Estimation of the regression slope by means of Gini’s cograduation index

D. Michele Cifarelli ()
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D. Michele Cifarelli: Università di Pavia

Decisions in Economics and Finance, 2016, vol. 39, issue 2, No 1, 113-142

Abstract: Abstract The simple linear model $$Y_i = \alpha + \beta \, x_i + \epsilon _i$$ Y i = α + β x i + ϵ i $$(i=1,2, \ldots ,N \ge 2)$$ ( i = 1 , 2 , … , N ≥ 2 ) is considered, where the $$x_i$$ x i ’s are given constants and $$\epsilon _1, \epsilon _2 , \ldots , \epsilon _N$$ ϵ 1 , ϵ 2 , … , ϵ N are independent identically distributed (iid) with continuous distribution function F. An estimator $$\tilde{\beta }$$ β ~ of the slope parameter is proposed, based on a stochastic process which makes use of Gini’s cograduation index. The properties of $$\tilde{\beta }$$ β ~ and of the related confidence interval are studied. Some comparisons are given, in terms of asymptotic relative efficiency, with other estimators of $$\beta $$ β including that obtained with the method of least squares.

Keywords: Linear regression; Gini’s cograduation index; Indifference; Theil-Sen estimator (search for similar items in EconPapers)
JEL-codes: C13 C14 (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10203-016-0174-4

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