Imposing Regularity Conditions to Measure Banks’ Productivity Changes in Taiwan Using a Stochastic Approach

Abstract

This paper develops a stochastic approach to impose regularity properties on a directional output distance function (DODF) and an output distance function, which can be estimated by maximum likelihood. We use the resulting parameter estimates to evaluate efficiency and total factor productivity (TFP) growth for Taiwan’s commercial banks over the period 2002–2015 and claim that the failure of considering the regularity restrictions and the exclusion of undesirables lead to miscalculated efficiency measures and productivity gains. The outcomes from the regularity-constrained DODF reveal that almost all data-points satisfy the regularity properties, that the managerial abilities of the banks improve after the subprime crisis of 2007, and that the sample banks’ TFP grow at an average rate of 1.93% per annum, whereby technical change is the driving force. However, our estimates show downward trends in the growth rate of TFP and technical change.