GEOValue

The Socioeconomic Value of Geospatial Information

Jamie Kruse, Joep Crompvoets, Francoise Pearlman, Jamie B. Kruse, Joep Crompvoets, Francoise Pearlman

• Publisher: CRC Press
• Year: 2017
• ISBN:
  9781351650687
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Civil Engineering
• Index: Technology & Engineering

Quantifying the social and economic value that geospatial information contributes to modern society is a complex task. To construct reliable and consistent valuation measures requires an understanding of the sequence of processes that starts with data acquisition, and leads to decision-makers' choices that impact society. GEO Value explores each step in this complex value chain from the viewpoint of domain experts spanning disciplines that range from the technical side of data acquisition and management to the social sciences that provide the framework to assess the benefit to society. The book is intended to provide foundational understanding of the techniques and complexities of each step in the process. As such it is intended to be assessable to a reader without prior training in data acquisition systems, information systems, or valuation methods.

In addition, a number of case studies are provided that demonstrate the use of geospatial information as a critical input for evaluation of policy pertaining to a wide range of application areas, such as agricultural and environmental policy, natural catastrophes, e-government and transportation systems.

Section III

Measuring Economic and Social Values, Benefits, and Impacts

Methods and Implementation Examples

10

A Review of Socioeconomic Evaluation Methods and Techniques

Alan Smart, Andrew Coote, Ben Miller, and Richard Bernknopf

CONTENTS

10.1 Introduction

10.1.1 Methodology

10.1.2 The Meaning of Value

10.2 Current State of the Art

10.2.1 Welfare Analysis

10.2.1.1 Application to Fundamental Geospatial Data

10.2.1.2 Issues with Welfare Analysis

10.2.2 Estimates of Gross Revenue

10.2.3 Value-Added Approaches

10.2.3.1 Value Added Along Supply Chains

10.2.3.2 Value Chain Analysis

10.3 Economic Impact Assessment

10.4 Economic Impact Methodologies

10.4.1 Benefit–Cost Analysis

10.4.2 The Benefit–Cost Analysis Process

10.4.3 Valuation of Tangible Benefits

10.4.3.1 Direct Benefits

10.4.3.2 Indirect Benefits—Defensive Expenditure or Substitute Cost Approaches

10.4.4 Valuation of Nonmarket (Intangible) Benefits

10.4.4.1 Methods for Calculating Nonmarket Benefits

10.4.5 Multi-Criteria Analysis

10.4.6 Computable General Equilibrium Modeling

10.4.7 Input–Output Multiplier Analysis

10.4.8 Real Options

10.5 Comparison of Methodologies

10.6 Case Studies

10.6.1 Benefit–Cost Analysis of the National Map

10.6.2 Value of Spatial Information in Catalonia

10.6.3 Value of a Spatial Data Infrastructure in Lombardy

10.6.4 Value of Remote Sensing from LANDSAT

10.6.5 Value of Remote Sensing from Space for Decision-Making

10.7 Summary

10.8 New and Emerging Techniques

References

10.1 Introduction

This chapter reviews methodologies in economics for valuing the benefits of geospatial data and services. It explores the meaning of socioeconomic value and reviews the methodologies underpinning value assessments. It explains the theoretical background to economic welfare, gross revenue, and value-added analyses. Different methods for economic impact assessment are discussed. These include benefit–cost analysis, and Computable General Equilibrium (CGE) modeling. Examples of the application of these techniques are discussed, and the issues that arise when applying these techniques are canvassed. It notes that the methodology selected should be appropriate to the context in which it is to be applied, including the decision support required by policy-makers and suppliers of geospatial data.

10.1.1 Methodology

The use and application of geospatial information have delivered significant economic and social benefits to society. It is anticipated that these benefits will increase in future as geospatial information is further integrated into emerging data systems and technologies.

Understanding the value of geospatial information has become important to decision-makers in government and private organizations to support the case for investment in and maintenance of spatial data infrastructure (SDI). It is also important for policy development with respect to the capture, curation, and dissemination of geospatial data. Most significantly, it underpins the understanding of the importance of geospatial infrastructure to society in general.

Numerous valuations of geospatial information have been undertaken over past 20 years. These have drawn on varying techniques, including economic welfare theory, gross revenue estimates, value-added analysis, and general equilibrium modeling. Each methodology has advantages and disadvantages.

It is important for policy-makers and decision-makers alike that the general economic principles underlying the different valuation techniques are understood. This chapter canvasses the main economic principles underlying these techniques and discusses their application in practice.

10.1.2 The Meaning of Value

Assessing the value of geospatial information is a complex task. Valuing the contribution made by open geospatial data provided at no cost is even more complex, because there is no market in which it can be bought or sold.^*

A starting point for estimating its value is to clarify what is meant by the term value. Fundamental geospatial data are intermediate goods that enable other activities through value-added services. To understand their value, we need to explore the value that suppliers and users draw from the data.

For a government agency, this could be as narrow as a financial benefit (e.g., realized future savings). For a policy decision-maker, it could be as wide as the expected benefits that would accrue to society as a whole from the use of the data.

A suggested framework for considering different concepts of value is provided in Figure 10.1. Values are divided into use and non-use values. Use values comprise direct use values (such as the value of goods and services), ecological values (such as biodiversity or sustainable rivers and streams), and option values (such as insurance against the costs of natural disasters).

FIGURE 10.1
The nature of socioeconomic value. (Based on a conceptual framework from Young, 1992. With permission.)

Non-use values can be considered as existence values (valuing the existence of a coral reef but never visiting it) and bequest values (preserving the value of assets for later generations). Although non-use values are conceptual, they are real in the minds of many in society and potentially become policy issues for this reason.

There is also a long history of valuation of intangible benefits derived from geospatial data by using willingness-to-pay methodologies.

There has been limited use of option valuation in assessing the value of geospatial applications; however, there are examples in areas such as astronomy and research and development. There appears to be little in the way substantive studies of non-use values for geospatial information in the literature.

10.2 Current State of the Art

Several techniques have been applied over the past 20 years to estimate the value of geospatial information. A representative sample is discussed in the following sections.

10.2.1 Welfare Analysis

Welfare analysis is a theoretical conceptual economic model that describes the economic value of a good or a service. In an efficient market, the economic welfare of a good or a service to society is measured by consumer and producer surplus. The conceptual base for consumer and producer surplus is the supply and demand or the market model depicted in Figure 10.2.

The market supply curve (which comprises the summation of individual firm supply curves) indicates the costs of extra production, that is, the costs to society of producing an extra unit of a good or service. Firms aim to operate on the upward sloping part of their marginal cost curve, above the minimum average variable cost. The upward slope reflects diminishing returns to factor inputs, which means that it costs more to produce each additional unit of output.

The market demand curve (which comprises the summation of individual demand curves) indicates the maximum amount that consumers are willing to pay for incremental increases in the quantity of the good or service. The demand curve slopes downward to the right because more consumers are willing to purchase the good as the price falls. This concept is generally known as diminishing marginal utility.

FIGURE 10.2
Standard concepts of producer and consumer surplus. (From Marshall, 1890; Hanley, 1997. With permission.)

The interaction of demand and supply determines the market price (P_E) for a good and the quantity that is produced in any given time period (Q_E).

This market model provides the basis for identifying and estimating the net economic value to consumers and producers, referred to as consumer surplus and producer surplus, respectively.

Consumer surplus is the difference between what consumers would be willing to pay for a good or service (the total benefit to the consumer) and what they have to pay (the cost to consumers). In Figure 10.2, consumer surplus is represented as the area between the demand curve and the price line (P₂XP_E).

Producer surplus is the difference between the revenue received for a good or a service (total benefit to producers) and the costs of the inputs used in the provision of the good or the service^* (economic cost to producers). In practical terms, it is the net revenue (before tax) that is earned by a producer of goods and services. In Figure 10.2, it is the area between the price line and the supply curve (P₁XP_E). If the diagram is specified in annual terms, the sum of the shaded areas will represent the annual value of the product to society.

10.2.1.1 Application to Fundamental Geospatial Data

The application of the economic welfare theory to empirical analysis of the value of fundamental geospatial data requires many assumptions about the real nature of the markets under examination. Its application to decision support for investment in geospatial data must account for two important issues. First, the custodian of the data is generally a government organization, where the price for access is set by a policy decision—not by the market. Second, the data can exhibit public good characteristics, which has implications for the value that is generated for society.

Under an ideal open data policy, the price for fundamental spatial data would be set at the marginal cost, which is close to or equal to zero when supplied through web-based applications. This is illustrated in Figure 10.3. The value to consumers of this arrangement is the consumer surplus, shown as the shaded area in the diagram.

Welfare analysis has been used on a number of occasions to estimate both the value of geospatial data services in general and the relative economic benefit of different pricing policies.

Pollock (2008) estimated the value of moving from average cost pricing to marginal cost in a report prepared for HM Treasury; the theoretical framework used by Pollock is illustrated in Figure ...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Dedication
• Table of Contents
• Foreword
• Preface
• Acknowledgments
• Editors
• Contributors
• Section I The Socioeconomic Value of Earth Observation: An Overview
• Section II From Data to Decisions
• Section III Measuring Economic and Social Values, Benefits, and Impacts: Methods and Implementation Examples
• Index