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Smooth approximations to monotone concave functions in production analysis: An alternative to nonparametric concave least squares

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  • Tsionas, Mike G.
  • Izzeldin, Marwan

Abstract

Estimation of banking efficiency and productivity is essential for regulatory purposes and for testing various theories in the context of banking such as the quiet life hypothesis, the bad management hypothesis etc. In such studies it is, therefore, important to place as few restrictions as possible on the functional forms subject to global satisfaction of the theoretical properties relating to monotonicity and concavity. In this paper, we propose an alternative to nonparametric segmented concave least squares. We use a differentiable approximation to an arbitrary functional form based on smoothly mixing Cobb-Douglas anchor functions over the data space. Estimation is based on Bayesian techniques organized around Markov Chain Monte Carlo. The approximation properties of the new functional form are investigated in a Monte Carlo experiment where the true functional form is a Symmetric Generalized McFadden. The new techniques are applied to a large U.S banking data set as well as a global banking data set.

Suggested Citation

  • Tsionas, Mike G. & Izzeldin, Marwan, 2018. "Smooth approximations to monotone concave functions in production analysis: An alternative to nonparametric concave least squares," European Journal of Operational Research, Elsevier, vol. 271(3), pages 797-807.
  • Handle: RePEc:eee:ejores:v:271:y:2018:i:3:p:797-807
    DOI: 10.1016/j.ejor.2018.05.053
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    Cited by:

    1. Tsionas, Mike G., 2020. "Bounded rationality and thick frontiers in stochastic frontier analysis," European Journal of Operational Research, Elsevier, vol. 284(2), pages 762-768.
    2. Toraubally, Waseem A., 2019. "Arbitrage equilibria in large games with many commodities," Economics Letters, Elsevier, vol. 179(C), pages 24-28.
    3. Assaf, A. George & Tsionas, Mike G., 2019. "A review of research into performance modeling in tourism research - Launching the Annals of Tourism Research curated collection on performance modeling in tourism research," Annals of Tourism Research, Elsevier, vol. 76(C), pages 266-277.
    4. Ya Chen & Mike Tsionas & Valentin Zelenyuk, 2020. "LASSO DEA for small and big data," CEPA Working Papers Series WP022020, School of Economics, University of Queensland, Australia.

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