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Book part
Publication date: 30 November 2011

David M. Drukker

This volume includes papers related to missing-data methods for time-series econometricians with applications in macroeconomics and empirical finance.

Abstract

This volume includes papers related to missing-data methods for time-series econometricians with applications in macroeconomics and empirical finance.

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Missing Data Methods: Time-Series Methods and Applications
Type: Book
ISBN: 978-1-78052-526-6

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Book part
Publication date: 23 November 2011

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Missing Data Methods: Cross-sectional Methods and Applications
Type: Book
ISBN: 978-1-78052-525-9

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Book part
Publication date: 30 November 2011

Abstract

Details

Missing Data Methods: Time-Series Methods and Applications
Type: Book
ISBN: 978-1-78052-526-6

To view the access options for this content please click here
Book part
Publication date: 23 November 2011

David M. Drukker

“The Elephant in the Corner: A Cautionary Tale About Measurement Error in Treatment Effects Models” by Daniel L. Millimet discusses the current use of the…

Abstract

“The Elephant in the Corner: A Cautionary Tale About Measurement Error in Treatment Effects Models” by Daniel L. Millimet discusses the current use of the unobserved-outcome framework to estimate population-averaged treatment effects, and it exposes the sensitivity of these estimators to assumption of no measurement error. The Monte Carlo simulation evidence in this chapter indicates that “nonclassical measurement error in the covariates, mean-reverting measurement error in the outcome, and simultaneous measurement errors in the outcome, treatment assignment, and covariates have a dramatic, adverse effect on the performance of the various estimators even with relatively small and infrequent errors” (Millimet article, p. 1–39). To some extent, all the estimators analyzed by Millimet are based on weak functional form assumptions and use semiparametric or nonparametric methods. Millimet's results indicate the need for measurement error models be they parametric or nonparametric models, see Schennach (2007), Hu and Schennach (2008), and Matzkin (2007) for some recent research in nonparametric approaches. Chapter 7 develops a Bayesian estimator that can handle some of the measurement errors discussed in this chapter.

Details

Missing Data Methods: Cross-sectional Methods and Applications
Type: Book
ISBN: 978-1-78052-525-9

To view the access options for this content please click here
Book part
Publication date: 30 November 2011

Abstract

Details

Missing Data Methods: Time-Series Methods and Applications
Type: Book
ISBN: 978-1-78052-526-6

To view the access options for this content please click here
Book part
Publication date: 23 November 2011

Abstract

Details

Missing Data Methods: Cross-sectional Methods and Applications
Type: Book
ISBN: 978-1-78052-525-9

To view the access options for this content please click here
Book part
Publication date: 30 November 2011

Abstract

Details

Missing Data Methods: Time-Series Methods and Applications
Type: Book
ISBN: 978-1-78052-526-6

To view the access options for this content please click here
Book part
Publication date: 30 November 2011

Abstract

Details

Missing Data Methods: Time-Series Methods and Applications
Type: Book
ISBN: 978-1-78052-526-6

To view the access options for this content please click here
Book part
Publication date: 23 November 2011

Abstract

Details

Missing Data Methods: Cross-sectional Methods and Applications
Type: Book
ISBN: 978-1-78052-525-9

To view the access options for this content please click here
Book part
Publication date: 23 November 2011

Abstract

Details

Missing Data Methods: Cross-sectional Methods and Applications
Type: Book
ISBN: 978-1-78052-525-9

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