Productivity growth in network models: An application to banking during the financial crisis

We construct Malmquist Productivity indices for two-stage processes. A two-stage data envelopment analysis model with an additive efficiency decomposition is used for the modeling of the two-stage process. We incorporate prior information into the analysis using the Weight Assurance Region (WAR) model. The WAR model offers advantages such as the weights representing the contribution of each stage to the overall process are always positive and also we can restrict them into a region given the available prior information. Therefore, WAR model is appropriate for policy making. We extend this model from efficiency analysis to productivity analysis and we calculate Malmquist Productivity indices using three alternative decomposition approaches (Fare et al., 1994; Ray and Desli, 1997; Gilbert and Wilson, 1998). The model is applied to a panel of banks in Central and Eastern European (CEE) countries and productivity change is evaluated for the financial crisis period. Specifically, we assess the productivity change of CEE banks during three sub-periods of recent Economic Crisis; the U.S. subprime crisis (2007-2008), the Global financial crisis (2008-2010) and the sovereign debt crisis (2010-2012).The alternative decompositions allow us to examine the various sources of productivity change during the financial crisis.