Search results for "Simulation modeling"

showing 10 items of 41 documents

A Note on added information in the RAS Procedure: reexamination of some evidence

2006

International audience; An example in Miernyk (1977) presented a rather counterintuitive result, namely that introducing accurate exogenous information into an RAS matrix estimating procedure could lead to an estimate that was worse than one generated by RAS using no exogenous information at all. This became an oft-cited black mark against RAS. Miller and Blair (1985) included a different (and small) illustration of the same possibility. It was recently pointed out by one of us that the Miller/Blair numerical results are wrong. For that reason, we decided to reexamine all the empirical evidence we could find on the subject. While figures in both Miernyk and Miller/Blair appear to be wrong, …

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsCounterintuitiveClosenessJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisEnvironmental Science (miscellaneous)Development[SHS.ECO]Humanities and Social Sciences/Economics and FinanceJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingInput-outputbiproportionEconometricsJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and FinanceEmpirical evidenceMathematical economicsCounterexampleMathematicsRAS
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Regional Multicriteria Analysis and Influence Relation

1986

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and financesJEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R0 - GeneralJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[SHS.ECO] Humanities and Social Sciences/Economics and Finance[SHS.ECO]Humanities and Social Sciences/Economics and FinanceJEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R0 - General
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Note about the concept of ‘Net Multipliers'

2002

International audience; Net multipliers, as introduced by Oosterhaven and Stelder (2002) accept outputs as entries instead of final demand. They are found by multiplying ordinary multipliers by the final demand ratio over the sector's output. This pragmatic solution suffers from ratio instability over time. The alternative net multipliers proposed here are based on the interpretation of the Leontief inverse matrix for the effects generated at each round. The new solution is not sensitive to the size of impacts. Now net multiplier is equal to the corresponding ordinary multiplier minus one, and the ordering of multipliers is unchanged.

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[SHS.ECO]Humanities and Social Sciences/Economics and Financeinput-output analysisdemand (economic theory)JEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R15 - Econometric and Input–Output Models • Other ModelsJEL: O - Economic Development Innovation Technological Change and Growth/O.O2 - Development Planning and Policy/O.O2.O20 - GeneralJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and finances<br />multiplier (economics)Hardware_ARITHMETICANDLOGICSTRUCTURES[SHS.ECO] Humanities and Social Sciences/Economics and FinanceJEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R15 - Econometric and Input–Output Models • Other ModelsJEL : O - Economic Development Innovation Technological Change and Growth/O.O2 - Development Planning and Policy/O.O2.O20 - General
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On Boolean topological methods of structural analysis

2001

The properties of Boolean methods of structural analysis are used to analyze the intern structure of linear or non linear models. Here they are studied on the particular example of qualitative methods of input-output analysis. First, it is shown that these methods generate informational problems like biases when working in money terms instead of percentages, losses of information, increasing of computation time, and so on. Second, considering three ways to do structural analysis, analysis from the inverse matrix, from the direct matrix and from layers (intermediate flow matrices), these methods induce topological problems; the adjacency of the adjacency cannot be defined from the inverse ma…

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Modelséconomieeconomic theoryjel:C67economicsJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[SHS.ECO]Humanities and Social Sciences/Economics and Financejel:D57JEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysisgestion[ SHS.ECO ] Humanities and Social Sciences/Economies and financesMFAmanagement economics[SHS.ECO] Humanities and Social Sciences/Economics and Financemanagementjel:R15
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Biproportion et offre dominante (A propos de l'article d'André Torre ‘Sur la signification théorique du modèle d'offre multisectoriel')

1996

One replies here to partisans of the reject of the supply-driven model in input-output analysis and especially to A. Torre (Revue Economique, 5, 44, 951-970). First of all, demand-driven hypothesis (Leontief) and supply-driven hypothesis (Ghosh) are symmetrical and incompatible, what forbidden to reject the second to the motive that it depends on the first. Secondly, the results earlier obtained for France of 1970 to 1985 from the method of the biproportionnal filter show that there is so much instability in the long term in the columns than in the rows of the flow matrix. Thirdly, the assimilation of the usage of allocation coefficients to the adoption of the supply-side model is excessive.

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsSupply-drivenJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsOffre dominanteInput-outputJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and financesLeontiefJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[SHS.ECO] Humanities and Social Sciences/Economics and Finance[SHS.ECO]Humanities and Social Sciences/Economics and FinanceGeneral Economics Econometrics and FinanceGhosh
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A Note on Qualitative Input-Output Analysis

1995

International audience; The paper discusses qualitative input—output methods. It is shown that information is lost. Because the binaiy relationship constructed by qualitative methods is not transitive, the model lacks economic consistency. Qualitative methods are tending to become more sophisticated, but some problems of economic interpretation are raised.

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelstopologyJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and financesQualitative input-outputJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[SHS.ECO] Humanities and Social Sciences/Economics and Finance[SHS.ECO]Humanities and Social Sciences/Economics and Finance
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Normalizing biproportional methods

2002

International audience; Biproportional methods are used to update matrices: the projection of a matrix Z to give it the column and row sums of another matrix is R Z S, where R and S are diagonal and secure the constraints of the problem (R and S have no signification at all because they are not identified). However, normalizing R or S generates important mathematical difficulties: it amounts to put constraints on Lagrange multipliers, non negativity (and so the existence of the solution) is not guaranteed at equilibrium or along the path to equilibrium.

JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output Modelsjel:C63Diagonaljel:C67JEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysismathematical economicsColumn (database)Projection (linear algebra)Combinatoricssymbols.namesakeMatrix (mathematics)JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingmatricesJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and financesNon negativity[SHS.ECO] Humanities and Social Sciences/Economics and FinanceGeneral Environmental ScienceMathematicsJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsGeneral Social Sciences[SHS.ECO]Humanities and Social Sciences/Economics and Financejel:D57community developmentJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingLagrange multiplierPath (graph theory)symbols
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Relevance of Tool Life Testing for Tool Replacement Strategies

1986

Several analytical and simulation models have been proposed in order to select the optimal tool replacement strategies both in single and multi-tool machining operations. All of these models, however, assume as known the probability density function that describes the stochastic behaviour of tool life. The costly efforts required in order to achieve an accurate estimate of the p.d.f. limits the use in the shop practice of the above models.

MachiningComputer scienceOrder (business)Simulation modelingRelevance (information retrieval)Probability density functionReliability engineeringLife testing
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A simulation/optimization model for selecting infrastructure alternatives in complex water resource systems

2010

The paper introduces a simulation/optimization procedure for the assessment and the selection of infrastructure alternatives in a complex water resources system, i.e. in a multisource (reservoirs) multipurpose bulk water supply scheme. An infrastucture alternative is here a vector X of n decision variables describing the candidate expansions/new plants/water transfers etc. Each parameter may take on a discrete number of values, with its own investment cost attached. The procedure uses genetic algorithms for the search of the optimal vector X through operators mimicking the mechanisms of natural selection. For each X, the value of the objective function (O.F.) is assessed via a simulation mo…

Mathematical optimizationEngineeringConservation of Natural ResourcesEnvironmental EngineeringUrban PopulationWater supplyInfrastructure optimizationWaste Disposal Fluidsimulation optimization water resource systemsResource AllocationWater PurificationResource (project management)Water SupplyHumansComputer SimulationTherapeutic IrrigationWater Science and TechnologyCost–benefit analysisbusiness.industrySimulation modelingEnvironmental resource managementModels TheoreticalInvestment (macroeconomics)DroughtsWater resourcesItalyMinificationbusinessAlgorithms
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Is the Ghosh model interesting?

2009

International audience; The overall value of the Ghosh model is appraised. Its treatment of quantities and prices is scrutinized by examining the variant with data in quantities and prices, and the variant with data in value and price indexes. The methodology involves returning to the accounting equations and shows that: (i) the Ghosh model offers solutions of limited interest, being incapable of providing prices or price indexes separately from quantities; (ii) what is taken to be the equation of Ghosh's value model is actually that of Ghosh's physical model; (iii) the Ghosh model may serve for cost-push exercises, but the dual of the Leontief model performs the same task in a much simpler…

Mixed modelLeontief modelJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsSupply-drivenJEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL: D - Microeconomics/D.D4 - Market Structure Pricing and Design/D.D4.D46 - Value TheoryJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisEnvironmental Science (miscellaneous)Development[SHS.ECO]Humanities and Social Sciences/Economics and FinanceAccounting equationDual (category theory)JEL : D - Microeconomics/D.D4 - Market Structure Pricing and Design/D.D4.D46 - Value TheoryInput-OutputPrice indexValue (economics)EconomicsJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and financesCroninDietzenbacher[SHS.ECO] Humanities and Social Sciences/Economics and FinanceMathematical economicsGhosh
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