Abstract

http://ssrn.com/abstract=2291034
 
 

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Pulling Econometrics Students up by Their Bootstraps


Michael O'Hara


Colgate University

July 8, 2013


Abstract:     
Although the concept of the sampling distribution is at the core of much of what we do in econometrics, it is a concept that is often difficult for students to grasp. The thought process behind bootstrapping provides a way for students to conceptualize the sampling distribution in a way that is intuitive and visual. However, teaching students to write bootstrapping code on their own would come at great expense in terms of instruction time. I propose the use of instructor-written macros as a balance between these opposing interests. I focus on the use of the nonparametric “pairwise” bootstrap procedure in order to make an intuitive link between bootstrapping and sampling from a population, which is one of the first ideas students meet in statistics.

Number of Pages in PDF File: 24

Keywords: Teaching, Bootstrapping, Sampling Distribution

JEL Classification: A20, A22, C15

working papers series


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Date posted: July 10, 2013  

Suggested Citation

O'Hara, Michael, Pulling Econometrics Students up by Their Bootstraps (July 8, 2013). Available at SSRN: http://ssrn.com/abstract=2291034 or http://dx.doi.org/10.2139/ssrn.2291034

Contact Information

Michael O'Hara (Contact Author)
Colgate University ( email )
13 Oak Drive
Hamilton NY 13346, NY 13346
United States
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References:  7

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