Rate of uniform consistency for nonparametric estimates with functional variables

2010 ◽  
Vol 140 (2) ◽  
pp. 335-352 ◽  
Author(s):  
Frédéric Ferraty ◽  
Ali Laksaci ◽  
Amel Tadj ◽  
Philippe Vieu
Author(s):  
Neha Gupta

Abstract This paper reviews rice procurement operations of Government of India from the standpoints of cost of procurement as well as effectiveness in supporting farmers’ incomes. The two channels in use for procuring rice till 2015, were custom milling of rice and levy. In the first, the government bought paddy directly from farmers at the minimum support price (MSP) and got it milled from private millers; while in the second, it purchased rice from private millers at a pre-announced levy price thus providing indirect price support to farmers. Secondary data reveal that levy, despite implying lower cost of procurement was discriminated against till about a decade back and eventually abolished in 2015 in favor of custom milling, better trusted to provide minimum price support. We analyze data from auctions of paddy from a year when levy was still important to investigate its impact on farmers’ revenues. We use semi-nonparametric estimates of millers’ values to simulate farmers’ expected revenues and find these to be rather close to the MSP; a closer analysis shows that bidder competition is critical to this result. Finally, we use our estimates to quantify the impact of change in levy price on farmers’ revenues and use this to discuss ways to revive the levy channel.


2019 ◽  
Vol 22 (07) ◽  
pp. 1950040
Author(s):  
GIANLUCA CASSESE

We propose a new nonparametric technique to estimate the call function based on the superhedging principle. This approach requires minimal assumptions on absence of arbitrage and other market imperfections. The estimates so obtained are then combined with SNP estimates of the actual density of market returns. This permits to investigate the time behavior of the relative distance between the two densities obtained. Our empirical findings suggest that the more the two densities differ, the shorter is time to maturity, suggesting a major role of uncertainty over shorter than longer horizons.


2018 ◽  
Vol 168 ◽  
pp. 118-122
Author(s):  
Emir Malikov ◽  
Kai Sun ◽  
Subal C. Kumbhakar

2019 ◽  
Author(s):  
Pietro Tebaldi ◽  
Alexander Torgovitsky ◽  
Hanbin Yang

Author(s):  
Sunil K. Dhar

AbstractConsider the additive effects outliers (A.O.) model where one observes , with The sequence of r.v.s is independent of and , are i.i.d. with d.f. , where the d.f.s Ln, n ≦ 0, are not necessarily known and εj's are i.i.d.. This paper discusses the asymptotic behavior of functional least squares estimators under the above model. Uniform consistency and uniform strong consistency of these estimators are proven. The weak convergence of these estimators to a Gaussian process and their asymptotic biases are also discussed under the above A.O. model.


2012 ◽  
Vol 28 (5) ◽  
pp. 935-958 ◽  
Author(s):  
Degui Li ◽  
Zudi Lu ◽  
Oliver Linton

Local linear fitting is a popular nonparametric method in statistical and econometric modeling. Lu and Linton (2007, Econometric Theory23, 37–70) established the pointwise asymptotic distribution for the local linear estimator of a nonparametric regression function under the condition of near epoch dependence. In this paper, we further investigate the uniform consistency of this estimator. The uniform strong and weak consistencies with convergence rates for the local linear fitting are established under mild conditions. Furthermore, general results regarding uniform convergence rates for nonparametric kernel-based estimators are provided. The results of this paper will be of wide potential interest in time series semiparametric modeling.


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