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Compression in stochastic frontier models

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  • Tsionas, Mike G.
  • Assaf, A. George

Abstract

•We develop a compressed SF model to account for heterogeneity.•We allow for cross-sectional and time-series variation in all coefficients.•We use Bayesian Compression to reduce the dimensionality of the parameter space.

Suggested Citation

  • Tsionas, Mike G. & Assaf, A. George, 2021. "Compression in stochastic frontier models," Annals of Tourism Research, Elsevier, vol. 88(C).
    • Handle: RePEc:eee:anture:v:88:y:2021:i:c:s0160738320301705
    DOI: 10.1016/j.annals.2020.103026
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    References listed on IDEAS

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    1. Hsiao,Cheng & Pesaran,M. Hashem & Lahiri,Kajal & Lee,Lung Fei (ed.), 1999. "Analysis of Panels and Limited Dependent Variable Models," Cambridge Books, Cambridge University Press, number 9780521631693, November.
    2. Rajarshi Guhaniyogi & David B. Dunson, 2015. "Bayesian Compressed Regression," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1500-1514, December.
    3. Assaf, A. George & Tsionas, Mike G., 2019. "Forecasting occupancy rate with Bayesian compression methods," Annals of Tourism Research, Elsevier, vol. 75(C), pages 439-449.
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