The financial costs of mitigating social risks: Costs and effectiveness of risk mitigation strategies for emerging market investors

Feyertag, Joseph; Bowie, Ben Research Report The financial costs of mitigating social risks: Costs and effectiveness of risk mitigation strategies for emerging market investors ODI Report Provided in Cooperation with: ODI Global, London Suggested Citation: Feyertag, Joseph; Bowie, Ben (2021) : The financial costs of mitigating social risks: Costs and effectiveness of risk mitigation strategies for emerging market investors, ODI Report, Overseas Development Institute (ODI), London This Version is available at: https://hdl.handle.net/10419/280286 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ Report The financial costs of mitigating social risks Costs and effectiveness of risk mitigation strategies for emerging market investors Joseph FeyertagID and Ben Bowie September 2021 Readers are encouraged to reproduce material for their own publications, as long as they are not being sold commercially. ODI and TMP Systems request due acknowledgement and a copy of the publication. For online use, we ask readers to link to quantifyingtenurerisk.org. The views presented in this paper are those of the author(s) and do not necessarily represent the views of ODI or our partners. This work is licensed under CC BY-NC-ND 4.0. How to cite: How to cite: Feyertag, J. and Bowie, B. (2021) The financial costs of mitigating social risks: costs and effectiveness of risk mitigation strategies for emerging market investors. ODI report. London: ODI (https://odi.org/en/publications/the-financial-costs-of-mitigating-social- risks-costs-and-effectiveness-of-risk-mitigation-strategies-for-emerging-market-investors). Photo: Wind turbines, Jiangxi Province, China. Credit: Visual China Group via Getty Images. Acknowledgements We would like to acknowledge and thank the following: • Roger Calow, Benedict Lever, Lou Munden and Lizzy Tan for their support in the data collection process. • Beatrice Tanjangco, Anna Locke and Kathryn Nwajiaku-Dahou for providing valuable guidance, advice and peer review. • Lorenzo Cotula, Shivani Kannabhiran, Charlotte van Andel and Kate Mathias for providing feedback on the questionnaire and reflections on the report. • Oliver Knight and Chris Penrose-Buckley for valuable inputs from FCDO, and for being flexible around the constraints created by the pandemic. • Sarah Cahoon, Orla Martin and Ana Lucia Nunez Lopez for managing the project so effectively. • Steven Dickie and Jessica Rennoldson for editing, creative ideas and design. • Ibrahima Ka for translating the business perceptions survey into French and distributing it to private sector partners in Senegal. We would also like to thank the investors who participated in this research by responding to the survey and speaking to us during interviews. We are constantly improving, expanding and refining our model and invite other businesses to take part. Sharing company data contributes to a better investment environment for the industry as a whole. All data shared with the QTR initiative is anonymised and confidential, and we would never share it or disclose the names of businesses without explicit permission. About this publication This report is part of an ongoing Quantifying Tenure Risk initiative, an FCDO-funded programme that began in September 2017 and is being implemented by ODI and TMP Systems. About the authors ORCID numbers are given where available. Please click on the ID icon next to an author’s name in order to access their ORCID listing. Joseph FeyertagID Joe is a Research Fellow in the Climate and Sustainability programme at ODI in London. He is an economist whose research focuses on the environmental and social impact of financial investments in emerging markets, including gender equality, land tenure security, skilled job creation and climate-resilient land use practices. Prior to joining ODI, Joe managed environmental and social risk assessments for agricultural investors in the private sector in the Americas, sub-Saharan Africa and Central and Southeast Asia. He has a DPhil and MSc in Social Policy from the University of Oxford, where he continues to teach as an Associate Member. Ben Bowie Ben Bowie has been with TMP Systems since 2011. During that time, he has successfully directed projects across more than 25 countries in Africa and Asia for problems such as poverty reduction, human rights, small-scale energy, gender equality, climate change and sustainable agriculture. He was formerly a consultant for a range of institutions, including ODI, Global Witness, the European Commission and Open Democracy, and for companies in the extractive industries. He received his MSc in Asian Politics from SOAS University of London, and his BA in Social and Political Sciences from Cambridge University. He lives outside Oxford. Contents Acknowledgements / i Display items / iv Acronyms / v Executive summary / 1 1 Introduction / 5 2 Approach / 7 2.1 Theory of change / 7 2.2 Quantitative data collection / 8 2.3 Business perceptions / 10 2.4 Data limitations / 11 2.5 Model methodology / 12 3 Findings / 14 3.1 Investors spend 2% on social risk mitigation / 14 3.2 The cost of social risks is up to four times higher than the cost of mitigating these risks / 15 4 Conclusions / 22 References / 25 Appendix 1 Descriptive statistics / 27 Appendix 2 Business perceptions survey / 30 Appendix 3 Interview template / 36 Display items Figures Figure 1 Summary of findings showing business case for social risk management / 2 Figure 2 Theory of change / 8 Figure 3 Map of DFI projects reviewed for this research / 9 Figure 4 Geographical distribution of business survey recipients / 11 Figure 5 Number of projects by expenditure on social and environmental risk mitigation / 14 Figure 6 Expenditure on social and environmental risk mitigation against risk score of project location / 15 Figure 7 Project locations by value for money / 16 Figure 8 Value for money of risk mitigation efforts by risk of location / 17 Figure 9 Effectiveness of social risk mitigation procedures / 18 Figure 10 Cost-effectiveness of social risk mitigation procedures / 19 Figure 11 Profile of investors answering the survey / 19 Figure 12 Range of losses by commodity and location according to Tenure Risk Tool / 23 Tables Table 1 Value for money criteria / 16 Boxes Box 1 Key findings / 4 Box 2 QTR methodology / 13 Box 3 What is social dialogue? / 18 Acronyms DCF discounted cash flow DFI development finance institution ESG environmental, social and governance ESIA environmental and social impact assessment ESMP environmental and social management plan FPIC free, prior and informed consent GIZ Deutsche Gesellschaft für Internationale Zusammenarbeit GRI Global Reporting Initiative IFC International Finance Corporation NPV net present value OPIC Overseas Private Investment Corporation QTR Quantifying Tenure Risk USAID United States Agency for International Development XIRR extended international rate of return XNPV extended net present value 1ODI Report Executive summary This report assesses the costs and effectiveness of responsible investment practices in emerging market contexts. Its results make the business case for investments in social risk mitigation and avoidance practices. Such practices include community engagement efforts, impact assessments and the establishment of grievance resolution mechanisms. Implemented correctly, responsible investment practices engender confidence and trust between investors and local communities, which secures social buy-in and mitigates the financial risks associated with disputes. To assess the costs of these practices, we analysed financial data from 137 development finance institution (DFI) investments in emerging markets. We consulted a further 85 agricultural investors in sub-Saharan Africa to further establish the effectiveness of those investments. Our results suggest the following: • The costs of implementing social risk mitigation activities in emerging markets are around 2% of project costs (roughly 10% of the net present value (NPV) of investments). Across the portfolio of projects analysed, this represents an average expenditure of around $10 million per project. • This compares to potential financial damages of $25–40 million per project, equivalent to 24–37% of the NPV of investments. • Investors consider social dialogue processes to be the most effective risk mitigation strategy. Over 90% of investors in sub-Saharan Africa considered social dialogue to be a highly effective way of identifying community needs, targeting them and achieving social license to operate. • There is room for improving the effectiveness and reducing the costs of social risk mitigation. Some complex and rigid procedures, such as those typically associated with environmental and social impact assessments or dispute resolution mechanisms, were perceived as cost-inefficient and ineffective by 12–15% of agricultural investors. We conclude that investments in social risk mitigation and avoidance make clear financial sense. By setting aside at least 2% of the initial NPV of an investment, investors can avoid financial risks that, conservatively, are up to four times the cost of risk mitigation procedures (Figure 1). To mitigate social risks in the broader emerging market investment landscape, social dialogue processes should be integrated in national and international investment approval procedures and disclosure requirements. Governments interested in mitigating the social risks of both domestic and international investors should introduce requirements for spending on stakeholder mapping, broad-based community consultation and needs-based community development programmes. As a rule of thumb, they could ask investors to set aside a minimum of 2% of project expenditure on community engagement activities. Voluntary environmental, social and governance (ESG) standards, such as the Global Reporting Initiative’s (GRI’s) topic-specific disclosure requirements, offer frameworks for monitoring such efforts and thereby ensuring social risks are mitigated. This would lead to better business performance, a better investment environment and better local impact. 8ODI Report Figure 2 Theory of change Note: DFI = development finance institution. 4 Often, this necessitates the use of expensive international consultants who may be similarly unfamiliar with the particular context. 5 In addition to DFI-funded projects, we used ESIAs and ESMPs from a hydropower project in Pakistan funded by the United States Agency for International Development (USAID) and Third Optional Protocol to the Convention on the Rights of the Child (OPIC) and a forestry project in Laos funded by Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ). 2.2 Quantitative data collection 2.2.1 Expenditure on social risk mitigation measures Social due diligence systems in emerging or frontier markets are often immature, allowing for little price transparency of social risk mitigation efforts.4 This makes it difficult for companies unfamiliar with a particular area or geography to determine how much of their investment needs to be set aside for such activities. Furthermore, where responsible investment processes are carried out, it may not always be possible to determine whether they have been effective in terms of reducing social risks. From a data collection perspective, most cost and risk data in private transactions is proprietary. Collecting and analysing it therefore requires close collaboration and mutual trust, especially around sensitive issues such as disputes over land and other natural resources. As such relationships are difficult to strike up remotely, planned data collection for this report was to involve three field visits in East, West and Southern Africa. In-person meetings and visits would have facilitated the collection of necessary financial data, but plans were disrupted by the Covid-19 pandemic. Instead, data collection concentrated on publicly available financial expenditure data in environmental and social impact assessments (ESIAs) or environmental and social management plans (ESMPs). This information was primarily collected for projects led by DFIs, such as the African Development Bank, the Asian Development Bank, AgDevCo, the Japan Bank for International Cooperation and the World Bank.5 DFIs and impact investors Raise awareness of social risks Quantify social risks Quantify effectiveness of social risk mitigation Quantify costs of social risk mitigation Social risk mitigation actions Mobilise socially responsible investment in emerging markets Risk-averse private investors QTR Phase I QTR Phase II Increase price transparency 9ODI Report In total, we reviewed financial data from 137 projects across 56 countries in Africa and Asia (Figure 3 and Appendix 1). For each project, a detailed financial breakdown of expenditure on social and environmental risk mitigation was available. We extracted relevant expenditure and converted it into United States dollars based on the date that the expenditures were made. The time period for the projects ran from 2002 to 2020, enabling the inclusion of at least two projects for each of the countries analysed. This approach allowed us to address two issues. First, many smaller privately-funded investments in emerging markets do not give a financial breakdown of expenditure on social risk mitigation, or have devoted negligible resources due to lack of awareness. While this is changing rapidly due 6 Nonetheless, a number of project accounts which did not have the suitable level of detail in the cost breakdown of the ESIA/ESMP documents had to be discarded. to a growing wave of private impact investors and increasingly strict disclosure requirements, DFIs have a much longer track record in investment in social and environmental risk mitigation measures. The International Finance Corporation (IFC)’s Performance Standards, for example, offer the most widely-used resource for assessing and managing social and environmental risks in emerging market settings (IFC, 2012). Second, where we did receive financial data from private investors, it was often so project-specific that it was impossible to compare with data from other projects and so could not be used for quantitative analysis. Although some data had to be aggregated because different institutions used different terms and breakdowns, the DFI data was broadly comparable.6 Figure 3 Map of DFI projects reviewed for this research SuperiorExcellent Good Fair Poor EnergyAgriculture Hydropower Infrastructure Sanitation Other 10 ODI Report 2.2.2 Delay data We also analysed whether the DFI projects had been involved in any delays. In most cases, delays could be identified from project completion or evaluation documents. Where these were unavailable, news media, independent reports and research studies were used to plug information gaps. Delays were rated using the following five-point scale: (i) no delay; (ii) less than a month; (iii) more than a month; (iv) more than a year; (v) cancellation/abandonment. 2.3 Business perceptions We complemented the financial analysis using qualitative data from a remote business perceptions survey. The survey was sent to 727 private businesses operating in the sub-Saharan African agricultural supply chain. The majority of the businesses surveyed were located in West Africa (41%) and Southern Africa (34%) (Figure4). The survey (see Appendix 2) comprised a short series of questions that covered four areas: • the profile of the business: e.g. sector and geography • experience of social risk: experience of dispute, financial impact of dispute • experience of social risk mitigation and avoidance actions: procedures implemented and perceived effectiveness of those procedures • options for follow-ups, including contact data, preferred mode of dissemination and willingness to be interviewed. 7 The survey was sent to US-based companies, fewer of whom would be familiar with the social risks associated with land rights compared with businesses operating in sub-Saharan Africa (where such issues are endemic). This may explain the difference in response rates. The survey was piloted with DFIs, commodity traders and producers in April 2020 to gather feedback on its design and presentation. As a result, the number of questions was reduced significantly and questions that were deemed too financially sensitive were removed. The survey was distributed using Mailchimp and personalised emails in English and French over three rounds between September 2020 and April 2021. The personalised emails proved most effective and resulted in an overall response rate of 11.7% (85 responses). We consider this high given the challenges of collecting remote survey data in a rural, emerging market during a global pandemic. The only comparable survey that the authors are aware of, the USAID Investor Survey on Land Rights (USAID, 2018), had a response rate of 2.9%.7 Of the businesses that responded, 35 agreed to being interviewed by telephone, video conference or in writing. Interviews were semi-structured and informal, following a template (see Appendix3) that was similar to the online survey, but which was focused on gathering information on the effectiveness of mitigation and avoidance actions, as well as ideas about how to make them more cost-effective. The data gathered from this process is largely anecdotal, but provided for a valuable supplementary layer of analysis that helped us to interpret the quantitative findings. The majority of participants spoke in a personal capacity, and therefore preferred not to disclose their name or the name of the business they work for. In some cases explicit permission was received to share this information, which has allowed us to include in this report some quotes extracted from participants’ responses. 11 ODI Report Figure 4 Geographical distribution of business survey recipients Note: Countries not displayed: Chad (2), Mauritania (2) and Niger (2) in Central Africa, Mauritius in Eastern Africa, Namibia (9) and Botswana (3) in Southern Africa, and Benin (4), Burkina Faso (8), Gabon (6), Gambia (1), Guinea (2), São Tomé and Príncipe (1) and Togo (2) in West Africa. 2.4 Data limitations Our research pulls together a strong set of quantitative and qualitative data across relatively large samples, but there are also limitations that might be addressed in subsequent research efforts. The main challenge related to identifying and categorising data related to expenditure on social risk mitigation. As noted, DFIs provide good breakdowns of expenditure which can be compared, but they do not use the same categories, currencies or terms consistently (even within organisations). We therefore needed to make judgments regarding which expenditures should be included. Expenditures on actions such as consultation, impact assessment, dispute resolution, capacitybuilding and compensation were all included because of their very direct connection to achieving social license to operate. However, we also took note of previous research that shows that 26% of disputes are caused by environmental issues (making this the second most common cause of disputes) Central Africa C.A.R., 12 Cameroon, 10 D.R.C., 17 Congo, 12 Ethiopia, 17 Kenya, 25 Rwanda, 12 Tanzania, 12 Uganda, 56 Southern Africa Eswatini, 11 Madagascar, 11 Malawi, 17 Mozambique, 107 South Africa, 18 Zambia, 49 Zimbabwe, 20 West Africa Côte d'Ivoire, 23 Ghana, 38 Liberia, 53 Mali, 21 Nigeria, 63 Senegal, 50 Sierra Leone, 29 Eastern Africa 12 ODI Report (TMPSystems,2016). We therefore also included some expenditures that related to the assessment and mitigation of environmental impacts, provided there was a clear connection to social license issues (e.g. managing air and noise pollution). This limitation in the data, which could be broken down with greater granularity, does not alter the force of our argument: it results in higher costs, but our research shows that these expenditures still represent good value for money (i.e. they represent one-fifth (20%) or less of the cost of social risk). The other key limitation in our data relates to the focus on DFIs in the quantitative data. As noted, this was the only data that we could find in the public domain that was fit for purpose. But our survey data comes from a different set of stakeholders: private businesses in the African agriculture sector. These differences are more than sufficient to prevent direct comparison of our quantitative and qualitative datasets. Since they have a specific mandate to secure development outcomes, DFIs may spend more on social risk mitigation than some private investors. However, they may also have more experience in social risk mitigation and therefore face lower costs than private sector actors. Nonetheless, our data is complementary. The basic picture substantiated by our quantitative research can be effectively compared and contrasted with our survey responses to present a balanced and revealing picture, albeit one that would benefit from further development. 2.5 Model methodology The data and information gathered from the financial analysis, the survey and the interviews was used to update a discounted cash flow(DCF) model that can be used by businesses to estimate social risk. The model is built on the assumption that the primary financial impact of social risk is to delay operations. This delay can occur in two ways: • At inception, typically through opposition from local communities directly or indirectly affected by an investment and requiring renegotiation, administrative delays (e.g. caused by opposition from local government) or, in the worst case, repair or reconstruction of damage caused by local opposition. • During operation, usually because of the associated disruption to production of an expected output (e.g. crop production, electricity generation, etc.) that is needed to generate revenue. In the meantime, we assume that operational expenditure continues. The financial impact of these delays can be captured using the DCF model to derive the NPV of a project. The NPV can be used to generate a comparable measure of the magnitude of social risks associated with investments. We ran the model for each of the 137 DFI projects for which financial data was available (see details in Appendix 1). Although data on the overall project size was available, it is not typically broken down on the year-on-year revenue, capital and operational expenditure basis required for a DCF model. When running the model, we therefore made the following basic assumptions when constructing the DCF for each project: • Project duration is 25 years, regardless of type or location. • Each project’s total cost is used as its capital expenditure. It is assumed that all capital expenses fall in the first year. 13 ODI Report • Annual operating expenditure is 2% of the capital expenditure. • There are no annual revenues for the first two years. Thereafter there is an annual increase of 200%, starting with a base of 0.5% of the capital expenditure in year three, until a plateau of revenues equivalent of 36% of capital expenditure is reached in year nine. • A 10% discount rate is applied to all projects to capture interest rate developments. This assumption is supported by existing research on discount rates in the Global South (Warusawitharana, 2014). The extended internal rate of return (XIRR) across all projects is calculated as 12.88%. This falls into the middle range of internal rates of return for DFI projects.8 The extended net present value (XNPV) varies depending on the total project cost. These baseline values are then compared with the equivalent XIRR and XNPV values resulting from delay scenarios. The extent of these delays (in number of days), and hence their financial impact on a project (e.g. in terms of foregone revenue), varies depending on a project’s geographic location. Risk factors associated with known historical disputes over land (social risks) vary by location and affect the parameters of the simulation. A summary of the methodology used to calculate this is provided in Box 2. The difference between the XNPV and XIRR values in a delay scenario and the baseline values represents the potential financial impact of social risks. This can be compared with the expenditure on social risk mitigation and avoidance actions to complete a cost–benefit analysis. 8 A recent review of historical IFC financial statements shows that rates of return (on equity) were between –0.9% and 20.6% between 2000 and 2019, averaging at exactly 7% (Cole et al., 2020). Another study by the Japan International Cooperation Agency for a public–private partnership infrastructure project in Vietnam in 2013 sets an internal rate of return of 10–15% as ‘medium’ (JICA, 2013). Box 2 QTR methodology 1. Using the project’s location as an input, a risk score is generated based on the correlation between various geospatial risk factors and historical reports of project delays. A detailed explanation of this methodology is provided in the 2019 QTR report and appendix (Locke et al., 2019). 2. The risk score is compared to a set of cases of known project delays to determine a best, median and worst scenario, expressed as a number of days. 3. The delays are applied at the inception (greenfield) and operational (brownfield) phases of the project, while retaining the original capital and operational expenditure projections and resulting in an XIRR of 12.28% across all projects. XNPV values are calculated for both scenarios, depending on costs and location. 4. The three XNPV values (best, median, worst) for the inception and operational delay scenarios are averaged to obtain two final XNPV values. 5. Finally, the XNPV values for greenfield and brownfield investments are subtracted from the baseline XNPV value (i.e. the value that would have resulted had no delays occurred). 14 ODI Report 3 Findings 9 This is due to compensation payments, amounting to $435 million, associated with the resettlement of 8,150 people in hamlets and villages affected by the reservoir and dam. 3.1 Investors spend 2% on social risk mitigation Average expenditure on social and environmental risk mitigation was approximately 2% of total project costs. With project costs averaging $497million across the 137 DFI projects analysed, this represents a cost of just under $10 million per project to mitigate social and environmental risks. The vast majority of projects analysed (106 projects or 77%) implemented social risk mitigation measures that represented 4% or less of their total expenditure (Figure 5). However, there were some outliers, for which expenditure on social risk mitigation was excessive. For many of these projects, the high costs were influenced by compensation or resettlement payments. For example, one extreme outlier, the Kandadji Dam Project in Niger, funded by the African Development Bank, involved risk mitigation costs of 56.8% of the total project cost.9 There is a weak but positive and statistically significant correlation between expenditure on social risk mitigation and the magnitude of social risks (Figure 6). However, there are numerous outliers at either end of the risk distribution, where projects have above- or below-average expenditure on social and environmental risk mitigation relative to the risks associated with the geographical location. Some of these outliers are located in small countries such as the Comoros, where risks are low but service delivery costs are high. In other locations where social risks are high, such as parts of Afghanistan or South Sudan, projects exist where expenditure on risk mitigation is below average. This suggests that expenditure is influenced by a host of contextual factors that are not necessarily captured by risk scores, and that investors therefore cannot rely on such metrics alone to determine how much budget should be set aside for risk mitigation. Figure 5 Number of projects by expenditure on social and environmental risk mitigation 0 5 10 15 20 25 30 35 0 1 2 3 4 5 6 7 8 9 10 10+ No. of projects Rounded expenditure on social and environmental mitigation as % of total project cost 15 ODI Report Figure 6 Expenditure on social and environmental risk mitigation against risk score of project location 10 For example, the analysis assumes that 100% of the capital expenditure falls within the first year of the investment. However, for most agricultural investments capital expenditure is likely to be spread across a number of years (e.g. to allow for planting), with large expenditures occurring at a later stage (e.g. when throughput is sufficient for processing). We discuss this in Chapter 4. 3.2 The cost of social risks is up to four times higher than the cost of mitigating these risks Without adopting social risk mitigation strategies, investors risk losing $25–40 million due to delays to the inception or operation of a project. This represents a loss of 24–37% of the NPV across all projects analysed. On average, the financial damage caused by social risks ($25–40 million) can therefore be up to four times higher than the cost of risk mitigation ($10 million). These figures represent averages, so again there are notable outliers. For nine cases, the financial risk of delays caused by social risks was more than $100 million, but in 38 cases it was less than $5 million. The size of a financial risk is highly dependent on a project’s location, its overall size and the structure of the investment.10 We also do not include projects that were cancelled or abandoned, and for which risk mitigation data is not available. For these projects, the financial risks are many times higher than the costs of mitigating them. To analyse this further, we compared the financial risks that projects face with their expenditure on social risk mitigation. If that expenditure is greater than 50% of the financial risk that a project faces in its particular location, the risk mitigation effort was considered ‘poor’ value for money. Using a hypothetical example, a project that spends more than $5 million on social risk mitigation efforts when the average financial risk in the project location is $10 million would be considered poor value for money. In addition, we automatically categorise projects that experienced delays of more than a year as ‘poor’ regardless of their expenditure on social risk mitigation (Table 1). Comoros Tanzania Ghana Ghana Cape Verde Benin Bangladesh Algeria South Sudan Afghanistan 0 2 4 6 8 10 12 14 16 18 20 0 10 20 30 40 50 60 70 80 90 100 Social and environmental risk mitigation expenditure (% of total project) Social risk score at location 16 ODI Report Table 1 Value for money criteria Value for money Cost of mitigation as % of social risk Additional criteria Poor 50 Delay > 1 year Fair 20–50 Delay = 1–12 months Good 11–20 N/A Superior 5–10 N/A Excellent 5N/A Risk mitigation expenditure was considered ‘good’ to ‘excellent’ if it represented 20% or less of the financial risk. Projects experiencing moderate delays of 1–12 months were automatically categorised as ‘fair’, regardless of their expenditure. The breakdown by category is shown in Figure 7, together with a map of project locations. There are two significant findings that result from this analysis. First, as shown in Figure 7, over half (52%) of the projects implemented social risk mitigation measures that represented good, superior or excellent value for money. That is, they did not experience delays of more than a month, and their expenditure did not exceed 20% of the financial losses that would have been incurred in the event of a delay. The remainder of the projects implemented risk mitigation measures that were either very expensive compared with the financial risks that could have been incurred, or they experienced delays of over a month. Figure 7 Project locations by value for money 22.0% 11.7% 18.2% 22.6% 25.5% Value for money SuperiorExcellent Good Fair Poor 17 ODI Report Second, we can disaggregate the data by location and thus by the risks associated with each location (Figure 8). This shows that the majority of investments (71%, or 97 projects) were in challenging locations (their risk score was above 60). It is notable that despite the significant social risks, the vast majority of projects in those locations (59% of the 97 projects) implemented social risk mitigation efforts that were deemed good to excellent. They did not experience significant delays, and their costs did not exceed 20% of the overall financial risks in those locations. This suggests that DFIs have developed effective ways of dealing with challenging social risks, and that by implementing moderate investment in the right mitigation measures significant financial damage can be managed or avoided. Of the 66 projects for which social risk mitigation efforts were considered poor or fair value for money, 25 experienced long delays despite their expenditure on managing social risks. These projects represent many of the outliers mentioned above, including projects that were located in small states or which involved significant costs for compensation. Social dialogue is the most effective form of risk mitigation With a few exceptions, the breakdown of expenditure on social risk mitigation by DFIs is not sufficient to allow analysis of the types of strategies or actions adopted. However, the business perceptions survey of 85 investments in sub-Saharan Africa shows that establishing social dialogue with local people is by far the most effective way of mitigating social risks (see Appendix 1 for descriptive statistics). Social dialogue activities include participatory monitoring processes, continuous assessments and meetings to help investors understand how communities feel about their operations and what those communities are expecting to achieve (see Box3). In total, 90% of businesses that had social risk Figure 8 Value for money of risk mitigation efforts by risk of location Good to excellent value for money Fair Poor value for money 57 11 3 71 21 7 3 31 19 8 8 35 0 10 20 30 40 50 60 70 80 90 100 Challenging location Standard risk Favourable location Total Projects (%) 24 ODI Report requirements, this emphasises that investors should report information on stakeholder engagement plans, broad-based local community consultation committees and local needs-based community development programmes. Although widely used, the GRI ESG framework remains voluntary. However, GRI and other similar frameworks (e.g. the Sustainability Accounting Standards Board’s Standards) could be used to guide governments seeking to tighten disclosure requirements to mitigate social risks to both domestic and international financial investments. A specific way of monitoring financial investments would be to require the disclosure of spending on social dialogue activities, including stakeholder mapping, broad-based community consultation and needs-based community development programmes. Our findings suggest that overall spending should be at least 2%. A similar measure adopted by South Africa’s Risk Mitigation Independent Power Producer Procurement Programme committed power producers to contribute a 1% share of the revenue to community needs. In fact, the average commitment level by producers was 2.2%, over double the level of the compliance threshold (IPPO, 2020). Regardless of voluntary and involuntary standards and guidelines, the findings of this report should add momentum to the business case for mitigating social risks. An increasing number of private investors are understanding that the financial benefits of mitigating social and environmental risks far outweigh the costs. However, many of these returns are not tangible and may only be realised in the medium to long term. These include effects on reputational or litigation risks not covered by this report. To realise these benefits, financial lenders need to structure their capital in a way that gives investors the time required to secure local buy-in and reduces long-term risks, and which looks beyond short-term financial profit-maximising strategies. This approach also needs to be extended to identifying and targeting climate-related risks. Involving local communities through social dialogue processes is an important part of determining how natural resources are used and protected (for example, see Ludi et al., 2015, on risk-screening for water supplies). Such approaches would help investors understand how their operations might affect the natural resources that local people care most about. It will therefore be vital to consider both social and environmental risks and impacts to ensure that future private investment, particularly in renewable energy and infrastructure projects, is designed in a just and equitable way. References Cole, S., Melecky, M., Mölders, F. and Reed, T. (2020) Long-run returns to impact investing in emerging market and developing economies. Policy Research Working Paper 9366. Washington DC: World Bank Group (https://openknowledge.worldbank.org/bitstream/handle/10986/34383/ Long-run-Returns-to-Impact-Investing-in-Emerging-Market-and-Developing-Economies. pdf?sequence=1&isAllowed=y). Cotula, L., Berger, T. and Schwartz, B. (2019) Are development finance institutions equipped to address land rights issues? A stocktake of practice in agriculture. LEGEND report (https://landportal.org/library/resources/legend-dfi-report-2019/are-development-finance- institutions-equipped-address-land). 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Centurion: IPPO (www.ipp-projects.co.za/Publications/Get PublicationFile?fileid=24721acc-cb80-eb11-952f-2c59e59ac9cd&fileName=20210222_IPP%20 Office%20Q2%20Overview%202020-21.pdf). JICA – Japan International Cooperation Agency (2013) Study on establishment of financing mechanism for the PPP infrastructure projects in Vietnam: final report. Tokyo: JICA (https://openjicareport.jica.go.jp/pdf/12086567.pdf). Locke, A., Munden, L., Feyertag, J. et al. (2019) Assessing the costs of tenure risks to agribusinesses. London and Lewes: ODI and TMP Systems (https://landportal.org/node/79770). Ludi, E., Calow, R. and Greaves, F. (2015) Environmental assessment and risk screening for rural water supply. SWIFT Consortium guidance note. Oxford: Oxfam GB (https://assets.publishing. service.gov.uk/media/57a3769240f0b652dd001c8c/SWIFT-enviro-risk-screening-tool-final.pdf). 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Appendix 1 Descriptive statistics Table A1 Financial data by region West Africa Central Africa Eastern and Southern Africa Middle East and North Africa Asia Global Risk location Favourable 5144–14 Standard 13 –55326 Challenging 22 13 27 1 4 67 Quite challenging 2 4 14 2 8 30 Location risk score (mean) 62 73 72 50 79 68 Value for money rating Superior 8331116 Excellent 5692830 Good 7 3 11 3 1 25 Fair 13 413 – 1 31 Poor 9 2 14 6 4 35 Value for money rating No delay 30 16 30 712 95 Short delay (<year) 817–117 Long delay (>year) or abandonment 4 1 13 5 2 25 Environmental and social (E&S) costs Total E&S as % of total project expenditure (mean) 2.9% 2.4% 1.2% 0.7% 2.1% 2.0% Total E&S as % of financial costs of risk (mean) 141% 17% 14% 13% 14% 30% Total E&S costs (US$ ’000, mean) 18,956 6,533 6,194 3,633 6,382 9,947 Total project costs (US$ ’000, mean) 652,139 276,158 508,259 489,169 298,410 497,225 Costs of social risks Baseline (US$ ’000, mean) 38,247 93,818 160,332 164,925 93,622 107,264 Brownfield (US$ ’000, mean) 21,579 46,000 107,420 133,904 34,619 67,383 Greenfield (US$ ’000, mean) 28,110 65,856 124,879 140,001 61,717 81,867 Average social risk (US$ ’000, mean) 13,402 37,890 44,182 27,972 45,454 32,639 Table A2 Financial data by risk location Favourable Standard Challenging Quite challenging Total Region West Africa 513 22 242 Central Africa 1 – 13 418 Eastern and Southern Africa 4 5 27 14 50 Middle East and North Africa 4 5 1 2 12 Asia – 3 4 8 15 Location risk score 25 57 73 85 68 Value for money rating Superior 1 3 7 5 16 Excellent – 5 18 730 Good 2 3 16 425 Fair 3 7 12 931 Poor 8 8 14 535 Value for money rating No delay 513 56 21 95 Short delay (<year) 3 6 5 3 17 Long delay (>year) or abandonment 6 7 6 6 25 E&S costs Total E&S as % of total project expenditure (mean) 1.3 0.2 7.1 2.8 2.0 Total E&S as % of financial costs of risk (mean) 40 5 53 17 30 Total E&S costs ($ ’000, mean) 4,537 2,944 16,139 4,713 9,947 Total project costs ($ ’000, mean) 349,621 1,653,646 226,402 168,714 497,225 Costs of social risks Baseline ($ ’000, mean) 110,212 254,891 73,643 53,029 107,26 4 Brownfield ($ ’000, mean) 99,239 191,889 35,225 16,433 67,383 Greenfield ($ ’000, mean) 98,752 207,032 51,361 33,638 81,867 Average social risk ($ ’000, mean) 11,217 55,431 30,350 27,993 32,639 Table A3 Basic characteristics of survey respondents Type of company* No. Sector No. Producer 47 Agriculture 45 Processor 19 Forestry 7 Financial investor 13 Consumer goods 7 Trader 9Energy 4 Retailer 4Infrastructure 2 Other 7Other 20 Processes implemented* Experienced dispute Community meetings 34 Yes 21 Training and operationl monitoring 31 No 25 Social impact assessment/monitoring 29 Don’t know/skip question 39 Dispute/grievance resolution mechanisms established 27 Stakeholder mapping 28 Other 14 *Multiple responses allowed Table A4 Effectiveness and cost effectiveness of risk mitigation measures Effectiveness of procedures Very effective Somewhat effective No effect/ difficult to tell Detrimental effect N/A Community meetings 513 22 242 Training and operationl monitoring 1 – 13 418 Social impact assessment/monitoring 4 5 27 14 50 Dispute/grievance resolution mechanisms established 451212 Stakeholder mapping –34815 Other 25 57 73 85 68 Cost effectiveness of procedures Wasted investment Not the best use of money No effect difficult to tell Good investment Excellent value for money Community meetings 137516 Training and operationl monitoring – 5 18 730 Social impact assessment/monitoring 2 3 16 425 Dispute/grievance resolution mechanisms established 3 7 12 931 Stakeholder mapping 8 8 14 535 Other Appendix 2 Business perceptions survey The costs and benefits of social license Background Local support for a project or investment can be vital. Just as businesses need to get and maintain legal license to operate, so they also need to earn and maintain “social license to operate” or local approval. This can be challenging in emerging markets where it is hard to identify and communicate with legitimate stakeholders and where property rights are unclear. In the shadow of the COVID-19 pandemic, for example, businesses may find that their social license is put to the test as they struggle to provide the support that local people need or expect. Loss of social license – meaning local opposition to a project – can lead to significant disruptions and large financial losses. Our previous research has demonstrated this and quantified its impact to help businesses make better decisions. Anecdotal evidence suggests that there is a strong business case for investments in services and procedures that earn social license. Examples include establishing dispute resolution mechanisms, implementing participatory monitoring processes and facilitating regular meetings with the community. What we want to know, and where we need your help, is how much these services and procedures cost and how effective they are. It should take you no more than 5 minutes to complete this survey. Most of the questions are optional and any data you provide will be held in the strictest confidence. With companies’ consent, we will publicise positive case studies of local engagement processes/procedures, underlining the way in which they have contributed to responsible investment practice and the delivery of public goods. Thank you in advance for your help, we really do appreciate it. If you have any questions or concerns, please don’t hesitate to contact us. Best wishes, Joseph Feyertag (j.feyer[email protected].uk) & Ben Bowie ([email protected]) Section A: Project information Some background information on your activities and their location(s) that will help us ensure that we can distinguish between different geographies or sectors. 1. What is the name of your company/organization? OPTIONAL - If you prefer not to provide this information, please skip this question. 2. Which sector best describes your company/organization’s activities? You can select more than one choice. * • Producer • Trader • Processor • Retailer • Investor • Other - Write In 3. Which area(s) does your company/organization operate in? You can select more than one choice. • Agriculture • Mining • Energy • Infrastructure • Forestry • Consumer goods • Real estate • Other - Write In Section B: Experience of dispute or local social unrest This section is optional and covers any previous experience of tension or disputes with local people within or around project locations. Any information provided will be held in the strictest confidence. 4. Have you experienced a dispute with local people in connection to your investment(s)? (optional) • Yes • No • Skip 5. Did this dispute affect the financial performance of the investment(s)? • Yes • No • Hard to say Section C: Procedures for building local relationships These questions capture the processes and procedures that you have in place to communitcate with and engage local people, as well as your reasons for using them. In general, we want to identify the most efficient interventions to improve and protect local relationships. 6. Have you implemented any of the following procedures to support social license? • Stakeholder mapping Research to understand who has a legitimate interest in the land and/or resources that your operation is accessing or having an impact on. • Community meetings Establishing a dialogue with local people and other stakeholders, often via meetings, to understand how they feel about your operations and what they expect from it. These community engagements will also allow key information to be collected through a participatory monitoring process that can help determine baselines and continuous assessment. • Social impact assessment/monitoring A process, often required by national investment approval procedures, to understand what positive and negative effects your operations might have on social wellbeing and social conditions e.g. impact on traditional livelihoods, impact on local wages or impact on access to food, water and energy. It will often come with a monitoring and management plan. • Training and operational monitoring Improving the ability of your staff to develop a good relationship with local people via processes like workshops and meetings. This could include agronomic training provided for smallholder suppliers or participatory monitoring that assists your organization to collect information (e.g. on health and safety or on water quality) with the help of local people. • Establishing dispute/grievance resolution mechanisms Establishing a clear, consistent and transparent process, generally involving a third party, that exists to identify possible dispute and find mutually satisfactory solutions to them. Naturally this includes negotiating with the various stakeholders to agree on expectations and outcomes. • Other 7. Would you be interested in publicity in relation to these procedures (anonymised if preferred)? • Yes • No • Skip 8. In your view, please rate which processes you think are successful in terms of ensuring trust and building relationships with local people and communities. Very effective Somewhat effective No effect/ difficult to tell Detrimental effect N/A Stakeholder mapping Organising community meetings Implementing social impact assessment/ monitoring Running training and operational monitoring Establishing dispute/ grievance resolution mechanisms Other