Foundations of Input–Output Analysis

Miller, Ronald E.; Blair, Peter D.

doi:10.1017/cbo9780511626982.003

Cited by 101 publications

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“…Methodologically our starting point is a MRIO model for the world economy [21][22][23] environmentally extended for water resources. The total water flows among countries and sectors, as well as the internal and external components of the water footprints can be obtained as follows:…”

Section: Methodsmentioning

confidence: 99%

Income, Economic Structure and Trade: Impacts on Recent Water Use Trends in the European Union

2018

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From the mid-1990s to the recent international economic crisis, the European Union (EU27) experienced a significant economic growth and a flat population increase. During these years, the water resources directly used by the EU countries displayed a growing but smooth trend. However, European activities intensively demanded water resources throughout the whole global supply chain. The growth rate of embodied water use was three times higher than the growth in water directly used by these economies. This was mainly due to the large upsurge of virtual water imports in the EU (e.g., about 25% of the change in water imports in the world was directly linked to the increasing imports in the EU27 countries). In this context, we analyze water use changes in the EU27 from 1995 to 2009, combining the production and consumption perspectives. To that aim, we use the environmentally extended input-output approach to obtain the volume of water embodied in domestic production and in trade flows at the sector and country levels. In the empirical analysis, we utilize multi-regional input-output data from the World Input Output Database. In addition, by means of a structural decomposition analysis we identify and quantify the factors explaining changes in these trends. We focus both on the role of domestic production and trade and estimate the associated intensity, technology and scale effects. This analysis is done for different clusters, identifying singular patterns depending on income criteria. Our results confirm the boost of demand growth in that period, the positive but negligible effect of structural change, and the decline in water intensity which, however, was not enough to compensate the effects on water associated to the economic expansion in the period. These findings also point at a gradual substitution of domestic water use for virtual water imports. More concretely, in most countries the food industry tended to reduce its backward linkages with the domestic agricultural sector, increasing the embodied water in agricultural imports from non-European regions.

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Section: Methodsmentioning

confidence: 99%

Income, Economic Structure and Trade: Impacts on Recent Water Use Trends in the European Union

2018

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“…This calculation results in the determination of the total consumption-based environmental impact across the economy for producing a particular product or service. A full description of the IO LCA derivation and calculation methodology can be found in [55][56][57].…”

Section: Methodsmentioning

confidence: 99%

Carbon Footprint of Inbound Tourism to Iceland: A Consumption-Based Life-Cycle Assessment including Direct and Indirect Emissions

2016

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Abstract:The greenhouse gas (GHG) emissions caused by tourism have been studied from several perspectives, but few studies exist that include all direct and indirect emissions, particularly those from aviation. In this study, an input/output-based hybrid life-cycle assessment (LCA) method is developed to assess the consumption-based carbon footprint of the average tourist including direct and indirect emissions. The total inbound tourism-related GHG emissions are also calculated within a certain region. As a demonstration of the method, the full carbon footprint of an average tourist is assessed as well as the total GHG emissions induced by tourism to Iceland over the period of 2010-2015, with the presented approach applicable in other contexts as well. Iceland provides an interesting case due to three features: (1) the tourism sector in Iceland is the fastest-growing industry in the country with an annual growth rate of over 20% over the past five years; (2) almost all tourists arrive by air; and (3) the country has an almost emissions-free energy industry and an import-dominated economy, which emphasise the role of the indirect emissions. According to the assessment, the carbon footprint for the average tourist is 1.35 tons of CO 2 -eq, but ranges from 1.1 to 3.2 tons of CO 2 -eq depending on the distance travelled by air. Furthermore, this footprint is increasing due to the rise in average flight distances travelled to reach the country. The total GHG emissions caused by tourism in Iceland have tripled from approximately 600,000 tons of CO 2 -eq in 2010 to 1,800,000 tons in 2015. Aviation accounts for 50%-82% of this impact (depending on the flight distance) underlining the importance of air travel, especially as tourism-related aviation is forecasted to grow significantly in the near future. From a method perspective, the carbon footprinting application presented in the study would seem to provide an efficient way to study both the direct and indirect emissions and to provide new insights and information to enable the development of appropriate GHG mitigation policies in the tourism sector.

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“…In the compilation of statistical economic data, such as a census-based Input-Output (IO) table or a social-accounting matrix (SAM), it is often the case that the data is not balanced, i.e., row and column sums do not add up [1]. Furthermore, data balancing is important in practical applications such as updating or regionalizing IO tables, or decomposing proximate causes of economic change [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

A Bayesian Approach to the Balancing of Statistical Economic Data

Rodrigues

2014

Entropy

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Abstract:This paper addresses the problem of balancing statistical economic data, when data structure is arbitrary and both uncertainty estimates and a ranking of data quality are available. Using a Bayesian approach, the prior configuration is described as a multivariate random vector and the balanced posterior is obtained by application of relative entropy minimization. The paper shows that conventional data balancing methods, such as generalized least squares, weighted least squares and biproportional methods are particular cases of the general method described here. As a consequence, it is possible to determine the underlying assumptions and range of application of each traditional method. In particular, the popular biproportional method is found to assume that all source data has the same relative uncertainty. Finally, this paper proposes a simple linear iterative method that generalizes the biproportional method to the data balancing problem with arbitrary data structure, uncertainty estimates and multiple data quality levels.

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Foundations of Input–Output Analysis

Cited by 101 publications

References 0 publications

Income, Economic Structure and Trade: Impacts on Recent Water Use Trends in the European Union

Income, Economic Structure and Trade: Impacts on Recent Water Use Trends in the European Union

Carbon Footprint of Inbound Tourism to Iceland: A Consumption-Based Life-Cycle Assessment including Direct and Indirect Emissions

A Bayesian Approach to the Balancing of Statistical Economic Data

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