Search results for "jel:C67"
showing 10 items of 12 documents
Bicausative matrices to measure structural change: Are they a good tool?
1999
The causative-matrix method to analyze temporal change assumes that a matrix transforms one Markovian transition matrix into another by a left multiplication of the first matrix; the method is demand-driven when applied to input-output economics. An extension is presented without assuming the demand-driven or supply-driven hypothesis. Starting from two flow matrices X and Y, two diagonal matrices are searched, one premultiplying and the second postmultiplying X, to obtain a result the closer as possible to Y by least squares. The paper proves that the method is deceptive because the diagonal matrices are unidentified and the interpretation of results is unclear. Keywords : Input-Output ; Ch…
About the criteria of output coincidence for forecasts to determine the orientation of the economy (application for France, 1980-1997)
2000
This note indicates that the method of output coincidence for forecasts used to determine if sectors are demand-driven or supply-driven in an input-output framework mixes two effects, the structural effect (choosing between demand and supply driven models) and the effect of an exogenous factor (final demand or added-value). The note recalls that another method is possible, the comparison of the stability of technical and allocation coefficients, generalized by the biproportional filter: if for a sector, after biproportional filtering, column coefficients are more stable than row coefficients, then this sector is declared as not supply-driven (but one cannot decide that it is demand-driven a…
On the Fallacy of Forward Linkages: A Note in the Light of Recent Results
2009
Following on from de Mesnard’s (2009) radical criticism of the Ghosh supply-driven model, this paper draws the dramatic consequences for the widespread use of forward linkages in input-output analysis applied to regional science: the practice must be abandoned. The arguments are based on three points: (i) it is impossible simultaneously to choose the Leontief model for the backward effects and the Ghosh model for the forward effects; (ii) it is impossible simultaneously to consider a production function of complementary inputs (Leontief) and a production function of perfectly substitutable inputs (Ghosh); and most importantly (iii) price effects and output effects remain inextricably mixed …
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.
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…
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.
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 …
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…
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
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..