Bootstrapping Density-Weighted Average Derivatives
Abstract
Employing the "small bandwidth" asymptotic framework of Cattaneo, Crump, and Jansson (2009), this paper studies the properties of a variety of bootstrap-based inference procedures associated with the kernel-based density-weighted averaged derivative estimator proposed by Powell, Stock, and Stoker (1989). In many cases validity of bootstrap-based inference procedures is found to depend crucially on whether the bandwidth sequence satisfies a particular (asymptotic linearity) condition. An exception to this rule occurs for inference procedures involving a studentized estimator employing a "robust" variance estimator derived from the "small bandwidth" asymptotic framework. The results of a small-scale Monte Carlo experiment are found to be consistent with the theory and indicate in particular that sensitivity with respect to the bandwidth choice can be ameliorated by using the "robust"variance estimatorClassification-JEL: C12, C14, C21, C24Download Info
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Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2010-23.Length: 30
Date of creation: 17 May 2010
Date of revision:
Handle: RePEc:aah:create:2010-23
Contact details of provider:
Web page: http://www.econ.au.dk/afn/
Related research
Keywords: Averaged derivatives; Bootstrap; Small bandwidth asymptotics;Other versions of this item:
- Matias D. Cattaneo & Richard K. Crump & Michael Jansson, 2010. "Bootstrapping density-weighted average derivatives," Staff Reports 452, Federal Reserve Bank of New York.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-05-29 (All new papers)
- NEP-ECM-2010-05-29 (Econometrics)
- NEP-ORE-2010-05-29 (Operations Research)
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Yulia Kotlyarova & Marcia M Schafgans & Victoria Zinde-Walsh, 2011. "Adapting Kernel Estimation to Uncertain Smoothness," STICERD - Econometrics Paper Series /2011/557, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- Clara Machado & Carlos León & Miguel Sarmiento & Freddy Cepeda, 2011.
"Riesgo Sistémico Y Estabilidad Del Sistema De Pagos De Alto Valor En Colombia: Análisis Bajo Topología De Redes Y Simulación De Pagos,"
ENSAYOS SOBRE POLÍTICA ECONÓMICA,
BANCO DE LA REPÚBLICA - ESPE.
- Clara Lía Machado & Carlos León & Miguel Sarmiento & Freddy Cepeda & Orlando Chipatecua & Jorge cely, . "Riesgo Sistémico y Estabilidad del Sistema de Pagos de Alto Valor en Colombia: Análisis bajo Topología de Redes y Simulación de Pagos," Borradores de Economia 627, Banco de la Republica de Colombia.
- Clara Lia Machado & Carlos León & Miguel Sarmiento & Orlando Chipatecua, 2010. "Riesgo Sistémico y Estabilidad del Sistema de Pagos de Alto Valor en Colombia: Análisis bajo Topología de Redes y Simulación de Pagos," BORRADORES DE ECONOMIA 007669, BANCO DE LA REPÚBLICA.
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