Trends in Assets and Liabilities of Commercial Banks in the USA

Trends in Assets and Liabilities of Commercial Banks in the USA

To big to fail means too interconnected to fail.
As the balance sheets of banks have expanded so has their number of counterparties on both sides of balance sheets.

The US commercial banks have have expanded their balance sheets.

On assets side, the loans portfolio has expanded.

Low Interest Rates and Banks’ Profitability – Update October 2020

On liabilities side, the deposits and borrowings have increased.

US Federal Reserve publishes H8 report on Assets and Liabilities of the US commercial banks. Detailed information on aggregate data presented in this post can be obtained from it.

On liabilities side, the borrowings from wholesale money markets and shadow banking contributed to systemic risk during 2008 financial crisis. Please see my posts on this subject.

Funding Strategies of Banks

Shadow Banking

There were also capital flows in US markets from foreign banks and other markets.

Low Interest Rates and International Capital Flows

On liabilities side, because of increased borrowings from short term markets, the financial interconnections have also increased resulting in systemic risk and financial contagion.

On assets side, because of increased volumes of loan portfolios, the systemic risk and chances for financial contagion have increased.

Balance Sheets, Financial Interconnectedness, and Financial Stability – G20 Data Gaps Initiative

Contagion in Financial (Balance sheets) Networks

For analytical framework, accounting approach (Post Keynesian Economics) is one of the option.

Balance Sheet Economics – Financial Input-Output Analysis (using Asset Liability Matrices) – Update March 2018

Foundations of Balance Sheet Economics

Economics of Money, Credit and Debt

Morris Copeland and Flow of Funds accounts

Stock-Flow Consistent Modeling

Key Terms

  • Money View
  • Money Flows
  • Stocks and Flows
  • System Dynamics
  • Business Dynamics
  • Business Strategy
  • Asset Liability Management ALM
  • Balance Sheet Economics
  • Monetary Policy
  • Interest Rates
  • Credit
  • Debt
  • Money
  • Balance Sheet Expansion
  • Systemic Risk
  • Interconnectivity
  • Loan Portfolio
  • To big to fail
  • Networks
  • Funding Strategy
  • Market Liquidity
  • Funding Liquidity
  • Deposits
  • Interest Income
  • Non Interest Income
  • Borrowings
  • Wholesale Money Markets
  • Shadow Banking
  • International Capital Flows
  • Round Tripping
  • Global Liquidity
  • Eurodollar Market
  • Money Market Mutual Funds
  • Quadruple Accounting
  • Morris Copeland
  • Hyman Minsky
  • Wynn Godley
  • Perry Mehrling

Image Source: Liberty Street Economics 2017

Image Source: Statista

Image Source: FRED

Total Assets, All Commercial Banks (TLAACBW027SBOG)
Image Source: FRED

Total Liabilities, All Commercial Banks (TLBACBW027NBOG)
Image Source: FRED

Image Source: FRED

My Related Posts

Balance Sheet Economics – Financial Input-Output Analysis (using Asset Liability Matrices) – Update March 2018

Foundations of Balance Sheet Economics

Balance Sheets, Financial Interconnectedness, and Financial Stability – G20 Data Gaps Initiative

Funding Strategies of Banks

Economics of Money, Credit and Debt

Low Interest Rates and International Capital Flows

Low Interest Rates and Banks’ Profitability – Update October 2020

Morris Copeland and Flow of Funds accounts

Key Sources of Research

Deposits, All Commercial Banks (DPSACBW027SBOG)

Total Liabilities, All Commercial Banks (TLBACBW027NBOG)


Between deluge and drought:
The future of US bank liquidity and funding

Rebalancing the balance sheet during turbulent times



Assets and Liabilities of Commercial Banks in the United States – H.8

The geography of dollar funding of non-US banks1

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

Click to access 4425421.pdf

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

Click to access i3468e.pdf

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

Click to access Fischer-Kowalski_Huttler_1998.pdf

“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.

Click to access 2-05_Material_Flow_Cost_Accounting.pdf

Click to access WEF_Richards.pdf

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

Click to access CENCIC%20and%20RECHBERGER%202008%20Material%20Flow%20Analysis%20with%20Software%20STAN.pdf

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

Click to access 39777_Recovery_Key_Metals_Electronics_Industry_China_Opportunity_Circularity_report_2018.pdf

Sankey diagram





Click to access material_flows_in_the_united_states.pdf

Industrial ecology and input-output economics: An introduction

Sangwon Suh


Click to access Industrial-ecology-and-input-output-economics-An-introduction.pdf

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

Click to access ab5b067aacafe555acbc1e077b5b42e1fc92.pdf

Theory of materials and energy flow analysis in ecology and economics

Sangwon Suh


Click to access Materials-and-energy-flows-in-industry-and-ecosystem-networks.pdf

Conceptual Foundations and Applications of Physical Input-Output Tables

Stefan Giljum

Hubacek Klaus


Click to access Conceptual-Foundations-and-Applications-of-Physical-Input-Output-Tables.pdf

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

Stefan Giljum

Hubacek Klaus


Click to access 00b7d51cc1257aba71000000.pdf

Industrial Ecology: A Critical Review

Click to access IE.pdf

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

Click to access 561d652a08aecade1acb3bfc.pdf

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

Article in Economic Systems Research · December 2005

Click to access 0c960531f1d910cda1000000.pdf

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

Click to access Material_Basis.pdf

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

Click to access 0deec51b7274ca0035000000.pdf

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

Click to access 2550.pdf

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

Stefan Giljum a, Christian Lutz b,Ariane Jungnitz

Click to access Giljum%20et%20al_IIOA.pdf

Click to access jungnitzgiljumlutz.pdf

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)

Click to access material.pdf

Human Ecology: Industrial Ecology

Faye Duchin
Rensselaer Polytechnic Institute

Stephen H. Levine
Tufts University

Click to access rpi0603.pdf

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

XU Ming


Click to access 2010010204.pdf

Accounting for raw material equivalents of traded goods

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

Click to access working-paper-87-web.pdf

Material Flow Accounts and Policy. Data for Sweden 2004

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


Click to access mi1301_2004a01_br_mift0701.pdf

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

Jukka Hoffrén (ed.)

Click to access isbn_978-952-244-233-8.pdf

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

Click to access IO-Workshop-2017_Wieland_abstract.pdf

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

Click to access gpa_101_wa.pdf

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

Click to access IR-02-057.pdf

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

Click to access 6271.full.pdf

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

Click to access Raw_material_Germany.pdf

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

Click to access FULLTEXT01.pdf

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.

Click to access Re_Main_Document.pdf

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

Click to access 10_MFand_MRIO_CSIRO_English.pdf

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


Click to access 6988.pdf

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

Click to access Paper_Distelkamp_et_al.pdf

Material Flow Analysis to Evaluate Sustainability in Supply Chains

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

Click to access 4189.pdf

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

Helga Weisz , Faye Duchin

Click to access Physical%20and%20monetary%20input-output.pdf

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

Click to access WP2008-4.pdf

The Water Footprint Assessment Manual

Click to access TheWaterFootprintAssessmentManual_2.pdf

The New Plastics Economy
Rethinking the future of plastics

Click to access WEF_The_New_Plastics_Economy.pdf

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

Click to access Comparing-Input-Output-and-Process-LCA-Data.CE-form2-LM-edits.pdf

Managing Logistics Flows Through Enterprise Input-Output Models

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

Click to access InTech-Managing_logistics_flows_through_enterprise_input_output_models.pdf

Social Metabolism and Accounting Approaches


Ecological economics

Input-Output Analysis in Laptop Computer Manufacturing


Final Project Report, March 2004

Click to access 0304_WP_Biffaward_Steel_Al-Final.pdf

A Framework for Sustainable Materials Management

Joseph Fiksel

Click to access Framework_for_SMM.pdf

Energy and water conservation synergy in China: 2007–2012

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

Click to access Energy-and-water-conservation-synergy-in-China-2007-2012.pdf

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

Niels B. Schulz

Click to access IAS-WP136.pdf

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

Click to access 35_20100427111_Hoekstra-PIOT.pdf

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


Click to access 2016_SA_Network-Analysis-Aluminum_EST.pdf





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


Click to access Tracing-Chinas-energy-flow-and-carbon-dioxide-flow-based-on-Sankey-diagrams.pdf





Materials Flow and Sustainability





Life-cycle assessment






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


Click to access chapter1_frontmatter_lca101.pdf





Life cycle analysis (LCA) and sustainability assessment


Click to access IntroductiontoLCAAU32013.pdf

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

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


A special issue of Economic Systems Research published in 2013 discussed currently available GMRIO data bases.  There are two strands of research in development and use of these databases:

  • Trade flows and global supply chains
  • Environmental Impacts of Economic Growth, Trade and Globalization



  • IDE JETRO Asian IO Tables
  • EORA
  • OECD Inter-Country Input-Output (ICIO) tables
  • GRAM (Global Resource Accounting Model )
  • World Input-Output Database (WIOD).
  • Global Trade Analysis Project (GTAP)


Another recent development is development of Trade in Value added databases analyzing trade flows of intermediate goods and fragmented global supply chains and production networks.  These projects are currently underway at the time of writing of this post.

TIVA Databases

  • NA TiVA Project
  • The OECD-WTO TiVA database
  • APEC TiVA initiative


There are also EE- GMRIO (Environmentally extended GMRIO) discussed else where in a related post.


GMRIO Databases



The Global Resource Accounting Model (GRAM) is a multi-regional input-output model (MRIO), which currently distinguishes between 62 countries and one ‘rest of the world’ region and 48 industrial sectors per country or region. The heart of the model is made up of OECD data on bilateral trade flows and input-output tables for 1995 to 2010. Combined with additional data sets, such as CO2 emissions and material extraction, the model enables production-related variables to be attributed to end consumption.




Arnold Tukker & Erik Dietzenbacher
Published online: 21 Mar 2013
This review is the introduction to a special issue of Economic Systems Research on the topic of global multi regional input–output (GMRIO) tables, models, and analysis. It provides a short historical context of GMRIO development and its applications (many of which deal with environmental extensions) and presents the rationale for the major database projects presented in this special issue. Then the six papers are briefly introduced. This is followed by a concluding comparison of the characteristics of the main GMRIO databases developed thus far and an outlook of potential further developments.



Bo Meng , Yaxiong Zhang & Satoshi Inomata
Published online: 21 Mar 2013
International input–output (IO) tables are among the most useful tools for economic analysis. Since these tables provide detailed information about international production networks, they have recently attracted considerable attention in research on spatial economics, global value chains, and issues relating to trade in value added. The Institute of Developing Economies at the Japan External Trade Organization (IDE-JETRO) has more than 40 years of experience in the construction and analysis of international IO tables. This paper explains the development of IDE-JETRO’s multi-regional IO projects including the construction of the Asian International Input–Output table and the Transnational Inter regional Input–Output table between China and Japan. To help users understand the features of the tables, this paper also gives examples of their application.




Arnold Tukker , Arjan de Koning , Richard Wood , Troy Hawkins , Stephan Lutter , Jose
Published online: 21 Mar 2013
EXIOPOL (A New Environmental Accounting Framework Using Externality Data and Input–Output Tools for Policy Analysis) was a European Union (EU)-funded project creating a detailed, global, multi regional environmentally extended Supply and Use table (MR EE SUT) of 43 countries, 129 sectors, 80 resources, and 40 emissions. We sourced primary SUT and input–output tables from Eurostat and non-EU statistical offices. We harmonized and detailed them using auxiliary national accounts data and co-efficient matrices. Imports were allocated to countries of exports using United Nations Commodity Trade Statistics Database trade shares. Optimization procedures removed imbalances in these detailing and trade linking steps. Environmental extensions were added from various sources. We calculated the EU footprint of final consumption with resulting MR EE SUT. EU policies focus mainly on energy and carbon footprints. We show that the EU land, water, and material footprint abroad is much more relevant, and should be prioritized in the EU’s environmental product and trade policies.




Robbie M. Andrew & Glen P. Peters
Published online: 21 Mar 2013
Understanding the drivers of many environmental problems requires enumerating the global supply chain. Multi-region input–output analysis (MRIOA) is a well-established technique for this purpose, but constructing a multi-region input–output table (MRIOT) can be a formidable challenge. We constructed a large MRIOT using the Global Trade Analysis Project (GTAP) database of harmonised economic, IO, and trade data. We discuss the historical development of the GTAP-MRIO and describe its efficient construction. We provide updated carbon footprint estimates and analyse several issues relevant for MRIO construction and applications. We demonstrate that differences in environmental satellite accounts may be more important than differences in MRIOTs when calculating national carbon footprints. The GTAP-MRIO is a robust global MRIOT and, given its easy availability and implementation, it should allow the widespread application of global MRIOA by a variety of users.




Erik Dietzenbacher , Bart Los , Robert Stehrer , Marcel Timmer & Gaaitzen de Vries
Published online: 21 Mar 2013
This article describes the construction of the World Input–Output Tables (WIOTs) that constitute the core of the World Input–Output Database. WIOTs are available for the period 1995–2009 and give the values of transactions among 35 industries in 40 countries plus the ‘Rest of the World’ and from these industries to households, governments and users of capital goods in the same set of countries. The article describes how information from the National Accounts, Supply and Use Tables and International Trade Statistics have been harmonized, reconciled and used for estimation procedures to arrive at a consistent time series of WIOTs.




Manfred Lenzen , Daniel Moran , Keiichiro Kanemoto & Arne Geschke
Published online: 21 Mar 2013
There are a number of initiatives aimed at compiling large-scale global multi-region input–output (MRIO) tables complemented with non-monetary information such as on resource flows and environmental burdens. Depending on purpose or application, MRIO construction and usage has been hampered by a lack of geographical and sectoral detail; at the time of writing, the most advanced initiatives opt for a breakdown into at most 129 regions and 120 sectors. Not all existing global MRIO frameworks feature continuous time series, margins and tax sheets, and information on reliability and uncertainty. Despite these potential limitations, constructing a large MRIO requires significant manual labour and many years of time. This paper describes the results from a project aimed at creating an MRIO account that represents all countries at a detailed sectoral level, allows continuous updating, provides information on data reliability, contains table sheets expressed in basic prices as well as all margins and taxes, and contains a historical time series. We achieve these goals through a high level of procedural standardisation, automation, and data organisation.




Thomas Wiedmann & John Barrett
Published online: 21 Mar 2013
The impressive development in global multi-region input–output (IO) databases is accompanied by an increase in applications published in the scientific literature. However, it is not obvious whether the insights gained from these studies have indeed been used in political decision-making. We ask whether and to what extent there is policy uptake of results from environmentally extended multi-region IO (EE-MRIO) models and how it may be improved. We identify unique characteristics of such models not inherent to other approaches. We then present evidence from the UK showing that a policy process around consumption-based accounting for greenhouse gas emissions and resource use has evolved that is based on results from EE-MRIO modelling. This suggests that specific, policy-relevant information that would be impossible to obtain otherwise can be generated with the help of EE-MRIO models. Our analysis is limited to environmental applications of global MRIO models and to government policies in the UK.







From Economic Systems Research

Volume 26, 2014 – Issue 3: A Comparative Evaluation of Multi-Regional Input-Output Databases


Daniel Moran & Richard Wood
Published online: 14 Jul 2014

In this paper, we take an overview of several of the biggest independently constructed global multi-regional input–output (MRIO) databases and ask how reliable and consonant these databases are. The key question is whether MRIO accounts are robust enough for setting environmental policies. This paper compares the results of four global MRIOs: Eora, WIOD, EXIOBASE, and the GTAP-based OpenEU databases, and investigates how much each diverges from the multi-model mean. We also use Monte Carlo analysis to conduct sensitivity analysis of the robustness of each accounts’ results and we test to see how much variation in the environmental satellite account, rather than the economic structure itself, causes divergence in results. After harmonising the satellite account, we found that carbon footprint results for most major economies disagree by<10% between MRIOs. Confidence estimates are necessary if MRIO methods and consumption-based accounting are to be used in environmental policy-making at the national level.


Satoshi Inomata & Anne Owen

Published online: 11 Aug 2014

This editorial is the introduction to a special issue of Economics Systems Research on the topic of intercomparison of multi-regional input–output (MRIO) databases and analyses. It explains the rationale for dedicating an issue of this journal to this area of research. Then the six papers chosen for this issue are introduced. This is followed by a concluding section outlining future directions for developers and users of MRIO databases.


Please see my related posts:

Accounting For Global Carbon Emission Chains

Development of Global Trade and Production Accounts: UN SEIGA Initiative

Stock Flow Consistent Models for Ecological Economics



Key Sources of Research:


The World Input‐Output Database (WIOD): Contents, Sources and Methods

Edited by Marcel Timmer (University of Groningen)

With contributions from:
Abdul A. Erumban, Reitze Gouma, Bart Los, Umed Temurshoev and
Gaaitzen J. de Vries (University of Groningen)
Iñaki Arto, Valeria Andreoni Aurélien Genty, Frederik Neuwahl, José
M. Rueda‐Cantuche and Alejandro Villanueva (IPTS)
Joe Francois, Olga Pindyuk, Johannes Pöschl and Robert Stehrer
(WIIW), Gerhard Streicher (WIFO)

April 2012, Version 0.9

Click to access WIOD_sources.pdf




Analyzing Global Value Chains using the World Input-Output

Bart Los (University of Groningen)
with Marcel Timmer (Groningen), Gaaitzen de Vries
(Groningen) and Robert Stehrer (wiiw Vienna)

BBVA Foundation – Ivie Workshop, October 30, 2017, Valencia

Click to access B.-Los.pdf


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

Click to access na-tiva_white_paper_for_posting_revised_02-20.pdf





The Global MRIO Lab – charting the world economy,

Manfred Lenzen, Arne Geschke, Muhammad Daaniyall Abd Rahman, Yanyan
Xiao, Jacob Fry, Rachel Reyes, Erik Dietzenbacher, Satoshi Inomata, Keiichiro Kanemoto, Bart Los, Daniel Moran, Hagen Schulte in den Bäumen, Arnold Tukker, Terrie Walmsley, Thomas Wiedmann, Richard Wood & Norihiko Yamano


Economic Systems Research, 29:2, 158-186

Click to access Lenzen%20et%20al._2017_Economic%20Systems%20Research_The%20Global%20MRIO%20Lab–charting%20the%20world%20economy.pdf






Erik Dietzenbacher, Manfred Lenzen, Bart Los, Dabo Guan, Michael L. Lahr,
Ferran Sancho, Sangwon Suh & Cuihong Yang


Economic Systems Research, 25:4, 369-389

Click to access Guan-ESR-2013-IO%20next%2025%20years.pdf




OECD Inter-Country Input-Output (ICIO) Tables, 2016 edition



Trade in Value Added





The Global Resource Accounting Model (GRAM)
a methodological concept paper

Stefan Giljum a, Christian Lutz b, Ariane Jungnitz b

a Sustainable Europe Research Institute (SERI), Vienna, Austria
b Institute for Economic Structures Research (GWS), Osnabrück, Germany

April 2008

Click to access Giljum_et_al_GRAM_concept_paper_final.pdf





Thomas Wiedmann & John Barrett


Economic Systems Research, 25:1, 143-156

Click to access Wiedmann__Barrett_-_2013_-_Policy-relevant_applications_of_evironmentally_extended_MRIO_databases_-_experiences_from_the_UK.pdf




Erik Dietzenbacher , Bart Los , Robert Stehrer , Marcel Timmer & Gaaitzen de


Economic Systems Research, 25:1, 71-98,

Click to access WIOD%20construction.pdf



System of Environmental-Economic Accounting 2012— Applications and Extensions



Calculating Trade in Value Added


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

July 2017



World Input-Output Network

Federica Cerina, Zhen Zhu, Alessandro Chessa and Massimo Riccaboni

July 1, 2015

Click to access 336.pdf




Making Global Value Chain Research More Accessible

Lin Jones, William Powers, and Ravinder Ubee1

U.S. International Trade Commission, Office of Economics

October 21, 2013

Click to access ec201310a.pdf


On the Measurement of Upstreamness and Downstreamness in
Global Value Chains

Pol Antras
Harvard University and NBER
Davin Chor
National University of Singapore

October 30, 2017

Click to access upstream_ac_oct30_2017_withtables.pdf






Norihiko Yamano and Nadim Ahmad

Click to access OECD%20Input-Output%20Database.pdf





Arnold Tukker & Erik Dietzenbacher


Econ omic Systems Research, 25:1,1-19

Click to access UNSD%20-%20Tukker%20-%20Overview%20on%20International%20IO%20Tables%20-%202013.pdf



Erik Dietzenbacher , Bart Los , Robert Stehrer , Marcel Timmer & Gaaitzen de


Economic Systems Research, 25:1, 71-98

Click to access WIOD%20construction.pdf




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

Thomas Wiedmann




World Input-Output Network

Federica Cerina, Zhen Zhu, Alessandro Chessa, Massimo Riccaboni


Click to access pone.0134025.pdf



A Network of Networks Perspective on Global Trade

Julian Maluck, Reik V. Donner

Click to access pone.0133310.pdf





Konstantin Stadler, Kjartan Steen-Olsen & Richard Wood


Economic Systems Research, 26:3, 303-326

Click to access Stadler,%20Steen-olsen,%20Wood_2015_Unknown_the%20‘%20Rest%20of%20the%20World%20’%20–%20Estimating%20the%20Economic%20Structure%20of%20Missing%20Regions%20in%20Global%20Multi.pdf



“Trade, Environment, and Growth: Advanced topics in Input-Output Analysis”*

Professor: Erik Dietzenbacher (U. Groningen)

March 9-13, 2015

Click to access outline___trade_growth_and_the_environment_.pdf





Wassily Leontief and the discovery of the input-output approach

Click to access memo-18-2016-versjon-2.pdf



Networks of value added trade,

Amador, João; Cabral, Sónia


ECB Working Paper, No. 1931, ISBN 978-92-899-2179-4,

Click to access ecbwp1931.pdf



Arnold Tukker , Arjan de Koning , Richard Wood , Troy Hawkins , Stephan
Lutter , Jose Acosta , Jose M. Rueda Cantuche , Maaike Bouwmeester , Jan Oosterhaven ,
Thomas Drosdowski & Jeroen Kuenen


Economic Systems Research, 25:1,50-70

Click to access Tukker%20et%20al._2013_Economic%20Systems%20Research_Exiopol%20–%20Development%20and%20Illustrative%20Analyses%20of%20a%20Detailed%20Global%20Mr%20Ee%20SutIot.pdf




The World Input-Output Database (WIOD) project

Robert Stehrer

OECD-WPTSG meeting

November 18, 2009 – OECD, Paris

Click to access 44197850.pdf



The World Input-Output Database (WIOD): Construction, Challenges and Applications

Abdul Azeez Erumbana, Reitze Goumaa, Bart Losa,b, Robert Stehrerc, Umed
Temurshoevb, Marcel Timmer a,b,*, Gaaitzen de Vries

Paper prepared for World Bank workshop
“The Fragmentation of Global Production and Trade in Value Added”,
June 9-10, 2011.

Click to access PAPER_13_Erumban_Gouma_Los_Stehrer_Temurshoev_Timmer_deVries.pdf


The World Input-Output Database: Content, Concepts and Applications.

Timmer, M. P., Dietzenbacher, E., Los, B., Stehrer, R., & de Vries, G. J.


GGDC Working Papers; Vol. GD-144).

Click to access gd144.pdf



Measuring Global Value Chains with the WIOD (World Input-Output Database)

Marcel Timmer

Groningen Growth and Development Centre
University of Groningen
(presentation at OECD conference,
Paris, 21 September, 2010)

Click to access 1-3_Timmer.pdf




Global value chains, trade, jobs, and environment: The new WIOD database

Hubert Escaith, Marcel Timmer

13 May 2012


Wassily Leontief and the discovery of the input-output approach

Olav Bjerkholt


Click to access 877412162.pdf





Guillaume Daudin (Lille-I (EQUIPPE) & Sciences Po (OFCE), Christine Rifflart, Danielle
Schweisguth (Sciences Po (OFCE))1

This version: July 2009

Click to access WP2009-18.pdf




An Anatomy of the Global Trade Slowdown based on the WIOD 2016 Release

Marcel P. Timmer, Bart Los,
Robert Stehrer, and Gaaitzen J. de Vries

December 2016

Click to access gd162.pdf

External Balance sheets of Nations

External Balance sheets of Nations

Also read my other related post.

Foundations of Balance Sheet Economics


From The role of external balance sheets in the financial crisis

Gross external balance sheets are important in explaining the incidence of the financial crisis across economies. Just as for banks, leverage of the national balance sheet was an indicator of subsequent vulnerability. Countries that also experienced strong domestic credit growth, in part fuelled by ‘savings glut’ net capital inflows, suffered particularly badly. And banks’ balance sheets were critical in the transmission mechanism: high gross external interbank debt — the ‘banking glut’ — and maturity and currency mismatches, contributed to foreign rollover risk.


From  Bilateral Financial Linkages and Global Imbalances: a View on The Eve of the Financial Crisis

During the last 15 years international financial integration has increased dramatically. This process was characterized in particular by two related trends: an explosion in the size of cross-border capital inflows and outflows, reflected in rapidly expanding stocks of external assets and liabilities; and the emergence of global imbalances, reflected in an increased dispersion in world current account positions and a sharp widening of global net debtor and creditor positions. With cross-border financial linkages becoming much stronger, measuring them accurately is essential to understand the impact and international transmission of shocks, as the global financial crisis has clearly shown. However, while research on causes and consequences of global imbalances and international financial integration has been extensive, and recent pioneering work by Kubelec and Sa (2010) has documented the increase in bilateral financial linkages among 18 advanced economies and emerging markets, we still lack a comprehensive global picture of bilateral net and gross positions across countries. This paper takes a first step towards filling that gap.

From The geographical composition of national external balance sheets: 1980–2005

Financial globalisation has been one of the most striking phenomena happening in the world economy in the past two decades. Until recently, very little was known about the size and composition of countries’ external nancial assets and liabilities. This gap was partly narrowed by the work of Lane and Milesi-Ferretti, which provides estimates of the total external nancial assets and liabilities of 145 countries, from 1970 to 2004. These data show that there has been a marked increase in the ratio of foreign assets and liabilities to GDP, particularly since the mid-1990s. This increase has been especially pronounced among industrial countries, where nancial integration has exceeded trade integration. However, very little is known about the geographical composition of assets and liabilities. This paper contributes to a better understanding of the geographical composition of countries’ external positions by constructing a data set of stocks of bilateral assets and liabilities for a group of 18 countries, covering the period from 1980 to 2005.

The data distinguish between four asset classes: foreign direct investment, portfolio equity, debt, and foreign exchange reserves. For the rst three asset classes, missing data are constructed using gravity models, which have been extensively applied to explain cross-border trade and have been increasingly used to explain nancial stocks and ows. These models explain bilateral assets by the geographical and historical proximity between the source and host countries, including variables such as distance, time difference, whether the source and host countries share a common border, a common language, or have colonial links. These models tend to have a large explanatory power, suggesting that nancial markets are not frictionless, but are segmented by information asymmetries and familiarity effects. For reserves, a two-step procedure is adopted. First, data on the currency composition are collected and then are translated into geographical composition.


Key Sources of Research:

Financial globalisation, external balance sheets and economic adjustment

By Chris Kubelec


Click to access qb070204.pdf


Global imbalances and external adjustment after the crisis

Philip R. Lane

Gian Maria Milesi-Ferretti

This draft: May 15, 2014


Click to access LMF%20EXTADJUST%20July2014.pdf


The External Wealth of Nations Mark II: Revised and Extended Estimates of Foreign Assets and Liabilities, 1970–2004

Philip R. Lane and Gian Maria Milesi-Ferretti



Click to access wp0669.pdf


Europe and Global Imbalances

Philip R. Lane and Gian Maria Milesi-Ferretti


Click to access wp07144.pdf


A Global Perspective on External Positions

Philip R. Lane and Gian Maria Milesi-Ferretti

Click to access c0122.pdf


Capital Flows to Central and Eastern Europe

Philip R. Lane

Gian Maria Milesi-Ferretti

Click to access iiisdp161.pdf


Cross-border portfolios: assets, liabilities, and non- flow adjustments

Stephanie E Curcuru,2 Charles P Thomas,2 Francis E Warnock

Click to access bispap82a.pdf


Why do Foreigners Invest in the United States?

Kristin J. Forbes


Click to access Why_Do_Foreigners_Invest_in_US-03-15-08.pdf



Kristin J. Forbes

Click to access cj27n2-9.pdf


Patterns of International Capital Flows and Their Implications for Economic Development

Eswar Prasad, Raghuram G. Rajan, and Arvind Subramanian

Click to access NEG11Rajan.pdf


Financial Globalisation and the Crisis

Philip R. Lane

June 2012

Click to access lseGC_lane_FinGlob.pdf


The financial crisis and its international transmission: some tentative lessons 

Gian Maria Milesi-Ferretti

September 14, 2009

Click to access 1_Milesi_Ferretti.pdf


External liabilities and crises

Luis A.V. Catão , Gian Maria Milesi-Ferretti


Click to access Catao_Milesi-Ferretti_External%20Liabil_Crises_jie%2014.pdf


International Investment Patterns

Philip R. Lane
Gian Maria Milesi-Ferretti


Click to access wp04134.pdf


Where Did All the Borrowing Go?
A Forensic Analysis of the U.S. External Position

Prepared by Philip R. Lane and Gian Maria Milesi-Ferretti1

February 2008

Click to access wp0828.pdf


An Elephant in the Room: The US External Balance Sheet and International Monetary Power


Iain Hardie

Sylvia Maxfield


Click to access An%20Elephant%20in%20the%20Room%20Brown%20Oct%202015.pdf


THE EXTERNAL WEALTH OF NATIONS Measures of Foreign Assets and Liabilities For Industrial and Developing Countries

Philip Lane

Gian Maria Milesi-Ferretti

August 14, 2000

Click to access TEPNo4PL21.pdf


The role of external balance sheets in the financial crisis

Yaser Al-Saffar, Wolfgang Ridinger and Simon Whitaker


Click to access fs_paper24.pdf


Domestic Credit Growth and International Capital Flows

Philip R. Lane and Peter McQuade


Click to access ecbwp1566.pdf



Alfredo Pistelli

Jorge Selaive

Rodrigo O. Valdés


Click to access 6360170.pdf


External Balance Sheets as Countercyclical Crisis Buffers

Joseph Joyce


Click to access MPRA_paper_66039.pdf


Bilateral Financial Linkages and Global Imbalances: a View on the Eve of the Financial Crisis

Gian Maria Milesi-Ferretti

Francesco Strobbe

Natalia Tamirisa

This Draft: May 13, 2011


Click to access Milesi-Ferretti_Bilateral%20Financial%20Linkages%20and%20Global%20Imbalances.pdf


Financial Globalization and Cross-Country Spillovers

Chris Kubelec  and Filipa Sa


The geographical composition of national external balance sheets: 1980–2005

Chris Kubelec and Filipa Sá

March 2010

Click to access wp384.pdf


U.S. Net International Investment Position


The International Balance Sheets of China and India

Philip R. Lane

Preliminary Draft. March 2006.


Click to access Philip_lane.pdf


Feedback Thought in Economics and Finance

Feedback Thought in Economics and Finance

  • Negative Feedbacks
  • Positive Feedbacks
  • Stocks and Flows
  • Limiting Factors


Key People:

  • Jay Forrester
  • George Richardson
  • John Sterman
  • Michael Radzicki
  • Mikhail Oet
  • Oleg Pavlov
  • Eric D. Beinhocker
  • Stuart A. Umpleby
  • Khalid Saeed
  • Kaoru Yamaguchi


Reflexivity and Second order economics are closely related concepts.


From System Dynamics and Its Contribution to Economics and Economic Modeling


System dynamics is a computer simulation modeling methodology that is used to analyze complex nonlinear dynamic feedback systems for the purposes of generating insight and designing policies that will improve system performance. It was originally created in 1957 by Jay W. Forrester of the Massachusetts Institute of Technology as a methodology for building computer simulation models of problematic behavior within corporations. The models were used to design and test policies aimed at altering a corporation’s structure so that its behavior would improve and become more robust.

Today, system dynamics is applied to a large variety of problems in a multitude of academic disciplines, including economics. System dynamics models are created by identifying and linking the relevant pieces of a system’s structure and simulating the behavior generated by that structure. Through an iterative process of structure identification, mapping, and simulation a model emerges that can explain (mimic) a system’s problematic behavior and serve as a vehicle for policy design and testing. From a system dynamics perspective a system’s structure consists of stocks, flows, feedback loops, and limiting factors.

Stocks can be thought of as bathtubs that accumulate/de-cumulate a system’s flows over time. Flow can be thought of as pipe and faucet assemblies that fill or drain the stocks. Mathematically, the process of flows accumulating/de-cumulating in stocks is called integration. The integration process creates all dynamic behavior in the world be it in a physical system, a biological system, or a socioeconomic system. Examples of stocks and flows in economic systems include a stock of inventory and its inflow of production and its outflow of sales, a stock of the book value of a firm’s capital and its inflow of investment  spending and its outflow of depreciation, and a stock of employed labor and its inflow of hiring and its outflow of labor separations.

Feedback is the transmission and return of information about the amount of information or material that has accumulated in a system’s stocks. Information travels from a stock back to its flow(s) either directly or indirectly, and this movement of information causes the system’s faucets to open more, close a bit, close all the way, or stay in the same place. Every feedback loop has to contain at least one stock so that a simultaneous equation situation can be avoided and a model’s behavior can be revealed recursively. Loops with a single stock are termed minor, while loops containing more than one stock are termed major. 

Two types of feedback loops exist in system dynamics modeling: positive loops and negative loops. Generally speaking, positive loops generate self-reinforcing behavior and are responsible for the growth or decline of a system. Any relationship that can be termed a virtuous or vicious circle is thus a positive feedback loop. Examples of positive loops in economic systems include path dependent processes, increasing returns, speculative bubbles, learning by-doing, and many of the relationships found in macroeconomic growth theory. Forrester [12], Radzicki and Sterman [46],Moxnes [32], Sterman (Chap. 10 in [55]), Radzicki [44], Ryzhenkov [49], and Weber [58] describe system dynamics models of economic systems that possess dominant positive feedback processes.

Negative feedback loops generate goal-seeking behavior and are responsible for both stabilizing systems and causing them to oscillate. When a negative loop detects a gap between a stock and its goal it initiates corrective action aimed at closing the gap. When this is accomplished without a significant time delay, a system will adjust smoothly to its goal. On the other hand, if there are significant time lags in the corrective actions of a negative loop, it can overshoot or undershoot its goal and cause the system to oscillate. Examples of negative feedback processes in economic systems include equilibrating mechanisms (“auto-pilots”) such as simple supply and demand relationships, stock adjustment models for invetory control, any purposeful behavior, and many of the relationships found in macroeconomic business cycle theory. Meadows [27], Mass [26], Low [23], Forrester [12], and Sterman [54] provide examples of system dynamics models that generate cyclical behavior at the macro-economic and micro-economic levels.

From a system dynamics point of view, positive and negative feedback loops fight for control of a system’s behavior. The loops that are dominant at any given time determine a system’s time path and, if the system is nonlinear, the dominance of the loops can change over time as the system’s stocks fill and drain. From this perspective, the dynamic behavior of any economy that is, the interactions between the trend and the cycle in an economy over time can be explained as a fight for dominance between the economy’s most significant positive and negative feedback loops.


Key Sources of Research:


Systemic Financial Feedbacks – Conceptual Framework and Modeling Implications

Dieter Gramlich1 and Mikhail V. Oet

Click to access 54992d5c0cf2519f5a1df20b.pdf




Mikhail V. Oet

Oleg V. Pavlov

Click to access P1441.pdf



Mr. Hamilton, Mr. Forrester, and a Foundation for Evolutionary Economics

Michael J. Radzicki


Click to access 0a85e52e41951a468c000000.pdf


European Contributions to Evolutionary Institutional Economics: The Cases of ‘Cumulative Circular Causation’ (CCC) and ‘Open Systems Approach’ (OSA).
Some Methodological and Policy Implications


Sebastian Berger and Wolfram Elsner


System Dynamicsand Its Contribution to Economics and Economic Modeling



Click to access 02e7e53331fe5f394b000000.pdf



Institutional Economics, Post Keynesian Economics, and System Dynamics: Three Strands of a Heterodox Economics Braid

Michael J. Radzicki, Ph.D.

Click to access 02e7e53331eeea388c000000.pdf



Was Alfred Eichner a System Dynamicist?


Michael J. Radzicki

Click to access 0f317536d3f41a13fb000000.pdf


Second-Order Economics as an Example of Second-Order Cybernetics

Stuart A. Umpleby


Click to access 890.pdf


Reflexivity, complexity, and the nature of social science

Eric D. Beinhocker


Click to access Beinhocker%20(JEM%202013).pdf


Path dependence, its critics and the quest for ‘historical economics’


Paul A. David

Click to access 0deec53b482217c114000000.pdf


Endogenous Feedback Perspective on Money in a Stock-Flow Consistent Model

I. David Wheat
University of Bergen


Click to access Wheat%20Endogenous%20Feedback%20Perspective%20on%20Money%20WP.pdf


Classical Economics on Limits to Growth

Khalid Saeed


Click to access Classical%20Economics%20on%20Limits%20to%20Growth.pdf



Misperceptions of Feedback in Dynamic Decisionmaking

John D. Sterman


Click to access 54359e4e0cf2bf1f1f2b3520.pdf


Learning in and about complex systems

John D. Sterman


Click to access sterman-learning-in-and-about-complex-systems.pdf


Micro-worlds and Evolutionary Economics

Michael J. Radzicki

Click to access radzi533.pdf


Feedback Thought in Social Science and Systems Theory

George Richardson

Pegasus Communications, Inc. ©1999


The Feedback concept in American Social Sciences 

George Richardson


Click to access richa001.pdf


Evolutionary Economics and System Dynamics

Radzicki and Sterman


Effects of Feedback Complexity on Dynamic Decision Making
Ernst Diehl, John D. Sterman

Organizational Behavior and Human Decision Processes

Volume 62, Issue 2, May 1995, Pages 198-215


Old Wine in a New Bottle:
Towards a Common Language for Post-Keynesian Macroeconomics Model

Ginanjar Utama


Click to access P1307.pdf


On Component Based Modeling Approach using System Dynamics for The Financial System (With a Case Study of Keen-Minsky Model)

Ginanjar Utama


Click to access P1209.pdf


On the Monetary and Financial Stability under A Public Money System

– Modeling the American Monetary Act Simplified –

Kaoru Yamaguchi


Click to access P1065.pdf


Integration of Real and Monetary Sectors with Labor Market
– SD Macroeconomic Modeling (3) –

Kaoru Yamaguchi


Balance of Payments and Foreign Exchange Dynamics

– SD Macroeconomic Modeling (4) –

Kaoru Yamaguchi, Ph.D


Click to access YAMAG211.pdf



Money and Macroeconomic Dynamics

Accounting System Dynamics Approach

Kaoru Yamaguchi, Ph.D


Click to access Macro%20Dynamics.pdf


Does Money Matter on the Formation of Business Cycles and Economic Recessions ?
– SD Simulations of A Monetary Goodwin Model –


Kaoru Yamaguchi

Click to access DBS12-01.pdf


Head and Tail of Money Creation and its System Design Failures

– Toward the Alternative System Design –

JFRC Working Paper No. 01-2016

Kaoru Yamaguchi, Ph.D.

Yokei Yamaguchi

Click to access Head-and-Tail-2016_WP__-_Japan_Futures_Research_Center.pdf


Modelling the Great Transition


Emanuele Campiglio

New Economics Foundation

Click to access Emanuel-SD-conference-9-2-12.pdf


The role of System Dynamics modelling to understand food chain complexity and address challenges for sustainability policies

Irene Monasterolo1, Roberto Pasqualino, Edoardo Mollona


Click to access CFP3-06_Full_Paper.pdf


Dynamic regional economic modeling: a systems approach

I. David Wheat



Click to access 1.17_wheat_pawluczuk.pdf


Expectation Formation and Parameter Estimation in Uncertain Dynamical Systems: The System Dynamics Approach to Post Keynesian-Institutional Economics



Michael J. Radzicki


Click to access 0deec536d3da974962000000.pdf


The Circular and Cumulative Structure of Administered Pricing

Mark Nichols, Oleg Pavlov, and Michael J. Radzicki


Click to access 02e7e5282d33c933df000000.pdf


A System Dynamics Approach to the Bhaduri‐Marglin Model

Klaus D. John

Click to access P1306.pdf


An Institutional Dynamics Model of the Euro zone crisis: Greece as an Illustrative Example

Domen Zavrl

Miroljub Kljajić

Click to access P1144.pdf


Is system dynamics modelling of relevance to neoclassical economists? 

Douglas J. Crookes Martin P. De Wit

Click to access 00b7d53861d6b14d9f000000.pdf


System dynamics modelling and simulating the effects of intellectual capital on economic growth

Ivona Milić Beran