What is it about?

This highly original paper develops a dynamic model of inefficiency and merger the estimation of which relies on Bayesian techniques organized around the use of Markov chain Monte Carlo, in order to investigate whether merging leads to greater efficiency.

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Why is it important?

The novelty of the method lies in the fact that it explicitly takes into account the possibility of a two-way relationship between merger and efficiency. The methodology itself can be extended to applications in other sectors. The work is rigorous in that it looks at the evolution of efficiency effects as they arise in the periods following the merger event.

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This page is a summary of: Dynamics of Inefficiency and Merger in English Higher Education From 1996/97 to 2008/9: A Comparison of Pre-Merging, Post-Merging and Non-Merging Universities Using Bayesian Methods, Manchester School, November 2018, Wiley, DOI: 10.1111/manc.12262.
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