Alternative Approaches of Physical Input–Output Analysis to Estimate Primary Material Inputs of Production and Consumption Activities

In the last few years, a number of studies have been presented that link material flow accounting and input–output analysis (based on monetary input–output tables) for the calculation of direct and indirect resource inputs for production and consumption activities. The compilation of the first physical input–output tables for some European countries in the 1990s opened new possibilities for linking physical accounting and input– output analysis. Physical input–output analysis has so far only been applied for selected materials, but it has not been used for comprehensive assessments of material requirements of economic activities. In this paper, possibilities and limits of this new input–output approach are clarified. We present and discuss a procedure similar to monetary input– output analysis and develop an alternative approach to account for primary inputs and waste otherwise not included in the analysis. Based on aggregated input–output tables for Germany, we present numerical examples intended to compare the alternative approaches of physical input–output analysis.     

An input–output virtual laboratory in practice – survey of uptake,usage and applications of the first operational IELab

ABSTRACT

The Industrial Ecology Virtual Laboratory (IELab) is a collaborative cloud-computing platform for compiling large-scale, high-resolution, enviro-socio-economic accounts based on multi-region input–output tables and for conducting integrated sustainability assessment projects. These include, for example, assessments of biofuels and low-carbon construction materials or high-resolution waste modelling. This contribution provides a structured review of IELab applications that were published in either peer-reviewed journal papers or in the form of conference proceedings. The main research question posed is ‘What are the specific features of IELab that were used in the research and could the research have happened without them?’ It is investigated whether the IELab has actually and truly enabled new research. A detailed analysis of IELab characteristics and their usage is presented. The results can help with the design of new research projects and inform existing and prospective users of the IELab about the options for academic research and practical applications.     

Does It Make Sense to Apply the Static Open Input–Output Model for Imputation and Structural Decomposition?

This paper aims to stimulate discussion on the question concerning whether input–output (10) analysts should go on applying the static open 10 model in times when data supply and computer capacity allow us to switch to semi-closed 10 models, which are rated as comparative improvements. It is argued that the most frequent of the open 10 model's applications, i.e. imputations and structural decompositions, with a switch to a semi-closed model, lose the properties which make them so attractive: imputations no longer are straightforward assignments of production and primary inputs to the components of total final demand; structural decomposition no longer is an additive assignment of changes of production and primary inputs to sources of structural change. In the author's opinion, imputations and structural decompositions on the basis of the open 10 model should be abandoned.     

CONSTRUCTING AN ENVIRONMENTALLY-EXTENDED MULTI-REGIONAL INPUT–OUTPUT TABLE USING THE GTAP DATABASE

The use of Multi-Regional Input–Output Analysis (MRIOA) for understanding global environmental problems is growing rapidly. Renewed interest in MRIOA has led to several large research projects focused on constructing detailed and accurate MRIOTs. However, very few researchers have made use of the already available and regularly updated database produced by the Global Trade Analysis Project (GTAP). We demonstrate and discuss how the GTAP database can be converted into an MRIOT without the need for additional balancing. An illustrative example uses the GTAP-MRIO to reallocate carbon dioxide emissions from producing to consuming countries. We suggest that an MRIOT that treats international transport exogenously is adequate until more reliable data on international transport margins and emissions are available. To focus resources and refine methods, a concerted research effort is needed to compare the results of the GTAP-MRIO model with the new MRIO datasets under development.     

A Synthetic Approach to Projecting Input–Output Tables

This paper describes an approach used in the Canadian input–output (IO) accounts, which seeks to enhance the timeliness of the tables. It combines traditional updating methods, balancing techniques and the most recent data. To assess the performance of this approach, aggregate estimates from the synthetic accounts are presented for two years, and compared with estimates from benchmarks and with estimates obtained from a mechanical estimation technique. The results show that most IO components can be estimated with a relatively small estimation error and that substantial accuracy is gained from using the synthetic approach compared with a mechanical technique. Results based on data which are two years away from IO benchmarks are obtained at the cost of large errors. Synthetic estimates of the IO accounts improve the timeliness problem by at least a full year.     

Improving footprint calculations of small open economies: combining local with multi-regional input–output tables

In a small, open and resource-poor economy, import and export dependency have an ever-growing impact on local policy decisions, which makes local (environmental) policy-makers increasingly depend on global data. This increases the interest in models that link local production and consumption data to global production, trade and environmental data. The recent increase in availability of global environmentally extended multi-regional input-output tables (EE-MRIO tables) provides an opportunity to link them with existing local environmentally extended input-output tables (EE-RIO tables). These combined tables make it possible (1) to analyse the links between local and global production and consumption and (2) to study global value chains, material use and environmental impacts simultaneously. However, estimations using input-output (I–O) analyses contain errors due to imperfect databases. In this article the magnitude of specification, aggregation and time errors are estimated and compared. The results show the need to combine local datasets with multi-regional ones and show that highest detailed (country and sector levels) as well as time series of I–O tables are the way forward for using I–O analyses in local policy-making. The paper provides guidance on trading off investments in model adoption and/or extension and the reliability of estimation results.     

A Simple Multi-Regional Input–Output Account for Waste Analysis

The present paper provides a simple multiregional input–output model for waste analysis with which to estimate intraregional and interregional effects of industrial wastes embodied in regional final consumptions. The empirical analyses using 1995 nine-regions input–output tables reveals the regional properties of the interregional linkage effects. The Kanto and Kinki regions remarkably control the industrial waste emissions and waste landfills within their own regions by importing waste-intensive intermediate goods and services from the other regions. The Chugoku and Shikoku regions greatly contributed to the production of the waste-intensive goods and services for the other regions, considering the waste emissions and waste landfills relative to the commodity production levels. We also find that the household consumption behaviour in other regions indirectly plays a more important role in waste emissions than the municipal waste disposal behaviour in the region in question at least in 1995.     

Regionalizing National Commodity-by-Industry Accounts

Exended input–output (IO) models are increasingly prominent in regional economic analysis. Social accounting matrices and associated multiplier decompositions, IO econometric model hybrids and computable general equilibrium models are finding greater acceptance in contexts in which simple IO models once dominated. Although the extended regional models build primarily on the foundation of regional, interindustry accounting frameworks, the data from which these regional accounts are drawn are most commonly in the form of a national commodity-by-industry account. Despite this longstanding fact, the IO table adaptation literature has focused almost solely on methods of adapting national interindustry accounts to regional economies. This paper presents a method designed specifically to regionalize commodity-by-industry accounts, in the context of the US reporting system. The focus on commodity-by-industry data demands a confrontation with several important issues that otherwise might go unattended. Using a particular system and its accompanying classification scheme ensures a comprehensive and consistent regionalization method.     

COMPLEMENTARITY IN INPUT–OUTPUT ANALYSIS AND STOCHASTICS

The complementarity between the quantity and value systems of input–output analysis is shown to be the basis of the complementarity problem approach to computable general equilibrium. The numerical superiority of the latter to the linear programming approach facilitates stochastic analysis of input–output scenarios. For the example where Kyoto targets are underachieved to uncertain degrees, confidence intervals are derived for the associated consumption reductions.     

Emissions burden shifting in global value chains – winners and losers under multi-regional versus bilateral accounting

ABSTRACT

International trade leads to emissions burden shifting and threatens mitigation targets. Multiregional input–output (MRIO) and bilateral trade input–output (BTIO) models are widely used to analyse emissions embodied in trade and global value chains. Especially, the last one is used in analysing border tax adjustment (BTA) on the carbon content of imports. The model choice is not trivial. The analysis shows BTIO's inability to capture the consumer-principle throughout the production chain and its inadequacy as an option for consumption-based accounting, because it allocates emissions to the first importing country and to the sector of production, instead to the consumer (both country and region). Regarding the BTA assessment, BTIO tax domestic carbon content of direct imports, but not indirect imported carbon content. MRIO does provide incentives for mitigation in third countries. The differences in allocation of emissions and taxes’ burden of both models have different consequences for developed and undeveloped regions.