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Quantile regression in lower bound estimation

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  • Giorgetti, Maria Letizia

Abstract

In this paper, I illustrate the additional information that can be prodivided in estimating the lower bound (Sutton 1991, 1998) by using quantile regression. Quantile regression allows us to invesigate the influence of outliers. Previous lower bound have been performed using the simplex method. In this paper, the lower bound estimates are obtained using both methods for sectors belonging to a 'control group' and sectors belonging to an 'experimental group' forItalian manufacturing sectors in 1995. The data employed are drawn from the ISTAT (National Institute of Statistics, Italy) dataset. The results suggest that Sutton's predictions are robust.

Suggested Citation

  • Giorgetti, Maria Letizia, 2001. "Quantile regression in lower bound estimation," LSE Research Online Documents on Economics 6746, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:6746
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    File URL: http://eprints.lse.ac.uk/6746/
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    Cited by:

    1. John Sutton, 2001. "Rich Trades, Scarce Capabilities: Industrial Development Revisited," STICERD - Economics of Industry Papers 28, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

    More about this item

    Keywords

    Lower bound; quantile regression; simplex;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms

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