European Business Schools Librarian's Group

SSE/EFI Working Paper Series in Economics and Finance,
Stockholm School of Economics

No 223: How to Bootstrap DEA Estimators: A Monte Carlo Comparison

Mickael Löthgren ()
Additional contact information
Mickael Löthgren: Dept. of Economic Statistics, Stockholm School of Economics, Postal: Stockholm School of Economics, P.O. Box 6501, S-113 83 Stockholm, Sweden

Abstract: This paper evaluates the performance of three bootstrap algorithms for the data envelopment analysis (DEA) estimator using a Monte Carlo simulation study. The Löthgren and Tambour (1997) (LT) algorithm; the Simar and Wilson (1997b) (SW) algorithm; and a combination of the LT and SW algorithms (the LSW-algorithm) are considered in the study. The empirical coverage accuracy of bootstrap confidence intervals are simulated under both variable returns to scale (VRS) and constant return-to-scale (CRS) restricted DEA estimators. The results indicate that the LSW-algorithm performs slightly better than the LT-algorithm, which in turn performs better than the SW-algorithm.

Keywords: Bootstrap; Confidence Intervals; Data Envelopment Analysis; Monte Carlo Simulation

JEL-codes: C14; C15; D24

22 pages, February 10, 1998

Full text files 

hastef0223.pdf.zip PDF-file Full text
hastef0223.pdf PDF-file Full text
hastef0223.ps.zip PostScript file Full text
hastef0223.ps PostScript file Full text

Download statistics

Questions (including download problems) about the papers in this series should be directed to Helena Lundin ()
Report other problems with accessing this service to Sune Karlsson ().

RePEc:hhs:hastef:0223This page generated on 2024-09-13 22:19:41.