cause recessions. The aforementioned paper by Basu, Fernald and Kimball uses RBC's own framework to show its internal contradictions - it jumps through all the hoops set up by Lucas and Prescott - but I don't exactly expect it to derail the neoclassical program any more than did Gali.
1 comentario:
Creo que el artículo de Mankiw es sólo un ejemplo de un problema más grande entre los economistas: la imposibilidad de hacer experimentos controlados. Desafortunadamente, la economía no es una ciencia exacta por lo que los resultados de las investigaciones deben tomarse con cautela.
Sarait
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