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Revista Colombiana de Estadística
Print version ISSN 0120-1751
Rev.Colomb.Estad. vol.33 no.2 Bogotá July/Dec. 2010
1Universidad de Antioquia, Facultad de Ciencias Económicas, Departamento de Economía, Medellín, Colombia. Profesor. Email: jbarr@economicas.udea.edu.co
2Georg August Universität Göttingen, Institut für Statistik und Ökonometrie, Göttingen, Germany. Professor. Email: stefan.sperlich@wiwi.uni-goettingen.de
In non- and semiparametric testing, the wild bootstrap is a standard method for determining the critical values of tests. If the null hypothesis is also semi- or nonparametric, then we know that at least asymptotically oversmoothing is necessary in the pre-estimation of the null model for generating the bootstrap samples. See Hardle & Marron (1990, 1991). However, in practice this knowledge is of little help. In this note we highlight that this bandwidth choice problem can become quite serious. As an alternative, we briegly discuss the possibility of subsampling.
Key words: Bandwidth choice, Bootstrap tests, Nonparametric specification tests.
En contrastes no- y semiparamétricos el wild-bootstrap es un método estándar para la determinación de los valores críticos de los estadísticos de contrastes. Si la hipótesis nula es no o semiparamétrica, sabemos que al menos asintóticamente es necesaria una sobre-suavización en la pre-estimación del modelo bajo la nula para generar las muestras bootstrap, ver por ejemplo Hardle & Marron (1990, 1991).
No obstante, en la práctica este conocimiento es de poca o ninguna ayuda. En este artículo, ponemos de manifiesto que el problema de la selección de la banda de suavidad para procedimientos de contraste puede ser muy serio. Como alternativa, discutimos brevemente la posibilidad de usar sub-muestras.
Palabras clave: ancho de banda, contrastes de especificación no-paramétricos, contrastes bootstrap.
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References
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Este artículo se puede citar en LaTeX utilizando la siguiente referencia bibliográfica de BibTeX:
@ARTICLE{RCEv33n2a08,
AUTHOR = {Barrientos-Marín, Jorge and Sperlich, Stefan},
TITLE = {{The Size Problem of Bootstrap Tests when the Null isNon- or Semiparametric}},
JOURNAL = {Revista Colombiana de Estadística},
YEAR = {2010},
volume = {33},
number = {2},
pages = {307-319}
}