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Model

Any mathematical formula or other structure that economists use to explain or predict occurrences. Economists test their models with real world facts before they gain wide acceptance, but, even then, there is no guarantee that a model will always be a correct predictor. See also: Model risk.
Farlex Financial Dictionary. © 2012 Farlex, Inc. All Rights Reserved

model

An abstraction of reality, generally referring in investments to a mathematical formula designed to determine security values. Economists also use models to project trends in economic variables such as interest rates, economic activity, and inflation rates.
Wall Street Words: An A to Z Guide to Investment Terms for Today's Investor by David L. Scott. Copyright © 2003 by Houghton Mifflin Company. Published by Houghton Mifflin Company. All rights reserved. All rights reserved.

model

see ECONOMIC MODEL.
Collins Dictionary of Economics, 4th ed. © C. Pass, B. Lowes, L. Davies 2005
References in periodicals archive ?
Hence, linear programming model can be utilized to determine feasible cropping systems for mixed cropping systems to optimize resource use and benefits (Tavallali and Karimi, 2014).
These authors propose several aggregation schemes and a novel mixed-integer linear programming model formulation based on a continuous representation of time.
Section 5 explains the multiobjective linear programming model of the APP.
Study (Maillot et al., 2011) develops a linear programming model with age and gender food patterns.
From our point of view, this simply implies a modification of the linear programming model described in the "Pricing and Hedging in Incomplete Markets" section.
Thus, linear programming models apply only in selected cases that require narrow and short parts with relatively even distribution.
Suppose the linear programming model we considering is
1 CWRS wheat for protein between $0.64 and $2.50 per tonne for the crop years 1989-90 to 1993-94 using a linear programming model. They also analyzed the profitability of investing in more precise protein testers for country elevators but without considering the impact of smaller protein increments on blending revenues.
In order to find the optimal solution of such a complicated problem, an integrated planning methodology was adopted and the problem was formulated as a linear programming model. Computations of example problems with practical production data were performed to test the model.
Zahavi (both of Tel-Aviv University) found that genetic algorithms performed even better than a linear programming model on their problem.
The constrained multiple objective linear programming model permits the articulation of multiple objectives and generates on ordered list of optimum solutions.

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