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Aggregation Method (aggregation + method)

Distribution by Scientific Domains
Business, Economics, Finance and Accounting60%

Selected Abstracts

Spatial Yield Risk Across Region, Crop and Aggregation Method

CANADIAN JOURNAL OF AGRICULTURAL ECONOMICS, Issue 2-3 2005
Michael Popp
A researcher interested in crop yield risk analysis often has to contend with a lack of field- or farm-level data. While spatially aggregated yield data are often readily available from various agencies, aggregation distortions for farm-level analysis may exist. This paper addresses how much aggregation distortion might be expected and whether findings are robust across wheat, canola and flax grown in two central Canadian production regions, differing mainly by rainfall, frost-free growing days and soil type. Using Manitoba Crop Insurance Corporation data from 1980 to 1990, this research, regardless of crop or region analyzed, indicates that (i) spatial patterns in risk are absent; (ii) use of aggregate data overwhelmingly under-estimates field-level yield risk; and (iii) use of a relative risk measure compared to an absolute risk measure leads to slightly less aggregation distortion. Analysts interested in conducting farm-level analysis using aggregate data are offered a range of adjustment factors to adjust for potential bias. Un chercheur qui s'intéresse à l'analyse du risque du rendement des cultures doit souvent composer avec un manque de micro-données provenant de l'exploitation. Bien qu'il soit possible d'obtenir des données sur les rendements spatialement cumulées auprès de divers organismes, ces données peuvent comporter des distorsions importantes dues à l'agrégation des données de base et être trompeuses si elles sont utilisées pour effectuer des analyses à l'échelle de l'exploitation. Le présent article traite de la quantité de distorsion due à l'agrégation à laquelle on doit s'attendre et examine si les résultats obtenus pour le blé, le canola et le lin dans deux principales régions productrices canadiennes, où les précipitations, les jours de croissance sans gel et le type de sol constituent les principales différences, sont robustes ou non. À l'aide des données obtenues auprès de la Société d'assurance-récolte du Manitoba pour la période 1980,1990, la présente étude, sans égard à la culture ou à la région analysée, indique (i) que les profils régionaux en matière de risque n'existent pas; (ii) que l'utilisation de données agrégées sous-estime considérablement le risque de rendement; (iii) que l'utilisation d'une mesure du risque relatif comparativement à une mesure du risque absolu entraîne légèrement moins de distorsion d'agrégation. Afin d'ajuster les données pour minimiser un biais éventuel, nous proposons une gamme de facteurs d'ajustement aux analystes intéressés à effectuer des analyses à l'échelle des exploitations à l'aide de données agrégées. [source]

A Knowledge Formalization and Aggregation-Based Method for the Assessment of Dam Performance

COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 3 2010
Corinne Curt
The model's inputs are the whole set of available information and data: visual observations, monitoring measurements, calculated data, and documents related to design and construction processes. First, a formal grid is proposed to structure the inputs. It is composed of six fields: name, definition, scale, references as anchorage points on the scale, and spatial and temporal characteristics. Structured inputs are called indicators. Second, an indicator aggregation method is proposed that allows obtaining not only the dam performance but also the assessment of its design and construction practices. The methodology is illustrated mainly with the internal erosion mechanism through the embankment, but results concerning other failure modes are also provided. An application of the method for monitoring dams through time is given. [source]

Preference solutions of probability decision making with rim quantifiers

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 12 2005
Xinwang Liu
This article extends the quantifier-guided aggregation method to include probabilistic information. A general framework for the preference solution of decision making under an uncertainty problem is proposed, which can include decision making under ignorance and decision making under risk methods as special cases with some specific preference parameters. Almost all the properties, especially the monotonicity property, are kept in this general form. With the generating function representation of the Regular Increasing Monotone (RIM) quantifier, some properties of the RIM quantifier are discussed. A parameterized RIM quantifier to represent the valuation preference for probabilistic decision making is proposed. Then the risk attitude representation method is integrated in this quantifier-guided probabilistic decision making model to make it a general form of decision making under uncertainty. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 1253,1271, 2005. [source]

Reflections on ethics and MCA in environmental decisions

JOURNAL OF MULTI CRITERIA DECISION ANALYSIS, Issue 2 2001
Felix Rauschmayer
Abstract The aim of decision analysis is normative. Consequently, at least in public spheres, one has to reflect on its normative foundation. Multi-criteria analysis (MCA) uses aggregated evaluations on several criteria to recommend a decision. The claim for the adequacy of the recommended solution is usually based on the assumption that the interests of the decision-maker(s) are adequately assessed by the MC model (see, for example, Munda G. 1996. Cost,benefit analysis in integrated environmental assessment: some methodological issues. Ecological Economics19: 157,168). I argue that as a prerequisite to a normative foundation, the criteria have to reflect not only the interests but possibly all values stemming from normative arguments of the decision-maker(s). These arguments might differ substantially from each other. This is especially true for environmental decisions. The integration of values will result in changes of the MCA understanding, criteria building, and aggregation method, and will not be possible without analytical capacities of the decision analyst in ethics. Copyright © 2001 John Wiley & Sons, Ltd. [source]

A Richer Understanding of Australia's Productivity Performance in the 1990s: Improved Estimates Based Upon Firm-Level Panel Data,

THE ECONOMIC RECORD, Issue 265 2008
ROBERT BREUNIG
Australian industry is characterised by differences across firms, entry of new firms and exit of unsuccessful firms. These facts highlight the inappropriateness of measuring productivity using aggregate production functions based upon representative firms. In this study, we model heterogeneous firms which change over time. We model the interrelationship between productivity shocks, input choices and decisions to cease production. Firm-level data provides production function estimates for 25 two-digit Australian industries. A new aggregation method for industry-level data allows us to separate productivity changes from output composition changes. Our study sheds new light on the Australian productivity performance. [source]