Using regression and Data Envelopment Analysis (DEA) to forecast bank performance over time

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Applications of Management Science

ISSN: 0276-8976
Series editor(s): Professor Kenneth D. Lawrence

Subject Area: Management Science/Management Studies

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Document Information:
Title:	Using regression and Data Envelopment Analysis (DEA) to forecast bank performance over time
Author(s):	Ronald K. Klimberg, Kenneth D. Lawrence, Ira Yermish, Tanya Lal, Daniel Mrazik
Volume:	13 Editor(s): Kenneth D. Lawrence, Gary Kleinman ISBN: 978-1-84855-878-6 eISBN: 978-1-84855-879-3
Citation:	Ronald K. Klimberg, Kenneth D. Lawrence, Ira Yermish, Tanya Lal, Daniel Mrazik (2009), Using regression and Data Envelopment Analysis (DEA) to forecast bank performance over time, in Kenneth D. Lawrence, Gary Kleinman (ed.) Financial Modeling Applications and Data Envelopment Applications (Applications of Management Science, Volume 13), Emerald Group Publishing Limited, pp.133-142
DOI:	10.1108/S0276-8976(2009)0000013010 (Permanent URL)
Publisher:	Emerald Group Publishing Limited
Article type:	Chapter Item
Abstract:	Forecasting is an important tool used to plan and evaluate business operations. Regression analysis is one of the most commonly used forecasting techniques for this purpose. Often forecasts are produced based on a set of comparable units such as individuals, groups, departments, or companies that perform similar activities. We apply a methodology that includes a new independent variable, the comparable unit's data envelopment analysis (DEA) relative efficiency, into the regression analysis. In this chapter, we apply this methodology to compare the performance of commercial banks over a 10-year time period.