Input-Output Analysis (or short "IOA") is a method that tracks all financial transactions between industrial sectors and consumers within an economy. By adding environmental information, such as greenhouse gas emissions, to each sector it becomes possible to assign an environmental burden (a "footprint") to these financial transactions. Similar to following the flow of money, or costs, from production to consumption, an environmentally extended input-output model allows following the flow of environmental footprints along supply and production chains. As each production step adds an environmental burden, the result is a life-cycle inventory of impacts of production and consumption, e.g. carbon, water or ecological footprints of companies, organisations, sectors, individuals, regions or countries.
Economic input-output analysis was first developed by Wassily Leontief in the 1930s to aid manufacturing planning and has been used ever since in countless applications addressing questions on economy, labour, social issues, trade, energy, ecology, resource use, industrial ecology and environmental science. The compilation of input-output tables of national and regional economies is a routine practice governed by a UN standard. Thousands of analysts and researchers use analytical input-output techniques. Environmental applications of IOA began in the early 1970s when it was widely used for energy analysis. In 1973, Leontief received the Nobel Prize for Economic Science for the development of the input-output methodology and its wide application.
Due to its economy-wide approach, environmental IOA allows for the allocation of all impacts along the production and supply chain to the consuming sector or groups of final products. This has the advantage of being complete and avoiding boundary issues commonly associated with process analysis. Results from IOA are fully consistent with standard accounting, and a direct and valid comparison of environmental performance (e.g. carbon footprint intensity) is possible between companies/organisations, sectors or nations.
Environmental IOA is also a very efficient technique that saves time and money as it requires a minimum of data collection; the required financial information is in most cases readily available.
Environmental input-output models work with data that are aggregated at the level of economic sectors rather than individual products. Input-output tables are the sum of countless individual activities (financial transactions) and for practical reasons this wealth of data is grouped in a limited number of industries (e.g. 112 in Australia). For this reason, the results of an IOA show the impact of an industry or product group (e.g. 'dairy products') but not of a specific product type (e.g. 'cheese') or even individual products (e.g. 'Cheddar'). To achieve this level of detail, IOA needs to be combined with a bottom-up analysis of specific processes.
Every country in the world holds statistics about the size and structure of its economy, for this is the basis of calculating the Gross Domestic Product (GDP) as an indicator of economic performance. Government’s statistical offices in most countries compile these data in a standard format specified by the UN. These annual economic accounts are regularly published and form the basis of input-output tables. Some data manipulation by the input-output analyst might be necessary because tables in basic prices are necessary for environmental input-output models, but such tables might not be published every year by the statistical agency.
Environmental extensions are added to the input-output framework in the form of inputs or 'factors' of production by industrial sector, e.g. emissions of greenhouse gases or air pollutants, water use, land use or the extraction of raw materials. Much of this is covered by environmental accounts published annually by statistical offices; again often adhering to a UN standard. This means that all environmental variables are a direct satellite account to the national accounts and to economic activities of industries and that the same system boundaries, classifications and definitions are used. In some cases it might be necessary to obtain additional statistics in order to break down aggregated data to the desired level of sectoral detail.
Input-output tables provide a complete picture of the value of products and services sold and bought in an economy for a given year, illustrating the interdependencies of industries and the relationship between producers and consumers. In its general form an input-output table shows the purchases made by each sector of the economy in order to produce their own output, including purchases of imported commodities (inputs) as well as the consumption of products and services by other sectors and final consumers, such as private households (outputs). The basic assumption is that what is produced by one industry must be consumed, either by other industries or by individual consumers. Input-output tables are a central element of economic National Accounts which are produced by national statistical offices and are used to generate annual accounts of the Gross Domestic Product (GDP).
Yes. The value of imports is part of national economic accounting and therefore part of input-output tables. The degree of detail, however, can vary and it depends on the data available and the type of input-output model constructed by the analyst as to how many countries or world regions can be distinguished in the calculations. Large multi-region input-output models include data for more than 100 economies and assign environmental impacts associated with products imported from these countries depending on the foreign production technology and efficiency.
Not more complicated than the multiplication of numbers. For the construction of an input-output model, knowledge of linear and matrix algebra as well as national economic and environmental accounting is required; computational skills are useful. Once the model is completed, conversion factors (called 'input-output multipliers') for total impacts per financial unit can be extracted used further in simple spreadsheet calculations. Software tools using environmental IOA are available that perform more sophisticated analyses with a minimum of data input by the analyst (see e.g. www.bottomline3.co.uk).
The ideal data basis for an input-output model are either detailed supply and use tables or symmetric input-output tables in basic prices, all of which are regularly compiled by statistical offices. Not all of the information is published, however, and it therefore depends on the quality and date of available information as well as capacity of the modeller to update and handle missing or conflicting data, how well the model reflects the real-world economy.
The uncertainty of input-output data is routinely and well documented by the statistical authority compiling the national accounts; the standard errors of input-output data are published. A similar process of uncertainty calculation and error publication has been established by the process of compiling national greenhouse gas inventories under the UN Framework Convention on Climate Change – the data set underpinning the national environmental accounts of greenhouse gases. Recent research has shown that national carbon footprint estimates using a multi-region input-output model have a standard error of about ±5%.
Input-output analysis is generally correct and accurate but not particularly precise. Because of its economy-wide and consistent character, IOA correctly and accurately apportions indirect impacts from production to industry sectors, product groups or individual companies. If added up, results for all companies within an economy, for example, would add up to the total impact of this economy. Different individual products coming from the same industry sector, however, cannot be distinguished sufficiently with IOA alone, as the analysis refers to the whole sector comprised of several sub-sectors or product groups.
Process analysis, on the other hand, can be precise and specific to one particular product as it aims to calculate life-cycle impacts bottom-up by using original, primary data collected from individual processes. However, the necessity of establishing a system boundary for the analysis means that important higher-order processes might be excluded and the result, even if it is precise, might not be accurate (not correct).
To increase both accuracy AND precision of life-cycle assessments, input-output analysis has been combined with process analysis in various forms of hybrid analysis which are state of the art and now are routinely employed. It depends on the application what level of accuracy or precision is required.
It is a common perception that physical data are more accurate than financial data. After all, the volume or mass of a commodity (e.g. one kilogram of steel) is a more accurate and stable description of a physical quantity than the value (e.g. $1000 of steel). This does not mean, however, that an environmental (life-cycle) analysis based on physical data is always and necessarily more accurate than one based on financial data. Undoubtedly, the most accurate way of attributing environmental impacts to a commodity is a primary analysis of all processes necessary for its production. In practice, it would be too time-consuming to analyse all but a few main processes, and it is unavoidable to use secondary data for the bulk of processes perceived to be lesser important. These secondary data, however, have a higher level of uncertainty, no matter whether they are based on physical or financial information. The decision for choosing secondary data derived from either physical or financial units should therefore be based on the quality and suitability for the specific purpose.
Price fluctuations and distortions are a concern for the input-output analyst and need to be taken into account. Usually, financial information for one whole year is used in the analysis, levelling out monthly or seasonal variation. It is good practice in IOA to remove the trade and tax margins to set up and operate the model in basic prices, rather than purchasers' prices. This eliminates another source of price distortion and aligns the financial flows in the model closer with the actual flows of physical quantities.
The difference in prices paid by various consumers of commodities is caused by differences in distribution costs (e.g. wholesale and retail trade margins) and taxation. The basic (raw material) price is likely to be very similar for consumers of any kind. It is therefore important that input-output models are constructed in basic prices and that trade and tax margins are removed from the commodity costs, depending on which sector or other consumer buys the commodity. This is good practice in input-output modelling and ensures accurate results, based on industry coefficients.
In the example above, the type and the source of the concrete used will be much more important in determining its environmental impact than its (basic) price. If an input-output screening analysis shows the use of concrete to be a major contributor to the overall environmental footprint of the sector/entity under investigation, then a hybrid analysis using primary data from the concrete manufacturer is likely to be the most suitable method in this case.
The best method for life-cycle assessment of products or processes is a combination (hybrid) of both process analysis and input-output analysis! Process analysis offers a high level of detail and specificity and in particular the collection of primary data relevant to the study system can reduce the uncertainty of the analysis. It requires, however, the truncation of system boundaries which can lead to a serious underestimation of the total environmental burden and to practical difficulties when trying to compare results from one study with another. In contrast, IOA offers system completeness but suffers from a high level of aggregation in industry and commodity classifications.
LCA researchers have therefore developed hybrid approaches that combine the strengths of process and input-output analysis. Hybrid LCA models and software tools are emerging and practitioners increasingly recognise the value of this combination of methods.
Hybrid LCA generally aims to combine the specificity of process analysis with the comprehensiveness of input-output analysis and has been applied to energy analysis since the 1970s. There are several possibilities for this combination, but in all cases specific data on individual processes – most preferably primary data – are connected with data from an input-output model. In integrated hybrid LCA, the monetary input-output table is augmented with a (physical) process matrix based on (primary) technical data. In the novel path exchange method, an analytical technique called structural path analysis is performed with a pure input-output model first, quantifying the environmental impacts associated with upstream production processes, and subsequently the most relevant paths are replaced with corresponding primary process data to improve the accuracy and precision of the calculation. The path exchange method is a particularly efficient approach to hybrid LCA.
IOA can identify the main contributors to embedded supply chain impacts for a bundle of goods and services bought by a company. This identification of supply chain hotspots is done by an analytic procedure called Structural Path Analysis (SPA). The results of a SPA allow to address specifically those suppliers that add most to the embedded impact, e.g. the carbon footprint. Therefore, 'low hanging fruits' in the supply chain (scope 3) footprint can easily be identified and prioritised. Having this information, the choice of abatement options is not restricted to the direct use of energy or resource, but it opens up the chance to reduce total impacts emissions effectively by addressing the supply chain. Depending on the type of input-output model, this is also valid for international supply chains.
Using hybrid LCA based on IOA, embedded environmental impacts of specific procurement options can be evaluated and benchmarked against similar products. This helps to identify opportunities for re-structuring and greening purchasing for companies or industry sectors.
Supply-chain issues are important for companies and embedded environmental and social impacts are becoming increasingly topical for Corporate Sustainability Reporting. Companies are increasingly reporting across the value chain. This represents a challenge in terms of reporting on the upstream (supplier related) issues linked to human rights, environmental and societal impacts, and also of coping with the wider downstream (consumer related) impact of products and services. Using IOA to identify those input paths that carry the largest impacts can help with organisational planning and priority setting for informed action towards financial, social and environmental sustainability. In particular, it shows organisations' alternatives for effective procurement policy changes, which may be applied instead of perhaps costly on-site measures.
Ethical investment portfolios try to invest selectively in companies that support or set environmental and social standards. IOA quantifies the indirect impacts associated with the operations of a company or industry sectors. These hidden (embedded) impacts are seen as a financial risk, either because the reputation of the portfolio might be at risk or under anticipated regulations. Pro-active reporting of all direct and indirect impacts on sustainability demonstrates engagement and willingness for change and helps to increase credibility with (ethical) investors.