Beyond GDP and Ecosystem Accounting

Traditional indicators such as the gross domestic product (GDP) and the human development index (HDI) have basic limitations as measures of social progress. Neither GDP/capita nor HDI reflect the state of the natural environment and both focus on the short term, with no indication of whether current wellbeing can be sustained. The green economy initiative which will be one of the key points of discussion in Rio+20 in June 2012, provides a unique opportunity to guide a new development paradigm that addresses not only economic effi ciency but also social equity. However, to measure the progress the green economy is providing, a new metric of measuring progress is needed at the individual and also at the macro level. As a large body of theory and empirical testing demonstrates, asset accounts can provide robust indicators of social welfare. While considerable progress has been made in measuring asset values for produced and natural capital (in the form of commercial natural resources), significant gaps remain,

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particularly with respect to ecosystem services and the effects of climate change. Research is needed to fill these gaps. Some of the issues needing attention on a priority basis are measurement and valuation of ecosystem services, and assessment of the potential effects of climate change on asset values, including ecosystem assets.

Policy Context

The flagship development reports of the international institutions (Human Development Report of United Nations Development Programme (UNDP), World Economic Outlook of the International Monetary Fund (IMF), and Global Economic Prospects of the World Bank) share a common weakness with GDP when it comes to measuring social progress: they are all focused on current, short-run measures. The other flagship, the World Bank’s World Development Report, is more research-oriented and less focused on the short term, but its thematic focus shifts from year to year.

There have been recent advances in addressing the weaknesses in contemporary measures of welfare that are used to judge the progress and regress of nations. The World Bank’s Where Is the Wealth of Nations? (2006) and the Changing Wealth of Nations (2011) were such initiatives, but they were only two monographs rather than part of a regular report series, and they had acknowledged limitations concerning the measurement of ecosystem assets. Turning to the question of ecosystem services, the Millennium Ecosystem Assessment made important progress on measuring the extent of damage to the ecosystems providing these services, but was weak on the valuation of these services and the linkages to human well-being. On climate change, there is a general tendency to focus on cost-benefit analysis of climate actions or on least-cost paths for climate stabilisation. Measuring the effects of climate change on ecosystem assets, and more generally on the other assets underpinning well-being, is relatively rare.

The recently launched Wealth Accounting and Valuation of Ecosystem Services (WAVES) in partnership with the World Bank and United Nations Environment Programme (UNEP) would carry out the exercise for six countries for the next fi ve years. The Global Environment Facility (GEF) has supported the Project for Ecosystem Services (Proecoserve) that is being implemented by UNEP in the Caribbean, South Afroca, Lesotho, Chile and Vietnam is also moving in the direction of generating data on ecosystem services to enable the ecosystem accounting operationalisable in those countries. The Government of India has constituted a similar group under the chairmanship of Partha Dasgupta to measure the impact of economic growth on biodiversity and ecosystem services. The output of the proposed work programme in this area should be a biennial report on wealth and change in wealth in over 100 countries, with a focus on developing countries. Such initiative and resultant report series will progressively increase the coverage of asset values over time, particularly with respect to ecosystem assets (and their associated services) as well as the impacts of climate change on these assets. Underpinning this progressive increase in coverage will be a research programme on these and wider topics in asset accounting.

Rationale for Ecosystem Accounting

The national income account (NIA) is a fundamental macroeconomic statistic which shows the level and performance of economic activities in an economy. The System of National Accounts (SNA) of the United Nations attempts to provide a benchmarked framework for the computation and presentation of national income across all the activities and economies to make the calculation comprehensive and comparable. A crucial component of the SNA is the estimation of GDP where, at the market price, the gross value of all the goods and services accruing to the society is estimated. GDP is supposed to show the change in the level of human welfare. However, in whichever way the GDP is calculated it does not capture many elements of human well-being. The shortcomings of GDP to reflect welfare are widely known and discussed in the literature (van den Bergh 2009). Designing the HDI where GDP is combined with status of health and education shows some advancement but even HDI is silent on the role of natural capital and ecosystems (Dasgupta 2010). In the process of GDP estimation, many contributions of the ecosystem in terms of ecosystem services such as bioremediation by wetlands, storm and flood protection by mangroves and prevention of soil erosion by forests get ignored. Ecosystem services which have a welfare-enhancing role do not enter into the macro-level calculations of nations. This is due to their poorly perceived value. Often ecosystems and their services fall outside the domain of the market and hence they remain unpriced and unaccounted for. Therefore, the calculated GDP provides an illusory sense of gains or losses. This ultimately means that GDP underestimates the level of welfare that society actually enjoys due to the unrecognised and unappreciated contributions of ecosystems. Economists are now in agreement that instead of measuring GDP or income which is a flow concept, the comprehensive measurement of stock of wealth including natural capital is the correct approach (Dasgupta and Maler 2000; Arrow et al 2004; Dasgupta 2010). This has a further bearing on the conservation strategy for ecosystems, where poor people depend upon the services from ecosystems more than the rest and if those services are unaccounted for, it would lead to erroneous policy for poverty alleviation. The rationale for accounting of ecosystem services also emerged from the findings of the Millennium Ecosystem Assessment (MA 2005), and other recent influential studies conducted by various agencies (TEEB 2009; Roy et al 2010) and the Commission on the Measurement of Economic Performance & Social Progress led by Joseph Stiglitz (Stiglitz, Sen and Fitoussi 2009).

Theoretical developments in environmental and welfare economics have emphasised the importance of recognising the value of natural capital (ecosystems and ecosystem services) in developing accounting methods aimed at policy developments for poverty alleviation (Pearce et al 1996; Dasgupta and Maler 2000; Arrow et al 2004; Maler et al 2008; Dasgupta 2010). Characteristically, in the development of GDP estimates, natural

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The Structure of Ecosystem Accounts

Typically, the accounting of an ecosystem would require the physical units used to measure the stocks of ecosystems and flows of ecosystem services. For accounting of wetland ecosystems thus, the stock of a wetland ecosystem should be measured in terms of its area, or a resource such as the population of a species that might be described in terms of numbers or density. Similarly, the production, regulating of cultural services that the system generates can be represented in terms of, for example, tonnes of fish harvested per day, the amount of water cleaned through bioremediation, or the annual number of visits to an area for recreational activities. The framework of an ecosystem differentiates various components of natural capital from those that can be used to make a connection with the various activity sectors used to characterise the economy. The accounts can be broken down into three major components:

First, basic accounts: this describes the important stocks and flows that constitute natural capital and its uses. These accounts describe the quantity of the different ecosystems, measured in terms of area (for habitats) or/and the use of these assets by different economic activity sectors. Also included in this basic set of tables are accounts that document the biodiversity status of the ecosystem units and its changes over time. Second, a set of accounts describing the condition of the ecosystem capital base which document the health status of the ecosystem. Essentially it is a measure of the integrity of the ecosystem, which they argue can be implemented at any scale

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and finally, third, a set of accounts that document the output of ecosystem services, their uses and values. They are mirrored by economic sector accounts that reflect the corresponding natural resource use (in physical and in monetary units) and the pressure on ecosystems as well as protection and management expenditures actually paid by governments and companies.

The services used directly by people include both marketed and non-marketed services. It is assumed that the value of the former is reflected in their observed market price. Accounting can be done and sometimes with sufficient persuasive power in physical terms. The closing and opening stock of ecosystems can provide adequate signal for required actions. The change in closing stock over a period of time would also refl ect the change in material balance. However, a meaningful integration for better sectoral allocation of resource in the economy, monetary valuation of changes in the stock or flow of services in time series experience would help in efficient design of policy instruments in the economy (Figure 1).

Figure 1: Structure of Accounts in SEEA 2003

Natural resources Economic assets Non-economic

Ecosystems (SNA) assets

Opening stocks Opening stocks Opening state Closing stocks Closing stocks Closing state Described in SNA SNA transactions and other flows Changes in stocks Changes in stocks Economic activities, natural processes, etc. Changes in state ⇐⇒⇒

Changing Inland Wetland Ecosystems of India

Wetlands, which are important providers of various types of services to the humans, are defined as “areas of marsh, fen, Peatland or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish or salt, including areas of marine water the depth of which at low tide does not exceed six metres” (Article 1.1, Ramsor 1971) and they are on decline due to various drivers of change. Wetlands constitute 9% of the land area and more than half of them are degraded on the verge of being lost (Zedler and Kercher 2005). Pollution, draining of water for agriculture and climate change are the major drivers identified for the loss of wetlands. In Asia, around 27% inland and coastal marshes were lost by 1985 (MA 2005). In India, a variety of wetlands are found, from natural to man-made. Assessment of the extent of wetlands in India, as globally, is fraught with dealing with the difficult issues of definition and methodologies. Consistent data sets are available only for certain wetland types, for example, mangroves, which have been covered under the biennial forest surveys since 1987. However, changes in assessment methodologies limit interpolation of the data to assess the trend of wetlands in the country. The national database of inland wetlands is much more inconsistent. The first major attempt to map the wetlands of India using remote sensing techniques was made in 1998. Using the satellite data for 1992-93, wetlands were mapped on scales of 1:250000 and for certain regions at a scale of 1:50000. Owing to the limitations of the resolutions, wetlands below 56.25 ha on a 1:250000 scale and 2.25 ha on

Table 1: Physical Area Loss of Wetlands in Several States in India over 1991-2001

* It is the data of year 1960; ** It is the data of year 2003.

a 1:50000 scale were not mapped. The Salim Ali Centre for Ornithology and Natural History (SACONH) further built on the inventory for selected districts for 13 states, mapping wetlands having an area two ha and above using the satellite data for 1999-2001 period. The assessment included change analysis for 72 districts using the data from the two time periods. Until recently, there has not been comprehensive and scientifi c assessment of wetland areas in India. The SACONH and the Space Application Centre (SAC) of the Government of India have been entrusted with the task of assessing wetland areas in India. Both of them have focused on inland wetlands, but the mapping of coastal wetlands still remains a challenging task. The SAC has generated information on the extent of inland wetlands

SPECIAL ARTICLE

wetland comes to be 0.04 million ha per annum if the declines is assumed to follow a linear path. The drivers of change in the wetland area have been mostly anthropocentric. Agricultural expansion and urbanisation processes have been the two most dominant forces of change (Kumar 2009). While the account of physical loss is a fi rst step towards operationalising the accounting approach, it does not help much in its integration with the existing accounts of those states. Monetary estimates of the loss would greatly facilitate the integration.

Methodology

In order to estimate the economic value of the wetland loss, we have used the benefit transfer method in this study. The benefit transfer method (BTM) or value transfer method can also be used for transfer of cost figures from a similar study known as “study site” to the site in question known as the “policy site”. Typically, the decision-maker requires an economic value of the loss and gain arising from the changes in ecosystem services and transfer of value from a similar study can help in that at far lower cost and time. Technically, transfer of value method is done by estimating the value of an ecosystem or ecosystem services by borrowing the existing valuation for a similar system. They can be in form of a unit value transfer and assumes that the marginal value to an average individual at the study site from an ecosystem service is the same as that which will be enjoyed by the average individual at the policy site (Navrud and Ready 2007). On the other transfer of unit value, transfer uses the value of ecosystem services per unit of spatial scale. Other form of transfer of value could be in the form of adjusted unit value transfer and value function (Brander et al 2009). In this study, we have used a meta analytic function transfer. Under meta analytic analysis, primary valuation studies are collated and analysed in a group and the results from each study are treated as a single observation in the new analysis of a pooled data set. This will enable us to evaluate the infl uence of the characteristics of ecosystem services, the features of the valuation method and other related assumptions. The resulting regression equations explaining variations in unit values can be used together with socio-economic contextual data on the independent variables in the model. The meta analytic transfer can be used for various purposes like costs benefi t analysis, environmental costing, natural resource damage assessment and ecosystem accounting. There have been successful examples of application of benefit transfer methods by Eshet et al (2007) and Johnston and Rosenberger (2009).

Benefit Transfer Method

The preliminary meta regression attempts to ascertain the impact upon wetland value (in constant terms) of wetland characteristics, valuation characteristics (both vectors of qualitative variables) and demographic characteristics of the region in which the wetland exists.

Data: The data of valuation studies is collected from the peerreviewed published and grey literature. There are 19 articles, including 17 study sites distributed in 13 states that have

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been used. Table 2 (p 80) gives an overview of them. We derive the current data set that includes types of wetlands, 14 categories of ecosystem services and five types of valuation methods. Tables 3 and 4 reflect some patterns in the data.

Some adjustments have been made to make the data comparable. First, the wetland values are in unit values, if the study does not already give value per ha. Second the wetland values pertain to different years so they have been adjusted to year 2007 prices uS dollars. The current values are deflated or infl ated (as the case may be) using 1999-2000 as the base year. Deflators are obtained by dividing the current year’s GDP by that of the base year (sourced from the Central Statistical Office), and then applied to the appropriate year’s value. Next, rupee values are converted into dollars (1$ = Rs 40, which is an approximate value that has been sustained during 2007-08, according to the Reserve Bank of India).

State-wise socio-economic data includes GDP per capita and population density. State GSDP is obtained from the RBI Handbook of Statistics (2007) and is similarly brought to the base year and in $ terms.

Meta Regression Model: The general regression model is: Y1 = α+ b X +bXE +bcX _u1 (1)

ssw c

where Yi is the dependent variable in $ value per ha in 1999-2000 terms; XS, XE and XC are three types of explanatory

Table 3: Cross Table of Ecosystem Service and Type of Wetland

Type of Wetland

Ecosystem Service Cultivable Floodplain Lake Mangrove National Wildlife Total Land Forest Park Sanctuary

Agricultural use 1 1 3 0 0 0 5

Aquaculture 0 1 0 0 0 0 1

Biodiversity 0 0 0 0 1 1 2

Carbon sequestration 0 0 0 1 0 0 1

Erosion control 0 0 1 1 0 0 2

Fish production 0 2 1 0 0 0 3

Fodder 0 1 1 0 1 0 3

Nutrient retention 0 1 0 0 0 0 1

Recreation 0 1 3 0 2 0 6

Storm protection 0 0 0 2 0 0 2

Thatching grass production 0 1 0 0 0 0 1

Water chestnut cultivation 0 0 1 0 0 0 1

Water recharge 0 2 0 0 0 0 2

Total 1 10 10 4 4 1 30

Table 4: Principal Services and Goods Provided by Wetlands and Valuation Methods Commonly Used to Estimate Their Value

Category Wetland Service Valuation Method

Provisioning Agricultural use CVM(2), market prices (1), replacement cost (2*) Aquaculture Market prices (1) Fish production Market prices (3) Fodder Market prices (2 ), opportunity cost (1) Thatching grass production Market prices (1) Water chestnut cultivation Market prices (1)

Regulating Biodiversity CVM (1), opportunity cost (1)

Carbon sequestration CVM(1)

Erosion control Market prices (1), opportunity cost (1)

Nutrient retention Replacement cost (1)

Storm protection Market prices (1), replacement cost (1)

Water recharge Production function (1), replacement cost (1)

Cultural Recreation CVM(4), production function (2)

CVM = Contingent valuation method.

* Figures in brackets indicate the number of observations for each wetland service according to the most commonly used valuation methods.

Table 8: Accumulated Values of the Loss of Wetlands in India in 10, 20 and Infinite Years Respectively

A = Z* 1/(1+ r)i, and for infinite, the formula is: A =z/r, where Z Annual Loss (Loss during 2001-1991/10) in $ 1999-2000 price, and r = rate of discount, 3%, 4%, 5%, respectively.

Conclusions

In this paper, the operationalisation of the concept of ecosystem accounting has been demonstrated by applying a benefi t transfer method to calculate the annual monetary value of the physical loss in wetlands in five selected states – Gujarat, J&K, Kerala, Rajasthan and West Bengal during 1991-2001. The maximum loss is in J&K, with its loss per capita up to $211.83 while that for the combined states is $11.57. Also, the use of the benefit transfer method for valuation is dependent upon the

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