Nitrate pollution from agriculture is an important environmental problem, caused bythe excessive use of inorganic fertilizers. The internalization of this externality, via a tax onmineral nitrogen, could lead to a second best solution, reducing nitrate emissions. Severalauthors suggest that a...

We analyze the current state and future requirements of an agricultural income stabilization mechanism in a transition country – namely, the crop insurance system in Kazakhstan. Three objectives will be pursued: First, factors influencing the development of the crop insurance market will be...

A mathematical programming model is developed and associated to a spatial pattern index (Ripley L function) to analyse the optimal reserve design and implementation for the Little Bustard conservation in Plaine de Niort. The model structure corresponds to three spatial levels, fields, farm and...

The biological nature of agricultural production processes induce a higher degree ofuncertainty surrounding the economic performance of farm enterprises. This has contributedto the development and acceptance of forms of public intervention aimed at reducing incomevariability that have no...

A water-crop simulation/mathematical programming model of irrigation water demand in northeastern Colorado is formulated to develop an original concept of derived demand for consumptive use of water. Conventional demand functions for water deliveries are also developed, and the effect of...

Recently, Branzei, Dimitrov, and Tijs (2003) introduced cooperative interval-valued games. Among other insights, the notion of an interval core has been coined and proposed as a solution concept for interval-valued games. In this paper we will present a general mathematical programming algorithm...

We consider the problem of model assessment by risk estimation. Variousapproaches to risk estimation are considered in a uni ed framework. This a discussion of various complexity dimensions and approaches to obtainingbounds on covering numbers is also presented.The second type of training sample...

Previous research implementing stratification on the propensity score has generally relied on using five strata, based on prior theoretical groundwork and minimal empirical evidence as to the suitability of quintiles to adequately reduce bias in all cases and across all sample sizes. This study...

In terms of risk measurement, probability and quantile risk estimation have developed enormously in the past decade, from value-at-risk measures to coherent measures such as expected shortfall. These measures allow an investor to determine their risk profile accounting for losses (quantiles) at...

To overcome the curse of dimensionality, dimension reduction is important andnecessary for understanding the underlying phenomena in a variety of fields.Dimension reduction is the transformation of high-dimensional data into ameaningful representation in the low-dimensional space. It can be...