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Journal of Economic Perspectives: Vol. 15 No. 4 (Fall 2001)
JEP Volume. 15, Issue 4 |
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The Bootstrap and Multiple Imputations: Harnessing Increased Computing Power for Improved Statistical Tests
Article Citation
Brownstone, David, and
Robert Valletta. 2001. "The Bootstrap and Multiple Imputations: Harnessing Increased Computing Power for Improved Statistical Tests."
Journal of Economic Perspectives,
15(4): 129-141.
DOI: 10.1257/jep.15.4.129
DOI: 10.1257/jep.15.4.129
Abstract
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.
Article Full-Text Access
Full-text Article (Complimentary)
Authors
Brownstone, David (U CA, Irvine)
Valletta, Robert (Federal Reserve Bank of San Francisco)
Valletta, Robert (Federal Reserve Bank of San Francisco)
JEL Classifications
C20: Single Equation Models; Single Variables: General
C13: Estimation
C12: Hypothesis Testing
C13: Estimation
C12: Hypothesis Testing
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