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Lower Bound Estimation – Quantile Regression and Simplex Method: An Application to Italian Manufacturing Sectors
Author(s) -
Giorgetti Maria Letizia
Publication year - 2003
Publication title -
the journal of industrial economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.93
H-Index - 77
eISSN - 1467-6451
pISSN - 0022-1821
DOI - 10.1111/1467-6451.00194
Subject(s) - quantile regression , outlier , microdata (statistics) , econometrics , estimation , quantile , statistics , regression , upper and lower bounds , manufacturing sector , sunk costs , economics , mathematics , labour economics , microeconomics , demography , mathematical analysis , population , management , sociology , census
This paper estimates Sutton's lower bound [1991, 1998] by quantile regression, and thus shows the influence of outliers on previous estimates that used the simplex method. The lower bound estimates are obtained separately for exogenous and endogenous sunk cost industries in Italian manufacturing sectors in 1995, using microdata from the SCI’95 (Firms Accounts System) survey conducted by ISTAT (National Institute of Statistics, Italy). The results suggest that Sutton's predictions are robust.