Some notes on statistic robustness of nonparametric bivariate probit model in a finite sample
This article describes qualitatively some interesting statistic aspects of the nonparametric bivariate Probit model, which was examined in Aoki (2005) as a nonparametrically modified version of the estimator to test asymmetric information, originally proposed in Chiappori and Salanie (2000). My computation results and analysis show that even in a finite sample case the nonparametric version is very robust to the variable bandwidth, which is relatively smaller than the optimal bandwidth policy. This statistic characteristics enables the proposed nonparametric estimator to be put widely and conveniently into practical use, without applied researcher's necessity to pay too much attention to the precise value of optimal bandwidth.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 16 (2009)
Issue (Month): 5 ()
|Contact details of provider:|| Web page: http://www.tandfonline.com/RAEL20|
|Order Information:||Web: http://www.tandfonline.com/pricing/journal/RAEL20|
When requesting a correction, please mention this item's handle: RePEc:taf:apeclt:v:16:y:2009:i:5:p:443-447. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty)
If references are entirely missing, you can add them using this form.