MARC Record from Scriblio

LEADER: 02616cam 22003257a 4500
001 2004620333
003 DLC
005 20050107184321.0
007 cr |||||||||||
008 050107s2001 dcu sb f000 0 eng
010 $a 2004620333
040 $aDLC$cDLC
043 $an-us---
050 00 $aHG2401
100 1 $aDietrich, Jason Lynn.
245 10 $aHow low can you go?$h[electronic resource]$ban optimal sampling strategy for fair lending exams /$cby Jason Dietrich.
260 $aWashington, DC :$bOffice of the Comptroller of the Currency,$c[2001]
490 1 $aEconomic and policy analysis working paper ;$v2001-3
538 $aSystem requirements: Adobe Acrobat Reader.
538 $aMode of access: World Wide Web.
500 $aTitle from PDF file as viewed on 1/7/2005.
530 $aAlso available in print.
504 $aIncludes bibliographical references.
520 3 $a"This study uses Monte Carlo simulation to examine the impact of nine sampling strategies on the finite sample performance of the maximum likelihood logit estimator. Empirical researchers face a tradeoff between the lower resource costs associated with smaller samples and the increased confidence in the results gained from larger samples. Choice of sampling strategy is one tool researchers can use to reduce costs yet still attain desired confidence levels. The nine sampling strategies examined in this study include simple random sampling and eight variations of stratified random sampling. Bias, mean-square-error, percentage of models that are feasibly estimated, and percentage of simulated estimates that differ statistically from the true population parameters are used as measures of finite sample performance. The results show stratified random sampling by action (loan approval/denial) and race of the applicant, with balanced strata sizes and a bias correction for choice-based sampling, outperforms each of the other sampling strategies with respect to the four performance measures. These findings, taken together with supporting evidence presented in Scheuren and Sangha (1998) and Giles and Courchane (2000) make a strong argument for implementing such a sampling strategy in future fair lending exams"--Office of the Comptroller of the Currency web site.
650 0 $aBank loans$xMathematical models.
650 0 $aBanks and banking$zUnited States$xExamination.
650 0 $aMonte Carlo method.
710 1 $aUnited States.$bOffice of the Comptroller of the Currency.
830 0 $aEconomic and policy analysis working paper (2000 : Online) ;$v2001-3.
856 40 $uhttp://www.occ.treas.gov/wp2001-3.htm