Estimating the Potential Gains from Mergers

Abstract

We introduce simple production economic models to estimate the potential gains from mergers. We decompose the gains into technical efficiency, size (scale) and harmony (mix) gains, and we discuss alternative ways to capture these gains. We propose to approximate the production processes using the non-parametric Data Envelopment Analysis (DEA) approach, and we use the resulting operational approach to estimate the potential gains from merging agricultural extension offices in Denmark.JEL Classification: D20, L11, L22, P41, G34

Estimation of potential gains from bank mergers: A novel two-stage cost efficiency DEA model

“…After eliminating technical inefficiency by learning from best practice individually, only 138, 133, and 137 hypothetical DMUs' pure merger efficiency scores are less than one for the whole system, DPP and PEP, respectively. This also indicates that the scale effects do not favor the merger which our results are consistent with Bogetoft and Wang (2005) that the gains from merging are considerably less under the VRS assumption.…”

“…Then, the pure merger efficiency is to adjust the overall merger gains for technical efficiency effect (Bogetoft and Wang, 2005), thus we use the technically efficient DMUs as the basis for evaluating the potential gains purely from mergers as discussed in Section 2.…”

“…All these hypothetical DMUs comprised efficient DMUs. Bogetoft and Wang (2005) used a radial input-oriented DEA model to estimate the potential gains from mergers by maximizing the proportional input reduction of the hypothetical DMU while keeping the DMU's outputs unchanged, and found that there existed several possible mergers with potential gains. The overall potential gains were then decomposed to technical, scale, and harmony gains.…”

“…However, they found that the hypothetical DMU may probably surpass the Production Possibility Set (PPS) constructed by candidate DMUs when using the input-oriented DEA model to estimate potential merger gains. In this case, one drawback of the model proposed in Bogetoft and Wang (2005) is that it may become infeasible. Färe et al (2011) proposed an output-oriented DEA approach by maximizing hypothetical DMUs' potential revenues to identify potential partners, which can avoid the problem that the hypothetical DMUs may surpass the PPS.…”

Semi-Parametric Measures of Scale Characteristics of German Natural Gas-Fired Electricity Generation

“…The parameter estimates, however, can vary with the functional relationship and with the distributional assumptions regarding the residuals (Kumbhakar et al, 2015). Thus, estimates of scale characteristics derived with DEA and SFA may depend on the assumptions by the researcher, which ultimately may influence policy implications (Bogetoft and Wang, 2005;Triebs et al, 2016). To overcome the limitations of DEA and SFA, a third approach known as Stochastic Non-Smooth Envelopment of Data (StoNED, Kuosmanen and Kortelainen, 2012) allows flexible estimation of production functions without an underlying functional form (similar to DEA) and stochastic treatment of inefficiency and noise (similar to SFA).…”