EFFECTS OF SECTOR AGGREGATION ON CO2 MULTIPLIERS IN MULTIREGIONAL INPUT–OUTPUT ANALYSES

The past few years have seen the emergence of several global multiregional input–output (MRIO) databases. Due to the cost and complexity of developing such extensive tables, industry sectors are generally represented at a rather aggregate level. Currently, one of the most important applications of input–output analysis is environmental assessments, for which highly aggregate sectors may not be sufficient to yield accurate results. We experiment with four of the most important global MRIO systems available, analyzing the sensitivity of a set of aggregate CO₂ multipliers to aggregations in the MRIO tables used to calculate them. Across databases, we find (a) significant sensitivity to background system detail and (b) that sub-sectors contained within the same aggregate MRIO sector may exhibit highly different carbon multipliers. We conclude that the additional information provided by the extra sector detail may warrant the additional costs of compilation, due to the heterogeneous nature of economic sectors in terms of their environmental characteristics.     

The Impact of Choice Inconsistencies in Stated Choice Studies

A new test procedure revealing mutuallyinconsistent choices has been developed andapplied to Stated Choice data. Our analysisshows that inconsistent choices commonly occurin several Stated Choice tasks. An applicationof the test to the Norwegian Value of Timestudy data shows that failing to excludeinconsistent choices resulted in asubstantially higher Value of time. Theinconsistent choices were made by less educatedparticipants. As the tasks were undertaken inthe easy context of choosing travelalternatives with three attributes,practitioners of more complex and cognitivedemanding designs should be particularilyconcerned with these results.     

A STRUCTURAL DECOMPOSITION APPROACH TO COMPARING MRIO DATABASES

The construction of multi-regional input–output tables is complex, and databases produced using different approaches lead to different analytical outcomes. We outline a decomposition methodology for investigating the variations that exist when using different multiregional input–output (MRIO) systems to calculate a region's consumption-based account. Structural decomposition analysis attributes the change in emissions to a set of dependent determinants, such as technical coefficients, the Leontief inverse and final demands. We apply our methodology to three MRIO databases – Eora, GTAP and WIOD. Findings reveal that the variation between Eora and GTAP can be attributed to differences in the Leontief inverse and emissions’ data, whereas the variation between Eora and WIOD is due to differences in final demand and the Leontief inverse. For the majority of regions, GTAP and WIOD produce similar results. The approach in this study could help move MRIO databases from the academic arena to a useful policy instrument.     

THE ‘REST OF THE WORLD’ – ESTIMATING THE ECONOMIC STRUCTURE OF MISSING REGIONS IN GLOBAL MULTI-REGIONAL INPUT–OUTPUT TABLES

Incomplete data for the economic structure of numerous countries hamper the compilation of global multi-regional input–output (MRIO) tables. By themselves, most of these countries are of only limited importance for the global economy and incumbent environmental issues. Hence, in most recent global MRIO tables these countries are either roughly estimated or summarised in one rest of the world (RoW) region. Combining a wide range of countries, this RoW region may play a significant role in global economic and environmental accounts. We conceptualise the importance of RoW in several environmental footprint accounts and present algorithms to estimate the structure of RoW. The approach utilises the information of the economic structure within known parts of the MRIO table to estimate the unknown structure. Using this method, global warming potential and employment footprints remain stable irrespective of the chosen initial estimates, whereas natural land use footprints and individual product impacts vary significantly.     

Accounting for value added embodied in trade and consumption: an intercomparison of global multiregional input–output databases

Global multiregional input–output (MRIO) tables constitute detailed accounts of the economic activity worldwide. Global trade models based on MRIO tables are being used to calculate important economic and environmental indicators such as value added in trade or the carbon footprint of nations. Such applications are highly relevant in international trade and climate policy negotiations, and consequently MRIO model results are being scrutinized for their accuracy and reproducibility. We investigate the variation in results from three major MRIO databases by comparing underlying economic data and territorial and consumption-based results across databases. Although global value-added accounts were similar across databases, we find some significant differences at the level of individual countries and sectors. Model disagreement was relatively stable from the territorial to the consumption perspective. Pairwise matrix comparison statistics indicated that the Global Trade Analysis Project and World Input-Output Database MRIO tables were overall more similar to each other than either was to the Eora database.     

Using qualitative types of risk assessments in conjunction with FRAM to strengthen the resilience of systems

Abstract

In this paper, we look into how some qualitative types of risk assessments can be used in conjunction with functional resonance analysis method (FRAM) to strengthen the resilience of systems. In FRAM, variation in relation to meeting specified functions is central, but risk and uncertainty considerations are not an integral part. We suggest to add to FRAM an assessment of the modelling choices and judgements using strength of knowledge considerations and a qualitative sensitivity analysis. In this way, an improved basis for assessing and strengthening system resilience with FRAM is established. We illustrate the idea with a simple example from the oil and gas industry.