Projection of input–output tables by means of mathematical programming based on the hypothesis of stable structural evolution

Tarancón, Miguel Ángel; Rı́o, Pablo del

doi:10.1080/09535310500034119

Cited by 16 publications

(4 citation statements)

References 12 publications

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“…The RAS method is connected to the second group as it is is an algorithm to solve the updating problem using a particular entropy measure (McDougall ). Some results related to the first group of measures can be found in Matuszewski et al (), Harrigan and Buchanan (), Canning and Wang () and Tarancón and Del Río (). Works about updating criteria based on entropy measures are Macgill (, ), Golan et al () and Robinson et al (), among others.…”

Section: Introductionmentioning

confidence: 92%

SAM updating using multi‐objective optimization techniques

Manrique-de-Lara-Peñate

Peñate

2017

Papers in Regional Science

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In this work we present an adjustment/updating procedure of Social Accounting Matrices (SAM) using multiobjective optimization techniques. The usual setting concentrates the adjustment effort in either the column or row coefficients of the SAM. The normal tendency consists in using the column coefficients because they better reflect the technical coefficients embedded in the SAM. Using the benchmark SAM as the basis, and incorporating the new information available we pose a double-objective optimization problem and apply the method of compromise programming that allow us to work together with column and row coefficients.We present samples of the adjustment procedure where we show and compare the Pareto optimal solutions obtained together with other solutions obtained with different adjustment criteria. We compare the results obtained with the ones obtained with other approaches like RAS and the minimum sum of cross entropy together with other methods proposed by the authors. This comparison allows us to evaluate the differences existing between these different methods and the pure vertical or horizontal adjustment criteria. We believe that the adjustment/updating criteria used does not need to be the same along the different parts of the SAM.We may want to update the input-output matrix included in the SAM concentrating in the vertical/column/technical coefficients. But there may be other parts of the SAM where we think that the use of row coefficients, or together both row and column coefficients, is more appropriate. The method we propose can be also applied to situations where the adjustment criteria is not the same for different parts of the SAM.

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Section: Introductionmentioning

confidence: 92%

SAM updating using multi‐objective optimization techniques

Manrique-de-Lara-Peñate

Peñate

2017

Papers in Regional Science

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“…In order to circumvent the restrictions imposed by incomplete and misaligned initial estimate data whilst at the same time ensuring smooth (that is hysteresis-free) inter-year transitions, Tarancon and Del Rio (2005) apply the stable structural evolution hypothesis, and use adjacent-year values in order to formulate bounds as constraints for unknown inputoutput coefficients, which stay active during balancing. However, since these bounds are fixed, it may happen during matrix optimisation that they conflict with other constraints.…”

Section: The Problem Of Hysteresis In Forecasting and Backcastingmentioning

confidence: 99%

A Cycling Method for Constructing Input–output Table Time Series From Incomplete Data

Lenzen

Moura

Geschke

et al. 2012

Economic Systems Research

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There are a number of approaches for constructing time series of input-output tables. Some authors generate an initial estimate for a base year, and then serially estimate tables for subsequent years using the balanced prior-year table as an initial estimate. Others first generate a series of initial estimates for the entire period, and then balance tables in parallel. Current serial methods are affected by sudden leaps in the magnitude of table elements, which occur straight after a period of data unavailability. Current parallel methods require two complete tables for base and final years in the same classification, and therefore do not work under misaligned or incomplete data. We present a new method for constructing input-output table time series that overcomes these problems by averaging over alternate forward and backward sweeps across the time series period. We also solve the problem of hysteresis causing forecast and backcast table estimates to differ.

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“…Changes in the prior to remove infeasibilities is another issue that we should address. Such changes are common when applying Euro and GRAS methods, as is relaxing certain constraints (Lenzen et al, 2009;Tarancón & Del Río, 2005). Nonetheless, GRAS/SUT-RAS methods are usually quite stable (Valderas-Jaramillo et al, 2019, p. 437) and, thus, tend to converge more easily than do SUT-Euro methods under identical conditions (same prior and same targets).…”

Section: Common Features Of the Sut-euro Gras-1 And Other Bi-proportmentioning

confidence: 99%

The Euro and SUT-RAS methods: some further considerations

Jaramillo

Rueda‐Cantuche

Beutel

2021

Economic Systems Research

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The main objective of this paper is to revisit the Euro method in a critical and constructive way. We have analysed some arguments against the Euro method published recently in the literature as well as some other relevant aspects of the SUT-Euro and SUT-RAS methods not covered before. Although not being the Euro method perfect, we believe that there is still space for the use of the Euro method in updating/regionalizing Supply and Use tables.

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Projection of input–output tables by means of mathematical programming based on the hypothesis of stable structural evolution

Cited by 16 publications

References 12 publications

SAM updating using multi‐objective optimization techniques

SAM updating using multi‐objective optimization techniques

A Cycling Method for Constructing Input–output Table Time Series From Incomplete Data

The Euro and SUT-RAS methods: some further considerations

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