scholarly journals Nonparametric estimates of the clean and dirty energy substitutability

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


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

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

2002 ◽  
Vol 19 (10) ◽  
pp. 1690-1707 ◽  
Author(s):  
Philippe Gaspar ◽  
Sylvie Labroue ◽  
Françoise Ogor ◽  
Guillaume Lafitte ◽  
Laurence Marchal ◽  
...  

1971 ◽  
Vol 17 (4) ◽  
pp. 275-284 ◽  
Author(s):  
Allen H Reed ◽  
Richard J Henry ◽  
William B Mason

Abstract The choice of statistical method can greatly influence the calculated normal range apart from any biological or chemical considerations. Nonparametric normal range estimates are, for practical purposes, as accurate as estimates that assume the distribution of data to be gaussian or loggaussian when the distribution assumed is true. When data are not distributed as assumed, nonparametric estimates are more accurate.


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