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The Bootstrap and Multiple Imputations: Harnessing Increased Computing Power for Improved Statistical Tests Author info | Abstract | Publisher info | Download info | Related research | Statistics David Brownstone
Robert Valletta
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The bootstrap and multiple imputations are two techniques that can enhance the accuracy of estimated confidence bands and critical values. Although they are computationally intensive, relying on repeated sampling from empirical data sets and associated estimates, modern computing power enables their application in a wide and growing number of econometric settings. We provide an intuitive overview of how to apply these techniques, referring to existing theoretical literature and various applied examples to illustrate both their possibilities and their pitfalls.
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Article provided by American Economic Association in its journal Journal of Economic Perspectives .
Volume (Year): 15 (2001)
Issue (Month): 4 (Fall)
Pages: 129-141
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Handle: RePEc:aea:jecper:v:15:y:2001:i:4:p:129-141Contact details of provider: Email: Web page: http://www.aeaweb.org/jep/ More information through EDIRC
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Keywords: References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.:
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references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
Asma Hyder & Barry Reilly, 2005.
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Monchuk, Daniel C. & Hayes, Dermot J. & Miranowski, John, 2008.
"Inference Based on Alternative Bootstrapping Methods in Spatial Models with an Application to County Income Growth in the United States ,"
Staff General Research Papers
12958, Iowa State University, Department of Economics.
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Asma Hyder & Barry Reilly, 2005.
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Fairlie, Robert W. & Robb, Alicia M., 2004.
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