Selecting Indicators to Monitor Local Impacts of Resource...
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RESOURCE DEVELOPMENT AND HUMAN WELL-BEING IN PAPUA NEW GUINEA ISSUES IN THE MEASUREMENT OF PROGRESS Wednesday 18th March 2015 Gateway Hotel, Port Moresby Selecting Indicators to Monitor Local Impacts of Resource Projects: Why, Who, How, When, Where and What? Assistant Professor Julia Horsley
Transcript of Selecting Indicators to Monitor Local Impacts of Resource...
RESOURCE DEVELOPMENT AND HUMAN WELL-BEING IN PAPUA NEW GUINEA ISSUES IN THE MEASUREMENT OF PROGRESS
Wednesday 18th March 2015 Gateway Hotel, Port Moresby
Selecting Indicators to Monitor Local Impacts of
Resource Projects:
Why, Who, How, When, Where and What? Assistant Professor Julia Horsley
OVERVIEW
• Why – should we bother to monitor local impacts of resource projects?
• Who – is currently monitoring the local impacts of resource projects - and who should be monitoring the impacts?
• How – should or could we monitor such local impacts?
• When – should we monitor the impacts (determining temporal scale and duration)?
• Where – what does ‘local’ impacts mean (determining spatial scale)?
• What – exactly what is it that should or could be measured (selecting indicators)?
WHY?
Macroeconomic contributions to low and middle income economies
Top four segments of contribution (foreign direct investment, exports, government revenue and national income measured by GDP) accrue to national governments.
Reasons for interpreting (economic) indicators (see Guide to Economic Indicators, Seventh Edition)
• Get a better understanding of how an economy is performing
• Judge the government’s (economic) policies
• Obtain a feel for an unfamiliar economy
• Compare several countries
• Make a forecast
• For investment purposes, get the best return for your money
• Judge if the time is right to give the go-ahead to a new capital investment project, or to move into new markets
SOCIAL (Nurturing Community)
ECONOMIC (Sufficient Economy)
ENVIRONMENTAL (Viable Natural Environment) Sustainable
Development
Sustainable Economic
Development
Sustainable Natural and
Built Environment
Equitable Social
Environment
National Context
Regional Context Global Context
The Enduring Tension in Mining Governance
Attracting Foreign Investments
Maximum National/Community
Benefit VS
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Resource Regions/Communities
• Often characterised by their volatility
• Population surges and crashes linked to the resource cycle (predictable by the commodity price)
• Local economic and social planning implications are worsened because many such settlements are single industry
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Lucas’ Model of Employment Demand in Resource Communities
Socio-Economic Issues
• Economic prosperity is not evenly distributed
• Conflict between “newcomers” and “established residents”
• Conflict over role of local government to fix problems
• Money to mitigate impacts is not available or is late to arrive
Environmental Impacts include:
• Land destruction, subsidence and water loss
• Pollution of water and soil
• Siltation – arising from mining operations and tailings
dam failures
• Loss of flora, fauna, biodiversity and food insecurity
• Apart from mine operations, other excavations for the
installation of facilities, such as portals for deep mining,
lumber yards, ore trains, mills, tailings ponds, power
houses, mine administration offices, and employee
housing
• Acid mine drainage
Exposed Local Communities and Mining Conflict
Davis and Franks (2011): Costs of conflict with local communities in the extractive industry
• Most frequent conflict issues – Pollution (environmental/regulatory) – Distribution of benefits (social/regulatory) – Competition over / access to resources (regulatory) – Consultation and communication (social) – Community health and safety (regulatory)
25 cases of mining conflict in the developing world 40 in-depth interviews with key individuals from extractive companies,
industry bodies, corporate law firms, insurers and researchers
Forms of Mining Conflicts
• Submissions to the company and/or government (23 out of 25 cases)
• Publicity campaigns (23/25)
• Demonstrations (22/25)
• Litigation (16/25)
• Blockades (14/25)
• Violence to property (9/25)
• Violence to person (9/25)
• Deaths (8/25)
Local Environmental and Socio-Economic Impacts – closely linked with human rights issues
Millennium Development Goals (Focus, AusAID, Oct-Dec 2011)
IGF Mining, Minerals, Metals and Sustainable Development
• Established in 2005
• 43 member countries
• Objective: ensure minerals sector contributes to sustainable development and poverty reduction
IGF Mining, Minerals, Metals and Sustainable Development
• Key Concerns: – Legal and policy
environment – Financial benefit
optimisation – Socio-economic benefit
optimisation – Environmental management – Post-mining transition – Artisanal and small scale
mining
Some of the ‘why’s’ of measuring local impacts so far • Compliance with regulations (EIA and SIA)
• Measure compliance with MDG/SDG
• Voluntary Corporate Initiatives and CSR
• Inform government policy, distribution of benefits, mitigation of harms and measure progress
• Measure Well-being
• Community empowerment
• Academic research
• Managing conflict
• Making investment decisions
WHO?
The Resource Sector Expands
• Developing countries encouraged to ‘open up’ to extractive industries (1980s-90s)
100 countries changed their laws and regulations New regions ‘opened up’ for mineral exploration ‘Retreat of the State’ on mining governance Relaxed regulation favoured over sustainable
development Formal delegation of resource rights + informal
delegation of civic responsibilities
Initiatives Applicable to Mining Industry
Brereton (2002:13)
Under increasing pressure to improve its environmental
and social performance
More closely involved in regulating the industry
From environmental issues to broader ‘social justice
agenda, NGO influence is growing
The Changing External Environment of the Mining Industry
MINING INDUSTRY
NGO SECTOR
GOVERNMENTS
FINANCIAL INSTITUTIONS
GENERAL PUBLIC
Highly publicised
environmental mishaps
had weakened
trust in the industry
Growing reluctance to lend for mining-
related projects seen as having significant
social and environmental risks
Adapted from Brereton (2002)
CORPORATE SOCIAL RESPONSIBILITY
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“Poverty alleviation and sustainable
development are not our responsibility”
“Poverty alleviation and sustainable
development are part of our core business”
Power and trust in mining-community relations
• Power = the ability to shape an outcome – Individual power or how system favours particular groups
• Trust = belief in how others will act. – Can communities trust the government and miners?
• Belief that miners and ‘government’ collude
• Perceived lack of access to information
• Mining employees and other beneficiaries unwilling to ‘rock the boat’
Evaluating Participatory Processes
• Community View of Participation – Reasons for participating: sense of
responsibility, anger, recognition of capacity to act
• Individual experiences of participation are often negative
– There can be many reasons for this – Any suggestions?
• Unmet needs and expectations • Lack of commitment or communication • Hidden agendas • Unequal relationships • ‘Tick box’ approach • Lack of empathy
Ladder of Participation
Community Aspirations
CSR / Risk Management
State Development Objectives
Shifting Perceptions of Development/ Human Well-
being
HOW?
Traditionally, the literature on sustainability indicators falls into two broad methodological paradigms (Bell and Morse 2001; Reed et. al 2006; Fraser et al. 2006):
• expert-led and top-down; and
• community-based and bottom-up.
Expert-led approaches predominantly use quantitative indicators drawn from a range of social and other sciences.
The second paradigm is based on a more localised, contextual and participatory philosophy -emphasises the importance of understanding local conditions, values and sustainability monitoring should be an on-going learning process for both communities and researchers (Reed et al. 2006; Freebairn and King 2003).
• Variety of methods and toolkits in use for EIA and SIA
• Reliable indicators of development are often limited by the availability and cost of collecting and analysing data.
• Pressing need to address the conceptual, methodological and practical constraints around understanding the impact of mining on development.
WHEN?
Gilmore’s 4 Stages of Boomtown Attitudes
Enthusiasm
Uncertainty
Near Panic
Adaptation
- Concentration on positive impacts
- Negative impacts are either unknown or dismissed
- Lots of pro-industry spin, but little objective knowledge
- Town starts to change - Realisation that negative
impacts have arrived and might grow
- Begin to research/ analyse the situation but few resources to draw upon
- Industry and State government claims nothing can be done
- Pro/Anti growth divisions emerge
- Industrial activity and impacts develop far faster than expected
- Town starts changing dramatically
- Residents become confused, angry at officials and with each other
- Government services overloaded and officials unprepared or ill-equipped
- Realisation that increased revenues will not match expenditures
- Core problems are identified
- Planning and mitigation strategies are developed
- Residents become solidified in their beliefs
- Sense of progress despite overwhelming impacts
WHERE?
Temporary and permanent migration
‘Push’ and ‘pull’ factors shaping migration decisions
Mining has traditionally been associated with significant labour mobility and processes of temporary and permanent migration
Labour market segments operate very differently Professionals Semi-professional Trades Unskilled
Highly mobile examples, such as Fly-in/Fly-out
Labour Migration and Mobility
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• Implications for the ‘host’ communities – Changes in demographic structure – Changes in social and cultural structure – Changes in economic structure
• Implications for the ‘source’ communities
– Demographic structure – Social and cultural life – Economic implications
• Residential and FIFO have quite different implications
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Implications of Labour Mobility and Migration
WHAT?
Indicators and Key Sustainability Issues (Azapagic, 2004:644)
– The World Bank Databank - http://databank.worldbank.org/ddp/home.do
– Statistics OECD – http://www.oecd.org/statistics/ – IMF/International Monetary Fund Data and Statistics –
http://www.imf.org/external/data.htm – ADB/Asian Development Bank –
http://www.adb.org/data/main – ILO/International Labour Organisation -
http://www.ilo.org/global/statistics-and-databases/lang--eng/index.htm
– Global Mining Initiative – International Council on Mining and Metals http://www.icmm.com/
– Global Reporting Initiative https://www.globalreporting.org/Pages/default.aspx
– International Institute for Environment and Development http://www.iied.org/
– National Resources Canada Minerals and Metals initiative http://www.nrcan.gc.ca/minerals-metals/home
– World Bank’s Oil, Gas and Mining Unit http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTOGMC/0,,menuPK:336936~pagePK:149018~piPK:149093~theSitePK:336930,00.html
– World Economic Forum http://www.weforum.org/ – Extractive Industries Transparency Initiative https://eiti.org/
• In the absence of a consistent approach to the selection of indicators based on clearly defined and conceptually robust notions of ‘development’, it is difficult to determine to what extent inconsistencies in conclusions about the effects of mining on developing countries are due to variations in objects and methods of ‘measurement’, and which represent substantive differences in development trajectories.
• Many ‘conventional wisdoms’ regarding the relationship between resource extraction and development, both positive and negative perspectives, are based on assumptions that have not always been subject to sufficient empirical testing.
Measuring Development in Mining Communities:
Case studies in Africa and Asia
(an IM4DC Action Research Project)
Project Aim
To develop and test a methodology
or ‘indicator toolkit’
for measuring ‘development’
at local and regional scales
in mining affected communities
in developing countries.
Background: Mining and Development
• General assumption that mining contributes positively to national economic development
• Conflicting research evidence about the relationship between mining and economic development
• Most existing analyses of the relationship are conducted at a national scale
• There is an absence of clear and consistent evidence regarding the impact of mining at local and regional levels
Background: Measuring Development
• Extending concept of development beyond national economic measures
• Range of indicators and assessment frameworks - World Bank - Sustainable Development - MDGs - Sustainable Livelihoods Approach - 5 capitals
• Surfacing stakeholder perceptions of ‘development’ underlying the frameworks for its measurement
Background: Applying Relevant Development Indicators to Mining
• What measures make sense to help us assess the relationship between mining and development at a local and regional scales?
Resource literature: Mining
measured by conventional
national, economic indicators
Development literature: broader
definitions and scales of
assessment
Applying relevant indicators to
measuring local and regional
impacts of mining
Case Study Countries
Country Commodity Additional Choice Factors Ghana Gold Strong history of democratic governance
over past decade. Long history of mining Zambia Copper Substantial concentration of mineral
wealth in particular area (Copperbelt). Long history of mining
Rwanda Tin, Tantalum, Tungsten
Post-conflict development profile; Emerging mining economy.
Indonesia Coal Substantial policies across archipelago. Indigenous issues.
Approach and Methods
1. Initial review of indicator frameworks and specific indicators
– NGO and government documents
– Academic literature
2. In country scoping and establishment of local partnerships
– Local academic research partners
– Initial government, NGO and industry contacts
– Scoping of possible fieldwork location
3. Fieldwork in each case study country
– Two sites in each country
– Stakeholder interviews on the relative merits of indicators
– Based on a Q-sort approach, supplemented with qualitative data from interviews
• A method originally developed in psychology for measuring and quantifying individuals’ perceptions on issues
• Essentially asks people to rank a large number of items from ‘most important’ to ‘least important’ using the matrix below
• Forces people to make choices about what the feel most strongly about
• Provides a systematic means of comparing perceptions across individuals and identifying common trends
Q-Sort Method
• A set of agreed indicators (drawn from the literature and local partner discussions) are presented to participants along with the table below
• Participants are asked to place indicators in the table according to which they feel are most important to least important as measures of development
• This forces a ‘normal’ distribution (or bell curve) on the responses
• Concurrent to the Q-sort is a discussion with the participant about their choices, offering more qualitative insights and views on ‘missing indicators’
How the Q-Sort can be used to select indicators
• Scores entered by each individual in the matrix are transcribed into the Statistical Package for the Social Sciences (SPSS)
• Initial stage includes producing simple descriptive statistics
– Highest and lowest ranked indicators – Variability by stakeholder group – Variability by location/country
• A principal components analysis (PCA) is then undertaken to look for statistical relationships between indicators
• Aim: identify common groupings of indicators that are regarded as important, and how these groupings vary between stakeholders and localities
Q-Sort Data Analysis
• In the example here 3 components are identified based on mock indicators
• Looking at the ‘loadings’ you can see that there are some patterns apparent
• Judgment is then used to try to work out what these components mean and should be called
• In the model here, there is a strong degree of variance explained by component 1 – in other words it is the most consistent pattern within the data
• Component 2 as some similarities with Component 1
• Component 3 is quite different
• We can now correlate back these components to individual stakeholders and see if there are patterns for particular groups or locations
• This can now form the basis of a comprehensive assessment of the viability of indicators
Interpreting the Findings
• Which indicators are commonly regarded as important across all groups
• Which indicators are important to particular stakeholder groups
• Which indicators are important within particular geographical contexts
• Which important indicators are missing
What we learn from the Analysis
1. Convergence and divergence – What were the indicators around which there was the
greatest level of agreement in terms of: • Importance • Lack of importance
2. Important missed indicators
3. Which indicators on the list are readily measurable? – Geographical scale – Temporal scale
4. How feasible (in terms of time and resources) is it to invest in developing these measures
5. Validity of indicators
Testing the Indicator Framework
Key Outcomes
• Methodology/toolkit for developing a framework to monitor local/regional development impacts of mining
– Selecting appropriate indicators – Investing strategically in data collection – Analysing data to inform mining and development policy
and planning
• A contribution to academic debate on the conceptualisation of ‘development’, and the relationship between mining and development.
25 SAMPLE INDICATORS
BASED ON THE
5 CAPITALS
FOR
MEASURING LOCAL IMPACTS
Conceptualisation (based on five
capitals)
Stakeholder engagement, testing & validation
Indicator development (focus on known mining impacts)
Outline of process of indicator selection (conceputalisation, reflection and experimentation) modified from Sayer et al. (2006).
The Five Capitals
Financial capital: savings, gold/jewellery, access to regular income, net access to credit, insurance.
Human capital: labour power, health and nutritional status, skills and knowledge.
Natural capital: access to land, water, wildlife, flora, forest.
Social capital: refers to those stocks of social trust, norms and networks that people can draw upon to solve common problems, and which is mediated through kin networks and group membership.
Physical capital: houses, vehicles, equipment, livestock.
• Various vulnerability factors (such as environmental stresses and shocks) directly impact assets + policies, institutions and governance processes indirectly impact access to assets – each affecting the degree to which livelihood objectives are realised.
Status of capital assets in the Tri-National de la Sangha, Congo (Endamama et al. 2010)
Attributes of SLA in resource context
• may be alternatively construed as a set of principles, an analytical framework, and a development objective and is thereby flexible enough to be combined with other constructs and paradigms;
• the evidence-based approach of the SL framework could be put to good use in testing the array of theoretical assumptions about the positive and negative impacts of mining;
• the ability of the SL framework to focus in at the micro level is a strength that may further enhance analysis of the impacts of the mining sector on development which has tended to focus at the macro level;
• the SL framework can be used not only to organise information, but also to help its users to restructure information and knowledge from multiple perspectives – another missing thread in resource literature; and
• the emphasis on participatory methods promoted by the SL framework may also contribute to better decisions in both public policy and private investment sectors of resource economies.
Q-Methodology
• a scientific method of analysing people’s opinions, concerns, perceptions, and standpoints about a certain issue.
• combines the strengths of both quantitative and qualitative research approaches in that it examines people’s subjectivity using a factor analysis technique Brown (1996).
• by defining and identifying main issues in a particular topic that are important to people in a given area, the method enables to pin down key viewpoints and values by specifying people’s positions regarding different aspects of the issues.
• ability to identify similarities, group items being studied into categories and looking for patterns and establish relationships between and within the categories (Shinebourne, 2009).
Applying SLA to Selection of Indicators
• Why – people-centred (cf. envrionment vs economy)
• Who – collaborative between community, govt and industry
• How – collecting data at household level, and multiple shared capitals – both quantitative and qualitative methods
• When – recognises the dynamic nature of livelihoods, and changes to capital over time
• Where – affected communities can be identified through shared capitals
• What – populating a series of indicators under the 5 capitals using top down and bottom up methods, adaptable to local and regional contexts
Other questions SLA could address
• How can the quality and relevance of the data that is collected to assess the social impact of major resource projects be improved without simply adding to the cost of collection?
• How can optimal use be made of measurements of human well-being at a local level in the design and delivery of more effective development interventions, both inside and outside the extractive industry sector?
• How can mining and petroleum companies work more effectively with government and non- government agencies involved in the measurement of human well-being at a local scale?
Dr VERONICA HUDDLESTON
Associate Professor School of Earth and
Environment The University of Western
Australia 35 Stirling Highway Crawley WA 6009
Australia Phone: (61-8) 6488-2705
Email: [email protected].
au
Horsley, Julia, Prout, Sarah, Tonts, Matthew and Ali, Saleem H. (2015) Sustainable livelihoods and indicators for regional development in mining economies. Extractive Industries and Society, . doi:10.1016/j.exis.2014.12.001
QUESTIONS?
