Search results for " quantitative method"

showing 10 items of 111 documents

Inverted and mirror repeats in model nucleotide sequences.

2007

We analytically and numerically study the probabilistic properties of inverted and mirror repeats in model sequences of nucleic acids. We consider both perfect and non-perfect repeats, i.e. repeats with mismatches and gaps. The considered sequence models are independent identically distributed (i.i.d.) sequences, Markov processes and long range sequences. We show that the number of repeats in correlated sequences is significantly larger than in i.i.d. sequences and that this discrepancy increases exponentially with the repeat length for long range sequences.

Independent identically distributedTime FactorsMolecular Sequence DataMarkov processNucleic Acid DenaturationQuantitative Biology - Quantitative MethodsCombinatoricssymbols.namesakeExponential growthChromosomes Human inverted repeatsNucleotideQuantitative Biology - GenomicsRNA Small InterferingQuantitative Methods (q-bio.QM)Sequence (medicine)MathematicsProbabilityRepetitive Sequences Nucleic AcidGenomics (q-bio.GN)chemistry.chemical_classificationStochastic ProcessesModels StatisticalBase SequenceNucleotidesProbabilistic logicMarkov ChainschemistryFOS: Biological sciencesNucleic acidsymbolsNucleic Acid RenaturationNucleic Acid ConformationAlgorithmsPhysical review. E, Statistical, nonlinear, and soft matter physics
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Understanding the shortcomings of commodity-based technology in input-output models: an economic-circuit approach

2004

International audience; The Make-Use Model serves as a basis for most national accounting systems as the System of National Accounts (SNA) and is acknowledged as the most suitable model for interregional analysis. Two hypotheses are traditionally made featuring either industry-based technologies (IBT) or commodity-based technologies (CBT). While industry-based technologies can be easily interpreted in terms of a demand-driven economic circuit, it will be shown that: (1) commodity-based technologies cannot be interpreted as a demand-driven economic circuit because this involves computing the inverse of a matrix (the matrix of industry output proportions), which is either impossible or genera…

Input/outputJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsBasis (linear algebra)JEL: C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsInput–output modelComputer scienceNational accountsMatrix (music)Environmental Science (miscellaneous)DevelopmentJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and Analysis[SHS.ECO]Humanities and Social Sciences/Economics and Financemathematical economicsIndustrial engineeringinput-output analysisdemand (economic theory)JEL : 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 FinanceCommodity (Marxism)Axiom
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Spatial mismatch through local public employment agencies Answers from a French quasi-experiment Spatial Mismatch through Local Public Employment Age…

2015

Using the unanticipated creation of a new agency in the French region of Lyon as a quasi-natural experiment, we question whether distance to local public employment agencies (LPEAs) is a new channel for spatial mismatch. Contrary to past evidence based on aggregated data and consistently with the spatial mismatch literature, we find no evidence of a worker/agency spatial mismatch, which pleads for a resizing of the French LPEA network. However, echoing with the literature on the institutional determinants of the local public employment agencies' efficiency, we do find detrimental institutional transitory effects.

JEL : C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C21 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressionsquasi-experimentunemploymentJEL : J - Labor and Demographic Economics/J.J5 - Labor–Management Relations Trade Unions and Collective Bargaining/J.J5.J58 - Public Policy[ SHS.ECO ] Humanities and Social Sciences/Economies and financesspatial mismatchJEL: C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C21 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressionspublic employment serviceJEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R5 - Regional Government Analysis/R.R5.R53 - Public Facility Location Analysis • Public Investment and Capital Stock[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.R5 - Regional Government Analysis/R.R5.R53 - Public Facility Location Analysis • Public Investment and Capital StockJEL: J - Labor and Demographic Economics/J.J5 - Labor–Management Relations Trade Unions and Collective Bargaining/J.J5.J58 - Public Policy
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Interactions, spillovers de connaissance et croissance des villes européennes. Faut-il préférer la géographie, le climat institutionnel ou les réseau…

2013

Knowledge spillovers within urban economies are also sources of spillovers between cities. We examine how knowledge spillovers influenced the economic growth of 82 European metropolises over the 1990-2005 period. We model knowledge spillovers between cities on the basis of five specific interaction patterns based on geography, networks of multinational firms in advanced services, institutional climate and two combinations of these factors. Spatial models are estimated to detail the effects of growth factors in terms of spillovers and externalities. We show that spillovers are local rather than global and that interactions among cities accelerate the convergence process based on gross value …

JEL : C - Mathematical and Quantitative Methods/C.C3 - Multiple or Simultaneous Equation Models • Multiple Variables/C.C3.C31 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions • Social Interaction ModelsJEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R11 - Regional Economic Activity: Growth Development Environmental Issues and ChangesCROISSANCE URBAINE[SHS.ECO]Humanities and Social Sciences/Economics and FinanceURBAN GROWTHJEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R11 - Regional Economic Activity: Growth Development Environmental Issues and ChangesINTERNATIONAL FIRM NETWORKSJEL: R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R12 - Size and Spatial Distributions of Regional Economic ActivityJEL: C - Mathematical and Quantitative Methods/C.C3 - Multiple or Simultaneous Equation Models • Multiple Variables/C.C3.C31 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile Regressions • Social Interaction ModelsSPILLOVERSSPATIAL ECONOMETRICSJEL : R - Urban Rural Regional Real Estate and Transportation Economics/R.R1 - General Regional Economics/R.R1.R12 - Size and Spatial Distributions of Regional Economic ActivityRESEAUX DES FIRMES MULTINATIONALESINSTITUTIONS[ SHS.ECO ] Humanities and Social Sciences/Economies and financesÉCONOMÉTRIE SPATIALEJEL: O - Economic Development Innovation Technological Change and Growth/O.O4 - Economic Growth and Aggregate Productivity[SHS.ECO] Humanities and Social Sciences/Economics and FinanceJEL : O - Economic Development Innovation Technological Change and Growth/O.O4 - Economic Growth and Aggregate Productivity
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Biproportional Methods And Interindustry Dynamics: The Case of Energy in France

1996

JEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C67 - Input–Output ModelsJEL : Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q4 - Energy/Q.Q4.Q43 - Energy and the MacroeconomyJEL: Q - Agricultural and Natural Resource Economics • Environmental and Ecological Economics/Q.Q4 - Energy/Q.Q4.Q43 - Energy and the MacroeconomyJEL: 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: 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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Dynamique de la structure industrielle française

1990

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.C63 - Computational Techniques • Simulation ModelingJEL: 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.C61 - Optimization Techniques • Programming Models • Dynamic AnalysisJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C63 - Computational Techniques • Simulation ModelingJEL: L - Industrial Organization/L.L1 - Market Structure Firm Strategy and Market Performance/L.L1.L16 - Industrial Organization and Macroeconomics: Industrial Structure and Structural Change • Industrial Price IndicesJEL : D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisJEL : C - Mathematical and Quantitative Methods/C.C6 - Mathematical Methods • Programming Models • Mathematical and Simulation Modeling/C.C6.C61 - Optimization Techniques • Programming Models • Dynamic Analysis[ SHS.ECO ] Humanities and Social Sciences/Economies and financesJEL: D - Microeconomics/D.D5 - General Equilibrium and Disequilibrium/D.D5.D57 - Input–Output Tables and AnalysisJEL : L - Industrial Organization/L.L1 - Market Structure Firm Strategy and Market Performance/L.L1.L16 - Industrial Organization and Macroeconomics: Industrial Structure and Structural Change • Industrial Price Indices[SHS.ECO]Humanities and Social Sciences/Economics and Finance[SHS.ECO] Humanities and Social Sciences/Economics and Finance
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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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