Sequential Downscaling Methods for Estimation from Aggregate Data

G. Fischer, T. Ermolieva, Y. Ermoliev and H. Velthuizen
Additional contact information
G. Fischer: Institute for Applied Systems Analysis
T. Ermolieva: Institute for Applied Systems Analysis
Y. Ermoliev: Institute for Applied Systems Analysis
H. Velthuizen: Institute for Applied Systems Analysis

A chapter in Coping with Uncertainty, 2006, pp 155-169 from Springer

Abstract: Abstract Global change processes raise new estimation problems challenging the conventional statistical methods. These methods are based on the ability to obtain observations from unknown true probability distributions, whereas the new problems require recovering information from only partially observable or even unobservable variables. For instance, aggregate data exist at global and national level regarding agricultural production, occurrence of natural disasters, on incomes, etc. without providing any clue as to possibly alarming diversity of conditions at local level. “Downscaling” methods in this case should achieve plausible estimation of local implications emerging from global tendencies by using all available evidences. The aim of this paper is to develop a sequential downscaling method, which can be used in a variety of practical situations. Our main motivation for this was the estimation of spatially distributed crop production, i.e., on a regular grid, consistent with known national-level statistics and in accordance with geographical datasets and agronomic knowledge. We prove convergence of the method to a generalized cross-entropy maximizing solution. We also show that for specific cases this method is reduced to known procedures for estimating transportation flows and doubly stochastic matrices.

Keywords: Cross-entropy; minimax likelihood; downscaling; spatial estimation (search for similar items in EconPapers)
Date: 2006
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnechp:978-3-540-35262-4_9

Ordering information: This item can be ordered from
http://www.springer.com/9783540352624

DOI: 10.1007/3-540-35262-7_9

Access Statistics for this chapter

More chapters in Lecture Notes in Economics and Mathematical Systems from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().