Disaggregating Input--Output Tables by the Multidimensional RAS Method: A Case Study of the Czech Republic

Holý, Vladimír; Šafr, Karel

doi:10.48550/arxiv.1704.07814

Cited by 2 publications

(5 citation statements)

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“…Undoubtedly, the problems addressed by the nD-GRAS method can be embedded and solved in this KRAS framework, as long as a feasible solution exists, using the same objective function, a set of constraints with unity coefficients and no conflicting information. This also applies, not only to the nD-GRAS method, but also to the rest of the multidimensional methods mentioned in this paper such as those proposed by Holý and Šafr (2020) or Temursho, Oosterhaven, and Cardenete (2020). Even though the advantages of the extended KRAS methodology and virtual labs proposals are obvious, other aspects also have to be taken into account.…”

Section: Literature Reviewmentioning

confidence: 92%

“…Holý and Šafr (2020) introduced a multidimensional RAS method (DRAS) that reformulates the bi-dimensional RAS problem in a purely multidimensional set-up that deals with only non-negative arrays. In Holý and Šafr (2020), the method was introduced only in an algorithmic way, similar to Tilanus (1976). Holý and Šafr (2020) prove that this algorithm is the solution of the cross-entropy optimization model in a multidimensional generalization.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In Holý and Šafr (2020), the method was introduced only in an algorithmic way, similar to Tilanus (1976). Holý and Šafr (2020) prove that this algorithm is the solution of the cross-entropy optimization model in a multidimensional generalization. The DRAS is a particular case of the nD-GRAS when no negative elements exist in the initial matrix.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In this situation, for instance, the aggregated table would be an annual table, and the third dimension would account for a temporal disaggregation (e.g., quarterly). The same applies for the breakdown of total coefficients into domestic and imported figures (see Holý & Šafr, 2020).…”

Section: Multidimensional Gras Balancing Problems In Practicementioning

confidence: 99%

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The multidimensional nD‐GRAS method: Applications for the projection of multiregional input–output frameworks and valuation matrices

Jaramillo

Rueda‐Cantuche

2021

Papers in Regional Science

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We present a multidimensional generalization of the GRAS method (nD-GRAS) for the estimation of multiple matrices in an integrated framework. The potential applications of this method in regional and multi-regional input-output analyses based on national/regional accounts frameworks are many. We provide two real applications, a 3D-GRAS that estimates a use table at basic prices jointly with valuation matrices for Denmark; and a 4D-GRAS for estimating intercountry input-output tables with OECD data. We show that higher dimensional GRAS methods provide more consistent and accurate estimates than those with lower number of dimensions. We provide the analytical closedform solution and the RAS-like algorithm for an easy operationalization.

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Section: Literature Reviewmentioning

confidence: 92%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Multidimensional Gras Balancing Problems In Practicementioning

confidence: 99%

See 2 more Smart Citations

The multidimensional nD‐GRAS method: Applications for the projection of multiregional input–output frameworks and valuation matrices

Jaramillo

Rueda‐Cantuche

2021

Papers in Regional Science

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“…In order to construct an updated version of the I-O matrix we used the Supply and Utilization Tables (SUT), SNA with detailed data for 2018. We follow the methodology as in Holỳ & Šafr (2017), Oropeza &Lagarda (2020), andTemursho et al (2021). Moreover, whenever needed, we used information from the Economic Census.…”

Section: Economymentioning

confidence: 99%

A Personalized VAT with Capital Transfers: A Reform to Protect Low-Income Households in Mexico

Kotlikoff¹,

LaGarda²,

Marin³

2023

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The Value-Added Tax (VAT) is the most prevalent consumption tax globally, yet it is frequently deemed highly regressive. To address this, we propose a Personalized VAT (PVAT) devised in conjunction with a distributional policy. We aim to achieve three objectives: increase revenue collection, achieve progressivity, and disrupt the intergenerational dependency of low-income households. We use Mexico as a case study, showing that eliminating all special VAT regimes and standardizing the rate at 16% could contribute an additional 2.2% of GDP to fiscal revenues. However, such a reform could have severe negative welfare impacts on the poor. To tackle this dilemma, we propose several PVAT scenarios. Our results indicate that a PVAT could be fiscally neutral or even increase revenues by up to 0.83% of GDP, while benefiting the lowest-income households. Lastly, we analyze the general equilibrium effects of a PVAT and various distributional policies, including lump-sum and capital transfers. For this purpose, we employ an overlapping generations model calibrated for Mexico. Our simulations reveal welfare enhancing and output growth results through a PVAT policy that includes capital transfers, thereby presenting a viable strategy for breaking intergenerational dependency.

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Disaggregating Input--Output Tables by the Multidimensional RAS Method: A Case Study of the Czech Republic

Cited by 2 publications

References 0 publications

The multidimensional nD‐GRAS method: Applications for the projection of multiregional input–output frameworks and valuation matrices

The multidimensional nD‐GRAS method: Applications for the projection of multiregional input–output frameworks and valuation matrices

A Personalized VAT with Capital Transfers: A Reform to Protect Low-Income Households in Mexico

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