An alternative approach to the construction of multi-regional input–output tables of the Czech Republic: application of the CHARM method

Radvansky, Marek; Lichner, Ivan

doi:10.1007/s10663-020-09490-6

Cited by 2 publications

(2 citation statements)

References 17 publications

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“…Another weakness therefore emerges in the formulations to be reviewed in the future. In relation to the Leontief inverse multipliers, only the sum by columns is taken into account, just as in other research studies [20,29,30]. Figure 9 shows the effect of LQ projections on the multipliers.…”

Section: Resultsmentioning

confidence: 99%

Spotting Error Patterns in Input–Output Projections Using Location Quotients

2022

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The Sustainable Development Goals (SDGs) stated by the United Nations (UN) constitute a universal agenda committed to human rights. In this context, mathematics can perform a fundamental role. Exploring possible contributions to these goals could be considered an interesting approach. Input–output (IO) tables provide detailed information for socio-economic quantifications. Thus, they allow for more precise policy decision-making and application in the SDG strategy. However, the smaller the subnational unit to be considered, the less statistical information that is available. Survey-based IO tables with large product/industry disaggregation are seldom published. Therefore, non-survey methods to estimate subnational IO tables based on the national are needed. These methodologies should yield optimal results. In the present investigation, different formulations for these non-survey regionalization methods are analyzed. The work focuses on the methodologies based on location quotients (LQ). As a result, some error patterns associated with current formulations present in literature are described. A slight refinement of these methodologies is proposed in order to improve the estimation’s accuracy.

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Section: Resultsmentioning

confidence: 99%

Spotting Error Patterns in Input–Output Projections Using Location Quotients

2022

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“…The impact of consumption activities in Tokyo was analyzed using the interregional waste input-output analysis model (Tsukui et al, 2015) and the Belgian regions of Brussels, Flanders and Wallonia were analyzed from the point of view of waste production using IO analysis called multi-regional hybrid IOT (Towa et al, 2021). In the Czech Republic, IO tables are available at the regional level but do not exist in individual municipalities (Radvanský & Lichner, 2021;Vltavská & Sixta, 2017). Due to insufficient and inaccurate data to perform the above IO EWF analysis for three city districts of the capital city of Prague, we decided to use the Salequzzaman method (Salequzzaman et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Waste Footprint of Selected City Districts of Prague

Vološinová

Ansorge

2021

EJSD

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The growing population, thriving economy, rapid urbanisation significantly accelerate the generation of municipal waste. Tightening conditions for waste management are a challenge for all stakeholders to comply with the law and, at the same time, motivate them to reduce waste production. The knowledge of the biosphere's assimilation capacity can quantify the environmental impact of waste in an understandable and popular form to better understand the human need to assimilate the waste produced. Utilising the waste footprint indicator and anthropogenic emissions in the form of waste are converted into soil adsorption capacity. The article compares the waste footprints of different areas of the city of Prague. It quantifies the influence of living and waste services on the waste footprints of the capital inhabitants. This article also discusses the relationship of the waste footprint with other footprints and is intended to inform future debate on trace accounting.

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An alternative approach to the construction of multi-regional input–output tables of the Czech Republic: application of the CHARM method

Cited by 2 publications

References 17 publications

Spotting Error Patterns in Input–Output Projections Using Location Quotients

Spotting Error Patterns in Input–Output Projections Using Location Quotients

Waste Footprint of Selected City Districts of Prague

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