Bootstrapping density-weighted average derivatives

Arbeitspapier

Employing the 'small-bandwidth' asymptotic framework of Cattaneo, Crump, and Jansson (2009), this paper studies the properties of several bootstrap-based inference procedures associated with a kernel-based estimator of density-weighted average derivatives proposed by Powell, Stock, and Stoker (1989). In many cases, the 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 that employs 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 estimator.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Staff Report ; No. 452

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Hypothesis Testing: General ; Semiparametric and Nonparametric Methods: General ; Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions ; Single Equation Models; Single Variables: Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
• Thema: Averaged derivatives ; bootstrap ; small-bandwidth asymptotics

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Cattaneo, Matias D. ; Crump, Richard K. ; Jansson, Michael
• Ereignis: Veröffentlichung
• (wer): Federal Reserve Bank of New York
• (wo): New York, NY
• (wann): 2010

Weitere Informationen

• Handle: http://hdl.handle.net/10419/60834
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ