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Lundgren, T.; Bostian, M. Valuing Ecosystem Services for Agricultural Total Factor Productivity. Encyclopedia. Available online: https://encyclopedia.pub/entry/21518 (accessed on 20 June 2024).
Lundgren T, Bostian M. Valuing Ecosystem Services for Agricultural Total Factor Productivity. Encyclopedia. Available at: https://encyclopedia.pub/entry/21518. Accessed June 20, 2024.
Lundgren, Tommy, Moriah Bostian. "Valuing Ecosystem Services for Agricultural Total Factor Productivity" Encyclopedia, https://encyclopedia.pub/entry/21518 (accessed June 20, 2024).
Lundgren, T., & Bostian, M. (2022, April 08). Valuing Ecosystem Services for Agricultural Total Factor Productivity. In Encyclopedia. https://encyclopedia.pub/entry/21518
Lundgren, Tommy and Moriah Bostian. "Valuing Ecosystem Services for Agricultural Total Factor Productivity." Encyclopedia. Web. 08 April, 2022.
Valuing Ecosystem Services for Agricultural Total Factor Productivity
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The United Nations (UN) Millennium Ecosystem Services Assessment (MA) defines ecosystem services as the benefits people obtain from ecosystems. These include provisioning services such as food and water; regulating services such as regulation of floods, drought, land degradation, and disease; supporting services such as soil formation and nutrient cycling; and cultural services such as recreational, spiritual, religious, and other nonmaterial benefits. Agriculture and ecosystem services are closely intertwined, giving rise to the term “agro-ecosystem” to denote the complex relationships between agricultural production and surrounding ecosystems. Total factor productivity (TFP), also termed multifactor productivity (MFP), relates total output quantity to total input quantity to provide an aggregate measure of economic performance. Total Factor Productivity (TFP) provides a general framework for modeling agricultural production and constructing aggregate index measures to allow for the multilateral assessment of agricultural productivity.

ecosystem services biodiversity valuation agricultural TFP

1. Introduction

Perhaps more than any other economic sector, agriculture and the environment are intimately linked. Natural resources, including soil and water, serve as key inputs into agricultural production. In turn, agricultural production affects these vital resources, both in terms of scarcity and quality, as well as the climate governing their function. Globally, agricultural production remains a leading contributor to both soil and water degradation and greenhouse gas emissions. At the same time, population growth and economic development exert ever-increasing pressure to increase production in order to meet global food demands. This highlights the need to better understand the role of the environment in agricultural production, better assess the potential for growth, and better account for both resource stock and quality on a global scale.
Total Factor Productivity (TFP) provides a general framework for modeling agricultural production and constructing aggregate index measures to allow for the multilateral assessment of agricultural productivity. Standard agricultural TFP measures the growth in total marketed agricultural output relative to the growth in total marketed input use, constructed as a ratio, where TFP values greater than one indicate overall gains to productivity. Standard TFP measures thus exclude any non-marketed natural resources and environmental effects.

2. Modeling Agricultural TFP

2.1. The TFP Concept

Total factor productivity (TFP), also termed multifactor productivity (MFP), relates total output quantity to total input quantity to provide an aggregate measure of economic performance. The TFP concept can be applied at different levels of economic production, from individual producers at the micro level, to the industry/sectoral level, to the national economy as a whole. Increasing TFP values result from output growth exceeding input growth, indicating improved economic performance. Economic index theory provides a theoretical framework for constructing TFP indices in practice, including key topics related to measurement and aggregation.

2.2. Theoretical Framework for TFP

The OECD Productivity Manual [1] overviews the main types of productivity measures used by the national statistics agencies, emphasizing that the choice of measure depends on both the measurement purpose and data availability. In general, these productivity measures can be constructed as the ratio of an output index to an input index, in either gross or value-added terms. Specialized measures for capital and labor productivity restrict inputs to these respective types, while TFP (or MFP, using the manual terminology) combines capital and labor into a single input quantity index. TFP/MFP accounts that integrate capital (K) and labor (L) inputs with intermediate inputs energy (E), materials (M), and services (S) are often referred to as ”KLEMS" accounts. The OECD guidelines [1] note that this integration makes KLEMS-type accounts the most appropriate measure for assessing technical change (the World KLEMS Initiative hosts a platform for accessing KLEMS-type data sets worldwide, including links to regional networks such as the EU KLEMS and Asia KLEMS, and statistical KLEMS databases published by national statistical institutes. See https://www.worldklems.net/wkhome (accessed on 22 January 2022)).

2.2.1. Economic Index Theory

Economic index theory connects index number formulae to the theoretical assumptions made for economic production processes, often termed the production theoretic approach to index numbers. The Laspeyres, Paasche, Fisher, and Törnquist indices emerge as the most widely implemented indices under the production theoretic approach. Laspeyres and Paasche indices aggregate quantities using base vs. current period values, respectively. The Fisher index takes the geometric average of the Laspeyres and Paasche indices, while the Törnquist index weights this geometric average by the individual quantity component shares.

2.2.2. Estimation

Empirical estimation of the indices can follow one of three general approaches: (i) the growth accounting/index number approach, (ii) production function-based approach, and (iii) productivity and efficiency analysis. Within and across these general approaches, estimation can employ both parametric and nonparametric methods.

2.3. Existing Agricultural TFP Indexes

Given the role of agriculture in feeding populations, trade, and the global economy, national statistics agencies and international bodies such as OECD and the UN devote considerable resources to measuring agricultural TFP. More broadly, three international agency manuals guide TFP index construction in practice [2]. The 2009 UN System of National Accounts (SNA) provides a set of internationally accepted standard accounting rules for tracking economic activity in any country, disaggregating the economy into production units and household units, whose income represents their economic production. The OECD Productivity Manual [1] provides a comprehensive theoretical framework for measurement to facilitate international comparisons at different levels of aggregation. At the sectoral level, the Eurostat (European Commission, 2000) manual for the Economic Accounts for Agriculture and Forestry [3] applies the SNA classification guidelines to the sectoral accounts. In addition to these, the United States Department of Agriculture (USDA) Economic Research Service (ERS) Agricultural Productivity Accounts have served as a leading model for measuring agricultural productivity [2].
Beginning with the output component to TFP, [4] overviews and compares the leading agency guidelines for measuring gross output for agricultural product accounts, focusing on the SNA [5] and OECD [1] guidelines, as well as the European Commission (EC) Economic Accounts for Agriculture (EEA) [3], the ERS TFP program [2], and the UN Food and Agriculture Organization (FAO) Global Strategy to improve Agricultural and Rural Statistics manual [6]. Key insights for output quantity include the following: first, only the FAO recommends using the value-added (as opposed to gross) approach to measure production output. ERS addresses the two as complements at the industry level, but states that gross measures are more appropriate because they do not impose the arbitrary and generally unsupported assumption of weak separability of the underlying production function between labor and capital provided by the sector and inputs provided by other sectors. The EEA excludes production for intermediate consumption, but includes intermediate production. The EEA also excludes on-farm losses, referring to the resulting measure as usable gross output. Areas left unaddressed by all of the manuals include commodity specificity (i.e., level of detail and disaggregation of commodity outputs) and the need for supply–demand balance (i.e., the adding up of output quantities produced vs. output quantities used). The manuals largely conflict on the treatment of intrasectoral use, which serves as an intermediate input, but must often be estimated from inventory data.
For output prices, there is a consensus regarding the use of basic unit prices, including unit subsidies, to value gross output. Furthermore, purchaser prices may be used in the absence of basic prices as a way to derive the basic unit price or, in the presence of basic price data of unknown quality, as a way to validate basic unit prices. Related to this, there is little consensus on which subsidy policies to include in basic prices; for instance, product subsidies vs. practice subsidies. For intermediate inputs and intrasectoral use, data availability and quality of inventory tracking pose a shared obstacle across agencies.
Another aspect, relevant to both the input and output components, concerns qualitative adjustments to index values [7]. For instance, while some of the accounting agencies do include agricultural land area as a capital input for agricultural TFP, they do not account for changing land quality over time (e.g., loss of fertility or increased erosion), with the exception (at least to some extent) of ERS [8]. In [7], the authors suggest two approaches to account for quality. The first is to disaggregate the input into qualitative classes; for instance, separate land quality categories, and then track changes in the composition of the input classes over time [9]. Alternatively, input prices should reflect qualitative attributes in competitive markets, so that as the distribution of these characteristics change over time, prices could be used to normalize the input to a constant quality unit [10]. Both approaches are consistent with the OECD guidelines to measure production in constant quality units. In [2], the authors also address quality adjustments, presenting a simple model of production with quality change to illustrate the identification issues in disentangling changes to output quality and changes to TFP. While changes to input quality simply move production along a given output frontier, changes to output quality shift the frontier, along with changes to TFP. Again, there are direct parallels for ecosystem service accounting, where often the services contributing to agricultural production depend on ecosystem condition. This aspect of ecosystem services is considered more in the next section.

3. Incorporating the Environment

3.1. Ecosystem Services

3.1.1. Classification and Accounting Methods

The MA [11] classification of ecosystem services into three types (provisioning, regulating, and cultural) provides a starting point for identifying the different types of services related to agro-ecosystems. Ref. [12] develop a standardized approach to measurement, drawing on gross domestic product (GDP) accounting methods to restrict analysis to final ecosystem services. They define final ecosystem services as components of nature directly enjoyed, consumed, or used to yield human well-being. They offer two alternative approaches to measurement, constructing a “Green GDP" based on final welfare benefit and an ecosystem service index (ESI) based on final contributions to both welfare and the ecosystem. Figure 1 illustrates these two approaches to measurement.
Figure 1. Green GDP vs. Ecosystem Service Index (ESI). Source: [12].

3.1.2. Challenges

One basic challenge to accounting for ecosystem services lies in reconciling the different definition and classification systems used in the literature and in practice.
Valuation poses another basic challenge to accounting. This includes the determination of which values to include and which methods to use. Types of value include both economic value to humans and non-economic values related to principles of fairness and equity, as well as ecological value [13]. Restricting to economic values, arguably most relevant to agricultural TFP, valuation methods include both consumption-oriented stated and revealed preference approaches [14], as well as production-oriented shadow price [15] and production-function approaches [16].
The SEEA AFF White Cover [17] lists a number of general accounting issues in practice. These include defining product scope (e.g., livestock rearing vs. slaughter); treatment of intra-unit flows (e.g., saving seed for future crops); treatment of own-account production (e.g., subsistence farming/fishing, land improvements); treatment of joint products (e.g., sugarcane for sugar and bio-energy); treatment of secondary production (e.g., agro-tourism); treatment of natural and cultivated biological resources (e.g., distinguishing products generated by natural processes from products generated by human activities); treatment of inventories, losses and waste (e.g., discarded fisheries catch, food spoilage, water and energy use inefficiency); and issues concerning measurement and aggregation (e.g., use of monetary aggregates in place of physical quantities to represent agricultural and biological processes).

3.1.3. Opportunities

Recent advances in institutional coordination, policy design, and integrated modeling offer a number of opportunities for ecosystem service accounting. In addition to the UN MA and SEEA programs, other large scale and/or multinational institutional programs include the UN TEEB program, which primarily focuses on biodiversity; the World Bank-led Wealth Accounting and Valuation of Ecosystem Services (WAVES) program; The Natural Capital Project (NatCap), which partners Stanford University, University of Minnesota, The Nature Conservancy, and the World Wildlife Fund; and the UN Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), created to support environmental decision making for 126 member countries [18]. Efforts to improve data collection, indicator selection, and standardize measurement and accounting systems for international comparison and assessment cross-cut these large-scale collaborations.
Integrated modeling links natural science-based biophysical models of ecosystem function to social science-based models of related human behavior for decision support. Computational advances, including parallel computing and genetic algorithm solution techniques, allow for more explicit modeling of complex interactions between ecosystems and human activities. Integrated agri-environmental models are now widely use, both in theory and in practice, for policy design and management [19]. Integrated frameworks can be used to simulate both quantitative changes to resource use, as well as qualitative changes in resource condition, resulting from human response to changing market prices and policy incentives. Integrated frameworks can also be used to model tradeoffs between ecosystems and economic activities, and estimate values for ecosystem effects.

3.2. Biodiversity

Biodiversity plays a unique role in accounting for ecosystem services, both by serving as an indicator of overall ecosystem condition, and supporting ecosystem service flows. The SEEA EEA framework considers biodiversity at three levels: the diversity of ecosystems, species, and genes. However, practical considerations limit the collection and use of genetic biodiversity measures. The SEEA EEA criteria for ecosystem and species-level biodiversity assessment include the following:
  • Appropriate spatial resolution for mapping to individual ecosystem assets and types;
  • Temporal relevance for assessing changes in stock or condition over the accounting period;
  • A common reference condition for comparison and aggregation purposes;
  • The ability to aggregate separate indicators into a composite indicator for overall condition;
  • Standardization to allow for comparison over space and time across ecosystem types.
These criteria mainly facilitate spatial/temporal matching and aggregation but speak less to determining the individual metrics. For this aspect, SEEA EEA notes that biodiversity-related policy priorities should guide metric selection. For instance, a policy goal to prevent species loss might guide the inclusion of more threatened and endangered species metrics, while maintaining ecosystem condition might guide the inclusion of more umbrella species metrics. For similar reasons, the UN Environment Program World Conservation Monitoring Centre (UNEP-WCMC) proposes the organization of species metrics into separate accounts for (i) conservation concern, (ii) ecosystem condition and/or functioning, and (iii) ecosystem service delivery [20].

3.3. Bad Outputs

Finally, undesirable environmental effects, often referred to as bad outputs, play an important role in accounting for ecosystem services. Bad outputs generally take one of two forms: those flowing from the ecosystem to humans, and those flowing from humans to the ecosystem. SEEA EEA terms the first of these ecosystem disservices, listing pests and diseases as examples. The second form, commonly termed negative externalities, includes pollution, land degradation, and biodiversity loss. SEEA EEA notes that in contrast to economics, accounting principles do not include welfare effects of use, but instead record strictly positive flows between producers and consumers. Thus, bad outputs only enter indirectly as changes in ecosystem condition and reduced flows of ecosystem services. The main exception to this is flows of greenhouse gas emissions, which SEEA EEA records directly in the carbon account, both as flows (sequestration and emissions) and changes in the stock of carbon.
SEEA EEA defines ecosystem degradation as the decline in condition of an ecosystem asset as a result of economic or other human activity, which is consistent with the SEEA Central Framework approach to natural resource depletion and the SNA approach to the depreciation of produced assets. Ecosystem degradation can be accounted for either as the net present value (NPV) of the decrease in expected flows of ecosystem services or as the change in the NPV of the ecosystem asset due to changes in capacity, in both cases holding prices constant. In addition to accounting for degradation in monetary terms, degradation can also be measured in physical terms through changes in the ecosystem condition indicators.
Another important aspect to accounting for degradation as part of the SEEA EEA framework, in either physical or monetary terms, concerns allocation to different economic units. As opposed to produced assets, ecosystem assets are often not single user/owner, meaning that the economic unit responsible for the degradation may be different from the economic unit affected by the degradation. For instance, the harmful effects of water pollution from agricultural production may be borne by fisheries downstream. Ecosystem complexity further complicates allocation for accounting purposes, as degradation can lead to reductions for multiple ecosystem services, flowing to multiple users.
Current practices are also moving away from the use of estimated restoration costs to value ecosystem degradation, as these values do not represent actual changes in the value of associated ecosystem services or actual payments made in a revealed preferences context. The restoration cost approach is also inconsistent with standard accounting methods for the depreciation of produced assets, which do not consider returning the asset to its original condition. SEEA EEA poses an alternative way to incorporate restoration costs, to instead use the change in estimated restoration costs from beginning to end of the accounting period as an indicator for the cost of a change in condition. Another alternative more consistent with depreciation for produced assets would be to consider the cost of constructing the ecosystem to its current condition.

4. Connecting Ecosystem Accounting to Agricultural TFP in Practice

The SEEA EEA provides the leading framework in current practice for incorporating ecosystem accounting into aggregate measures of TFP. In [8], the authors overview the framework, illustrated in Figure 2 below, emphasizing its importance: the SEEA EEA represents a synthesis of approaches to the measurement of ecosystems designed to enable integration with standard national accounting concepts and measurement boundaries.
Figure 2. An overview of the SEEA EEA framework. Source: [21], also adapted by [8].
In this framework, ecosystems (considered assets) generate ecosystem services, which along with human inputs (labor and produced assets) are used to produce benefits to society. These benefits include the goods and services measured by SNA, as well as other social benefits. In [8], the authors highlight the analogous role of ecosystem services to produced capital: the conceptual basis for the extension lies in recognizing that the flows of ecosystem services from agricultural land (in line with the flow of ecosystem services from ecosystem assets in Figure 1) are directly analogous, in accounting terms, to the capital services that flow from produced capital and which are already included in the standard growth accounting MFP measures. Relevant analogues include the use of produced capital depreciation methods for natural resource depletion in the SEEA EEA framework [22], theoretical connections to wealth accounting [23], and the use of produced capital growth accounting methods for natural capital [24].
Obst (2019) distills practical implementation of the SEEA EEA framework to five key steps in order to incorporate ecosystem services into current SNA practices for constructing environmentally adjusted agricultural TFP measures:
  • Delineate spatial areas. For agriculture, a spatial area unit of analysis could be single farm or a farming region with similar ecosystem characteristics;
  • Measure condition of the ecosystem. The SEEA EEA asset accounts record condition in biophysical indicator terms only;
  • Measure the flow of ecosystem services. SEEA EEA guidelines are to maintain a supply use account to record services used by economic units included in the national accounts;
  • Relate ecosystem services to standard measures of economic activity. Ecosystem services used as inputs (e.g., water for crops), like other intermediate inputs, have zero net effect on GDP. Ecosystem services considered final outputs (e.g., carbon sequestration), should be added to GDP;
  • Use exchange values. Physical trade offs require only quantities, while measurement in monetary terms requires price information. The use of valuation estimates is necessary for many non-marketed ecosystem services.

References

  1. Organisation for Economic Co-Operation and Development (OECD). Measuring Productivity, Measurement of Aggregate and Industry-level Productivity Growth; Organisation for Economic Co-Operation and Development (OECD): Paris, France, 2001.
  2. Shumway, C.R.; Fraumeni, L.E.; Fulginiti, J.D.; Stefanou, S.E. U.S. Agricultural Productivity: A Review of USDA Economic Research Service Methods. Appl. Econ. Perspect. Policy 2016, 38, 1–29.
  3. European Commission Office for Official Publications of the European Communities. Manual on Economic Accounts for Agriculture and Forestry; European Commission Office for Official Publications of the European Communities: Luxembourg, 1997.
  4. Cahil, S. What the Manuals Say (or Don’t Say) About Measurement of Gross Output; Background Document; OECD Network on Agricultural Total Factor Productivity and the Environment: Paris, France, 2019.
  5. SNA. System of National Accounts 2008; International Monetary Fund: Washington, DC, USA, 2009.
  6. United Nations Economic and Social Council Statstical Commission. Global Strategy to Improve Agricultural and Rural Statistics Report of the Friends of the Chair on Agricultural Statistics Global Strategy to Improve Agricultural and Rural Statistics Report of the Friends of the Chair on Agricultural Statistics; United Nations Economic and Social Council Statstical Commission: New York, NY, USA, 2010.
  7. Fuglie, K.; Benton, T.; Sheng, Y.; Hardelin, J.; Mondelaers, K.; Laborde, D. Metrics for Sustainable Agricultural Productivity; White Paper, G20 MACS; OECD: Paris, France, 2016.
  8. Obst, C. Incorporating the Environment in Agricultural Productivity: Connecting to Advances in Natural Capital Accounting; Technical Report; OECD Network on Agricultural Total Factor Productivity and the Environment: Paris, France, 2019.
  9. Wang, S.; Heisey, P.; Schimmelpfennig, D.; Ball, E. Agricultural Productivity Growth in the United States: Measurement, Trends, and Drivers; ERS Report ERR-189; United States Department of Agriculture Economic Research Service (USDA ERS): Washington, DC, USA, 2015.
  10. Ball, E.; Butault, J.; Juan, C.S.; Mora, R. Productivity and international competitiveness of agriculture in the European Union and the United States. In Expert Workshop on Measuring Environmentally Adjusted tfp and Its Determinants; OECD Network on Agricultural Total Factor Productivity and the Environment: Paris, France, 2015.
  11. Millennium Ecoysystem Assessment. Ecosystems and Human Well-being: Current State and Trends; Island Press: Washington, DC, USA, 2005.
  12. Boyd, J.; Banzhaf, S. What are ecosystem services? The need for standardized environmental accounting units. Ecol. Econ. 2007, 63, 616–626.
  13. Costanza, R.; Folke, C. Valuing Ecosystem Services with Efficiency, Fairness, and Sustainability as Goals. In Nature’s Services: Societal Dependence on Natural Ecosystems; Daily, G.C., Ed.; Island Press: Washington, DC, USA, 1997; pp. 49–69.
  14. Haab, T.C.; McConnell, K.E. Valuing Environmental and Natural Resources: The Econometrics of Non-Market Valuation; New Horizons in Environmental Economics, Edgar Elgar Publishing: Northampton, UK, 2002.
  15. Färe, R.; Grosskopf, S.; Margaritis, D. Pricing Non-Marketed Goods Using Distance Functions; Now Publishers: Boston, MA, USA; Delft, The Netherlands, 2019.
  16. Barbier, E.B. Valuing ecosystem services as productive inputs. Econ. Policy 2007, 49, 178–229.
  17. Tubiello, F.; Obst, C.; Mayo, R.; Cerilli, S. System of Environmental-Economic Accounting for Agriculture, Forestry and Fisheries: SEEA AFF; White Paper; United Nations: New York, NY, USA, 2018.
  18. Costanza, R.; de Groot, R.; Braat, L.; Kubiszewski, I.; Fioramonti, L.; Sutton, P.; Farber, S.; Grasso, M. Twenty years of ecosystem services: How far have we come and how far do we still need to go? Ecol. Econ. 2017, 28, 1–16.
  19. Plantinga, A.J. Integrating economic land-use and biophysical models. Annu. Rev. Resour. Econ. 2015, 7, 233–249.
  20. UNEP-WCMC. Exploring Approaches for Constructing Species Accounts in the Context of the SEEA EEA; Technical Report; United Nations: New York, NY, USA, 2016.
  21. System of Environmental-Economic Accounting 2012—Experimental Ecosystem Accounting; United Nations Publication Sales No. E.13.XVII.13; United Nations: New York, NY, USA; European Commission: Brussels, Belgium; Food and Agriculture Organization of the United Nations: Rome, Italy; Organization for Economic Cooperation and Development: Paris, France; World Bank Group: Washington, DC, USA, 2014.
  22. Schreyer, P.; Obst, C. Towards Complete Balance Sheets in the National Accounts: The Case of Mineral and Energy Resources; OECD Green Growth Papers 2015/2; OECD Publishing: Paris, France, 2015.
  23. Hamilton, K. Measuring sustainability in the UN System of Environmental-Economic Accounting. Environ. Resour. Econ. 2016, 64, 25–36.
  24. Fenichel, E.P.; Abbott, J.K. Natural capital: From metaphor to measurement. J. Environ. Resour. Econ. 2014, 1, 1–27.
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