Desde que se anunció el premio Nobel para Sims y Sargent, se han publicado distintas reflexiones sobre sus contribuciones y sobre el debate en la Macroeconomía. Les comparto algunas de estas notas que vale la pena revisar. En particular creo que hay dos temas bastante informativos: el papel del uso de modelos como los vectores autoregresivos (VAR) y el debate sobre el supuesto de expectativas racionales en la macro moderna.
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Otro gran economista (econometrista), Lars Peter Hansen, escribe este editorial en Bloomberg en donde explica cuáles son sus contribuciones, tales como los VAR y otros...
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Mark Thoma hace lo mismo, pero en relación a Sims
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Esta es una buena nota en economic principals, en donde sugiere cuatro momentos importantes en la historia económica desde Keynes, que permite poner en contexto las contribuciones de Sims y Sargent. Revisa el surgimiento de la Curva de Phillips, su uso y la critica que se plantea con Lucas. En esta misma nota se hace referencia al debate sobre expectativas racionales y otras alternativas, como la sugerida por Frydman y Goldberg en el sentido de un conocimiento imperfecto, idea expuesta en un controvertido libro, Beyond Mechanical Markets. y al cual también se refiere de Long en este post en su blog. Por cierto, en este post se transcribe parte de una entrevista de Evans y Honkapohja a Sargent que es lo siguiente
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Evans and Honkapohja: What were the profession's most important responses to the Lucas Critique?
Sargent: There were two. The first and most optimistic response was complete rational expectations econometrics. A rational expectations equilibrium is a likelihood function. Maximize it.
Evans and Honkapohja: Why optimistic?
Sargent: You have to believe in your model to use the likelihood function. it provides a coherent way to estimate objects of interest (preferences, technologies, information sets, measurement processes) within the context of a trusted model.
Evans and Honkapohja: What was the second response?
Sargent: Various types of calibration. Calibration is less optimistic about what your theory can accomplish because you would only use it if you din't fully trust your entire model, meaning that you think your model is partly misspecified or incompetely specified, or if you trusted someone else's model and data set more than your own. My recollection is that Bob Lucas and Ed Prescott were initially very enthusiastic about rational expetations econometrics. After all, it simply involved imposing on ourselves the same high standards we had criticized the Keynesians for failing to live up to. But after about five years of doing likelihood ratio tests on rational expectations models, I recall Bob Lucas and Ed Prescott both telling me that those tests were rejecting too many good models. The idea of calibration is to ignore some of the probabilistic implications of your model but to retain others. Somehow, calibration was intended as a balanced response to professing that your model, although not correct, is still worthy as a vehicle for quantitative policy analysis....
Evans and Honkapohja: Do you think calibration in macroeconomics was an advance?
Sargent: In many ways, yes. I view it as a constructive response to Bob' remark that "your likelihood ratio tests are rejecting too many good models". In those days... there was a danger that skeptics and opponents would misread those likelihood ratio tests as rejections of an entire class of models, which of course they were not.... The unstated cse for calibration was that it was a way to continue the process of acquiring experience in matching rational expectations models to data by lowering our standards relative to maximum likelihood, and emphasizing those features of the data that our models could capture. Instead of trumpeting their failures in terms of dismal likelihood ratio statistics, celebrate the featuers that they could capture and focus attention on the next unexplained feature that ought to be explained. One can argue that this was a sensible response... a sequential plan of attack: let's first devote resources to learning how to create a range of compelling equilibrium models to incorporate interesting mechanisms. We'll be careful about the estimation in later years when we have mastered the modelling technology...
.
Otro gran economista (econometrista), Lars Peter Hansen, escribe este editorial en Bloomberg en donde explica cuáles son sus contribuciones, tales como los VAR y otros...
.
Mark Thoma hace lo mismo, pero en relación a Sims
.
Esta es una buena nota en economic principals, en donde sugiere cuatro momentos importantes en la historia económica desde Keynes, que permite poner en contexto las contribuciones de Sims y Sargent. Revisa el surgimiento de la Curva de Phillips, su uso y la critica que se plantea con Lucas. En esta misma nota se hace referencia al debate sobre expectativas racionales y otras alternativas, como la sugerida por Frydman y Goldberg en el sentido de un conocimiento imperfecto, idea expuesta en un controvertido libro, Beyond Mechanical Markets. y al cual también se refiere de Long en este post en su blog. Por cierto, en este post se transcribe parte de una entrevista de Evans y Honkapohja a Sargent que es lo siguiente
.
Evans and Honkapohja: What were the profession's most important responses to the Lucas Critique?
Sargent: There were two. The first and most optimistic response was complete rational expectations econometrics. A rational expectations equilibrium is a likelihood function. Maximize it.
Evans and Honkapohja: Why optimistic?
Sargent: You have to believe in your model to use the likelihood function. it provides a coherent way to estimate objects of interest (preferences, technologies, information sets, measurement processes) within the context of a trusted model.
Evans and Honkapohja: What was the second response?
Sargent: Various types of calibration. Calibration is less optimistic about what your theory can accomplish because you would only use it if you din't fully trust your entire model, meaning that you think your model is partly misspecified or incompetely specified, or if you trusted someone else's model and data set more than your own. My recollection is that Bob Lucas and Ed Prescott were initially very enthusiastic about rational expetations econometrics. After all, it simply involved imposing on ourselves the same high standards we had criticized the Keynesians for failing to live up to. But after about five years of doing likelihood ratio tests on rational expectations models, I recall Bob Lucas and Ed Prescott both telling me that those tests were rejecting too many good models. The idea of calibration is to ignore some of the probabilistic implications of your model but to retain others. Somehow, calibration was intended as a balanced response to professing that your model, although not correct, is still worthy as a vehicle for quantitative policy analysis....
Evans and Honkapohja: Do you think calibration in macroeconomics was an advance?
Sargent: In many ways, yes. I view it as a constructive response to Bob' remark that "your likelihood ratio tests are rejecting too many good models". In those days... there was a danger that skeptics and opponents would misread those likelihood ratio tests as rejections of an entire class of models, which of course they were not.... The unstated cse for calibration was that it was a way to continue the process of acquiring experience in matching rational expectations models to data by lowering our standards relative to maximum likelihood, and emphasizing those features of the data that our models could capture. Instead of trumpeting their failures in terms of dismal likelihood ratio statistics, celebrate the featuers that they could capture and focus attention on the next unexplained feature that ought to be explained. One can argue that this was a sensible response... a sequential plan of attack: let's first devote resources to learning how to create a range of compelling equilibrium models to incorporate interesting mechanisms. We'll be careful about the estimation in later years when we have mastered the modelling technology...
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