Articoli correlati a Macroeconomic Patterns and Stories: A Guide for MBAs
Sinossi
The story of this book began with my dif?cult transition from teaching international economics and econometrics in Economics Ph. D. programs at Harvard and UCLA to teaching in the MBA programs at the Anderson School at UCLA. On the basis of 20 years of apparent teaching success in Ph. D. education, I arrived at the Anderson School in 1990 with a self-image as a star teacher, but I was greeted with highly disturbingmediocreteachingevaluations. Facedwithadatasetthatwasinconsistent with my view of reality, I did what analysts usually do I formulated a theory why the data were misleading. Here is how I thought about it. Two aspects of the course content and amu- ment drive numerical course evaluations. If you rank courses by the average of the content score and the amusement score, then the component that can be measured most accurately will determine the ranking. Do you understand why? It is what - eraging does: it eliminates the noise. Suppose, for example, that a student cannot tell anything about the content, and the content score is simply a random number, varying from student to student. Those random numbers will average out across students to about the same number for each course. As the average course content score is about the same for every course, it is the amusement score that will drive the rankings.
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Dalla quarta di copertina
This book offers the wisdom and insight regarding the US economy from a well-known and distinguished econometrician who found himself first teaching macro economics to MBAs and then Directing the highly-regarded and widely-quoted UCLA/Anderson Forecast which provides quarterly forecasts for the US economy. Edward Leamer argues that "We are pattern-seeking story-telling animals." He provides in this book the patterns and stories that are the basis for his understanding of what determines the business cycle and what determines long-run economic growth.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
- EditoreSpringer Nature
- Data di pubblicazione2007
- ISBN 10 3540463887
- ISBN 13 9783540463887
- RilegaturaCopertina rigida
- LinguaInglese
- Numero di pagine359
- Contatto del produttorenon disponibile
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Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The story of this book began with my dif cult transition from teaching international economics and econometrics in Economics Ph. D. programs at Harvard and UCLA to teaching in the MBA programs at the Anderson School at UCLA. On the basis of 20 years of apparent teaching success in Ph. D. education, I arrived at the Anderson School in 1990 with a self-image as a star teacher, but I was greeted with highly disturbingmediocreteachingevaluations. Facedwithadatasetthatwasinconsistent with my view of reality, I did what analysts usually do - I formulated a theory why the data were misleading. Here is how I thought about it. Two aspects of the course - content and amu- ment - drive numerical course evaluations. If you rank courses by the average of the content score and the amusement score, then the component that can be measured most accurately will determine the ranking. Do you understand why It is what - eraging does: it eliminates the noise. Suppose, for example, that a student cannot tell anything about the content, and the content score is simply a random number, varying from student to student. Those random numbers will average out across students to about the same number for each course. As the average course content score is about the same for every course, it is the amusement score that will drive the rankings. 360 pp. Englisch. Codice articolo 9783540463887
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The story of this book began with my dif cult transition from teaching international economics and econometrics in Economics Ph. D. programs at Harvard and UCLA to teaching in the MBA programs at the Anderson School at UCLA. On the basis of 20 years of apparent teaching success in Ph. D. education, I arrived at the Anderson School in 1990 with a self-image as a star teacher, but I was greeted with highly disturbingmediocreteachingevaluations. Facedwithadatasetthatwasinconsistent with my view of reality, I did what analysts usually do - I formulated a theory why the data were misleading. Here is how I thought about it. Two aspects of the course - content and amu- ment - drive numerical course evaluations. If you rank courses by the average of the content score and the amusement score, then the component that can be measured most accurately will determine the ranking. Do you understand why It is what - eraging does: it eliminates the noise. Suppose, for example, that a student cannot tell anything about the content, and the content score is simply a random number, varying from student to student. Those random numbers will average out across students to about the same number for each course. As the average course content score is about the same for every course, it is the amusement score that will drive the rankings. Codice articolo 9783540463887
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