Measuring Managerial Ability: Getting Close to the Holy Grail

23 Pages Posted: 8 Feb 2017

See all articles by Manthos D. Delis

Manthos D. Delis

Montpellier Business School

Efthymios G. Tsionas

Lancaster University

Date Written: February 8, 2017

Abstract

Managerial ability is remarkably difficult to robustly measure, especially when unique data on firms and their managers are not available. We propose a new latent-variable model estimated with Bayesian techniques that requires only the usual accounting data on inputs and outputs and thus can be applied to any firm. We show that our managerial ability estimates are more than 90% correlated with existing robust measures derived from a very specialized data set by Bloom and Van Reenen (2007). We also validate our model using Monte Carlo simulations and show that frontier-based methods previously used to estimate managerial ability do not provide good approximations. We conclude that our method produces robust estimates of managerial ability, while having the advantage that can be applied to all firms for which very simple accounting data are available.

Suggested Citation

Delis, Manthos D. and Tsionas, Efthymios G., Measuring Managerial Ability: Getting Close to the Holy Grail (February 8, 2017). Available at SSRN: https://ssrn.com/abstract=2913493 or http://dx.doi.org/10.2139/ssrn.2913493

Manthos D. Delis (Contact Author)

Montpellier Business School ( email )

2300 Avenue des Moulins
Montpellier, 34080
France

Efthymios G. Tsionas

Lancaster University ( email )

Lancaster LA1 4YX
United Kingdom

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