Search results for "jel:D5"

showing 9 items of 19 documents

Analyzing structural change : the biproportional mean filter and the biproportional bimarkovian filter

1998

The biproportional filter was created to analyze structural change between two input-output matrices by removing the effect of differential growth of sectors without predetermining if the model is demand or supply-driven, but with the disadvantage that projecting a first matrix on a second is not the same thing than projecting the second matrix on the first. Here two alternative methods are proposed which has not this last drawback, with the additional advantage for the biproportional bimarkovian filter that effects of sector size are also removed. Methods are compared with an application for France for 1980 and 1996.

Gestionjel:C63Economicséconomieeconomic theoryjel:C67[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and Finance[SHS.ECO]Humanities and Social Sciences/Economics and FinanceManagement economicsjel:D57management
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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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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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Prices and Pareto optima

2006

We provide necessary conditions for Pareto optimum in economies where tastes or technologies may be nonconvex, nonsmooth, and affected by externalities. Firms can pursue own objectives, much like the consumers. Infinite-dimensional commodity spaces are accommodated. Public goods and material balances are accounted for as special instances of linear restrictions.

Microeconomicsjel:C60first and second welfare theorem; weak and strong Pareto optimum; nonconvex tastes or technologies; public goods; externalities; local separation; subdifferentials; normal conesControl and OptimizationApplied Mathematicsjel:D60jel:D50EconomicsPareto principleManagement Science and Operations ResearchPublic goodCommodity (Marxism)ExternalityOptimization
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Qualitative methods of structural analysis : layer-based methods are informationally trivial

2000

Some methods of qualitative structural analysis, as MFA, are based on the analysis of layers (flow matrices generated at each iteration when the equilibrium of an input-output model is computed). MFA mixes the analysis of the pure structure of production (the technical coefficients) and of the final demand. I have demonstrated that all column-coefficient matrices (or row-coefficient matrices) computed from each layer are the same in MFA: the information brought by one layer is identical to those of another layer. For a given structure of production, the only element of variability over layers is caused by the flows that final demand generates.If the new definition of layers proposed by the …

QIOAéconomieHigh Energy Physics::Latticeeconomic theoryjel:C67economics[SHS.ECO]Humanities and Social Sciences/Economics and Financejel:D57GeneralLiterature_MISCELLANEOUSbooleangestion[ SHS.ECO ] Humanities and Social Sciences/Economies and financesMFAmanagement economics[SHS.ECO] Humanities and Social Sciences/Economics and Financemanagementjel:R15
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True prices, latent prices and the Ghosh model : some inconsistencies

2001

Beside the traditional Leontief demand-driven model, there is the Ghosh supply-driven model. This paper explores the typology of the possible models: demand driven models versus supply driven models, true prices versus latent (or index) prices, coefficients in physical terms versus coefficients in value. This demonstrates that the supply-driven model offers results of limited interest, being incapable to separate quantities and prices; and it is only when a very strange hypothesis is chosen -- demand prices, controlled by the buyer -- that the supply-driven model gives an interesting result with a separation between quantities and prices in the solution, becoming the dual of the Leontief mo…

TheoryofComputation_MISCELLANEOUSSupply-drivenEconomicsjel:C67TheoryofComputation_GENERAL[SHS.ECO]Humanities and Social Sciences/Economics and Financejel:D46jel:D57ManagementGestionEconomic theoryInput-outputEconomie[ SHS.ECO ] Humanities and Social Sciences/Economies and finances[SHS.ECO] Humanities and Social Sciences/Economics and FinanceManagement economics
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Failure of the normalization of the RAS method : absorption and fabrication effects are still incorrect

2000

The r and s vectors of the RAS method of updating matrices are presented often as corresponding to an absorption effect and a fabrication effect. Here, it is proved that these vectors are not identified, so their interpretation in terms of fabrication and absorption effect is incorrect and even if a normalization was proposed to remove underidentification, this normalization fails and poses many difficulties.. Keywords : Input-Output ; RAS ; Biproportion

input-outputjel:C63économieeconomic theoryjel:C67economics[SHS.ECO]Humanities and Social Sciences/Economics and Financejel:D57biproportiongestion[ SHS.ECO ] Humanities and Social Sciences/Economies and financesmanagement economics[SHS.ECO] Humanities and Social Sciences/Economics and Financemanagement
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Interpretation of the RAS method : absorption and fabrication effects are incorrect.

1999

The r and s vectors of the RAS method of updating matrices are presented often as corresponding to an absorption effect and a fabrication effect. Here, it is proved that these vectors are unidentified, so their interpretation in terms of fabrication and absorption effect is incorrect..

jel:C63parasitic diseasesPhysics::Space Physicstechnology industry and agriculturePhysics::Opticsjel:C67jel:D57Computer Science::Other
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About the reinterpretation of the Ghosh model as a price model

2001

The Ghosh model assumes that, in an input-output framework, each commodity is sold to each sector in fixed proportions. This model is strongly criticized because it seems implausible in the traditional input-output field. To answer to these critics, Dietzenbacher stresses that it can be reinterpreted as a price model: the Leontief price model is equivalent to the Ghosh model when this one is interpreted as a price model. This paper shows that the interpretation of the Ghosh model as a price model cannot be accepted because Dietzenbacher makes a strong assumption, dichotomy, while the Ghosh model does not determine prices...

supplyinput-outputéconomieeconomic theoryjel:C67demandeconomics[SHS.ECO]Humanities and Social Sciences/Economics and Financejel:D46jel:D57gestion[ SHS.ECO ] Humanities and Social Sciences/Economies and financesmanagement economics[SHS.ECO] Humanities and Social Sciences/Economics and Financemanagement
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