Tools and methods for integrated analysis and assessment of sustainable development

Note: The author welcomes comments, which may be sent to MIND.

Some important tools and methods that may be used for integrated analysis and assessment are summarized below. Given the vast scope of sustainable development, the “tool kit” is eclectic and by no means exhaustive. The idea is to provide the sustainomics practitioner with a selection of key methods. Later chapters provide practical applications that indicate appropriate tools under various circumstances.

Action Impact Matrix (AIM)

The Action Impact Matrix (AIM) is a multi-stakeholder consultative approach that facilitates the integration of the social, economic and environmental dimensions of development, identifies and prioritizes key interactions among them, and determines policies and projects that make development more sustainable. The method has been widely used since the early 1990s, and was originally presented as part of the sustainomics framework, at the 1992 Rio Earth Summit [1]. Initially, it was used to integrate a range of environmental and social concerns into development planning [2], and subsequently, adapted to address broader issues like climate change [3].

Typically, the AIM is used as a strategic tool to better understand inter-linkages among critical elements, at the country-specific level:

  1. major national development policies and goals.
  2. key sustainable development vulnerabilities and issues – e.g., relating to economic sectors, ecological systems, and social factors.

Basic Procedure

The AIM process begins with an ex-ante analysis of the two-way linkages between the fundamental elements (a) and (b) – i.e., the effects of (a) on (b), and vice versa. By explicitly linking development goals with key economic-environmental-social issues, the AIM identifies potential barriers to sustainable development, and helps to determine the priority strategies that will overcome them.

The approach uses a fully participative multi-stakeholder exercise to generate the AIM itself. Up to 50 analysts and experts are drawn from government, academia, civil society and the private sector, who represent various disciplines and sectors relevant to both sustainable development and other issues relevant to the exercise. Initially, the stakeholders interact intensively over a period of about two days, to build a preliminary AIM. This participative process is as important as the product (i.e., the AIM), since important synergies and cooperative team-building activities emerge. The collaboration helps participants to better understand opposing viewpoints, resolves conflicts, builds ownership, and facilitates implementation of agreed policy remedies. On subsequent occasions, the updating or fine-tuning of the initial AIM can be done quickly by the same group, since they are already conversant with the methodology.

For maximum effectiveness, the AIM workshop needs to be carefully prepared by trained instructors who conduct the exercise, documentation (e.g., AIM Guide), screening and pre-selection of a balanced group of participants, and advance gathering of relevant background data.

The AIM methodology draws on the basic principles and methods of the sustainomics framework described earlier in this chapter, including a focus on making development more sustainable (MDMS), balanced consideration of the sustainable development triangle, emphasis on transcending boundaries, and full cycle application of integrative tools – where the AIM plays a key role. Thus, the AIM is the key link from initial data gathering to practical policy application and feedback.

The AIM process consists of the following key steps:
Screening and Problem Identification
a) Determine the most important development goals and policies (DG) – matrix rows.
b) Determine key sustainable development vulnerabilities and issues (VI) – matrix columns.
c) Determine the current status of VI – matrix cells.
d) Identify how DG might affect VI (Matrix DEV) – matrix cells.
e) Identify how VI might affect DG (Matrix VED) – matrix cells.

Analysis, Prioritization and Remediation
f) Analyze and prioritize most important interactions and determine appropriate remedial policies and measures.
g) Perform more detailed studies and analysis of key interactions and policy options identified in step f above.
h) Update and refine steps (c) to (f) above.


Two matrices are derived, representing the two-way links:.

  1. Matrix DEV – effects of development goals and policies on vulnerabilities and issues (DG → VI).
  2. Matrix VED – effects of vulnerabilities and issues on development goals and policies (VI → DG).

To summarize, the AIM rows represent national development goals and policies (DG) and the columns indicate sustainable development vulnerabilities and issues (VI). The cells of the two preliminary matrices identify broad relationships between DG and VI, provide a quantitative and qualitative idea of the magnitudes of the key interactions, help to prioritize the most important links, and facilitate formulation of appropriate policy responses. Meanwhile, the organization of the overall matrices facilitates the tracing of impacts, as well as the coherent articulation of the links among development activities (policies and projects).

The AIM process is flexible and may be adapted in various ways to address different problems. Typical examples include:

  1. Once the preliminary AIM is prepared, priority linkages may be pursued in two complementary ways:
    1. Upward link: where SD vulnerability concerns are embedded in the macroeconomic and sectoral development strategy of a country via the medium- to long-term sustainable development path.
    2. Downward link: where SD vulnerability concerns are integrated into the subnational-level development strategy in the short- to medium-term, by carrying out sustainable development assessments aimed at making specific projects and policies more sustainable.
  2. After completing a national level AIM exercise, it is possible to apply the process at a subnational or community level, to fine-tune the analysis.
  3. In a subsequent step, the impacts of other major external factors (such as climate change, natural disasters, rising oil prices, etc.) may be overlaid on the primary interaction between national development goals and policies (DG) and sustainable development vulnerabilities and issues (VI).

Other methods and indicators

Sustainable Development Assessment (SDA)

Sustainable development assessment (SDA) is an overarching methodology (with many components), which is used in evaluating investment projects (as well as programs and policies), to ensure balanced analysis of both development and sustainability concerns. The ‘economic’ component of SDA is based on conventional economic and financial analysis (including cost benefit analysis, as described below and in Chapter 3). The other two key components are environmental and social assessment (EA and SA) – Chapter 4 [4]. However, many other more specialized types of assessments may be included within an integrated SDA.

Economic, environmental and social analyses need to be integrated and harmonized within SDA. Historically, Environmental Assessments (EA) and Social Assessments (SA) had developed as separate processes. However, a full appreciation of all impacts requires a thorough understanding of all biophysical and social changes invoked as a result of planned interventions. Biophysical impacts have social impacts, and social changes also affect the biophysical environment. Recent work attempts to integrate biophysical and social impacts using a conceptual framework which is consistent with sustainomics, and this has led to a better understanding of the full extent of human impacts as well as the impact pathways that result from such interventions [5]. Green [6] shows a practical application to mining.

There is increasing interest in exploring various integrated approaches for sustainable development assessment (SDA), to facilitate research, policy planning and decision making [7]. Among the growing list of more specialized forms of appraisal are social assessment, health assessment, risk assessment, climate assessment, development impact assessment, poverty assessment and environmental assessment, and gender impact assessment.

This increase in number of different components within the SDA framework has brought about an increasing number of difficulties. At the procedural level it has become more difficult to coordinate the timings of separate appraisals and to synchronize this with decisions made about the project. At the methodological level, there is an increasing likelihood of inconsistencies between the appraisal methods used, of interdependencies between certain types of impacts, and of increasing difficulties in constructing an overall appraisal for use in decision making. At the organizational level, the workload has increased considerably, due to the burdens of managing and coordinating separate appraisals and multi-disciplinary teams as part of the project planning and management process. The weaknesses in this aspect by aspect approach include the risk of misjudgment of impacts and overlooking of better alternative solutions based on taking cross-cutting issues into account [8]. Projects appraised in this manner risk failure as their formulation is biased or incomplete. In an ideally integrated SDA approach, different assessments are no longer required and the project officer would be presented with an integrated overall picture, covering all choices that can be made.

Various degrees of integration could be done. For example, procedural tuning of the various sectoral assessments may create sufficient overlap in the timing of assessments so that different assessment teams have the opportunity to communicate and exchange findings. Assefa argues that SDA may be combined with traditional technology assessment (TA) and systems analysis to provide an integrated, holistic approach [9].

Development cooperation has resulted, so far, in less than optimal project quality. Initially development cooperation targeted only economic and technical goals. As awareness grew, policy themes relating to culture, equity, gender, environment, and institutional capacity emerged. An integrated approach would overcome the weaknesses of an aspect-by-aspect approach, which would lead to a more optimal project formulation and would greatly simplify project decision making.

Since the sustainable development goal has independent economic, social and environmental components, it is argued that appraisal procedures and methodologies should use interconnected economic, social and environmental appraisal criteria which are consistent with achieving this goal. There is a clear need to strengthen SDA methods to use at a more strategic level of decision making relating to development policies, plans and programs.

Traditional decision making relies heavily on economics. Thus, an initial practical step towards integration would be the systematic incorporation of environmental and social issues into the economic policy framework of human society – e.g., using the Issues-Policy Transformation Mapping (ITM) method.

Issues-Policy Transformation Mapping (ITM)

caption Figure 2: Issues-policy transformation mapping (ITM) to incorporate sustainable development issues into conventional decisions. (Source: Munasinghe 1992)

Issues-policy transformation mapping (ITM) is a method of integrating and applying various components of SDA (like environmental and social assessments) within the policy process. Figure 2 provides an example of how environmental issues are transformed and mapped into implementable actions and policies in the decision making domain. The right-hand side of the diagram indicates the hierarchical nature of conventional decision making and implementation in a modern society.

The global and transnational level consists of sovereign nation states. In the next level are individual countries, each having a multi-sector macroeconomy. Various economic sectors (like industry and agriculture) exist in each country. Finally, each sector consists of different subsectors and projects. The usual decision making process on the right side of the figure relies on techno-engineering, financial and economic analyses of projects and policies. In particular, conventional economic analysis has been well developed in the past, and uses techniques such as project evaluation/cost-benefit analysis (CBA), sectoral/regional studies, multisectoral macroeconomic analysis, and international economic analysis (finance, trade, etc.) at the various hierarchic levels.

Unfortunately, environmental and social analysis cannot be carried out readily using the above decision making structure. We examine how environmental issues might be incorporated into this framework (with the understanding that similar arguments may be made with regard to social issues). The left side of the figure shows one convenient environmental breakdown in which the issues are:

In each case, a holistic environmental analysis would seek to study an integrated biogeophysical system in its entirety. Complications arise when such natural systems cut across the structure of human society. For example, a large and complex forest ecosystem (like the Amazon) could span several countries, and also interact with many economic sectors within each country.

The causes of environmental degradation arise from human activity (ignoring natural disasters and other events of non-human origin), and therefore, we begin on the right side of the figure. The ecological effects of economic decisions must then be traced through to the left side. The techniques of environmental assessment (EA) have been developed to facilitate this difficult analysis [10]. For example, destruction of a primary moist tropical forest may be caused by hydroelectric dams (energy sector policy), roads (transport sector policy), slash and burn farming (agriculture sector policy), mining of minerals (industrial sector policy), land clearing encouraged by land-tax incentives (fiscal policy), and so on. Disentangling and prioritizing these multiple causes (right side) and their impacts (left side) needs a complex analysis.

Sustainomics could play its bridging role at the ecology-economy interface, by transforming and mapping the EA results (measured in physical or ecological units) onto the framework of conventional economic analysis. A variety of environmental and ecological economic techniques including valuation of environmental impacts (at the local/project level), integrated resource management (at the sector/regional level), environmental macroeconomic analysis and environmental accounting (at the economy-wide level), and global/transnational environmental economic analysis (at the international level), facilitate this process of incorporating environmental issues into traditional policy making. Since there is considerable overlap among the analytical techniques described above, this conceptual categorization should not be interpreted too rigidly. Furthermore, when economic valuation of environmental impacts is difficult, techniques such as multi-criteria analysis (MCA) would be useful (see below).

Once the foregoing steps are completed, projects and policies must be redesigned to reduce their environmental impacts and shift the development process towards a more sustainable path. Clearly, the formulation and implementation of such policies is itself a difficult task. In the deforestation example described earlier, protecting this ecosystem is likely to raise problems of coordinating policies in a large number of disparate and (usually) non-cooperating ministries and line institutions (i.e., energy, transport, agriculture, industry, finance, forestry, etc.).

Analogous reasoning may be readily applied to social assessment (SA) at the society-economy interface, in order to incorporate social considerations more effectively into the conventional economic decision-making framework. In this case, the left side of the figure would include key elements of SA, such as asset distribution, inclusion, cultural considerations, values and institutions. Impacts on human society (i.e., beliefs, values, knowledge and activities), and on the biogeophysical environment (i.e., both living and non-living resources), are often interlinked via second and higher order paths, requiring integrated application of SA and EA. This insight also reflects current thinking on the co-evolution of socio-economic and ecological systems (Chapter 4).

In the framework of the figure, the right side represents a variety of institutional mechanisms (ranging from local to global) which would help to implement policies, measures and management practices to achieve a more sustainable outcome. Implementation of sustainable development strategies and good governance would benefit from the trans-disciplinary approach advocated in sustainomics. For example, economic theory emphasizes the importance of pricing policy to provide incentives that will influence rational consumer behavior. However, cases of seemingly irrational or perverse behavior abound, which might be better understood through findings in areas like behavioral and social psychology, and market research. Such work has identified basic principles that help to influence society and modify human actions, including reciprocity (or repaying favors), behaving consistently, following the lead of others, responding to those we like, obeying legitimate authorities, and valuing scarce resources [11].

Cost-Benefit Analysis (CBA) and Multi-Criteria Analysis (MCA)

Cost-benefit analysis (CBA) is the main tool for economic and financial assessment. It is a single valued approach based on neoclassical economics, which seeks to assign monetary values to the consequences of an economic activity. The resulting costs and benefits are combined into a single decision making criterion like the net present value (NPV), internal rate of return (IRR), or benefit-cost ratio (BCR). Useful variants include cost effectiveness, and least cost based methods. Both benefits and costs are defined as the difference between what would occur with and without the project being implemented. The economic efficiency viewpoint usually requires that shadow prices (or opportunity costs) be used to measure costs and benefits. All significant impacts and externalities need to be valued as economic benefits and costs. However, since many environmental and social effects may not be easy to value in monetary terms, CBA is useful mainly as a tool to assess economic and financial outcomes. Chapter 3 provides further details.

Multi-criteria analysis (MCA) or multi-objective decision making is particularly useful in situations when a single criterion approach like CBA falls short – especially where significant environmental and social impacts cannot be assigned monetary values. In MCA, desirable objectives are specified and corresponding attributes or indicators are identified. Unlike in CBA, the actual measurement of indicators does not have to be in monetary terms – i.e., different environmental and social measures may be developed, side by side with economic costs and benefits. Thus, more explicit recognition is given to the fact that a variety of both monetary and non-monetary objectives and indicators may influence policy decisions. MCA provides techniques for comparing and ranking different outcomes, even though a variety of indicators are used.

Other Specific Models and Methods

The subsequent chapters contain several other methods and models which are specific to particular applications and adapted to the sustainomics approach, including:

  • Integrated assessment models (IAM)
  • Macroeconomic models (simulation, growth, computable general equilibrium - CGE, etc.)
  • Green Accounting (e.g., integrated national economic-environmental accounting or SEEA),
  • Sectoral approaches (sustainable energy development - SED, sustainable transport development - STD, sustainable water resources management - SWARM, sustainable hazard reduction and management - SHARM, etc.)
  • Shadow pricing and costing methods (economic efficiency, social equity, environmental externalities, separable costs remaining benefits allocation - SCRB, etc.)
  • Integrated resource pricing (energy – LRMC based, water, etc.)

Indicators and Measures

The practical implementation of sustainomics principles and application of integration tools will require the identification of specific economic, social and environmental indicators, that are relevant at different levels of aggregation ranging from the global/macro to local/micro. It is important that these measures of sustainable development be comprehensive in scope, multi-dimensional in nature (where appropriate), and account for spatial differences. If we wished to apply the full cycle analysis approach of sustainomics to trace causal linkages, one useful classification of indicators would be by pressure, driver, state, impact, and response. For example, consider the following chain (Chapter 5): underlying pressure - societal values and tastes; immediate driver – greater use of sport utility vehicles (SUV); state – increased greenhouse gas (GHG) concentrations; impact – global warming; policy response – tax on SUVs and consumer education to encourage more sustainable behavior.

A wide variety of indicators are described already in the literature [12]. We discuss briefly below, how measuring economic, environmental (natural), human and social capital raises various problems. In the economic dimension, the word “capital” or “asset” implies stock of wealth to produce economic goods and services. Social and environmental assets have a broader meaning, as discussed below.

Manufactured capital may be estimated using conventional neoclassical economic analysis. As described later in the section on cost-benefit analysis, market prices are useful when economic distortions are relatively low, and shadow prices could be applied in cases where market prices are unreliable [13].

Natural assets need to be quantified in terms of key biophysical attributes. Typically, damage to natural capital may be assessed by the level of air pollution (e.g., suspended particulates, sulfur dioxide or GHGs), water pollution (e.g., biochemical oxygen demand (BOD) or chemical oxygen demand (COD), and land degradation (e.g., soil erosion or deforestation). Then the physical damage could be valued using a variety of techniques based on environmental economics [14] (Chapter 3).

Social capital is the one that is most difficult to assess [15]. Putnam described it as ‘horizontal associations’ among people, or social networks and associated behavioral norms and values, which affect the productivity of communities [16]. A somewhat broader view was offered by Coleman [17], who viewed social capital in terms of social structures, which facilitate the activities of agents in society – this permitted both horizontal and vertical associations (like firms). An even wider definition is implied by the institutional approach espoused by North [18] and Olson [19], that includes not only the mainly informal relationships implied by the earlier two views, but also the more formal frameworks provided by governments, political systems, legal and constitutional provisions, etc. Recent work has sought to distinguish between social and political capital (i.e., the networks of power and influence that link individuals and communities to the higher levels of decision making). Human resource stocks may be measured in terms of the value of educational levels, productivity and earning potential of individuals. Chopra argues that one key measure of social capital especially relevant to development of poor communities is the cooperation between individuals across the traditional divides separating state, market and non-market institutions [20].

Currently, there is no universally accepted aggregate measure of sustainable development to rival economic indicators of welfare like gross domestic product (GDP) (whose shortcomings are discussed in Chapters 3 and 7). While many alternative indicators have been suggested by individual researchers, measures proposed by United Nations (UN) organizations are more widely known, including the human development index [21], wealth stocks [22], and environmentally adjusted national accounts [23] – see "Economy-wide policies and the environment". The UN Commission on Sustainable Development proposes a set of social, economic, environmental and institutional indicators. Data for most nations are available through the "Dashboard of Sustainability" – a versatile and effective tool which allows users to select various sustainable development indicators, aggregate them appropriately, and apply them at different geographic scales and for specific years [24]. This tool also contains the Millennium Development Goal (MDG) indicators, currently the most important framework for development policy. IISD provides further information on indicators [25].

Notes

  1. ^Munasinghe, M. 1992a. Environmental Economics and Sustainable Development, Paper presented at the UN Earth Summit, Rio de Janeiro, Environment Paper No.3, World Bank, Wash. DC, USA.
  2. ^Munasinghe, M. 1994a. ‘Sustainomics: a transdisciplinary framework for sustainable development’, Keynote Paper, Proc. 50th Anniversary Sessions of the Sri Lanka Assoc. for the Adv. of Science (SLAAS), Colombo, Sri Lanka.
    Munasinghe, M. 1997. “Sustainable long term growth: prospects for Asian cities”, Proc. of the APEC Seminar on Sustainable Cities, Asia Pacific Economic Cooperation (APEC), Taiwan, December.
    Munasinghe, M. 2002a. “The sustainomics trans-disciplinary meta-framework for making development more sustainable”, Paper presented at the UN World Summit on Sustainable Development (WSSD), Johannesburg, International Journal of Sustainable Development, Vol.5 (1-2), pp.125-82.
    Munasinghe, M. (2006) “Mainstreaming and implementing the millennium ecosystem assessment (MA) results by integrating them into sustainable development strategy”, in Ranganathan, J., Munasinghe, M. and Irwin, F. 2006. Millennium Ecosystems Assessment:Implications for Policy and Governance, Edward Elgar Publishing, Cheltenham, UK.
  3. ^Munasinghe, M. (Ed) 2002b. Macroeconomics and the Environment, The International Library of Critical Writings in Economics, Edward Elgar Publ., London, UK.
    Munasinghe, M. and Swart, R. 2005. Primer on Climate Change and Sustainable Development: Facts, Policy Analysis and Applications, Cambridge University Press, Cambridge, UK.
    MIND 2004. Action Impact Matrix Manual, Munasinghe Institute for Development, Colombo.
  4. ^World Bank 1998. Environmental Assessment Operational Directive, (EAOD4.01). Washington DC, USA.
  5. ^Lee, N. and Kirkptrick, C., 2000. Integrated Appraisal, decision making and sustainable development : an overview. In N. Lee and C. Kirkpatrick (Editors), Sustainable Development and Integrated Appraisal in a Developing World, Cheltenham, Northampton: Edward Elgar: 1-14.
  6. ^Green, T.L. 2001. Mining and Sustainability: the Case of the Tulsequah Chief Mine, Environmental Mining Council, BC, Canada.
  7. ^Boulanger, P-M, and Brechet, T. 2002. Improving Scientific Tools for Sustainable Development Decision Making, Directorate General Research, European Commission, Brussels, Belgium.
  8. ^Brown, P.G. 1998. ‘Towards an economics of stewardship: the case of climate’, Ecological Economics, Vol. 26, pp.11–21, July.
  9. ^Assefa, G. 2005. On Sustainability Assessment of Technical Systems, PhD Thesis, Royal Institute of Technology, Stockholm, Sweden, December.
  10. ^World Bank 1998. Environmental Assessment Operational Directive, (EAOD4.01). Washington DC, USA.
  11. ^Cialdini, R.B. 2001. Influence: Science and Practice, Fourth Edition, Allyn and Bacon, London, UK.
  12. ^Adriaanse, A. 1993. Environmental Policy Performance Indicators, Sdu, Den Haag, Netherlands.
    Alfsen, K. H., and Saebo H.V. 1993. ‘Environmental quality indicators: background, principles and examples from Norway’, Environmental and Resource Economics, October, Vol. 3, pp. 415–35.
    Azar, C., Homberg, J. and Lindgren, K. 1996. ‘Socio-ecological indicators for sustainability’, Ecological Economics, Vol. 18, August, pp.89–112.
    Bergstrom, S. 1993. ‘Value standards in sub-sustainable development: On limits of ecological economics’, Ecological Economics, Vol. 7, pp.1–18, February.
    Eurostat 2006. European Union Sustainable Development Indicators, Brussels, Belgium.
    Gilbert, A. and Feenstra, J. 1994. ‘Sustainability indicators for the Dutch environmental policy theme ‘diffusion’ cadmium accumulation in soil’, Ecological Economics, Vol. 9, pp.253–65, April.
    Holmberg, J., and Karlsson, S. 1992. ‘On designing socio-ecological indicators’, in U. Svedin and Bhagerhall-Aniansson (Eds.) Society and Environment: A Swedish Research Perspective, Kluwer Academic, Boston.
    Kuik, O. and Verbruggen, H. (Eds.) 1991. In Search of Indicators of Sustainable Development, Kluwer, Boston.
    Liverman, D., Hanson, M., Brown, B.J. and Meredith, R. Jr. 1988. ‘Global sustainability: towards measurement’, Environmental Management, Vol. 12, pp.133–143.
    Moffat, I. 1994. ‘On measuring sustainable development indicators’, International Journal of Sustainable Development and World Ecology, Vol. 1, pp.97–109.
    Munasinghe, M., and Shearer, W. (Eds.) 1995. Defining and Measuring Sustainability: The Biogeophysical Foundations, UN University and World Bank, Tokyo and Washington, DC, USA.
    OECD 1994. Environmental Indicators, OECD, Paris, France.
    Opschoor, J.B. and Reijnders, L. 1991. ‘Towards sustainable development indicators’, in O. Kuik and H. Verbruggen (Eds.) In Search of Indicators of Sustainable Development, Kluwer, Boston, MA, USA.
    UN 1996. Indicators of Sustainable Development: Framework and Methodology, United Nations, New York, NY, USA.
    UNDP 1998. Human Development Report, United Nations Development Programme, New York, USA.
    UNCSD 2005. “Indicators of sustainable development – CSD theme indicator framework”, UN Commission on Sustainable Development, NY, USA.
    World Bank 1998. Environmental Assessment Operational Directive, (EAOD4.01). Washington DC, USA.
  13. ^Squire, L. and H. Van der Tak 1975. Economic analysis of Projects, Johns Hopkins Univ. Press, Baltimore MD.
  14. ^Munasinghe, M. 1992a. Environmental Economics and Sustainable Development, Paper presented at the UN Earth Summit, Rio de Janeiro, Environment Paper No.3, World Bank, Wash. DC, USA.
    Freeman, A. M. 1993. The Measurement of Environmental and Resource Values: Theory and Methods. Resources For the Future. Washington, D.C.
    Tietenberg, T. 1992. Environmental and Natural Resource Economics, Harper Collins Publ., New York NY.
  15. ^Grootaert, C. 1998. ‘Social capital: the missing link’, Social Capital Initiative Working Paper No. 3, World Bank, Washington DC.
  16. ^Putnam, R.D. 1993. Making Democracy Work: Civic Traditions in Modern Italy, Princeton Univ. Press, Princeton.
  17. ^Coleman, J. 1990. Foundations of Social Theory, Harvard Univ. Press, Cambridge MA.
  18. ^North, D. 1990. Institutions, Institutional Change and Economic Performance, Cambridge Univ. Press, Cambridge, UK.
  19. ^Olson, M. 1982. The Rise and Decline of Nations, Yale Univ. Press, New Haven, CN, USA.
  20. ^Chopra, K. 2001. ‘Social capital and sustainable development: the role of formal and informal institutions in a developing country’, Institute of Economic Growth, Delhi, India.
  21. ^UNDP 2005b. Human Development Report 2005, United Nations Development Programme, New York, USA.
  22. ^World Bank 2006. Where is the Wealth of Nations, World Bank, Washington D.C., USA.
  23. ^UN 2003. Handbook of National Accounting: Integrated Environmental and Economic Accounting – An Operational Manual, United Nations, New York.
  24. ^CGSDI 2006. Consultative Group on Sustainable Development Indicators, Winnipeg, Canada; and the Dashboard of Sustainability.
  25. ^IISD 2006. Compendium of Sustainable Development Indicators, International Institute for Sustainable Development, Winnipeg, Canada.



This is a chapter from Making Development More Sustainable: Sustainomics Framework and Applications (e-book).
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Munasinghe, M., & Development, M. (2007). Tools and methods for integrated analysis and assessment of sustainable development. Retrieved from http://www.eoearth.org/view/article/156655

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