How sustainable are our economies_5 pptx

4.3 Real world and statistical systems 1 Goods and services for private and public consumption; 2 Capital goods; 3 Supply of social services and use of goods in ‘other activities’; 4 Use

Box 4.1 Environmental topics in the CARICOM compendium

Water abstraction, supply, use, treatment and quality

7 Coastal and marine resources

Water quality, vulnerable areas and protection, fisheries and aquaculture

8 Land use and agriculture

Land use, biochemicals

9 Forests

10 Biodiversity

Threatened species, protected areas

11 Minerals, energy and transport

Economic and environmental agents

Information

Pressures

Resources

tion

Informa-Societal responses Societal responses

Fig 4.2 Pressure-state-response framework (PSRF)

Source: OECD (1993, fig 1a, simplified).

their environment statistics in the FDES format, as recommended for ‘newcomers

to this field’ (ADB, 2002)

Following the lead of most international organizations, countries seem generally content to use the different frameworks for an initial check of data needs and availability, and to present their data for the traditional environmental

media of air, water, land and, sometimes, human settlements This allows flexibility, but introduces a certain degree of arbitrariness in selecting and presenting environment statistics.

The remaining question is what are the actual needs for and uses of a prehensive environment statistics publication? One of the first assessments of

result of high schools as the main user Most decision-makers apparently tinued to rely on their own databases, tailored to their specific needs such as water data for a water department or hydrological institute Of course, such specialization impairs data integration across institutions and environmental and socio-economic fields

con-Policymakers tend to ignore the extensive and difficult-to-read measurement

of environmental issues in large statistical compendia The reason might be their preference for more selective and aggregate indicators related to pressing policy concerns Moreover, statistical compendia rarely specify concrete use and applications, beyond generics like the objective of ‘sustained monitoring and evaluation of the state of the environment and sustainable development’ (CARICOM, 2003) Perhaps the most important use of a common framework for environmental topics and statistical variables is to foster better communi-cation between data producers and users

4.1.2 Integrating Economic, Environmental

and Social/Demographic Statistics4

Chapter 2 identified interactions and repercussions between the environment and socio-economic activities as the cause of potential non-sustainability of economic activity Obviously, environmental statistics cannot assess these interactions on their own, but need to be linked to the other statistical fields

Figure 4.3 illustrates the numerous interrelationships among the stocks and flows of the three basic areas of economic, environmental and demographic (and social) statistics The figure thus elaborates on Fig 2.1, the environment-economy interface, in terms of statistical topics and variables The (highlighted) sequence

of flows of pollutants from production and consumption (flows 6 and 7) illustrates this interaction Emissions are partially controlled by environmental protection (8), or escape control and accumulate in environmental media (14); subsequent

‘consumption’ of pollutants by humans is shown as part of ‘other’ population activities (18) A further extension of this sequence refers to health and welfare effects from pollution (19) and natural disasters (15)

3 Oral communication by a representative of Statistics Finland at a United Nations expert group meeting.

4 This section is based on Bartelmus (1987).

Real-world complexities and interactions call for better and transparent age of the statistical systems across their conventional boundaries The FDES offers some linkage through its information categories of economic activities, environmental impacts and social responses The flexible structure of the FDES appeals as a tool for the coordination and connection of all basic statistical areas Table 4.3 thus applies FDES criteria to the SNA and SSDS in order to outline an overall Framework for Statistical Integration (FSI) (or put more mod-estly, for statistical coordination) Contrary to a systems approach, the frame-work does not try to relate variables through strict functional or accounting relationships It should help, though, developing common concepts, definitions, classifications and tabulations.

Emission

Natural events

Environmental capital

Population movement

Social services

Other activities

Human and social capital

(19) (8)

(18) Production

Fig 4.3 Real world and statistical systems

(1) Goods and services for private and public consumption; (2) Capital goods; (3) Supply of social services and use of goods in ‘other activities’; (4) Use of natural resources in production; (5) Fixed capital consumption; (6) Emission of waste and pollutants from production; (7) Emission from consumption; (8) Pollution control, environmental protection; (9) Consumption of natural resources (subsistence, physiological); (10) Capital formation; (11) Construction of shelter and infrastructure; (12) Depletion of natural resources; (13) Destruction of human settlements and natural resources by natural disasters; (14) Ambient concentrations in the human environment; (15) Loss of life and limb from natural disasters; (16) Net population growth; (17) Labour; (18) Human consumption of pollutants; (19) Health and welfare effects.

Source: Bartelmus (1987, fig 1, modified).

The FSI largely maintains the original subject areas or topics of SNA, FDES and SSDS On the other hand, it organizes these subjects around the FDES information categories These categories simply reflect the common interest of all statistical systems in describing the state and changes of the real world, as well as the major activities responsible for these changes Marking the first column of the framework

as opening assets and adding a last column of closing assets could display accountingrelationships This is the approach taken in greening the national accounts (Section 7.2) Given ever-changing social concerns, the framework should also facilitate the evaluation of established but under- or overused statistical series, and reveal new data needs

The category of social response is unusual in traditional statistics Much of the dissatisfaction with conventional statistics stems from ignoring policy responses and their evaluation This is one reason for the interest of policymakers in more flexible ‘indicators’ that relate to policy objectives and can be readily adapted to changing concerns and priorities

Table 4.3 Framework for statistical integration (FSI)

Responses to impacts SNA (economy) - Financial assets

- Net tangible assets

- Saving

- Net capital formation

- Other volume changes

- Macroeconomic policies

FDES (environment) - Stocks/reserves

of natural resources and environmental assets

- Human ments

settle Use of natural resources

- Emissions

- Natural events

- Construction and use of shelter and infrastructure

- Resource depletion or increase

- Ambient centrations of substances

con Ecological impacts

- Environmental policies and programmes

- Environmental management

- Welfare effects SSDS (population) - Population - Population

movements

- Other social activities

- Population increase or decrease

- Changes in public health

- Other changes

in human capital

- Population policy

- Employment policy

- Provision of social services

Source: Bartelmus (1987, table 1, modified).

4.2 From Statistics to Indicators ‘for’ Sustainable

Development

4.2.1 Indicator Selection: Reducing Information Overload

The main drawback of the FDES is the generation of nearly 500 statistical variables in its follow-up methodological publications (United Nations, 1988, 1991) International organizations advanced, therefore, shorter lists of ‘core’, ‘key’ or ‘headline’ indicators

of both the environment [FR 4.3] and sustainable development [FR 4.4]

Selecting key statistics as indicators for environmental assessment and policy analysis blurs the distinction between environmental statistics and broader indi-cators Most definitions stress, indeed, the capability of an indicator to represent

a social concern beyond the immediate meaning of the underlying statistic(s) (Box 4.2)

Indicator selection and definition are first steps towards aggregation of data for assessing the state of the environment or sustainable development The inherent sub-jectivity in choosing indicators for multidimensional sustainable development, and a call by the Rio Summit to nonetheless develop indicators for the paradigm (United Nations, 1994, ch 40) are the reasons for a flurry of different indicator proposals International organizations, governments, NGOs and experts in the field proposed

Box 4.2 Indicator definition

The social indicator movement of the 1970s is probably the best-known attempt to reflect the standard of living by selected non-monetary statistics

It brought about a large and confusing variety of definitions and terms for indicators, statistics and indices (e.g Gallopín, 1997) Most definitions refer

to the broader ‘representativeness’ of a selected statistic or combination of statistics This suggests the generic definition of an indicator as:

simple average of a statistical variable or ratio of variables that provides an image beyond the immediate attribute or observation of the variable or ratio itself.

Besides selection of the statistics, the interpretation of the overall image introduces a further subjective element into indicator use A good example is average life expectancy that is generally taken as a measure of population health

In contrast to an average of statistical variables, an index is a combination

of indicators The index is usually calculated as a weighted or unweighted (equally weighted) indicator average; other more complex aggregation methods also apply (see Section 5.1)

widely differing indicator sets, undeterred by the largely negative experience of the social indicator movement in the 1970s [FR 4.3] Indicator lists of varying length and contents reflect the concerns or interests of their authors [FR 4.4] Typically these concerns refer to some or all of the following topics:

use, production and consumption patterns, technologies)

Clearly, these topics overlap Determining the desired scope and coverage, mizing overlap and choosing the best indicators for different topics requires a more systematic selection process – than ad hoc choices by interested parties Urging the use of good criteria for indicator selection and definition, such as those of Box 4.3, may help improve indicator quality and validity However, admonition will not do: what we need is a clear procedure, which identifies

mini-4.2 From Statistics to Indicators ‘for’ Sustainable Development 73

Box 4.3 Principles and criteria for sustainable development indicators

Bellagio principles (http://www.iisd.org/measure/principles/bp.asp):

sus-tainable development

standardization, targets and thresholds)

institutional capacity

to which one could add OECD (2003) criteria:

quantifiable topics of broad concerns and relates the topics to the appropriate data system This is indeed the approach of the above-described FDES and similar indicator frameworks.

4.2.2 A Framework for Sustainable Development Indicators

As shown in Section 4.1.2, the FDES is capable of presenting different statistical fields

in terms of stock and flow categories The FDES also facilitates linking these variables across the different fields and categories through its action-impact-reaction structure

In principle the – expanded – FDES could thus facilitate the transparent selection and definition of a reasonable number of sustainable development indicators

The Earth Summit’s Agenda 21 (United Nations, 1994; see also Fig 1.1) reflects international agreement on the scope and coverage of sustainable development For

developing a Framework for Sustainable Development Indicators (FSDI) (Bartelmus,

environmental and institutional dimensions of sustainable development classification with the FDES information categories obtains a framework, which combines the concerns of potential data users (reflected in Agenda 21) with those

Cross-of the data producers (presented as FDES-type statistical topics) Most indicator proposals applied, at least initially, some version of FSDI (mostly under the PSR label), but without resort to the statistical database [FR 4.4]

In the environmental field, the contents of the FSDI consist mostly of FDES statistical topics For sustainable development indicators, new topics stem from other statistical fields for the economic, social and institutional dimensions of sustainable development

The impacts/effects column shows the physical impact of economic activity on the state of the environment and on humans as welfare effects of these impacts; these are the symptoms of environmental non-sustainability of socio-economic development The activities/events category refers to the causes (driving forces and pressures) of impacts and effects from production and consumption, population dynamics, natural resource use, emission of pollutants and waste, and natural and man-made disasters The social response to impacts and effects can be carried out through natural resource management, pollution control, macro-policies of sustainabledevelopment, private sector adaptation and institutional change Inventories/stocks describe the economic and environmental capacities of supporting sustainable growth and development in the long term; they are a key element of environmental sustainability and accounting

5 The original proposal was for a framework for indicators of sustainable development The belling as Framework for Sustainable Development Indicators’ is more in line with distinguishing between indicators ‘of’ and ‘for’ sustainable development (see Section 4.3).

The importance of frameworks in tracing generic concerns down to statistics becomes evident when indicators need to be defined rigorously and transparently

in terms of their underlying statistics Unfortunately, data users mostly ignore this aspect when negotiating for indicator lists that serve different policy agendas Note that in comparison to the core FDES topics the statistical topics of socio-economic and institutional sustainability dimensions are quite undeveloped in the FSDI This may have contributed to the later abandonment of the FSDI by data users Typically, data users are less concerned or familiar with the nitty-gritty statistical work

Table 4.5 shows – in the FSDI format and for the example of freshwater – different indicators advanced by the original FSDI, the United Nations and the European Environment Agency (EEA) Some relabelling and break-ups of the

use the general pressure-state-response idea for their own environmental and tainability concerns However, applying similar information categories to differing

sus-or differently clustered environmental and socio-economic concerns still generates different indicator sets [FR 4.3, 4.4]

Deviations from the FSDI and the DSR framework reflect an unwillingness by national and international data users to be bound by the – non-binding – recom-

The OECD thus limited its ‘core’ environmental indicators to 40–50 indicators and reduced these further to 10–13 ‘key’ indicators as ‘signals to policymakers’ (OECD

2003) Similarly, the EEA uses 12 indicators in its summary of the Environmental Signals 20028 report

The same motivation seems to be behind the abandonment of the DSR framework

by the United Nations in a more recent publication: on the one hand, policymakers did not want to be bothered by a cumbersome data framework, which, ‘although suitable in environmental context, was not as appropriate for the social, economic,

6 The DPSIR framework of the EEA distinguishes explicitly between a state category (‘impact’ in the FSDI/FDES) and an impact category (‘effects’ in the FSDI/FDES); the framework also extends the activities/events category by introducing ‘drivers’ (of economic sectors) and present- ing activities and events as ‘pressures’ (of natural resource use and emissions) The DSR frame- work of the United Nations simply renames the FISD categories of activities/events as ‘driving force’ and impacts/effects as ‘state’ Note also that the omission of a stock category shifts the availability of natural resources such as groundwater or mineral reserves to the state category in the DSR framework, and to the response (reservoir stocks) categories in the EEA’s DPSIR frame- work (indicated by arrows in Table 4.5).

7 An initial ‘starter set’ of FSDI indicators (Bartelmus, 1994b) came up with 107 indicators; later, the DSR framework generated 130 indicators (United Nations, 1996).

8 http://reports.eea.europa.eu/environmental_assessment_report_2002_9/en (summary); ued in the EEA 2004 Signals which present the full set of 30 indicators (http://reports.eea.europa eu/signals-2004/en/ENSignals2004web.pdf).

discontin-Table 4.5 FSDI and related frameworks: Freshwater indicators

Frameworks Activities/events Impacts/effects Responses

Inventories/ stocks FSDI (statistical

- Fish stock changes

- Water resource changes

- Water quality

- Resource agement and rehabilitation

man Pollution monitoring and control

- Fish stocks

- logical systems

Hydro-DSR (indicators) b Driving force:

- Annual

with-drawal of ground and surface water as per cent of total available water

- Domestic

con-sumption of water per capita

State:

- BOD in water bodies

- Concentration of faecal coliform [- Groundwater reserves] d ®

Response:

- Wastewater treatment cov- erage

- Density of hydrological networks

- Emissions of

organic matter and hazardous substances

- Mean water

allocation for irrigation

- Water

exploita-tion index

- Water use by

sectors and in urban areas

State and Impact:

State:

- Concentration of ammonium, BOD, nitrates, phosphates, hazardous substances, nutrients, organic matter in rivers

- Bathing water quality

- Drinking water quality

- Biological quality of lakes

- Hazardous substances, phosphates in lakes (eutrophication)

- Nitrates, pesticides in groundwater Impact:

- National river cation schemes

classifi Nonclassifi indigenous species in rivers and lakes

- Saltwater intrusion

- Water exploitation index

Responses:

[- Overall reservoir ® stocks] d

- Urban waste water treatment (effectiveness)

- Water prices

- Water use efficiency

Notes:a Table 4.4.

b United Nations (1996); DSR is the acronym for Driving force, State, Response

c European Environment Agency (http://themes.eea.eu.int/Specific_media/water/indicators); DPSIR stands for Driving forces, Pressures, States, Impacts and Responses

d Arrows indicate a misplacement of stock variables in the respective frameworks.

4.2 From Statistics to Indicators ‘for’ Sustainable Development 77

and institutional dimensions of sustainable development’ (United Nations, 2001b)

On the other hand, discarding a framework that might reveal large data gaps, allowed ignoring missing issues and data, and facilitated agreement on a short ‘core set’ of

58 indicators for selected policy ‘themes’

The sometimes-heated discussion of theme and indicator selection reveals another dichotomy between data users and official (governmental) data produc-ers Impatient data users are eager to obtain rough-and-ready information, even

at the cost of less clarity and accuracy, whereas statisticians may question the validity of crude estimates This dichotomy carries over into the assessment of the sustainability of economic growth and development by means of ad hoc compilations of indices (Ch 5) and more systematic environmental accounting (Chs 6 to 8)

4.2.3 Indicator Use: Alert, Action or Evaluation?

Policymakers are usually unable to specify their data needs beyond generics such

as to ‘provide solid bases for decision-making’ (United Nations 1994, ch 40),

‘reporting on the state of sustainable development’, ‘fulfillment of governmental goals and targets’ (United Nations 2001b), or ‘to support and illustrate country environmental performance’ (OECD 2003) A ‘short list’ of 14 ‘structural indica-tors’ is to measure progress towards the somewhat conceited goal of the European Union ‘to become the most competitive and dynamic knowledge-based economy in the world capable of sustainable economic growth with more and better jobs and

Three general purposes of indicator use can be distinguished:

Implicit or explicit extrapolation of trends of environmental and social impacts

of economic growth can alert us to risks of environmental degradation, tion of natural resources and social problems More sophisticated modelling of impacts and repercussions between environment and economic growth can provide more accurate prediction, if based on realistic assumptions and valid data (Ch 11)

exhaus-9 2000 Lisbon European Council Presidency Conclusions (http://www.europarl.europa.eu/ summits/lis1_en.htm) The structural indicators can be found on Eurostat’s web site: http://epp eurostat.ec.europa.eu/portal/page?_pageid = 1133,47800773,1133_47803568&_dad = portal&_schema

= PORTAL.