Towards the Circular Economy

Towards the Circular Economy



Circular Economy in reuse of

  • Metals
  • Plastics
  • Paper and Paper Board
  • Glass
  • Rubber
  • Wood/Timber/Construction Composites
  • Textiles
  • Organic Waste/Food/Agricultural/Biological




Key points

  • Keeping materials longer in the economy through reuse, re-purposing or recycling could reduce 33 per cent of the carbon dioxide emissions embedded in products.
  • Circularity requires a significant bridge between trade in goods and trade in services.
  • Increased recycling could reduce demand for primary resources, leading to both risks and opportunities in developing countries dependent on the extraction of natural resources.



Linear production is a familiar cycle. Resources are extracted and transformed into goods and services, sold and used, after which they are scrapped. This model has underpinned the expansion of the global economy since the industrial revolution.

It has linked material prosperity to the extraction of resources, yet has often overlooked the undue pressures placed on the environment and has rarely considered the cost of handling, scrapping and disposing of used materials, some of which are hazardous to human health. As the global population increases, incomes rise and nations strive to eradicate poverty, demand for goods and services will necessarily grow. The aim of achieving Sustainable Development Goal 12 on responsible consumption and production requires changing the linear production model. The concept of a circular economy and practice therefore merits close attention, as it can open new opportunities for trade and job creation, contribute to climate change mitigation and help reduce the costs of cleaning and scrapping in both developed and developing countries.

A circular economy entails markets that give incentives to reusing products, rather than scrapping them and then extracting new resources. In such an economy, all forms of waste, such as clothes, scrap metal and obsolete electronics, are returned to the economy or used more efficiently. This can provide a way to not only protect the environment, but use natural resources more wisely, develop new sectors, create jobs and develop new capabilities.

Each year, 1.3 billion tons of garbage are produced by 3 billion urban residents.1 This is the end point of a linear economic flow that starts with manufacturing, which uses 54 per cent of the world’s delivered energy, especially in energy-intensive industries such as petrochemicals, cement, metals and paper.2 Each year, 322 million tons of plastic, 240 million tons of paper and 59 million tons of aluminium are produced in the world, much of which goes to export markets and is not recycled.3

A rusty container or an obsolete mobile telephone are only two examples of the many products that end up being discarded, along with their transistors, metal structures and complex plastics. Each component requires a great deal of energy, time, land and capital to be produced and, even as the products become obsolete, their components often do not. The potential value of metals and plastics currently lost in electronic waste may be €55 billion annually.4

As the supply of recycled, reused and re-manufactured products increases, such products are maintained for longer in the economy, avoiding their loss to landfills. Food losses could be halved through food- sharing and discounting models that reduce fresh food waste. Access to efficient home appliances could be increased through leasing instead of sales. Organic waste could be recovered or transformed into high-value protein through the production of insect larvae.

Benefits such as these could be gained by both developed and developing countries; the potential economic gains are estimated at over $1 trillion per year in material cost savings.5 Several economies are already exploring circular strategies, including Brazil, China, India, Kenya, the Lao People’s Democratic Republic, Morocco, South Africa, Turkey, Uruguay, VietNam and the European Union.6 India and the European Union stand to gain savings of $624 billion and €320 billion, respectively.7

The effects of increased recycling on global value chains are an important area for research. For example, a circular model for metals implies an increase in the re-purposing, reuse and recycling of such materials. This can transform end points of the value chain, such as junkyards and dumping sites for metals, into new reprocessing hubs that supply metals to markets. This growth trend in recycling markets may be desirable from an environmental perspective, yet could reduce demand for primary resources, requiring an adjustment in employment, logistics and scal structures in countries dependent on the extraction of natural resources.8 At the same time, growth in the recycling, re-purposing and reuse of materials could support the emergence of regional reprocessing and recycling hubs and open new opportunities for the commodities and manufacturing sectors. Greater circularity could reduce the depreciation of physical capital in the economy, increasing overall wealth in societies. The specific benefits that developing countries could obtain by adopting formal circular economy strategies is a new subject for research, and further studies and data are needed.


Circularity can change trade patterns and improve the utilization of idle capacity

Circular models could help countries grow with resources already available in their territories. This may imply a reduction in international trade, yet the 140 million people joining the middle class each year guarantee growth in overall trade.9 Such growth may occur not in goods but in services such as access-over-ownership models.10 In addition, increased circularity can change production patterns, improving asset utilization rates and producing value chains based on recycling and re-manufacturing centres close to where products are used. This could lead to fewer transport-related losses, quicker turnarounds between orders and deliveries, lower levels of carbon dioxide emissions and the creation of jobs that cannot be offshored.

Some countries have trade surpluses in physical goods and others in immaterial services. Trade therefore results in a net transfer of materials from one region to another as seen, for example, in trade patterns between China and the United States. The United States imports many goods from China but does not export nearly as many finished goods in return. However, nearly 3,700 containers of recyclables per day are exported to China; in 2016, such exports amounted to 16.2 million tons of scrap metal, paper and plastics worth $5.2 billion.11


Key Terms:

  • Circular Economy
  • Cradle to Cradle
  • Closed Supply Chains
  • Industrial Ecology
  • Reverse Ecology
  • Blue Economy
  • Regenerative Design
  • Performance Economy
  • Natural Capitalism
  • Bio-mimicry
  • Doughnut Economics



From Input to the European Commission from European EPAs about monitoring progress of the transition towards a circular economy in the European Union




Circular Economy System Diagram




From Towards the Circular Economy: Accelerating the scale-up across global supply chains



Comprehensive Concept of Circular Economy


From Input to the European Commission from European EPAs about monitoring progress of the transition towards a circular economy in the European Union


From Taking the Circular Economy to the City Level


Please see my related post:

Resource Flows: Material Flow Accounting (MFA), Life Cycle Analysis (LCA), Input Output Networks and other methods

Stock Flow Consistent Input Output Models (SFCIO)

Stock Flow Consistent Models for Ecological Economics

Jay W. Forrester and System Dynamics


Key Sources of Research:

Ellen MacArthur Foundation






Circular economy booklet

 Ellen MacArthur Foundation







Economic and business rationale for an accelerated transition

Ellen MacArthur Foundation


Volume 1




Opportunities for the consumer goods sector


Ellen MacArthur Foundation


Volume 2





Accelerating the scale-up across global supply chains

Volume 3


Ellen MacArthur Foundation






Towards the Circular Economy: Accelerating the scale-up across global supply chains

World Economic Forum

Prepared in collaboration with the Ellen MacArthur Foundation and McKinsey & Company

January 2014


rethinking value chains to boost resource productivity




Circular Economy in Cities

Evolving the model for a sustainable urban future


Towards a circular economy: A zero waste programme for Europe

DG Environment

Minsk, 8 October 2014





Transitioning IKEA Towards a Circular Economy: A Backcasting Approach

Claudia Szerakowski

Master’s Thesis in Industrial Ecology





Circular Economy Industry Roundtable:




Sustainable Supply Chain Management and the transition towards a Circular Economy: Evidence and some Applications.

Genovese, Andrea and Acquaye, Adolf and Figueroa, Alejandro and Koh, S.C. Lenny






Are you ready for the circular economy? The necessity of an integrated approach.





Barriers & Drivers towards a Circular Economy

Literature Review A-140315-R-Final

March 2015


The Circular Economy Powered by Cradle to Cradle®




 Towards a Circular Economy

Venkatachalam Anbumozhi Jootae Kim




Circular Economy

European Commission






Business Sweden






Oliver Wyman




Transition towards a circular economy: The case of the Metropole region Amsterdam

Jacqueline Cramer

Ambassador Circular Economy





The Circular Economy – a new sustainability paradigm?

Geissdoerfer, Martin1,2†; Savaget, Paulo1; Bocken, Nancy M.P.1,2; Hultink, Erik Jan2






SS8: Circular economy and decoupling




Input to the European Commission from European EPAs about monitoring progress of the transition towards a circular economy in the European Union


May 2017




The European Economy: From a Linear to a Circular Economy

Florin Bonciu










The opportunities of a circular economy for Finland

October, 2015




Circular economy

A review of definitions, processes and impacts














Report on State-of-the-Art Research in the Area of the Circular Economy


Sylvie Geisendorf

Felicitas Pietrulla ESCP Europe Campus Berlin




A Wider Circle? The Circular Economy in Developing Countries





A safe and just space for humanity


Kate Raworth




Doughnut Economics: seven ways to think like a 21st century economist

Kate Raworth


Taking the Circular Economy to the City Level






Mapping the Political Economy of Design

Dr. Joanna Boehnert

Research Fellow
Centre for the Evaluation of Complexity Across the Nexus University of Surrey




A circular Economy





Rethinking Sustainability in Light of the EU’s New Circular Economy Policy

JULY 03, 2018





Resource Efficiency & Circular Economy Project






by Andrew McCarthy, Rob Dellink, and Ruben Bibas







A European Strategy for Plastics in a Circular Economy





The New Plastics Economy

Rethinking the future of plastics






MARCH 2017








May 2018





The circular economy: Moving from theory to practice

McKinsey Center for Business and Environment Special edition,

October 2016





Renewable materials in the Circular Economy

April 2018




A Review of the Circular Economy and its Implementation

Almas Heshmati

Sogang University and IZA




Rethinking finance in Rethinking nance in a circular economy

Financial implications of circular business models







The Circular Economy in International Trade







Circular economy:
a commentary from the perspectives of the natural and social sciences





Circular by design

Products in the circular economy






Ellen MacArthur Foundation


Resource Flows: Material Flow Accounting (MFA), Life Cycle Analysis (LCA), Input Output Networks and other methods

Resource Flows: Material Flow Accounting (MFA), Life Cycle Analysis (LCA), Input Output Networks and other methods




From Materials Flow and Sustainability



Key Terms:

  • MFA (Material Flow Analysis)
  • MFCA (Material Flow Cost Accounting)
  • LCA (Life Cycle Analysis)
  • SFA (Substance Flow Analysis)
  • MF WIO (Material Flow Waste Input Output)
  • IO LCA (Input Output Life Cycle Analysis)
  • KLEM (Capital, Labor, Energy, Materials)
  • PIOT ( Physical Input Output Tables)
  • MIOT (Monetary Input Output Tables)
  • IO MFN (Input Output Material Flow Network)
  • Social Ecology
  • Industrial Ecology
  • Urban Metabolism
  • Industrial Symbiosis
  • Industrial Metabolism
  • M-P Chains (Material Product Chains)
  • Global Value Chains
  • National Footprint Accounts
  • Inter Industry Analysis
  • Input Output Economics
  • End to End Supply Chains
  • Supply and Use Tables
  • Material Balance
  • Mass Balance
  • Biophysical Economics
  • Ecological Economics
  • Environmentally Extended Input Output Analysis (EE-IOA)
  • Stocks and Flows
  • MaTrace
  • Global MaTrace


Software for Data Analysis and Visualization:


This article lists several other software packages for MFA/SFA



Material Flow Analysis

From Practical Handbook of MATERIAL FLOW ANALYSIS

Material flow analysis (MFA) is a systematic assessment of the flows and stocks of materials within a system defined in space and time. It connects the sources, the pathways, and the intermediate and final sinks of a material. Because of the law of the conservation of matter, the results of an MFA can be controlled by a simple material balance comparing all inputs, stocks, and outputs of a process. It is this distinct characteristic of MFA that makes the method attractive as a decision-support tool in resource management, waste management, and environmental management.

An MFA delivers a complete and consistent set of information about all flows and stocks of a particular material within a system. Through balancing inputs and outputs, the flows of wastes and environmental loadings become visible, and their sources can be identified. The depletion or accumulation of material stocks is identified early enough either to take countermeasures or to promote further buildup and future utilization. Moreover, minor changes that are too small to be measured in short time scales but that could slowly lead to long-term damage also become evident.

Anthropogenic systems consist of more than material flows and stocks (Figure 1.1). Energy, space, information, and socioeconomic issues must also be included if the anthroposphere is to be managed in a responsible way. MFA can be performed without considering these aspects, but in most cases, these other factors are needed to interpret and make use of the MFA results. Thus, MFA is frequently coupled with the analysis of energy, economy, urban planning, and the like.

In the 20th century, MFA concepts have emerged in various fields of study at different times. Before the term MFA had been invented, and before its comprehensive methodology had been developed, many researchers used the law of conservation of matter to balance processes. In process and chemical engineering, it was common practice to analyze and balance inputs and outputs of chemical reactions. In the economics field, Leontief introduced input–output tables in the 1930s, thus laying the base for widespread application of input–output methods to solve economic problems. The first studies in the fields of resource conservation and environmental management appeared in the 1970s. The two original areas of application were (1) the metabolism of cities and (2) the analysis of pollutant pathways in regions such as watersheds or urban areas. In the following decades, MFA became a widespread tool in many fields, including process control, waste and wastewater treatment, agricultural nutrient management, water-quality management, resource conservation and recovery, product design, life cycle assessment (LCA), and others.


Substance Flow Analysis

From Feasibility assessment of using the substance flow analysis methodology for chemicals information at macro level

SFA is used for tracing the flow of a selected chemical (or group of substances) through a defined system. SFA is a specific type of MFA tool, dealing only with the analysis of flows of chemicals of special interest (Udo de Haes et al., 1997). SFA can be defined as a detailed level application of the basic MFA concept tracing the flow of selected chemical substances or compounds — e.g. heavy metals (mercury (Hg), lead (Pb), etc.), nitrogen (N), phosphorous (P), persistent organic substances, such as PCBs, etc. — through society.

An SFA identifies these entry points and quantifies how much of and where the selected substance is released. Policy measures may address these entry points, e.g. by end‐of‐pipe technologies. Its general aim is to identify the most effective intervention points for policies of pollution prevention. According to Femia and Moll (2005), SFA aims to answer the following questions:

• Where and how much of substance X flows through a given system?

• How much of substance X flows to wastes?
• Where do flows of substance X end up?
• How much of substance X is stored in durable goods?
• Where could substance X be more efficiently utilised in technical processes?
• What are the options for substituting the harmful substance?
• Where do substances end up once they are released into the natural environment?

When an SFA is to be carried out, it involves the identification and collection of data on the one hand, and modelling on the other. According to van der Voet et al. (OECD, 2000), there are three possible ways to ‘model’ the system:

Accounting (or bookkeeping) The input for such a system is the data that can be obtained from trade and production statistics. If necessary, further detailed data can be recovered on the contents of the specific substances in those recorded goods and materials. Emissions and environmental fluxes or concentration monitoring can be used for assessing the environmental flows. The accounting overview may also serve as an identification system for missing or inaccurate data.

Missing amounts can be estimated by applying the mass balance principle. In this way, inflows and outflows are balanced for every node, as well as for the system as a whole, unless accumulation within the system can be proven. This technique is most commonly used in material flow studies, and can be viewed as a form of descriptive statistics. There are, however, some examples of case studies that specifically address societal stocks, and use these as indicator for possible environmental problems in the future (OECD, 2000).

Static modelling is the process whereby the network of flow nodes is translated into a mathematical ‘language’, i.e. a set of linear equations, describing the flows and accumulations as inter‐dependent. Emission factors and distribution factors over the various outputs for the economic processes and partition coefficients for the environmental compartments can be used as variables in the equations. A limited amount of substance flow accounting data is also required for a solution of the linear equations. However, the modelling outcome is determined largely by the substance distribution patterns.

Static modelling can be extended by including a so‐called origin analysis in which the origins of one specific problematic flow can be traced on several levels. Three levels may be distinguished:

• direct causes derived directly from the nodes balance (e.g one of the direct causes of cadmium (Cd) load in soil is atmospheric deposition);

• economic sectors (or environmental policy target groups) directly responsible for the problem. This is identified by following the path back from node to node to the point of emission (e.g. waste incineration is one of the economic sectors responsible for the cadmium load in soil);

• ultimate origins found by following the path back to the system boundaries (e.g. the extraction, transport, processing and trade of zinc (Zn) ore is one of the ultimate origins of the cadmium load in soil).

Furthermore, the effectiveness of abatement measures can be assessed with static modelling by recording timelines on substances (OECD, 2000).

Dynamic modelling is different to the static SFA model, as it includes substance stocks accumulated in society as well as in various materials and products in households and across the built‐up environments.

For SFA, stocks play an important role in the prediction of future emissions and waste flows of products with a long life span. For example, in the case of societal stocks of PVC, policy makers need to be supplied with information about future PVC outflows. Today’s stocks become tomorrow’s emissions and waste flows. Studies have been carried out on the analysis of accumulated stocks of metals and other persistent toxics in the societal system. Such build‐ups can serve as an ‘early warning’ signal for future emissions and their potential effects, as one day these stocks may become obsolete and recognisably dangerous, e.g. as in the case of asbestos, CFCs, PCBs and mercury in chlor‐alkali cells. As the stocks are discarded, they end up as waste, emissions, factors of risks to environment and population. In some cases, this delay between inflow and outflow can be very long indeed.

Stocks of products no longer in use, but not yet discarded, are also important. These stocks could include: old radios, computers and/or other electronic equipment stored in basements or attics, out‐of‐use pipes still in the ground, obsolete stocks of chemicals no longer produced but still stored, such as lead paints and pesticides. These ‘hibernating stocks’ are likely to be very large, according to OECD estimates (2000). Estimating future emissions is a crucial issue if environmental policy makers are to anticipate problems and take timely, effective action. In order to do this, stocks cannot be ignored. Therefore, when using MFA or SFA models for forecasting, stocks should play a vital part. Flows and stocks interact with each other. Stocks grow when the inflows exceed the outflows of a (sub)‐system and certain outflows of a (sub)‐system are disproportional to the stocks.

For this dynamic model, additional information is needed for the time dimension of the variables, e.g. the life span of applications in the economy; the half life of compounds; the retention time in environmental compartments and so forth. Calculations can be made not only on the ‘intrinsic’ effectiveness of packages of measures, but also on their anticipated effects in a specific year in the future. They can also be made on the time
it takes for such measures to become effective. A dynamic model is therefore most suitable for scenario analysis, provided that the required data are available or can be estimated with adequate accuracy (OECD, 2000).


Life Cycle Analysis (LCA)


What is Life Cycle Assessment (LCA)?

As environmental awareness increases, industries and businesses are assessing how their activities affect the environment. Society has become concerned about the issues of natural resource depletion and environmental degradation. Many businesses have responded to this awareness by providing “greener” products and using “greener” processes. The environmental performance of products and processes has become a key issue, which is why some companies are investigating ways to minimize their effects on the environment. Many companies have found it advantageous to explore ways of moving beyond compliance using pollution prevention strategies and environmental management systems to improve their environmental performance. One such tool is LCA. This concept considers the entire life cycle of a product (Curran 1996).

Life cycle assessment is a “cradle-to-grave” approach for assessing industrial systems. “Cradle-to-grave” begins with the gathering of raw materials from the earth to create the product and ends at the point when all materials are returned to the earth. LCA evaluates all stages of a product’s life from the perspective that they are interdependent, meaning that one operation leads to the next. LCA enables the estimation of the cumulative environmental impacts resulting from all stages in the product life cycle, often including impacts not considered in more traditional analyses (e.g., raw material extraction, material transportation, ultimate product disposal, etc.). By including the impacts throughout the product life cycle, LCA provides a comprehensive view of the environmental aspects of the product or process and a more accurate picture of the true environmental trade-offs in product and process selection.

The term “life cycle” refers to the major activities in the course of the product’s life-span from its manufacture, use, and maintenance, to its final disposal, including the raw material acquisition required to manufacture the product. Exhibit 1-1 illustrates the possible life cycle stages that can be considered in an LCA and the typical inputs/outputs measured.


Methods of LCA

  • Process LCA
  • Economic Input Output LCA
  • Hybrid Approach



From Life cycle analysis (LCA) and sustainability assessment





Material Input Output Network Analysis

  • PIOT (Physical Input Output Tables)
  • MIOT (Monetary Input Output Tables)
  • WIOT (Waste Input Output Tables
  • MRIO (Multi Regional Input Output)
  • SUT (Supply and Use Tables)


From Industrial ecology and input-output economics: An introduction

Although it was the pioneering contributions by Duchin (1990, 1992) that explicitly made the link between input–output economics and industrial ecology, developments in input– output economics had previously touched upon the core concept of industrial ecology.

Wassily Leontief himself incorporated key ideas of industrial ecology into an input– output framework. Leontief (1970) and Leontief and Ford (1972) proposed a model where the generation and the abatement of pollution are explicitly dealt with within an extended IO framework. This model, which combines both physical and monetary units in a single coefficient matrix, shows how pollutants generated by industries are treated by so-called ‘pollution abatement sectors.’ Although the model has been a subject of longstanding methodological discussions (Flick, 1974; Leontief, 1974; Lee, 1982), its structure captures the essence of industrial ecology concerns: abatement of environmental problems by exploiting inter-industry interactions. As a general framework, we believe that the model by Leontief (1970) and Leontief and Ford (1972) deserves credit as an archetype of the various models that have become widely referred to in the field of industrial ecology during the last decade, including mixed-unit IO, waste IO and hybrid Life Cycle Assessment (LCA) models (Duchin, 1990; Konijn et al., 1997; Joshi, 1999; Nakamura and Kondo, 2002; Kagawa et al., 2004; Suh, 2004b). Notably, Duchin (1990) deals with the conversion of wastes to useful products, which is precisely the aim of industrial ecology, and subsequently, as part of a study funded by the first AT&T industrial ecology fellowship program, with the recovery of plastic wastes in particular (Duchin and Lange, 1998). Duchin (1992) clarifies the quantity-price relationships in an input–output model (a theme to which she has repeatedly returned) and draws its implications for industrial ecology, which has traditionally been concerned exclusively with physical quantities.

Duchin and Lange (1994) evaluated the feasibility of the recommendations of the Brundtland Report for achieving sustainable development. For that, they developed an input–output model of the global economy with multiple regions and analyzed the consequences of the Brundtland assumptions about economic development and technological change for future material use and waste generation. Despite substantial improvements in material efficiency and pollution reduction, they found that these could not offset the impact of population growth and the improved standards of living endorsed by the authors of the Brundtland Report.

Another pioneering study that greatly influenced current industrial ecology research was described by Ayres and Kneese (1969) and Kneese et al. (1970), who applied the massbalance principle to the basic input–output structure, enabling a quantitative analysis of resource use and material flows of an economic system. The contribution by Ayres and Kneese is considered the first attempt to describe the metabolic structure of an economy in terms of mass flows (see Ayres, 1989; Haberl, 2001).

Since the 1990s, new work in the areas of economy-wide research about material flows, sometimes based on Physical Input–Output Tables (PIOTs), has propelled this line of research forward in at least four distinct directions: (1) systems conceptualization (Duchin, 1992; Duchin, 2005a); (2) development of methodology (Konijn et al., 1997; Nakamura and Kondo, 2002; Hoekstra, 2003; Suh, 2004c; Giljum et al., 2004; Giljum and Hubacek, 2004; Dietzenbacher, 2005; Dietzenbacher et al., 2005; Weisz and Duchin, 2005); (3) compilation of data (Kratterl and Kratena, 1990; Kratena et al., 1992; Pedersen, 1999; Ariyoshi and Moriguchi, 2003; Bringezu et al., 2003; Stahmer et al., 2003); and (4) applications (Duchin, 1990; Duchin and Lange, 1994, 1998; Hubacek and Giljum, 2003; Kagawa et al., 2004). PIOTs generally use a single unit of mass to describe physical flows among industrial sectors of a national economy. In principle, such PIOTs are capable of satisfying both column-wise and row-wise mass balances, providing a basis for locating materials within a national economy.3 A notable variation in this tradition, although it had long been used in input–output economic studies starting with the work of Leontief, is the mixed-unit IO table. Konijn et al. (1997) analyzed a number of metal flows in the Netherlands using a mixed-unit IO table, and Hoekstra (2003) further improved both the accounting framework and data. Unlike the original PIOTs, mixed-unit IOTs do not assure the existence of column-wise mass-balance, but they make it possible to address more complex questions. Lennox et al. (2004) present the Australian Stocks and Flows Framework (ASFF), where a dynamic IO model is implemented on the basis of a hybrid input–output table. These studies constitute an important pillar of industrial ecology that is generally referred to as Material Flow Analysis (MFA).4

Although the emphasis in industrial ecology has arguably been more on the materials side, energy issues are without doubt also among its major concerns. In this regard, energy input–output analysis must be considered another important pillar for the conceptual basis of ‘industrial energy metabolism.’ The oil shock in the 1970s stimulated extensive research on the structure of energy use, and various studies quantifying the energy associated with individual products were carried out (Berry and Fels, 1973; Chapman, 1974). Wright (1974) utilized Input–Output Analysis (IOA) for energy analysis, which previously had been dominated by process-based analysis (see also Hannon, 1974; Bullard and Herendeen, 1975; Bullard et al., 1978). The two schools of energy analysis, namely process analysis and IO energy analysis, were merged by Bullard and Pillarti (1976) into hybrid energy analysis (see also van Engelenburg et al., 1994; Wilting,1996). Another notable contribution to the area of energy analysis was made by Cleveland et al. (1984), who present a comprehensive analysis, using the US input–output tables, quantifying the interconnection of energy and economic activities from a biophysical standpoint (see Cleveland, 1999; Haberl, 2001; Kagawa and Inamura, 2004). These studies shed light on how an economy is structured by means of energy flows and informs certain approaches to studying climate change (see for example Proops et al., 1993; Wier et al., 2001).

What generally escapes attention in both input–output economics and industrial ecology, despite its relevance for both, is the field of Ecological Network Analysis (ENA). Since Lotka (1925) and Lindeman (1942), material flows and energy flows have been among the central issues in ecology. It was Hannon (1973) who first introduced concepts from input–output economics to analyze the structure of energy utilization in an ecosystem. Using an input–output framework, the complex interactions between trophic levels or ecosystem compartments can be modeled, taking all direct and indirect relationships between components into account. Hannon’s approach was adopted, modified and re-introduced by various ecologists. Finn (1976, 1977), among others, developed a set of analytical measures to characterize the structure of an ecosystem using a rather extensive reformulation of the approach proposed by Hannon (1973). Another important development in the tradition of ENA is so-called environ analysis. Patten (1982) proposed the term ‘environ’ to refer to the relative interdependency between ecosystem components in terms of nutrient or energy flows. Results of environ analysis are generally presented as a comprehensive network flow diagram, which shows the relative magnitudes of material or energy flows between the ecosystem components through direct and indirect relationships (Levine, 1980; Patten, 1982). Ulanowicz and colleagues have broadened the scope of materials and energy flow analysis both conceptually and empirically (Szyrmer and Ulanowicz, 1987). Recently Bailey et al. (2004a, b) made use of the ENA tradition to analyze the flows of several metals through the US economy. Suh (2005) discusses the relationship between ENA and IOA and shows that Patten’s environ analysis is similar to Structural Path Analysis (SPA), and that the ENA framework tends to converge toward the Ghoshian framework rather than the Leontief framework although using a different formalism (Defourny and Thorbecke, 1984; Ghosh, 1958).



From Materials and energy flows in industry and ecosystem netwoks : life cycle assessment, input-output analysis, material flow analysis, ecological network flow analysis, and their combinations for industrial ecology




From Regional distribution and losses of end-of-life steel throughout
multiple product life cycles—Insights from the global multiregional
MaTrace model


From Feasibility assessment of using the substance flow analysis methodology for chemicals information at macro level




Sankey Diagram

From Hybrid Sankey diagrams: Visual analysis of multidimensional data for understanding resource use

Sankey diagrams are used to visualise flows of energy, materials or other resources in a variety of applications. Schmidt (2008a) reviewed the history and uses of these diagrams. Originally, they were used to show flows of energy, first in steam engines, more recently for modern systems such as power plants (e.g. Giuffrida et al., 2011) and also to give a big-picture view of global energy use (Cullen and Allwood, 2010). As well as energy, Sankey diagrams are widely used to show flows of resources (Schmidt, 2008a). Recent examples in this journal include global flows of tungsten (Leal-Ayala et al., 2015), biomass in Austria (Kalt, 2015), and the life-cycle of car components (Diener and Tillman, 2016). More widely, they have been used to show global production and use of steel and aluminium (Cullen et al., 2012; Cullen and Allwood, 2013), and flows of natural resources such as water (Curmi et al., 2013). In all of these cases, the essential features are: (1) the diagram represents physical flows, related to a given functional unit or period of time; and (2) the magnitude of flows is shown by the link1 widths, which are proportional to an extensive property of the flow such as mass or energy (Schmidt, 2008b). Creating these diagrams is supported by software tools such as e!Sankey (ifu Hamburg, 2017), and several Life Cycle Assessment (LCA) and Material Flow Analysis (MFA) packages include features to create Sankey diagrams.


From Hybrid Sankey diagrams: Visual analysis of multidimensional data for understanding resource use




Please see my related posts:

Wassily Leontief and Input Output Analysis in Economics

Shell Oil’s Scenarios: Strategic Foresight and Scenario Planning for the Future

Water | Food | Energy | Nexus: Mega Trends and Scenarios for the Future

Stock Flow Consistent Input Output Models (SFCIO)

Measuring Globalization: Global Multi Region Input Output Data Bases (G-MRIO)

Production and Distribution Planning : Strategic, Global, and Integrated

Intra Industry Trade and International Production and Distribution Networks

Trends in Intra Firm Trade of USA

Development of Global Trade and Production Accounts: UN SEIGA Initiative

Accounting For Global Carbon Emission Chains

Stock Flow Consistent Models for Ecological Economics

Jay W. Forrester and System Dynamics

Classical roots of Interdependence in Economics

Stock-Flow Consistent Modeling





Key Sources of Research:



Paris, 24 October 2000

An Innovative Accounting Framework for the Food-Energy-Water Nexus
Application of the MuSIASEM approach to three case studies

Creating your own online data visualizations: SankeyMatic, OMAT, CartoDB

Hybrid Sankey diagrams: Visual analysis of multidimensional data for understanding resource use


Visualization of energy, cash and material flows with a Sankey diagram

UPIOM: A New Tool of MFA and Its Application to the Flow of Iron and Steel Associated with Car Production

Material flow analysis


Economy-wide Material Flow Accounting. Introduction and Guide.

Version 1.0

Article · January 2015

Fridolin Krausmann, Helga Weisz, Nina Eisenmenger, Helmut Schütz, Willi Haas
and Anke Schaffartzik

Society’s Metabolism The Intellectual History of Materials Flow Analysis,

Part II, 1970-1998

Marina Fischer-Kowalski and Walter Huttler

Institute for Intenliscipiimny
Studies of Austrian Universities
University of Vienna
Vienna, Austria

“Society’s Metabolism. The Intellectual History of Material Flow Analysis,

Part I, 1860 – 1970″.

Fischer-Kowalski, M.


Journal of Industrial Ecology 2(1): 61-78

Analysis on energy–water nexus by Sankey diagram: the case of Beijing

Unified Materials Information System (UMIS): An Integrated Material Stocks and Flows Data Structure

First published: 07 February 2018

Material Flow Cost Accounting with Umberto®

Schmidt, A. Hache, B.; Herold, F.; Götze, U.

Study on Data for a Raw Material System Analysis: Roadmap and Test of the Fully Operational MSA for Raw Materials

Final Report

BIO by Deloitte


Prepared for the European Commission, DG GROW.

Integrated Analysis of Energy, Material and Time Flows in Manufacturing Systems

e! Sankey

Visualization of energy, cash and material flows with a Sankey diagram

The most popular software for creating Sankey diagrams. Visualize the cash, material & energy flow or value streams in your company or along the supply chain. Share these appealing diagrams in reports or presentations.


Oliver Cencic* and Helmut Rechberger
Institute for Water Quality Resources and Waste Management
Vienna University of Technology
Vienna A-1040, Austria

Recovery of Key Metals in the Electronics Industry in the
People’s Republic of China: An Opportunity in Circularity
(Initial Findings)

January 2018

Created as Part of the Platform for Accelerating the Circular Economy

Sankey diagram





Industrial ecology and input-output economics: An introduction

Sangwon Suh


A Handbook of Industrial Ecology

Robert Ayres

Leslie Ayres

Physical and Monetary Input-Output Analysis:
What Makes the Difference?

Helga Weisz
Klagenfurt University
Faye Duchin
Rensselaer Polytechnic Institute

Theory of materials and energy flow analysis in ecology and economics

Sangwon Suh


Conceptual Foundations and Applications of Physical Input-Output Tables

Stefan Giljum

Hubacek Klaus


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

Stefan Giljum

Hubacek Klaus


Industrial Ecology: A Critical Review

EXIOPOL – development and illustrative analyses of a detailed global
multiregional environmentally-extended supply and use table/input output

Article in Economic Systems Research · May 2013

Developing the Sectoral Environmental Database for Input- Output Analysis: Comprehensive Environmental Data Archive of the U.S.

Article in Economic Systems Research · December 2005

The material basis of the global economy

Worldwide patterns of natural resource extraction and their
implications for sustainable resource use policies

Arno Behrens,⁎, Stefan Giljum, Jan Kovanda, Samuel Niza

The Sankey Diagram in Energy and Material Flow Management

Part I: History

The Sankey Diagram in Energy and Material Flow Management

Part II: Methodology and Current Applications

First published: 28 April 2008

Material and Energy Flow Analysis

First published: 23 March 2010

8. Biophysical economics: from physiocracy to ecological economics and industrial

Cutler J Cleveland

Article · January 1999

The Use of Input-Output Analysis in REAP to allocate Ecological Footprints and Material Flows to Final Consumption Categories

Waste Input–Output Material Flow Analysis of Metals in the Japanese Economy

Shinichiro Nakamura1 and Kenichi Nakajima2

A multi-regional environmental input-output model to quantify embodied material flows

Stefan Giljum a, Christian Lutz b,Ariane Jungnitz

Material Flow Accounting and Analysis (MFA)

A Valuable Tool for Analyses of Society-Nature Interrelationships

Entry prepared for the Internet Encyclopedia of Ecological Economics

Friedrich Hinterberger *, Stefan Giljum, Mark Hammer

Sustainable Europe Research Institute (SERI)

Human Ecology: Industrial Ecology

Faye Duchin
Rensselaer Polytechnic Institute

Stephen H. Levine
Tufts University

Development of the Physical Input Monetary Output Model for Understanding Material Flows within Ecological -Economic Systems

XU Ming


Accounting for raw material equivalents of traded goods

A comparison of input-output approaches in physical, monetary, and mixed units

Material Flow Accounts and Policy. Data for Sweden 2004

by: Annica Carlsson, Anders Wadeskog, Viveka Palm, Fredrik Kanlén Environmental Accounts, Statistics Sweden,


Economy-wide Material Flow Accounts with Hidden Flows for Finland: 1945–2008

Jukka Hoffrén (ed.)

Analysing environmental impacts of the global, interlinked economy

Konstantin Stadler, Richard Wood

Industrial Ecology Programme, NTNU, Norway


An Input-Output Analysis

Using Material Flow Analysis for Sustainable Materials Management: Part of the Equation for Priority Setting

Frederick W. Allen

Priscilla A. Halloran

Angela H. Leith

M. Clare Lindsay

“Supply-Extension versus Use-Extension in Environmentally Extended Input-Output Modelling: Analyzing Physical Flows within the Austrian Economy”

Hanspeter Wieland*1, Nina Eisenmenger2, Dominik Wiedenhofer2, Martin Bruckner1

A Material Flow Analysis of Phosphorus in Japan
The Iron and Steel Industry as a Major Phosphorus Source

Kazuyo Matsubae-Yokoyama, Hironari Kubo, Kenichi Nakajima,
and Tetsuya Nagasaka

Material Flows and Economic Development
Material Flow Analysis of the Hungarian Economy

The material footprint of nations

Thomas O. Wiedmanna,b,c,1, Heinz Schandlb,d, Manfred Lenzenc, Daniel Moranc,e, Sangwon Suhf, James Westb, and Keiichiro Kanemotoc

Calculation of direct and indirect material inputs by type of raw material and economic activities

Paper presented at the London Group Meeting
19 – 21 June 2006

Karl Schoer

Wiesbaden, July 2006

Waste Input-Output  (WIO) Table

Shinichiro NAKAMURA and Yasushi KONDO,

Waste Input-Output Analysis: Concepts and Application to Industrial Ecology.

In Series: Eco-Efficiency in Industry and Science,

Vol. 26, Springer, February 2009.

Economy Wide Material Flow Accounting (EW-MFA)

Material flow analyses in technosphere and biosphere
– metals, natural resources and chemical products

Viveka Palm

The UK waste input-output table: Linking waste generation to the UK economy.

Salemdeeb, R., Al-Tabbaa, A. and Reynolds, C.

Waste Management & Research, 34 (10). pp. 1089-1094.

Multiregion input / output tables and material footprint accounts session

Discussion of aspects of of MRIO / material footprinting work, and considerations for developing and resource based economies.

James West | Senior experimental scientist
25 May 2016

Construction of hybrid Input-Output tables for E3 CGE model calibration and consequences on energy policy analysis


Prospects and Drivers of Future European Resource Requirements
Evidence from a Multi-National Macroeconomic Simulation Study*

Paper prepared for the final WIOD Conference
Groningen, April 2012
Martin Distelkamp, Mark Meyer** and Bernd Meyer

GWS mbH Osnabrueck

Material Flow Analysis to Evaluate Sustainability in Supply Chains

Haroune Zaghdaoui, Anicia Jaegler, Natacha Gondran, Jairo Montoya-Torres

Physical and monetary input–output analysis: What makes the difference?

Helga Weisz , Faye Duchin

Recycling and Remanufacturing in Input-Output Models

Randall W Jackson, West Virginia University
Taelim Choi, Georgia Institute of Technology
Nancey Green Leigh, Georgia Institute of Technology

The Water Footprint Assessment Manual

The New Plastics Economy
Rethinking the future of plastics

A Comparison of Environmental Extended Input-Output (EEIO) and Process Data in Life Cycle Assessment

Managing Logistics Flows Through Enterprise Input-Output Models

V. Albino1, A. Messeni Petruzzelli1 and O. G. Okogbaa2

Social Metabolism and Accounting Approaches


Ecological economics

Input-Output Analysis in Laptop Computer Manufacturing


Final Project Report, March 2004

A Framework for Sustainable Materials Management

Joseph Fiksel

Energy and water conservation synergy in China: 2007–2012

Yi Jina, Xu Tanga,⁎, Cuiyang Fenga, Mikael Höökb

Contributions of Material and Energy Flow Accounting to Urban Ecosystems Analysis: Case Study Singapore

Niels B. Schulz

A review of recent multi-region input–output models used for consumption-based
emission and resource accounting

Thomas Wiedmann

Physical Input Output (PIOT) Tables:  Developments and Future

Materials and energy flows in industry and ecosystem netwoks : life cycle assessment, input-output analysis, material flow analysis, ecological network flow analysis, and their combinations for industrial ecology

Suh, S,


Applying Ecological Input‐Output Flow Analysis to Material Flows in Industrial Systems: Part I: Tracing Flows

First published: 08 February 2008

Applying Ecological Input‐Output Flow Analysis to Material Flows in Industrial Systems: Part II: Flow Metrics

First published: 08 February 2008

Local systems, global impacts
Using life cycle assessment to analyse the
potential and constraints of industrial symbioses

rising to global challenges

25 Years of Industrial Ecology

Literature study on Industrial Ecology

Gerard Fernandez Gonzalez






Practical Handbook of MATERIAL FLOW ANALYSIS

Paul H. Brunner and Helmut Rechberger

Handbook of Input-Output Economics in Industrial Ecology

edited by Sangwon Suh

Taking Stock of Industrial Ecology

edited by Roland Clift, Angela Druckman

Ecological Input-Output Analysis-Based Sustainability Analysis of Industrial Systems


Cristina Piluso and Yinlun Huang*


Helen H. Lou

An Extended Model for Tracking Accumulation Pathways of Materials Using Input–Output Tables: Application to Copper Flows in Japan

Ryosuke Yokoi * ID , Jun Nakatani ID and Yuichi Moriguchi


Kálmán KÓSI and András TORMA




Metabolism of Cities






Feasibility assessment of using the substance flow analysis methodology for chemicals information at macro level




Structural Investigation of Aluminum in the US Economy using Network Analysis

Philip Nuss, Wei-Qiang Chen Hajime Ohno, and T.E. Graedel





Economy-wide Material Flow Analysis and Indicators





Regional distribution and losses of end-of-life steel throughout
multiple product life cycles—Insights from the global multiregional
MaTrace model


Stefan Pauliuka,∗, Yasushi Kondob, Shinichiro Nakamurab, Kenichi Nakajimac





MaTrace: Tracing the Fate of Materials over Time and Across Products in Open-Loop Recycling

Shinichiro Nakamura,*,† Yasushi Kondo,† Shigemi Kagawa,‡ Kazuyo Matsubae,§ Kenichi Nakajima,⊥ and Tetsuya Nagasaka§






Tracing China’s energy flow and carbon dioxide flow based on Sankey diagrams


Feiyin Wang1,2 • Pengtao Wang1,2 • Xiaomeng Xu1,2 • Lihui Dong1,2 • Honglai Xue1,2 • Shuai Fu1,2 • Yingxu Ji





Materials Flow and Sustainability





Life-cycle assessment






Scientific Applications International Corporation (SAIC) 11251 Roger Bacon Drive
Reston, VA 20190





Life cycle analysis (LCA) and sustainability assessment

The Hidden Geometry of Trade Networks

The Hidden Geometry of Trade Networks


From The hidden hyperbolic geometry of international trade: World Trade Atlas 1870–2013



Key Terms:

  • Trade Networks
  • Complex Networks
  • Preferential Attachment
  • Positive Feedback
  • Fractals
  • Power Laws
  • Hyperbolic Geometry
  • Economic Geography
  • Regional Trading Blocks
  • Bilateral Trade
  • Multilateral Trade
  • Free Trade Agreements
  • Metabolism of a City
  • Metabolism of a Nation
  • Metabolism of the World
  • Industrial Ecology
  • Social Ecology
  • Growth and Form



From The hidden hyperbolic geometry of international trade: World Trade Atlas 1870–2013

Here, we present the World Trade Atlas 1870–2013, a collection of annual world trade maps in which distance combines economic size and the different dimensions that affect international trade beyond mere geography. Trade distances, based on a gravity model predicting the existence of significant trade channels, are such that the closer countries are in trade space, the greater their chance of becoming connected. The atlas provides us with information regarding the long-term evolution of the international trade system and demonstrates that, in terms of trade, the world is not flat but hyperbolic, as a reflection of its complex architecture. The departure from flatness has been increasing since World War I, meaning that differences in trade distances are growing and trade networks are becoming more hierarchical. Smaller-scale economies are moving away from other countries except for the largest economies; meanwhile those large economies are increasing their chances of becoming connected worldwide. At the same time, Preferential Trade Agreements do not fit in perfectly with natural communities within the trade space and have not necessarily reduced internal trade barriers. We discuss an interpretation in terms of globalization, hierarchization, and localization; three simultaneous forces that shape the international trade system.

From The hidden hyperbolic geometry of international trade: World Trade Atlas 1870–2013

When it comes to international trade, the evidence suggests that we are far from a distance-free world. Distance still matters1 and in many dimensions: cultural, administrative or political, economic, and geographic. This is widely supported by empirical evidence concerning the magnitude of bilateral trade flows. The gravity model of trade2–4, in analogy to Newton’s law of gravitation, accurately predicts that the volume of trade exchanged between two countries increases with their economic sizes and decreases with their geographical separation. The precision of that model improves when it is supplemented with other factors, such as colony–colonizer relationships, a shared common language, or the effects of political borders and a common currency5–7. Despite the success of the gravity model at replicating trade volumes, it performs very poorly at predicting the existence of a trade connection between a given pair of countries8; an obvious limitation that prevents it from explaining the striking regularities observed in the complex architecture of the world trade web9–13. One of the reasons for this flaw is that the gravity model focuses on detached bilateral relationships and so overlooks multilateral trade resistance and other network effects14.

Another drawback of the classical gravity model is that geography is not the only factor that defines distance in international trade. Here, we use a systems approach based on network science methodologies15,16 to propose a gravity model for the existence of significant trade channels between pairs of countries in the world. The gravity model is based on economic sizes and on an effective distance which incorporates different dimensions that affect international trade, not only geography, implicitly encoded on the complex patterns of trade interactions. Our gravity model is based on the connectivity law proposed for complex networks with underlying metric spaces17,18 and it can be represented in a pure geometric approach using a hyperbolic space, which has been conjectured as the natural geometry underlying complex networks19–22. In the hyperbolic trade space, distance combines economic size and effective distance into a sole distance metric, such that the closer countries are in hyperbolic trade space, the greater their chance of becoming connected. We estimate this trade distance from empirical data using adapted statistical inference techniques23,24, which allow us to represent international trade through World Trade Maps (WTMs). These define a coordinate system in which countries are located in relative positions according to the aggregate trade barriers between them. The maps are annual and cover a time span of fourteen decades. The collection as a whole, referred to as the World Trade Atlas 1870–2013, is presented via spatial projections25, Table S5, and trade distance matrices, Table S6. Beyond the obvious advantages of visualization, the World Trade Atlas 1870–2013 significantly increases our understanding of the long-term evolution of the international trade system and helps us to address a number of important and challenging questions. In particular: How far, in terms of trade, have countries traveled in recent history? What role does each country play in the maps and how have those roles evolved over time? Are Preferential Trade Agreements (PTAs) consistent with natural communities as measured by trade distances? Has the formation of PTAs led to lesser or greater barriers to trade within blocs? Is trade distance becoming increasingly irrelevant?

The answers to these questions can be summarized by asserting that, in terms of trade, the world is not flat; it is hyperbolic. Differences in trade distances are growing and becoming more heterogeneous and hierarchical; at the same time as they define natural trade communities—not fully consistent with PTAs. Countries are becoming more interconnected and clustered into hierarchical trade blocs than ever before.

Please see my related posts:

Networks and Hierarchies

Increasing Returns, Path Dependence, Circular and Cumulative Causation in Economics

Relational Turn in Economic Geography

Boundaries and Networks

Multilevel Approach to Research in Organizations

Regional Trading Blocs and Economic Integration

Increasing Returns and Path Dependence in Economics

Growth and Form in Nature: Power Laws and Fractals

Key Sources of Research:


The hidden hyperbolic geometry of international trade: World Trade Atlas 1870–2013

Guillermo García-Pérez  Marián Boguñá, Antoine Allard & M. Ángeles Serrano




Uncovering the hidden geometry behind metabolic networks


Molecular BioSystems · March 2012



The hidden geometry of complex networks





Deciphering the global organization of clustering in real complex networks

Pol Colomer-de-Simo ́n1, M. A ́ ngeles Serrano1, Mariano G. Beiro ́2, J. Ignacio Alvarez-Hamelin2 & Maria ́n Bogun ̃a ́1






Hidden geometric correlations in real multiplex networks


Kaj-KoljaKleineberg,1,∗ Mari ́anBogun ̃ ́a,1 M.A ́ngelesSerrano,2,1 andFragkiskosPapadopoulos






Emergent Hyperbolic Network Geometry

Ginestra Bianconi1 & Christoph Rahmede





The geometric nature of weights in real complex networks


Antoine Allard1,2, M. A ́ngeles Serrano1,2,3, Guillermo Garc ́ıa-Pe ́rez1,2 & Maria ́n Bogun ̃a ́




Network Geometry and Complexity

Daan Mulder · Ginestra Bianconi




Multiscale unfolding of real networks by geometric renormalization


Guillermo Garc ́ıa-P ́erez,1,2 Mari ́an Bogun ̃ ́a,1,2 and M. A ́ngeles Serrano




Topology of the World Trade Web

Ma A ́ngeles Serrano and Mari ́an Bogun ̃a ́



Patterns of dominant flows in the world trade web


M. A ́ngeles Serrano,1 Mari ́an Bogun ̃ ́a,2 and Alessandro Vespignani3,4





Clustering and the hyperbolic geometry of complex networks

Elisabetta Candellero and Nikolaos Fountoulakis





Hyperbolic Geometry of Complex Networks


Dmitri Krioukov, Fragkiskos Papadopoulos, Maksim Kitsak, Amin Vahdat, and Mari ́an Boguna






On Hyperbolic Geometry Structure of Complex Networks

Wenjie Fang


Water | Food | Energy | Nexus: Mega Trends and Scenarios for the Future

Water | Food | Energy | Nexus: Mega Trends and Scenarios for the Future




Facts and Figures

  • Agriculture accounts for 70% of global water withdrawal. (FAO)
  • Roughly 75% of all industrial water withdrawals are used for energy production. (UNESCO, 2014)
  • The food production and supply chain accounts for about 30% of total global energy consumption. (UNESCO, 2012)
  • 90% of global power generation is water-intensive. (UNESCO, 2014)
  • Global water demand (in terms of water withdrawals) is projected to increase by 55% by 2050, mainly because of growing demands from manufacturing (400% increase). More than 40% of the global population is projected to be living in areas of severe water stress by 2050. (UNESCO, 2014)
  • Power plant cooling is responsible for 43% of total freshwater withdrawals in Europe (more than 50% in several countries), nearly 50% in the United States of America, and more than 10% of the national water cap in China. (UNESCO, 2014)
  • By 2035, water withdrawals for energy production could increase by 20% and consumption by 85%, driven via a shift towards higher efficiency power plants with more advanced cooling systems (that reduce water withdrawals but increase consumption) and increased production of biofuel. (UNESCO, 2014)
  • There is clear evidence that groundwater supplies are diminishing, with an estimated 20% of the world’s aquifers being over-exploited, some critically so. Deterioration of wetlands worldwide is reducing the capacity of ecosystems to purify water. (UNESCO, 2014)
  • It typically takes 3,000 – 5,000 litres of water to produce 1 kg of rice, 2,000 litres for 1kg of soya, 900 litres for 1kg of wheat and 500 litres for 1kg of potatoes. (WWF).
  • While almost 800 million people are currently hungry, by 2050 global food production would need to increase by 50% to feed the more than 9 billion people projected who live on our planet (FAO/IFAD/UNICEF/WFP/WHO, 2017).


From Background paper for the Bonn 2011 Nexus Conference: THE WATER, ENERGY AND FOOD SECURITY NEXUS





From How Shell, Chevron and Coke tackle the energy-water-food nexus

We know how important food, water and energy are to our daily lives, but what happens when we fail to value them as critical, interconnected resources for our economy?

In the summer of 2012, the U.S. was affected by one of the worst droughts in recent decades. Eighty percent of U.S. farms and ranches were affected, crop losses exceeded $20 billion and unforeseen ripple effects followed.

With corn crops withering from the lack of rainfall, prices for food and livestock feed supplies rose, as did ethanol, predominantly sourced from corn. Numerous power plants had to scale back operations or even shut down because the water temperatures of many rivers, lakes and estuaries had increased to the point where they could not be used for cooling. Household, municipal and farm wells in the Midwest had to be extended deeper into rapidly depleting aquifers to make up for the lack of rainfall, draining groundwater supplies and demanding more electricity to run the pumps. It is estimated that consumers will feel these ripple effects for years to come — over the next year alone, this impact could result in personal costs up to $50 billion.

Now more than ever, our infrastructure is built on an interlinked system for the production and use of energy, water and food. Water is needed for almost all forms of energy production and power generation, energy is required to treat and transport water, and both water and energy are needed to produce food.

This interconnection, or energy-water-food nexus, underscores the global challenges that we face as a society. The growing global population, increased wealth and urbanization will continue to stress energy, water and food supplies. Climate change and unsustainable development practices will exacerbate them. In preparing for a population that could top 10 billion by 2050, according to U.N. estimates, in the next 15 to 20 years alone we will need 30 percent more water, 45 percent more energy and 50 percent more food.

Consvation International’s Business & Sustainability Council (PDF) examined the corporate risk and opportunities related to the energy-water-food nexus. The nexus is still new in the minds of many corporations, but CI sees several examples of companies broadening their strategies to build synergistic solutions.

Shell shines the spotlight on the pressures from the energy-water-food stress nexus in its 2013 report, “The New Lens Scenario.” The company is using scenario planning to test and collaborate on the design of synergistic solutions to tackle these interlinked resource constraints. In British Columbia, Shell collaborated with the city of Dawson Creek to build a reclaimed water facility that virtually eliminated its need to draw on local freshwater sources for the operation of a natural gas venture. It also worked with the World Business Council for Sustainable Development and the University of Utrecht to develop a new methodology that could more accurately estimate the amount of water needed to generate energy from different sources — oil, gas, coal, nuclear and biofuels — using different technologies and in different locations.

In Kern County, about 100 miles from Los Angeles and home to Chevron’s largest California oil field, Chevron partnered with the Cawelo Water District to provide much needed water to local farmers for agricultural use. Water is a significant byproduct from steam flooding, a technology employed to extract thick, viscous oil out of the ground. For every barrel of oil, 10 barrels of water are produced, about 700,000 gallons per day. Chevron reclaims about one-third to generate new steam, and provides most of the remaining treated water to the Cawelo Water District to distribute to 160 farmers to irrigate 45,000 acres of crops, such as almonds, grapes, pistachios and citrus. This innovative solution is critical to creating a more sustainable local water supply and helping Kern County growers keep agriculture thriving in the region.

Since 2005, The Coca-Cola Company has set an ambitious water security commitment for its beverages and operations. In order to meet its goal, it implemented a series of technical and natural solutions in nearly 400 community water projects in more than 90 countries. These community water partnerships include rainwater harvesting, drip irrigation, agricultural water efficiency improvements and protecting watersheds. The company has taken an even broader perspective, enhancing the ability of watersheds to absorb threats associated with the uncertainties around climate change, and increased demands for water, energy and food from a burgeoning population.

Ensuring energy, water and food security on a global level requires equal consideration of the interdependency among all three systems and the underlying natural capital that supports them.

CI believes that addressing the stress nexus requires collaboration among government, business and civil society. Public-private partnerships offer an innovative way to leverage expertise and financing in order to pilot practical, scalable and collaborative solutions. The Sustainable Landscape Partnership being piloted in Indonesia with support from CI, USAID and the Walton Family Foundation looks to understand integrated approaches to build local economies while reducing deforestation and ensuring food and water security.

Lack of data specific to the nexus is currently a limiting factor in building solutions. Improved frameworks to price natural resources such as water will be critical — one reason CI is engaged with WAVES and the TEEB for Business Coalition. CI is also piloting a game-changing monitoring system called Vital Signs in Africa to provide near real-time ecological and social data and diagnostic tools to guide agricultural development decisions and monitor their outcomes. As we continue to pilot models that demonstrate resiliency of landscapes, open platforms for information sharing will generate innovations and efficiencies.

Combined together, this integrated approach will be critical to fully understanding where critical nexus interactions lie, where they are most susceptible and how we can meaningfully make better decisions, for this generation and the next.


Please see my related post:

Jay W. Forrester and System Dynamics

Art of Long View: Future, Uncertainty and Scenario Planning



Key Sources of Research:



World Water Development Report 2014

UN Water


Nexus in the Media



Tools and Databases




The Energy-Water-Food Nexus: The Emerging Challenge to Sustainable Prosperity






The Food, Water, Energy Nexus

Published on Thursday, 20 March 2014


Asian Development Bank




How Shell, Chevron and Coke tackle the energy-water-food nexus





Understanding the Stress Nexus

Shell International




The Energy | Water | Food Nexus

Conservation International




Energy-water-food stress nexus

Royal Geographical Society

Energy-water-food stress nexus




A review of the current state of research on the water, energy, and food nexus






The Water–Energy–Food Security Nexus: Towards a practical planning and decision-support framework for landscape investment and risk management


Livia Bizikova
Dimple Roy
Darren Swanson
Henry David Venema
Matthew McCandless







Tracing the water-energy-food nexus: description, theory and practice.

Leck, Hayley, Conway, Declan, Bradshaw, Michael and Rees, Judith A.


Geography Compass, 9 (8). pp. 445-460. ISSN 1749-8198






United Nations University




Tools for analyzing the water-food-energy-ecosystems nexus

Compiled for UNECE by the Energy Systems Analysis group of the Royal Institute of Technology (KTH), Stockholm

September 2015





Energy -Water-Food Nexus

D.L. Keairns, R.C. Darton, and A. Irabien





Understanding the Energy-Water Nexus

Matthew Halstead
Tom Kober
Bob van der Zwaan

September 2014





“Towards sustainable synergy between water, energy and food”













Nina Weitz, Claudia Strambo, Eric Kemp-Benedict, Måns Nilsson







Water, Food and Energy












A bottom-up approach to the nexus of energy, food and water security in the Economic Community of West African States (ECOWAS) region

Prof. Subhes Bhattacharyya
Mr. Nicola Bugatti
Mr. Hannes Bauer





Understanding the Nexus. Background Paper for the Bonn2011
Conference: The Water, Energy and Food Security Nexus.

Hoff, H.


Stockholm Environment Institute, Stockholm.




Anatomy of a buzzword: the emergence of ‘the
water-energy-food nexus’ in UK natural resource debates

Rose Cairns

Anna Krzywoszynska*





Understanding the Nexus of Food, Water, and Energy

AT Kearney





A quick scan

Water-food-energy nexus

Stijn Reinhard, Jan Verhagen, Wouter Wolters and Ruerd Ruben




The Circular Economy and the Water-Energy-Food Nexus





The global food – water – energy nexus






Water Food Energy Climate Nexus

World Economic Forum





Development of Pardee Rand Water Energy Food Security Index






Review of the Current State of Research on the Water, Energy, and
Food Nexus

Aiko Endo, Izumi Tsurita, Kimberly Burnett,
And Pedcris M. Orencio



Mitigating Risks and Vulnerabilities in the Energy-Food-Water Nexus in Developing Countries

Sustainability Institute





Gabriel Collins, J.D.
Baker Botts Fellow in Energy & Environmental Regulatory Affairs
June 2017




Managing the food,water,and energy nexus for achieving the
Sustainable Development Goals in South Asia

Golam Rasul





The Water-Energy Nexus and Urban Metabolism – Connections in Cities

Steven Kenway

January 2013



Thinking about Water Differently
Managing the Water–Food–Energy Nexus






Walking the Nexus Talk:
Assessing the Water-Energy-Food Nexus
in the Context of the Sustainable Energy for All Initiative






The 15 projects that will take on the food-water-energy nexus









Food, Water and Energy Nexus in India




The Food-Energy-Water Nexus

(GEO/NRSM 595)

University of Montana




Water–food–energy nexus with changing agricultural scenarios in
India during recent decades

Beas Barik1, Subimal Ghosh1,2, A. Saheer Sahana1, Amey Pathak1, and Muddu Sekhar






The Energy–Water–Food Nexus at Decentralized Scales

Lucy Stevens and Mary Gallagher, Practical Action, UK





Making governance work for water–energy–food nexus approaches

By Andrew Scott




Food, Water and Energy: Know the Nexus





Global Trends 2030: Alternative Worlds
a publication of the National Intelligence Council







A publication of the National Intelligence Council





Global Trends





Understanding Water- Energy-
Food Nexus from Mountain Perspective

David Molden, Aditi Mukherji, Golam Rasul, Arun Shrestha,
Ramesh Vaidya, Shahriar M. Wahid and Philippus Wester




Regulating the water-energy-food nexus: Interdependencies, transaction costs and procedural justice




Innovating at the food, water, and energy interface




The Water-Energy-Food Nexus. A New Approach in Support of Food Security and Sustainable Agriculture


Wassily Leontief and Input Output Analysis in Economics

Wassily Leontief and Input Output Analysis in Economics



Wassily Leontief: The Concise Encyclopedia of Economics | Library of Economics and Liberty

From the time he was a young man growing up in Saint Petersburg, Wassily Leontief devoted his studies to input-output analysis. When he left Russia at the age of nineteen to begin the Ph.D. program at the University of Berlin, he had already shown how leon walras’s abstract equilibrium theory could be quantified. But it was not until many years later, in 1941, while a professor at Harvard, that Leontief calculated an input-output table for the American economy. It was this work, and later refinements of it, that earned Leontief the Nobel Prize in 1973.

Input-output analysis shows the extensive process by which inputs in one industry produce outputs for consumption or for input into another industry. The matrix devised by Leontief is often used to show the effect of a change in production of a final good on the demand for inputs. Take, for example, a 10 percent increase in the production of shoes. With the input-output table, one can estimate how much additional leather, labor, machinery, and other inputs will be required to increase shoe production.

Most economists are cautious in using the table because it assumes, to use the shoe example, that shoe production requires the inputs in the proportion they were used during the time period used to estimate the table. There’s the rub. Although the table is useful as a rough approximation of the inputs required, economists know from mountains of evidence that proportions are not fixed. Specifically, when the cost of one input rises, producers reduce their use of this input and substitute other inputs whose prices have not risen. If wage rates rise, for example, producers can substitute capital for labor and, by accepting more wasted materials, can even substitute raw materials for labor. That the input-output table is inflexible means that, if used literally to make predictions, it will necessarily give wrong answers.

At the time of Leontief’s first work with input-output analysis, all the required matrix algebra was done using hand-held calculators and sheer tenacity. Since then, computers have greatly simplified the process, and input-output analysis, now called “interindustry analysis,” is widely used. Leontief’s tables are commonly used by the World Bank, the United Nations, and the U.S. Department of Commerce.

Early on, input-output analysis was used to estimate the economy-wide impact of converting from war production to civilian production after World War II. It has also been used to understand the flow of trade between countries. Indeed, a 1954 article by Leontief shows, using input-output analysis, that U.S. exports were relatively labor intensive compared with U.S. imports. This was the opposite of what economists expected at the time, given the high level of U.S. wages and the relatively high amount of capital per worker in the United States. Leontief’s finding was termed the Leontief paradox. Since then, the paradox has been resolved. Economists have shown that in a country that produces more than two goods, the abundance of capital relative to labor does not imply that the capital intensity of its exports should exceed that of its imports.

Throughout his life Leontief campaigned against “theoretical assumptions and nonobserved facts” (the title of a speech he delivered while president of the American Economic Association, 1970–1971). According to Leontief too many economists were reluctant to “get their hands dirty” by working with raw empirical facts. To that end Wassily Leontief did much to make quantitative data more accessible, and more indispensable, to the study of economics.

Selected Works

1941. The Structure of American Economy, 1919–1929. Cambridge: Harvard University Press.

1966. Essays in Economics: Theories and Theorizing. New York: Oxford University Press.


From NY Times

Wassily Leontief, Economist Who Won a Nobel, Dies at 93


Wassily Leontief, who won the Nobel prize in economics in 1973 for his analyses of America’s production machinery, showing how changes in one sector of the economy can exact changes all along the line, affecting everything from the price of oil to the price of peanut butter, died Friday night at the New York University Medical Center. He was 93.

His analytic methods, as the Nobel committee observed, were adopted and became a permanent part of production planning and forecasting in scores of industrialized nations and in private corporations all over the world.

Following the model of his so-called input-output analysis, General Electric, for example, was able to load data from 184 sectors of the economy — such as energy, home construction and transportation — into a mammoth computer to help it predict how the energy crisis brought on by the Arab oil boycott in 1973 would affect public demand for its products and services, from light bulbs to turbines.

A well-known academic figure, Mr. Leontief was the director of the Institute for Economic Analysis of New York University from 1975 until 1991; even after his retirement he still taught at the university into his 90’s. Before coming to N.Y.U. he taught economics at Harvard for 44 years and directed large research projects there as well.

Mr. Leontief was a thinker who often complained that too many of his academic colleagues spent too much time staring out their office windows instead of being out in the field, as any good economist ought to be, counting things. ”Facts,” he said. ”You have to have facts. Theories aren’t good unless you have facts to back them.”

When asked how he developed the input-output analysis recognized by his Nobel memorial prize, he would invariably begin, ”Oh, it’s really very simple — what I wanted to do was collect facts.” The facts he sought were those that explained how segments of production were interconnected.

He showed that if you carefully studied changes in the cost and components of one type of product, you could determine the resulting changes in cost and components of others along the production chain.

Suppose you have a sudden rise the price of oil or steel? Mr. Leontief taught government officials and corporate executives to track how this influenced the costs of production in other segments of a local or national economy, both within an industry or more broadly across many industries and many nations.

Wassily Leontief was born Aug. 5, 1905, in St. Petersburg, the son of Wassily W. Leontief, an economist, and the former Eugenia Bekker. A brilliant student, he was allowed to enroll when he was only 15 at the newly renamed University of Leningrad. But he got in trouble by expressing vehement opposition to the lack of intellectual and personal freedom under the country’s Communist regime, which had taken power three years earlier. He was arrested as he was nailing up anti-Communist posters on the wall of a military barracks and placed in solitary confinement. Released after several days, he promptly resumed his anti-Communist activities and was arrested several more times.

Finally, in 1925, he was allowed to leave the country, a turn of fate he attributed to a growth on his neck. He said the authorities believed that the growth was cancerous and that he would die and be of no use to the state. He left Russia to resume his studies in economics at the University of Berlin, and his parents soon followed. The growth was benign and he completed his doctorate in 1929. He spent a year as an economist advising the Government of China, particularly on the planning of a new railroad network.

Then he came to the United States and worked briefly in New York at the National Bureau of Economic Research, where his published work quickly attracted attention, and Harvard invited him to join its economics faculty. He agreed, provided the university help him develop his ideas about production. Harvard gave him a research assistant and a $2,000 grant to develop the system of input-output analysis that the world was to adopt. He and his assistant began constructing a table covering 42 American industries, taking months to compile figures and perform calculations that computers would latter handle in fractions of seconds.

During the war, he helped the United States Government with planning for industrial production, worked as a consultant to the Office of Strategic Services and supervised compilation of a 92-economic-sector table for the Department of Labor. In 1948, Mr. Leontief set up the Harvard Research Project on the Structure of the American Economy with the aid of large grants from the Ford and Rockefeller Foundations and the Air Force to expand and refine his input-output models. Soon he had a staff of 20 — and a 650-punch-card computer from I.B.M., then the state-of-the art.

He did not, however, keep the Air Force grant long once the Eisenhower Administration came to power; some of its officials were critical of his input-output theory as smacking too much of a planned economy. That was precisely what he thought it should smack of.

One of his goals in studying the nature of changes in industrial production was to enable nations to plan in ways that would be economically beneficial and help them avoid periods of economic hardship. But to some economists the idea of national economic planning was ill advised: not only would it not work, they said, but it might make matters worse and also might open the door to excessive Government control. They maintained it would be better to let the private sector and the free market determine the course of future economic events.

To Mr. Leontief, it seemed short-sighted for nations to devote little or no thought to the analysis of the future of the overall economy, especially after what he regarded as the effective work of modern economists in devising projections that are mathematically and statistically sound. He spoke out often on the subject in the 1970’s and 80’s.

He and Leonard Woodcock, then president of the United Auto Workers, proposed that the Federal Government establish an Office of National Economic Planning to help coordinate economic projects and make recommendations on policies they said could avert unnecessary unemployment, inflation, failures in health care, shortages in affordable housing, energy, public transportation and other requirements of a civilized society.

The idea never materialized. If anything, the generation of younger economists who followed him, many of whom he taught, developed less respect for the abilities of national Governments to plan for the long term. It bothered him greatly that toward the end of the century many Americans seemed to have lost broad faith in their Government’s ability to improve the lot of its citizens, particularly through economic programs.

In an Op-Ed article in The New York Times in 1992, he said there was little doubt that the United States Government had played an important role in a generally prosperous economy for more than half the century, from ending the Great Depression in the 30’s to guiding the nation through most of the rest of the century in generally sounder economic health than most of the rest of the world.

Mr. Leontief was always fearful that employment problems would accompany widespread use of the high-speed computers that he himself relied on almost from the moment they first became applicable for nonmilitary purposes after World War II. He warned that computers would be for many workers what the tractor was to the horse — great for the farmer but not great for the horse.

In an interview in 1996, when he was 90, Mr. Leontief, noting the trend toward corporate downsizing, said: ”Individual entrepreneurs will continue to do better and better and better, but significant segments of the work force will do worse and worse. Ultimately, Governments will have to play a role in arbitrating and correcting this.”

Mr. Leontief seemed to grow more liberal with age. During the student protests on the Harvard campus in 1969, he split with most senior faculty members and joined with a younger group more sympathetic to the protesting students. In 1975, he resigned from Harvard, where he was the Henry Lee Professor of Economics and chairman of the university’s Society of Fellows, its most distinguished group of scholars. He left a year ahead of schedule, complaining that too often teachers at the graduate level did not teach and researchers did not do research.

Shortly before he resigned, he joined an internal report criticizing Harvard’s economics department, which had long been regarded as among the world’s best. The report said that the department had failed to adequately recruit minority faculty members, that it took an overly narrow approach in scholarship and that a ”deterioration in attitudes and relationships” had occurred.

At N.Y.U., he continued to expand his work on input-output analysis and helped foreign nations adopt it. China was among the last to do so, as it intensified its industrialization in the late 1980’s.

Wassily Leontief, a balletomane and connoisseur of fine wines, said he also thought of himself as a squire of Willoughby Brook in northern Vermont, where he and his family had a summer home. It was all very well to be an internationally regarded scholar, but landing a beautiful brook trout, he would say with his sly smile, was his passion.

He is survived by his wife, Estelle Helena Marks, a writer, whom he married in 1932, his daughter, Svetlana Alpers, the art historian, author, and professor of fine arts at the University of California at Berkeley, and two grandsons.



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Stock Flow Consistent Input Output Models (SFCIO)

Stock Flow Consistent Input Output Models (SFCIO)


SFCIO  = SFC + IO Models

SFC = Stock Flow Consistent

IO = Input Output

Stock Flow Consistent Input Output Models (SFCIO)


Integrating Varieties of Modeling Methods

  • Monetary Input Output Models
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From Stock-Flow Consistent Input–Output Models as a Bridge
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One effort to explicitly represent the dynamics of debt, finance, and other monetary factors has been the post-Keynesian stock-flow consistent (SFC) approach. At the same time, input–output (IO) models have been widely used to investigate sectoral interdependencies within the real economy, while environmentally extended input–output models have been used to analyze the relationship between the economy and ecological subsystems. However, the role of monetary dynamics has been left relatively unexplored in IO models (Caiani et al., 2014). This paper proposes a synthesis of elements from both SFC and IO models with insights from ecological economics to provide an avenue for investigating the interrelations between the monetary economy and the physical environment.


From Stock-Flow Consistent Input–Output Models as a Bridge
Between Post-Keynesian and Ecological Economics

By combining SFC models and IO models, financial flows of funds can be integrated with flows of real goods and services. Lawrence Klein, who developed large scale macroeconomic models typified by the FRB-MIT-Penn model, has noted the natural synergies between the National Income and Product accounts, the IO accounts, and the FF accounts (Klein, 2003). The approach of combining both SFC and IO models with ecological macroeconomics affords one method to unite those accounts, as suggested by Klein, and to simultaneously model monetary flows through the financial system, flows of produced goods and services through the real economy, and flows of physical materials through the natural environment. Models of this type may provide additional tools to aid macro economists, ecological economists, and physicists in the task of understanding the economy and the physical environment as one united and complexly interrelated system, rather than as a colloidal agglomeration of artificially separated analytical domains. These modes of analysis are required to study pressing problems such as climate change, which are neither purely economic, nor purely environmental, nor purely physical, but rather are all of the above (Rezai et al., 2013).



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USA and China: What are Trade in Value Added (TiVA) Balances

USA and China: What are Trade in Value Added (TiVA) Balances


Changes in Global Trade

  • Global Value Chains
  • Production Fragmentation
  • Vertical Specialization
  • Value added content of Trade





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From Measurement and Determinants of Trade in Value Added







Ongoing TiVA Projects

  • OECD TIVA Initiative
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There is also OECD TiVA – MNE Project which incorporates Intra Firm trade of MNEs.


From An Overview on the Construction of North American Regional Supply-Use and Input-Output Tables and their Applications in Policy Analysis


Trade-in-Value Added (TiVA) is a statistical approach used to measure the interconnectivity and marginal contribution in production of participating economies in global value chains (GVCs) (Degain and Maurer, 2015). The advantage of TiVA over traditional trade statistics is that TiVA measures trade flows consistent with internationally, vertically integrated global production networks, often called GVCs. TiVA statistics allow us to better analyze three aspects of international trade: measuring the contribution of domestic versus foreign intermediates in the exports, tracing production across countries to their final destination, and finally quantifying how individual industries contribute to producing exports (Lewis, 2013).

TiVA statistics allow us to map and quantify the interdependencies between industries and economies, and help us develop better estimates of the contribution from each country in the production processes and, consequently, better measure the impact from GVC engagement for domestic economies. However, it is necessary to highlight the underlying compilation methodology of TiVA in order to better understand the characteristics, scope and interpretation of TiVA. Hence, it is important to remember that TiVA statistics are estimated statistics that are derived, in part, from official statistics. TiVA statistics are meant to complement but not to replace official statistics.

Measuring trade flows in value added as opposed to gross value of trade flows has become increasingly important as the influence that GVCs has on international trade continues to rise. (Johnson, 2014; Ahmad and Ribarsky, 2014). The proliferation of GVCs means that production has become increasingly fragmented and vertically integrated across countries (Jones and Kierzkowski, 1988; Hummels, Ishii, and Yi, 2001; OECD, 2013). At the micro level, this means that many firms in disparate countries are interconnected. Across international borders, these firms take part in particular stages of the production process, together forming a global supply chain. As a result, intermediate inputs may cross international borders several times before being used to produce final consumable goods. This matters for several reasons. First, when goods cross multiple borders multiple times, they are exposed to more trade costs, which accumulate and compound before the goods are sold for final consumption. Additionally, traditional gross trade flows are overstated because gross trade flows may count intermediates multiple times. Relatedly, gross trade flows obscure the marginal contributions of countries along GVCs. TiVA measures the flows related to the value that is added at each stage of production by each country and maps from where value is created, where it is exported, and how it is used, as final consumption or as an input for future exports. How we understand gains from trade from trade flows is fundamental, and value-added approaches lead to better understanding of GVCs and their role in international trade.

There are two ways to capture TiVA. The first method is a direct approach, which decomposes existing data on trade statistics. Johnson (2012) introduce a TiVA indicator using value-added to output ratios from the source country to compute the value-added associated with the implicit output transfer to each destination. Koopman, Wang, and Wei (2014) build on the literature in vertical specialization (e.g. Hummels, Ishii, and Yi 2001) and the literature on TiVA (e.g. Johnson and Noguera, 2012; Daudin, Rifflart, and Schweisguth, 2011) to implement a complete decomposition of a country’s gross exports by value added components. This work has evolved into a second, indirect method of capturing TiVA. The indirect method is employed in the regional North American supply-use table (NASUT) and the regional North American inter-country input-output table (NAIOT). Estimating TiVA this way relies on national and international input-output tables as well as bilateral trade statistics to derive the international intermediate and final supply-demand matrices. These matrices reveal the origin and use of goods and services produced and exchanged among the countries and industries within the table domain. Other major international input-output tables include the Asian International Input-Output (AIO) Tables published by the Institute of Developing Economies Japan External Trade Organization (IDE-JETRO), the Inter-Country Input-Output (ICIO) Tables published by the OECD, the World Input-Output Tables (WIOT) published by the World Input-Output Database (WIOD) project, and the Eora Multi-region Input-Output Database (Eora MRIO).

The studies based on the above two approaches have revealed a trend of rising foreign value-added content in international trade flows and the resulting implications for trade policies. Johnson and Noguera (2016) find that value-added exports are falling relative to gross exports, which means that double-counting is increasingly more common in trade flows. This is consistent with increased GVC activity. Hummels, Ishii, and Yi (2001) show that vertical specialization has grown about 30 percent and accounts for about one-third of the growth in trade from about 1970 to 1990.

In recent years, more than half of global manufacturing imports are intermediate goods and more than 70 percent of global services imports are intermediate services (OECD, 2013). This is relevant because tariffs (and other trade costs) have a higher impact on the cost of GVC activity. Each time an intermediate input crosses an international border as part of the production process, the input incurs trade costs. As first observed by Yi (2003), trade costs are compounded when intermediate goods cross borders multiple times to complete the production process. Rouzet and Miroudot (2013) demonstrate that small tariffs can add up to a significant sum by the time a finished product reaches its consumers. Other trade costs such as non-tariff measures also have such accumulative effect on downstream products.

What the literature indicates the trends in GVCs mean for trade flows, generally, are two-fold. First, with the growth of GVC activity, gross value of trade flows will continue to be larger than the value of final goods that cross borders. Second, trade policy designed with respect to gross trade flows could have the potential to be overly restrictive or even impose costs indirectly on domestic production. Trade-in-Value Added thus provides a supplementary, relevant reference for evaluating the economic effect of trade policies.

In this paper, we introduce the North American Trade-in-Value Added (NA-TiVA) project, a trilateral, multiyear initiative that aims to produce a regional TiVA database that maps the value chains connecting Canada, the United States, and Mexico. Furthermore, we introduce and discuss the project’s deliverables, the agencies involved, how the NA-TiVA project complements other ongoing TiVA initiatives around the world, the technical framework for producing a regional inter-country input-output table for the NA region, and the value of this work to resolving open policy questions within international trade.

Ongoing TiVA Initiatives

Currently there are three major ongoing global and regional TiVA projects that are related to the North America TiVA project. They are the World Input-Output database (WIOD), OECD-WTO TiVA, and APEC TiVA initiatives.

The World Input-Output database (WIOD): The official WIOD project ran from May 1, 2009 to May 1, 2012, as a joint effort of eleven European research institutions. It was funded by the European Commission. Under the official WIOD project, the accounting framework and methodologies of constructing the TiVA databases, as well as the first version of the World Input-Output database were developed. The database was officially launched in April 2012. Since then, two additional versions of WIOD databases, namely the 2013 and 2016 Releases, were published. The 2016 Released database covers 28 EU countries and 15 other major economies in the world for years 2000-2014 with 56 industries.

The OECD-WTO TiVA database: The Organization for Economic Cooperate and Development (OECD) and World Trade Organization (WTO) undertook a joint initiative on TiVA in 2013. Since then, two versions of TiVA databases have been released (2013 and 2015 release). The 2015 release of OECD-WTO TiVA database covers 61 countries and 13 regions, with 34 industries, for years 1995, 2000, 2005, 2008-2011.

APEC TiVA initiative: In 2014, APEC economic leaders endorsed the APEC TiVA database initiative, a four-year project co-led by China and the United States. Under this project, an APEC TiVA database would be constructed by the end of 2018, covering 21 APEC economies.

Each of these three major global and regional TiVA initiatives include Canada, Mexico, and the United States. In the light of this, why is there still a need for constructing the NA TiVA database? What kind of additional value can the NA TiVA project bring to this global and regional network of TiVA initiatives?

The NA-TiVA project was motivated by regional statistical developments and continuous improvements in compiling TiVA databases. The 2003 Mexican input-output table distinguishes trade flows by domestic producers and production undertaken in Maquiladoras, a tax-free, tariff-free special processing zone, which allowed the estimates of separate production coefficients and thus TiVA measures for these two distinctive zones in Mexico (Koopman, Powers, Wang, and Wei, 2010; De la Cruz, Koopman, Wang, and Wei, 2011). The government of Canada further highlighted the importance and relevance of global value chains in the publication of a book assessing the impact and implication of GVCs (Foreign Affairs and International Trade Canada, 2011); and as of the 2015 edition of the OECD’s ICIO tables, Mexico is broken out as Mexico Global Manufacturers and Mexico Non-Global Manufacturers. This NA TiVA project builds off of these developments.

Constructing inter-country input-output tables, or so called TiVA databases, requires the harmonization of national supply-use tables (SUTs) or input-output tables (IOTs) as well as bilateral trade statistics from different countries. However, the data produced by countries often vary greatly in the level of detail and differ in industry and product classifications. Thus, the more countries are included in a global or regional TiVA project, the higher level of aggregation would be required for the purpose of harmonization. With only three countries involved, it is feasible for the NA TiVA database to include more products and sectors than other global and regional TiVA projects.

Moreover, other factors, such as all three countries adopt the same industry and product classifications (e.g. using the North American Industry Classification System (NAICS)), and produce SUTS at similarly detailed levels, would ensure the compatibility of data components, and thus lead to better quality of the resulting NA TiVA database.

Finally, the NA TiVA project could synthesize the ongoing trilateral trade statistics reconciliation effort and produce better-quality balanced bilateral trade data to feed into other global and regional TiVA initiatives. One of the key inputs for constructing TiVA databases is balanced bilateral trade statistics. However, countries rarely report symmetric bilateral trade statisticsone country’s reported exports rarely equals its trading partner’s reported imports, and vice versa. To reconcile such asymmetries to produce balanced bilateral trade statistics, joint effort by both trading countries is warranted, including investigating the causes of asymmetries at detailed product level and making corresponding adjustment mechanically. However, global and regional TiVA initiatives often have to consider an incredible number of country pairs, making such an elaborate reconciliation practice rather infeasible. Thus, global and regional TiVA initiatives often turn to economic modelling to balance bilateral trade statistics which could be applied in a systematic way to all countries. Although such approach can be mathematically sound, the resulting data often require additional scrutiny, validation, and adjustment, as they do not always reflect the reality accurately. Canada, Mexico, and the United States have ongoing bilateral trade reconciliation. This NA TiVA project provides additional motivation and framework for this effort.

The History, Scope, and Major Objectives of the NA TiVA Initiative

In October 2014, the representatives from the United States, Canada, and Mexico met and kicked off the idea of constructing the NA TiVA database at a UN conference in Mexico. The main objective of this project is to construct the NA TiVA database by 2021 covering three NA countries with more detailed industry and firm information, and to improve the quality of TiVA measures for the value chains in the NA region.

The NA-TiVA project involves eight government agencies across the three NA countries: for Canada, Statistics Canada (STATCAN) and Global Affairs Canada; for Mexico, Instituto Nacional de Estadística y Geografía (INEGI) and Banco de Mexico; and for the United States, the Bureau of Economic Analysis (BEA), the U.S. Census Bureau (CENSUS), the U.S. International Trade Commission (USITC), and the Office of the U.S. Trade Representative (USTR).

In addition, because the resulting NA-TiVA database would be eventually integrated into the OECD-WTO TiVA database to improve the quality of information on the North American region, participants of the NA-TiVA project regularly meet with OECD representatives to harmonize TiVA database compilation methodologies, exchange data to synthesize the effort and ensure consistency across countries, and discuss best practices. Other international organizations, such as United Nations Statistics Division (UNSD), and WTO, are often consulted as well for national account and trade statistics related issues.

Under the NA-TiVA initiative, three parallel work streams have been established: The trade in goods and services reconciliation team, which is tasked to produce balanced bilateral trade statistics for goods and services; the SUT team, whose goal is to harmonize the national SUTs and compile the regional NASUTs and NAIOTs; and the White Paper team, the goal of which is to produce documentation that outlines the conceptual methodology, identifies major technical issues, describes policy applications of a NA-TiVA initiative, and details project outputs as well as future work.






From Supply-Use Tables, Trade-in-Value-Added Initiatives, and their Applications


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Antonio Rodriguez-Lopez




Trade in Value Added and the Value Added in Trade

Robert Stehrer





US Trade Wars with Emerging Countries in the 21st Century: Make America and Its Partners Lose Again

Antoine Bouët (International Food Policy Research Institute, Washington, D.C., and Groupe de Recherche en Économie Théorique et Appliquée [GREThA], University of Bordeaux, France)
David Laborde (International Food Policy Research Institute)





Measuring Value Added in the People’s Republic of China’s Exports: A Direct Approach.

Xing, Y.


ADBI Working Paper 493. Tokyo: Asian Development Bank Institute





International Trade Costs, Global Supply Chains and Value-added Trade in

Gerard Kelly and Gianni La Cava
RDP 2014-07




Trade in Value Added Revisited: A Comment on R. Johnson and G. Noguera,
Accounting for Intermediates: Production Sharing and Trade in Value Added


Masaaki Kuboniwa
January, 2014





How iPhone Widens the US Trade Deficits with PRC

Yuqing Xing
Neal Detert

Nov 2010





Trade in value added (TIVA)




Global Value Chains (GVCs)

















The Growth of Chinese Exports:
An Examination of the Detailed Trade Data

Brett Berger
Robert F. Martin

US Federal Reserve





Comparing Trade Performance of China and India

Sarah Y TONG





Trade in Value Added : China






Value-Added Trade and Its Implications for International Trade Policy

Kemal Derviş, Joshua P. Meltzer, and Karim Foda





Bilateral Trade Balances with China: A Matter of Accounting

Submitted by Dana Vorisek

co-authors: Tianli Zhao

On Thu, 02/05/2015




Value-Added Exports and U.S. Local Labor Markets:
Does China Really Matter?

Leilei Sheny
Peri Silvaz


August 2017






Robert Koopman
Zhi Wang
Shang-Jin Wei


June 2008






Robert Koopman
William Powers
Zhi Wang
Shang-Jin Wei

September 2010





Richard Baldwin
Anthony Venables

December 2010





Gene M. Grossman
Esteban Rossi-Hansberg

December 2006






David K. Levine

December 2010





Arnaud Costinot
Jonathan Vogel
Su Wang

April 2011





Richard Baldwin
Frédéric Robert-Nicoud

April 2010



Measurement of Trade in Value-Added: using Chinese Input-output Tables
Capturing Processing Trade

Yang Cuihong1, Chen Xikang1, Duan Yuwan1, Jiang Xuemei1, Pei Jiansuo3, Xu Jian2,
Yang Lianling1, Zhu Kunfu1




Adjusted China-US Trade Balance

Lawrence J. Lau, Xikang Chen and Yanyan Xiong

March 2017




Domestic Value Added in Chinese Exports

Hiau Looi Kee and Heiwai Tang

World Bank and Tufts University
December 2011





João Amador | Sónia Cabral

Bank of Portugal





Processing Trade, Exchange Rates and China’s Bilateral Trade Balances

Yuqing Xing

Jan 2011




Trade in Value Added
WTO TiVA Profiles

Regional Workshop on
International Merchandise Trade Statistics
11-13 September 2017
Suzhou, China







Robert C. Johnson
Guillermo Noguera

June 2012






Robert Koopman
Zhi Wang
Shang-Jin Wei

November 2012






Pol Antràs
Davin Chor

June 2012






Richard Baldwin
Frederic Robert-Nicoud

March 2007






Gene M. Grossman
Esteban Rossi-Hansberg

December 2006





Trade in Value Added: Developing New Measures of Cross-Border Trade

World Bank






Trade in Value Added

Maria Borga Jiemin Guo

BEA Advisory Committee

May 10, 2013





Trade in value added Concepts, applications and challenges

Training Workshop on Trade in Services Negotiations for AU-CFTA Negotiators
Nairobi, Kenya





Trade in Value-Added: I-O approach and the domestic content of exports







Courtesy of Sébastien Miroudot (OECD)












Trade in Value Added and the Value Added in Trade


Working Paper Number: 8
Author: Robert Stehrer




Measuring Trade in Value-Added

Draft Chapter 9

Meeting of Group of Experts on National Accounts –
Interim meeting on Global Production
Geneva, 3-4 April 2013




Trade in Value Added: The Challenge of International Trade Statistics
With an Empirical Study on Trade in Norway and the Netherlands 2000-2012

Ida Helene Berg




Trade in Value-Added and Comparative Advantage

DrRadford Schantz

25thINFORUM Conference

August 28-September 2, 2017




Trade in Value Added: An East Asian Perspective.

Inomata, S.


ADBI Working Paper 451. Tokyo: Asian Development Bank Institute.





Global Value Chains and Trade in Value-Added: New Insights, Better Policies

Ken Ash

March 2013





Koen De Backer






The Value-added Structure of Gross Exports and Global Production Network

Robert Koopman and Zhi Wang
United States International Trade Commission

Shang-Jin Wei, Columbia University, CEPR and NBER




Singapore’s Trade in Value Added:
Importance and Implication of Information from the OCED-WTO TiVA Database

Mun–Heng TOH





Value added and participation in Global Value Chains:
the case of Spain

Marta Solaz
Universitat de Valencia

Fourth World KLEMS Conference, 23-24 May 2016





Trade in Value Added (TiVA): December 2016






An Overview on the Construction of North American Regional Supply-Use and Input-Output Tables and their Applications in Policy Analysis

Statistics Canada
Anthony Peluso
U.S. Bureau of Economic Analysis
Gabriel Medeiros
Jeffrey Young
U.S. International Trade Commission
Ross J. Hallren
Lin Jones
Richard Nugent
Heather Wickramarachi

Working Paper 2017-12-A





C. The rise of global value chains

World Trade Report







Rashmi Banga

May 2013





Highlights and Challenges of Measuring Global Production

Tom Howells
Federal Economic Statistics Advisory Committee
Suitland Federal Center

June 9, 2017





Value added trade: A tale of two concepts

Robert Stehrer

The Vienna Institute for International Economic Studies (wiiw)
Version: 2012-12-09

December 10-11, 2012 – CompNet workshop
ECB Frankfurt, Germany.




Summary Report of the Fifth Meeting of
APEC Technical Group of Measurement on TiVA under GVCs

August 2017





Trade in value added: do we need new measures of competitiveness?

Kirsten Lommatzsch, Maria Silgoner and Paul Ramskogler






Who Faces the Risk of Collateral Damage from U.S. Tariffs?

wells Fargo

March 2018





Supply-Use Tables, Trade-in-Value-Added Initiatives, and their Applications

William Powers

ADB Supply and Use Tables Validation Workshop

Bangkok, Thailand
30 June, 2016











APEC: Trade in Value Added under Global Value Chains

Erich H. Strassner

2ndStatistics Conference “Measuring the Economy in a Globalized World”
Santiago, Chile
3-4 October 2017





Norihiko YAMANO






Estimating Extended Supply-Use Tables in Basic Prices with Firm Heterogeneity for the United States:A Proof of Concept

Lin Z. Jones and ZhiWang (USITC)
James J. Fetzer, Thomas F. Howells III, Erich H. Strassner (BEA)

The Fourth World KLEMS Conference
Madrid, Spain
May 23-24, 2016






Work Plan for the Technical Group for the Measurement of APEC TiVA Under GVCs
Purpose: Information

Submitted by: China, United States
First Committee on Trade and Investment Meeting
Clark, Philippines
3-4 February 2015





APEC in 2014




Global value chains and trade in value added





Services and Manufacturing : Patterns of Linkages

Expert Group Meeting on “Global Value Chains, Regional Integration and Sustainable Development: Asia-Pacific Perspectives”

12 Dec 2014 – UNESCAP, Bangkok




The 3rd Capacity Building Workshop on Strategic Framework on Measurement of APEC TiVA under GVCs and its Action Plan







Capacity Building Workshop on Strategic Framework on Measurement of APEC TiVA under GVCs and its Action Plan







Enhancing Value Chains An Agenda for APEC






Changing Patterns of Trade and Global Value Chains in Postcrisis Asia

Ganeshan Wignaraja

Juzhong Zhuang

Mahinthan J. Mariasingham

Madeline Dumaua-Cabauatan





Global value chains in a changing world

Edited by Deborah K. Elms and Patrick Low






Trade in value added: Concepts, estimation and analysis,

Javorsek, Marko; Camacho, Ignacio

(2015) :

ARTNeT Working Paper Series, No. 150




India’s Future in Asia: The APEC Opportunity

By Harsha V. Singh and Anubhav Gupta




Update on New Measurements of the Impacts of Globalization

James J. Fetzer and Thomas F. Howells III

Advisory Committee Meeting
Washington, DC
November 13, 2015





Recent Trends and Developments

Shamshad Akhtar

Hongjoo Hahm

Susan F. Stone

Copyright © United Nations 2016





Asia’s Rise in the
New World Trade Order
The Effects of Mega-Regional Trade Agreements on Asian Countries
Part 2 of the GED Study Series:
Effects of Mega-Regional Trade Agreements




The role of different types of firms in GVCs

GGDC 25th Anniversary Conference


Stephen Chong, Rutger Hoekstra, Oscar Lemmers, Ilke Van Beveren, Marcel van den Berg, Ron van der Wal, Piet Verbiest










Annex 5: Strategic Framework on Measurement of






Estimating Extended Supply-Use Tables in Basic Prices with Firm Heterogeneity for the United States: A Proof of Concept

James J. Fetzer, Thomas F. Howells III, Lin Z. Jones, Erich H. Strassner, and Zhi Wang1

The Fourth World KLEMS Conference
Madrid, Spain
May 23-24, 2016




 “Participation of Developing Countries in Global Value Chains: Implications for Trade and Trade-Related Policies”

Kowalski, P. et al.


OECD Trade Policy Papers, No. 179,
OECD Publishing, Paris





Complex Network Analysis for Characterizing Global Value Chains in Equipment Manufacturing.

Xiao H, Sun T, Meng B, Cheng L


PLoS ONE 12(1):




A Network of Networks Perspective on Global Trade.

Maluck J, Donner RV


PLoS ONE 10(7)




Trends of the World Input and Output Network of Global Trade.

del RõÂo-Chanona RM, Grujić J, Jeldtoft Jensen H


PLoS ONE 12(1):




World Input-Output Network.

Cerina F, Zhu Z, Chessa A, Riccaboni M


PLoS ONE 10(7):




FAQ on GVCs: some answers from the Global I-O tables approach

Rita Cappariello,






A Markovian model of evolving world input-output network.

Moosavi V, Isacchini G


PLoS ONE 12(10):





Hierarchicality of Trade Flow Networks Reveals Complexity of Products.

Shi P, Zhang J, Yang B, Luo J


PLoS ONE 9(6):




International Trade Modelling Using Open Flow Networks: A Flow-Distance Based Analysis.

Shen B, Zhang J, Li Y, Zheng Q, Li X

PLoS ONE 10(11):





G. Suder (Melbourne Business School), P. Liesch (UQ), S. Inomata (JETRO- IDE), I. Jormanainen (Aalto University) and B. Meng (JETRO- IDE and OECD),

For: Journal of World Business






Charles Cadestin, Koen De Backer, Isabelle Desnoyers-James,
Sébastien Miroudot, Davide Rigo and Ming Ye










Identifying Heterogeneity in the Production Components of Globally Engaged Business Enterprises in the United States

James Fetzer and Erich H. Strassner

June 10, 2015




The EU Inter-country Supply, Use and Input-Output Tables (FIGARO Project): Recent progress

Prepared by Eurostat




Tracing value-added and double counting in sales of foreign affiliates and domestic-owned companies

Sebastien Miroudot and ming ye

Trade and Agriculture Directorate, OECD, Trade and Agriculture Directorate, OECD

14 March 2018


Identifying Heterogeneity in the Production Components of Globally Engaged Business Enterprises in the United States

Prepared by Bureau of Economic Analysis, U.S. Department of Commerce






Estimating Extended Supply-Use Tables in Basic Prices with Firm Heterogeneity for the United States: A Proof of Concept (Draft)

Prepared by the United States






Fabienne Fortanier (Head of Trade Statistics, OECD) Christophe Degain (Senior Statistician, WTO)






Full International and Global Accounts for Research in Input-
Output analysis
The EU Inter-country Supply, Use and Input-Output Tables

José M. Rueda-Cantuche

Isabelle Rémond-Tiedrez

Item 4, NAWG Meeting, Luxembourg, 11 May 2016




OECD-WTO Trade in Value Added (TiVA) data: introduction





Trade and Investment Linkages in Global Value Chains: Insights from the new TiVA-MNE Dataset






Dirk Pilat,

Global Industry and Economy Forum 2013:
Fostering Industrial Innovation through
Seoul, 24 June 2013



Calculating Trade in Value Added

Prepared by Aqib Aslam, Natalija Novta, and Fabiano Rodrigues-Bastos1

July 2017