The aim of this study is to provide a tool which enables us to conduct statistical analysis in the context of changes in productivity and profit. We build on previous initiatives to decompose profit change into mutually exclusive and exhaustive sources. To do this we use distance functions, which are calculated empirically using linear programming techniques. However, we may not learn a great deal by solving these linear programs unless methods of statistical analysis are used to examine the properties of the relevant estimators. Our purpose is to provide a methodology based on bootstrap that allows us to conduct statistical inference for the profit change decomposition. Thus, it will be possible to answer questions such as whether variations in the profit change components, or the differences across firms, are statistically significant. We provide an application to Spanish commercial banks for the 2003/2004 period. Results suggest that profit change differentials between them are not always significant. Therefore, the validity of the conclusions which do not factor in the bootstrap may be jeopardized to varying degrees. © 2010 Elsevier Ltd. All rights reserved.
|Journal||Surveys in Operations Research and Management Science|
|Publication status||Published - 1 Aug 2012|