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.
CIRCULAR ECONOMY: THE NEW NORMAL?
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
Cradle to Cradle
Closed Supply Chains
From Input to the European Commission from European EPAs about monitoring progress of the transition towards a circular economy in the European Union
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
Economic Input Output LCA
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
From Hybrid Sankey diagrams: Visual analysis of multidimensional data forunderstanding 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
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.
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
Public traded companies are always under pressure to show earnings growth and sales revenue growth to enhance shareholder value.
How do they do it when markets have matured and economy has slowed?
Increase Market Share
Find New Markets
Create New products and servicces
How do then companies lower their costs?
Vertical Mergers and Acquisitions
Outsourcing (Sourcing parts and components / Intermediate Goods / Inputs from cross border)
Offshoring (Shifting Production cross border)
How do then companies increase their market share?
Horizontal Mergers and Acquisitions
Cross Border Markets Share (Sales in other countries)
In the last thirty years, this is exactly what has happened in US economy.
Macro Trends of increase in Outsourcing/Offshoring, Increase in Market Concentration, Increase in Inequality, Increase in Corporate Profits, Rising Equity Prices, Slower Productivity Growth, Lower Interest Rates, Low Labor Share, and Capital Share.
Please see my other posts expanding on these issues.
Please note that these forces are continuing and trends will remain on current trajectory.
Stakeholder vs Shareholder Capitalism
Slow Productivity Growth
Rising Market Concentration
Rising Equities Market
Dupont Ratio Analysis
Financial Planning (Micro – Firm Level)
Economic Planning (Macro- Aggregate Level)
From SHAREHOLDER CAPITALISM: A SYSTEM IN CRISIS
Our current, highly financialised, form of shareholder capitalism is not just failing to provide new capital for investment, it is actively undermining the ability of listed companies to reinvest their own profits. The stock market has become a vehicle for extracting value from companies, not for injecting it.
No wonder that Andy Haldane, Chief Economist of the Bank of England, recently suggested that shareholder capitalism is ‘eating itself.’1 Corporate governance has become dominated by the need to maximise short-term shareholder returns. At the same time, financial markets have grown more complex, highly intermediated, and similarly shorttermist, with shares increasingly seen as paper assets to be traded rather than long term investments in sound businesses.
This kind of trading is a zero-sum game with no new wealth, let alone social value, created. For one person to win, another must lose – and increasingly, the only real winners appear to be the army of financial intermediaries who control and perpetuate the merry-goround. There is nothing natural or inevitable about the shareholder-owned corporation as it currently exists. Like all economic institutions, it is a product of political and economic choices which can and should be remade if they no longer serve our economy, society, or environment.
Here’s the impact this shareholder model is currently having:
• Economy: Shareholder capitalism is holding back productive investment. Even the Chief Executive of BlackRock, the world’s largest asset manager, has admitted that pressure to keep the share price high means corporate leaders are ‘underinvesting in innovation, skilled workforces or essential capital expenditures.’ 2
• Society: Shareholder capitalism is driving inequality. There is growing evidence that attempts to align executive pay with shareholder value are largely responsible for the ballooning of salaries at the top. The prioritisation of shareholder interests has also contributed to a dramatic decline in UK wages relative to profits, helping to explain the failure of ordinary people’s living standards to rise in line with economic growth.
• Environment: Shareholder capitalism helps to drive environmental destruction. It does this by driving risky shortterm behaviour, such as fossil fuel extraction, which ignores long-term environmental risks.
The idea that shareholder capitalism is the most efficient way to mobilise large amounts of capital is no longer tenable.
We need both to create new models of companies, and implement new ways of organising investment that are fit for building an inclusive, equal, and sustainable economy.
Companies should be explicitly accountable to a mission and a set of interests beyond shareholder returns. Equally, investment must provide long-term capital for socially and environmentally useful projects, and damaging forms of speculation must be restricted.
For most people, our economy simply is not working, and the damaging aspects of shareholder capitalism are at least in part responsible. Reforming shareholder capitalism must not be dismissed as too difficult – the crisis is too urgent for that. We can take the first steps towards a better economic model right now. It’s time to act.
A Crash Course in Dupont Financial Ratio Analysis
What happens when economic growth slows ?
What happens when profit margins decline ?
What happens when Sales growth is limited ?
What does lead to Mergers and Acquisitions ?
What is the impact of Cost of Capital ?
What is EVA (Economic Value Added) ?
What is impact of Outsourcing/Offshoring on Financial Ratios ?
What is impact of Mergers and Acquisitions on Financial Ratios ?
What is impact of Stock Buy Backs on Financial Ratios ?
What is impact of Dividends on Financial Ratios ?
ROS (Return on Sales)
ROE (Return on Equities)
ROA (Return on Assets)
ROIC (Return on Invested Capital)
EVA (Economic Value Added)
MVA (Market Value Added)
From The DuPont Equation, ROE, ROA, and Growth
The DuPont Equation
The DuPont equation is an expression which breaks return on equity down into three parts: profit margin, asset turnover, and leverage.
Explain why splitting the return on equity calculation into its component parts may be helpful to an analyst
By splitting ROE into three parts, companies can more easily understand changes in their returns on equity over time.
As profit margin increases, every sale will bring more money to a company’s bottom line, resulting in a higher overall return on equity.
As asset turnover increases, a company will generate more sales per asset owned, resulting in a higher overall return on equity.
Increased financial leverage will also lead to an increase in return on equity, since using more debt financing brings on higher interest payments, which are tax deductible.
competitive advantage: something that places a company or a person above the competition
The DuPont Equation
The DuPont equation is an expression which breaks return on equity down into three parts. The name comes from the DuPont Corporation, which created and implemented this formula into their business operations in the 1920s. This formula is known by many other names, including DuPont analysis, DuPont identity, the DuPont model, the DuPont method, or the strategic profit model.
The DuPont Equation: In the DuPont equation, ROE is equal to profit margin multiplied by asset turnover multiplied by financial leverage.
Under DuPont analysis, return on equity is equal to the profit margin multiplied by asset turnover multiplied by financial leverage. By splitting ROE (return on equity) into three parts, companies can more easily understand changes in their ROE over time.
Components of the DuPont Equation: Profit Margin
Profit margin is a measure of profitability. It is an indicator of a company’s pricing strategies and how well the company controls costs. Profit margin is calculated by finding the net profit as a percentage of the total revenue. As one feature of the DuPont equation, if the profit margin of a company increases, every sale will bring more money to a company’s bottom line, resulting in a higher overall return on equity.
Components of the DuPont Equation: Asset Turnover
Asset turnover is a financial ratio that measures how efficiently a company uses its assets to generate sales revenue or sales income for the company. Companies with low profit margins tend to have high asset turnover, while those with high profit margins tend to have low asset turnover. Similar to profit margin, if asset turnover increases, a company will generate more sales per asset owned, once again resulting in a higher overall return on equity.
Components of the DuPont Equation: Financial Leverage
Financial leverage refers to the amount of debt that a company utilizes to finance its operations, as compared with the amount of equity that the company utilizes. As was the case with asset turnover and profit margin, Increased financial leverage will also lead to an increase in return on equity. This is because the increased use of debt as financing will cause a company to have higher interest payments, which are tax deductible. Because dividend payments are not tax deductible, maintaining a high proportion of debt in a company’s capital structure leads to a higher return on equity.
The DuPont Equation in Relation to Industries
The DuPont equation is less useful for some industries, that do not use certain concepts or for which the concepts are less meaningful. On the other hand, some industries may rely on a single factor of the DuPont equation more than others. Thus, the equation allows analysts to determine which of the factors is dominant in relation to a company’s return on equity. For example, certain types of high turnover industries, such as retail stores, may have very low profit margins on sales and relatively low financial leverage. In industries such as these, the measure of asset turnover is much more important.
High margin industries, on the other hand, such as fashion, may derive a substantial portion of their competitive advantage from selling at a higher margin. For high end fashion and other luxury brands, increasing sales without sacrificing margin may be critical. Finally, some industries, such as those in the financial sector, chiefly rely on high leverage to generate an acceptable return on equity. While a high level of leverage could be seen as too risky from some perspectives, DuPont analysis enables third parties to compare that leverage with other financial elements that can determine a company’s return on equity.
ROE and Potential Limitations
Return on equity measures the rate of return on the ownership interest of a business and is irrelevant if earnings are not reinvested or distributed.
Calculate a company’s return on equity
Return on equity is an indication of how well a company uses investment funds to generate earnings growth.
Returns on equity between 15% and 20% are generally considered to be acceptable.
Return on equity is equal to net income (after preferred stock dividends but before common stock dividends) divided by total shareholder equity (excluding preferred shares ).
Stock prices are most strongly determined by earnings per share (EPS) as opposed to return on equity.
fundamental analysis: An analysis of a business with the goal of financial projections in terms of income statement, financial statements and health, management and competitive advantages, and competitors and markets.
Return On Equity
Return on equity (ROE) measures the rate of return on the ownership interest or shareholders’ equity of the common stock owners. It is a measure of a company’s efficiency at generating profits using the shareholders’ stake of equity in the business. In other words, return on equity is an indication of how well a company uses investment funds to generate earnings growth. It is also commonly used as a target for executive compensation, since ratios such as ROE tend to give management an incentive to perform better. Returns on equity between 15% and 20% are generally considered to be acceptable.
Return on equity is equal to net income, after preferred stock dividends but before common stock dividends, divided by total shareholder equity and excluding preferred shares.
Return On Equity: ROE is equal to after-tax net income divided by total shareholder equity.
Expressed as a percentage, return on equity is best used to compare companies in the same industry. The decomposition of return on equity into its various factors presents various ratios useful to companies in fundamental analysis.
ROE Broken Down: This is an expression of return on equity decomposed into its various factors.
The practice of decomposing return on equity is sometimes referred to as the “DuPont System. ”
Potential Limitations of ROE
Just because a high return on equity is calculated does not mean that a company will see immediate benefits. Stock prices are most strongly determined by earnings per share (EPS) as opposed to return on equity. Earnings per share is the amount of earnings per each outstanding share of a company’s stock. EPS is equal to profit divided by the weighted average of common shares.
Earnings Per Share: EPS is equal to profit divided by the weighted average of common shares.
The true benefit of a high return on equity comes from a company’s earnings being reinvested into the business or distributed as a dividend. In fact, return on equity is presumably irrelevant if earnings are not reinvested or distributed.
Assessing Internal Growth and Sustainability
Sustainable– as opposed to internal– growth gives a company a better idea of its growth rate while keeping in line with financial policy.
Calculate a company’s internal growth and sustainability ratios
The internal growth rate is a formula for calculating the maximum growth rate a firm can achieve without resorting to external financing.
Sustainable growth is defined as the annual percentage of increase in sales that is consistent with a defined financial policy.
Another measure of growth, the optimal growth rate, assesses sustainable growth from a total shareholder return creation and profitability perspective, independent of a given financial strategy.
retention: The act of retaining; something retained
retention ratio: retained earnings divided by net income
sustainable growth rate: the optimal growth from a financial perspective assuming a given strategy with clear defined financial frame conditions/ limitations
Internal Growth and Sustainability
The true benefit of a high return on equity arises when retained earnings are reinvested into the company’s operations. Such reinvestment should, in turn, lead to a high rate of growth for the company. The internal growth rate is a formula for calculating maximum growth rate that a firm can achieve without resorting to external financing. It’s essentially the growth that a firm can supply by reinvesting its earnings. This can be described as (retained earnings)/(total assets ), or conceptually as the total amount of internal capital available compared to the current size of the organization.
We find the internal growth rate by dividing net income by the amount of total assets (or finding return on assets ) and subtracting the rate of earnings retention. However, growth is not necessarily favorable. Expansion may strain managers’ capacity to monitor and handle the company’s operations. Therefore, a more commonly used measure is the sustainable growth rate.
Sustainable growth is defined as the annual percentage of increase in sales that is consistent with a defined financial policy, such as target debt to equity ratio, target dividend payout ratio, target profit margin, or target ratio of total assets to net sales.
We find the sustainable growth rate by dividing net income by shareholder equity (or finding return on equity) and subtracting the rate of earnings retention. While the internal growth rate assumes no financing, the sustainable growth rate assumes you will make some use of outside financing that will be consistent with whatever financial policy being followed. In fact, in order to achieve a higher growth rate, the company would have to invest more equity capital, increase its financial leverage, or increase the target profit margin.
Optimal Growth Rate
Another measure of growth, the optimal growth rate, assesses sustainable growth from a total shareholder return creation and profitability perspective, independent of a given financial strategy. The concept of optimal growth rate was originally studied by Martin Handschuh, Hannes Lösch, and Björn Heyden. Their study was based on assessments on the performance of more than 3,500 stock-listed companies with an initial revenue of greater than 250 million Euro globally, across industries, over a period of 12 years from 1997 to 2009.
Due to the span of time included in the study, the authors considered their findings to be, for the most part, independent of specific economic cycles. The study found that return on assets, return on sales and return on equity do in fact rise with increasing revenue growth of between 10% to 25%, and then fall with further increasing revenue growth rates. Furthermore, the authors attributed this profitability increase to the following facts:
Companies with substantial profitability have the opportunity to invest more in additional growth, and
Substantial growth may be a driver for additional profitability, whether by attracting high performing young professionals, providing motivation for current employees, attracting better business partners, or simply leading to more self-confidence.
However, according to the study, growth rates beyond the “profitability maximum” rate could bring about circumstances that reduce overall profitability because of the efforts necessary to handle additional growth (i.e., integrating new staff, controlling quality, etc).
Dividend Payments and Earnings Retention
The dividend payout and retention ratios offer insight into how much of a firm’s profit is distributed to shareholders versus retained.
Calculate a company’s dividend payout and retention ratios
Many corporations retain a portion of their earnings and pay the remainder as a dividend.
Dividends are usually paid in the form of cash, store credits, or shares in the company.
Cash dividends are a form of investment income and are usually taxable to the recipient in the year that they are paid.
Dividend payout ratio is the fraction of net income a firm pays to its stockholders in dividends.
Retained earnings can be expressed in the retention ratio.
stock split: To issue a higher number of new shares to replace old shares. This effectively increases the number of shares outstanding without changing the market capitalization of the company.
Dividend Payments and Earnings Retention
Dividends are payments made by a corporation to its shareholder members. It is the portion of corporate profits paid out to stockholders. On the other hand, retained earnings refers to the portion of net income which is retained by the corporation rather than distributed to its owners as dividends. Similarly, if the corporation takes a loss, then that loss is retained and called variously retained losses, accumulated losses or accumulated deficit. Retained earnings and losses are cumulative from year to year with losses offsetting earnings. Many corporations retain a portion of their earnings and pay the remainder as a dividend.
A dividend is allocated as a fixed amount per share. Therefore, a shareholder receives a dividend in proportion to their shareholding. Retained earnings are shown in the shareholder equity section in the company’s balance sheet –the same as its issued share capital.
Public companies usually pay dividends on a fixed schedule, but may declare a dividend at any time, sometimes called a “special dividend” to distinguish it from the fixed schedule dividends. Dividends are usually paid in the form of cash, store credits (common among retail consumers’ cooperatives), or shares in the company (either newly created shares or existing shares bought in the market). Further, many public companies offer dividend reinvestment plans, which automatically use the cash dividend to purchase additional shares for the shareholder.
Cash dividends (most common) are those paid out in currency, usually via electronic funds transfer or a printed paper check. Such dividends are a form of investment income and are usually taxable to the recipient in the year they are paid. This is the most common method of sharing corporate profits with the shareholders of the company. For each share owned, a declared amount of money is distributed. Thus, if a person owns 100 shares and the cash dividend is $0.50 per share, the holder of the stock will be paid $50. Dividends paid are not classified as an expense but rather a deduction of retained earnings. Dividends paid do not show up on an income statement but do appear on the balance sheet.
Stock dividends are those paid out in the form of additional stock shares of the issuing corporation or another corporation (such as its subsidiary corporation). They are usually issued in proportion to shares owned (for example, for every 100 shares of stock owned, a 5% stock dividend will yield five extra shares). If the payment involves the issue of new shares, it is similar to a stock split in that it increases the total number of shares while lowering the price of each share without changing the market capitalization, or total value, of the shares held.
Dividend Payout and Retention Ratios
Dividend payout ratio is the fraction of net income a firm pays to its stockholders in dividends:
The part of the earnings not paid to investors is left for investment to provide for future earnings growth. These retained earnings can be expressed in the retention ratio. Retention ratio can be found by subtracting the dividend payout ratio from one, or by dividing retained earnings by net income.
Dividend Payout Ratio: The dividend payout ratio is equal to dividend payments divided by net income for the same period.
Relationships between ROA, ROE, and Growth
Return on assets is a component of return on equity, both of which can be used to calculate a company’s rate of growth.
Discuss the different uses of the Return on Assets and Return on Assets ratios
Return on equity measures the rate of return on the shareholders ‘ equity of common stockholders.
Return on assets shows how profitable a company’s assets are in generating revenue.
In other words, return on assets makes up two-thirds of the DuPont equation measuring return on equity.
Capital intensity is the term for the amount of fixed or real capital present in relation to other factors of production. Rising capital intensity pushes up the productivity of labor.
return on common stockholders’ equity: a fiscal year’s net income (after preferred stock dividends but before common stock dividends) divided by total equity (excluding preferred shares), expressed as a percentage
quantitatively: With respect to quantity rather than quality.
Return On Assets Versus Return On Equity
In review, return on equity measures the rate of return on the ownership interest (shareholders’ equity) of common stockholders. Therefore, it shows how well a company uses investment funds to generate earnings growth. Return on assets shows how profitable a company’s assets are in generating revenue. Return on assets is equal to net income divided by total assets.
Return On Assets: Return on assets is equal to net income divided by total assets.
This percentage shows what the company can do with what it has (i.e., how many dollars of earnings they derive from each dollar of assets they control). This is in contrast to return on equity, which measures a firm’s efficiency at generating profits from every unit of shareholders’ equity. Return on assets is, however, a vital component of return on equity, being an indicator of how profitable a company is before leverage is considered. In other words, return on assets makes up two-thirds of the DuPont equation measuring return on equity.
ROA, ROE, and Growth
In terms of growth rates, we use the value known as return on assets to determine a company’s internal growth rate. This is the maximum growth rate a firm can achieve without resorting to external financing. We use the value for return on equity, however, in determining a company’s sustainable growth rate, which is the maximum growth rate a firm can achieve without issuing new equity or changing its debt-to-equity ratio.
Capital Intensity and Growth
Return on assets gives us an indication of the capital intensity of the company. “Capital intensity” is the term for the amount of fixed or real capital present in relation to other factors of production, especially labor. The underlying concept here is how much output can be procured from a given input (assets!). The formula for capital intensity is below:
Capital Intensity=Total AssetsSales
The use of tools and machinery makes labor more effective, so rising capital intensity pushes up the productivity of labor. While companies that require large initial investments will generally have lower return on assets, it is possible that increased productivity will provide a higher growth rate for the company. Capital intensity can be stated quantitatively as the ratio of the total money value of capital equipment to the total potential output. However, when we adjust capital intensity for real market situations, such as the discounting of future cash flows, we find that it is not independent of the distribution of income. In other words, changes in the retention or dividend payout ratios can lead to changes in measured capital intensity.
This document was prepared by the OECD Secretariat to serve as an issues paper for the hearing on market concentration taking place at the 129th meeting of the OECD Competition Committee on 6-8 June 2018