{"query_echo":{"q":"","filters":{"analysis_type":["indicator analysis"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'indicator analysis' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":7,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=indicator+analysis","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"clipolin-000002","url":"https://climateinsightsdirectory.org/document/clipolin-000002","title":"Tracking the Quality of Climate Finance: From Theory to Practice","publisher":{"name":"Climate Policy Initiative","organization":"climate-policy-initiative"},"document_type":"research paper","language":"en","date_published":"2025-11-21","source_url":"https://www.climatepolicyinitiative.org/publication/tracking-the-quality-of-climate-finance-from-theory-to-practice/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"This research paper by the Climate Policy Initiative (CPI) proposes a quantitative approach to tracking the quality of public climate finance. It builds upon a three-level conceptual framework—project, market, and system levels—to identify practical indicators that can reduce subjectivity in quality judgments and improve coordination among public finance providers.","ai_generated":true,"unit":"clipolin-000002#summary","date_modified":"2026-08-17"},"key_insights":[{"text":"While methodologies for tracking the quantity of climate finance are well-established, common approaches for assessing and tracking the quality of public climate finance are still in their early stages.","ai_generated":true,"unit":"clipolin-000002#insight-1","date_modified":"2026-08-17"},{"text":"The lack of harmonized quality assessment and comparison capabilities hinders the coordination between actors and the strategic allocation of limited public climate finance based on evidence from previous interventions.","ai_generated":true,"unit":"clipolin-000002#insight-2","date_modified":"2026-08-17"},{"text":"CPI utilizes a three-level conceptual framework—project, market, and system levels—to track how finance drives sustained transformational change toward equitable, climate-resilient, and low-emission economies, rather than just supporting isolated projects.","ai_generated":true,"unit":"clipolin-000002#insight-3","date_modified":"2026-08-17"},{"text":"The paper aims to establish a quantitative basis for quality assessment by distilling practical indicators from existing monitoring approaches used by public climate finance institutions to reduce subjectivity and allow for aggregation across different institutions.","ai_generated":true,"unit":"clipolin-000002#insight-4","date_modified":"2026-08-17"}],"climate_tags":["climate finance","public finance","monitoring and evaluation","energy transition"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["framework development","indicator analysis"]},{"id":"clipolin-001315","url":"https://climateinsightsdirectory.org/document/clipolin-001315","title":"Tracking the Quality of Climate Finance","publisher":{"name":"Climate Policy Initiative","organization":"climate-policy-initiative"},"document_type":"report","language":"en","date_published":"2025-11","source_url":"https://www.climatepolicyinitiative.org/wp-content/uploads/2025/11/Tracking-the-Quality-of-Climate-Finance.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report argues that while tracking the quantity of climate finance is established, tracking its quality remains nascent. It proposes a three-level conceptual framework—project, market, and system—to move beyond one-off project outputs toward sustained transformational change. At the project level, it emphasizes core indicators like tCO2e for mitigation and beneficiaries reached for adaptation. At the market level, it focuses on creation, scalability, and inclusiveness, highlighting private finance catalyzation and job creation. At the system level, it identifies three catalytic pathways (singular, centralized, and decentralized) to track structural shifts in paradigms, policies, and institutional arrangements. The report concludes by identifying nine key indicators as a starting point for a common reporting approach across public climate finance actors.","ai_generated":true,"unit":"clipolin-001315#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The core indicator for tracking mitigation results is the quantity of greenhouse gas emissions reduced or avoided, measured in metric tonnes of carbon dioxide equivalent (tCO2e).","ai_generated":true,"unit":"clipolin-001315#insight-1","date_modified":"2026-10-23"},{"text":"For adaptation finance, the most common core output indicator is the number of beneficiaries reached, while a more robust but complex outcome variant is the number of beneficiaries made more resilient to climate hazards.","ai_generated":true,"unit":"clipolin-001315#insight-2","date_modified":"2026-10-23"},{"text":"Project-level quality can be evaluated through co-benefits using a two-tier SDG approach: Level 1 involves keyword-based SDG tagging, and Level 2 requires evidence-based verification and quantification of actual contributions to SDG targets.","ai_generated":true,"unit":"clipolin-001315#insight-3","date_modified":"2026-10-23"},{"text":"Key indicators for tracking market-level quality include the volume of private finance catalyzed and the number of jobs directly supported.","ai_generated":true,"unit":"clipolin-001315#insight-4","date_modified":"2026-10-23"},{"text":"System-level change is tracked through three catalytic pathways: Pathway 1 (singular catalytic impact via individual interventions), Pathway 2 (centralized catalytic impact via coordinated portfolios), and Pathway 3 (decentralized catalytic impact via independent, aligned interventions).","ai_generated":true,"unit":"clipolin-001315#insight-5","date_modified":"2026-10-23"},{"text":"The report identifies nine priority indicators for a common approach to assessing climate finance quality: emissions mitigated, beneficiaries reached, SDGs targeted, co-financing secured, technical assistance provided, private finance catalyzed, jobs supported, project-level theories of change, and the percentage of a portfolio contributing to system-level change.","ai_generated":true,"unit":"clipolin-001315#insight-6","date_modified":"2026-10-23"},{"text":"Quantitative indicators must be supplemented with qualitative evidence to capture the 'how' and 'why' behind observed changes and to inform future project design.","ai_generated":true,"unit":"clipolin-001315#insight-7","date_modified":"2026-10-23"}],"climate_tags":["climate finance","climate change mitigation","climate change adaptation","greenhouse gas emissions","Sustainable Development Goals","renewable energy","climate resilience"],"geography_discussed":["Kenya","South Africa","Tajikistan","Maldives","Rwanda","Sri Lanka","Morocco"],"frame_perspective":[],"analysis_type":["framework development","indicator analysis","policy recommendation"]},{"id":"fordecl-000064","url":"https://climateinsightsdirectory.org/document/fordecl-000064","title":"Goal 6 Assessment Technical Annex to the Five-Year Assessment Report","publisher":{"name":"Forest Declaration Assessment","organization":"forest-declaration-assessment"},"document_type":"report","language":"en","date_published":"2019-09","source_url":"https://forestdeclaration.org/wp-content/uploads/2021/08/2019NYDFGoal6.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The report concludes that Goal 6 has been achieved through the adoption of the SDGs in 2015. However, it highlights a critical gap in the measurement of SDG 15.2, noting that indicators track net rather than gross deforestation, which obscures the loss of natural forests. Additionally, it finds that targets for forest restoration, afforestation, and reforestation lack quantifiable metrics.","ai_generated":true,"unit":"fordecl-000064#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Goal 6 is considered achieved because the United Nations member states adopted the Sustainable Development Goals (SDGs) in September 2015, incorporating forest-related targets.","ai_generated":true,"unit":"fordecl-000064#insight-1","date_modified":"2026-10-23"},{"text":"While SDG 15.2 aims to halt deforestation by 2020, the actual indicators used to measure progress track net forest loss instead of gross forest loss, which weakens the target by failing to show the extent of natural forest deforestation.","ai_generated":true,"unit":"fordecl-000064#insight-2","date_modified":"2026-10-23"},{"text":"The components of SDG 15.2 related to forest restoration, reforestation, and afforestation are not quantifiable, as proposals for such targets were removed from the final SDGs and no specific measurement indicators exist for them.","ai_generated":true,"unit":"fordecl-000064#insight-3","date_modified":"2026-10-23"},{"text":"Analysis from the 2018 High-level Political Forum on Sustainable Development indicates that SDG 15 indicators lack measures for the quality of management, specifically omitting forest intactness and the effectiveness of protected area management.","ai_generated":true,"unit":"fordecl-000064#insight-4","date_modified":"2026-10-23"},{"text":"Data from the OECD's SDG Financing Lab shows that SDG 15 is among the least-funded goals, receiving only 3.5 percent of donor finance for SDGs.","ai_generated":true,"unit":"fordecl-000064#insight-5","date_modified":"2026-10-23"}],"climate_tags":["forest conservation","forest restoration","deforestation","afforestation","reforestation","Sustainable Development Goals","climate finance","biodiversity"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["policy assessment","indicator analysis"]},{"id":"geconco-000111","url":"https://climateinsightsdirectory.org/document/geconco-000111","title":"The Green Economy Barometer 2018 Mongolia","publisher":{"name":"Green Economy Coalition","organization":"green-economy-coalition"},"document_type":"report","language":"en","date_published":"2018-05","source_url":"https://www.greeneconomycoalition.org/assets/reports/Barometers-2018/Mongolia-GE-Barometer-2018-Final-WEB.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The 2018 Green Economy Barometer for Mongolia highlights a significant gap between the country's legislative commitments and actual implementation. While the government has adopted the National Green Development Policy and Sustainable Development Vision 2030, Mongolia ranked 79th out of 80 countries in the 2016 Global Green Economy Index. The report argues that investing 4% of GDP into green development could reduce poverty to 10% and cut greenhouse gas emissions by 17% by 2030. Current challenges include severe air pollution in Ulaanbaatar, land degradation affecting 77.8% of land, and a precarious economic dependence on volatile mineral exports.","ai_generated":true,"unit":"geconco-000111#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Investing 4% of GDP in green development is projected to result in a 5.23% increase in employment by 2030, a reduction of the poverty rate to 10% (from 21.6% in 2014), and a 17% reduction in greenhouse gas emissions per unit of GDP.","ai_generated":true,"unit":"geconco-000111#insight-1","date_modified":"2026-10-23"},{"text":"Mongolia's performance in the 2016 Global Green Economy Index was very low, ranking 79th out of 80 countries, indicating a disconnect between official government narratives and tangible implementation.","ai_generated":true,"unit":"geconco-000111#insight-2","date_modified":"2026-10-23"},{"text":"Ulaanbaatar faces severe air pollution, with PM 2.5 levels averaging 75, which is substantially higher than WHO standards; this is largely driven by the burning of coal and waste in ger districts due to a lack of central heating and infrastructure.","ai_generated":true,"unit":"geconco-000111#insight-3","date_modified":"2026-10-23"},{"text":"Environmental degradation is widespread, with a desertification atlas from the Ministry of Environment and Green Development showing that 77.8% of land has been affected by desertification to some degree.","ai_generated":true,"unit":"geconco-000111#insight-4","date_modified":"2026-10-23"},{"text":"The Mongolian financial sector shows limited support for the green transition, though some progress exists, such as the Green Climate Fund transferring USD 20 million to XacBank for low-carbon SME initiatives and the establishment of the Mongolian Green Climate Fund.","ai_generated":true,"unit":"geconco-000111#insight-5","date_modified":"2026-10-23"},{"text":"As of the second quarter of 2016, there were 112,300 green jobs in Mongolia, representing 9.9% of all jobs, with the highest concentration in education (30.3%) and manufacturing (15.9%).","ai_generated":true,"unit":"geconco-000111#insight-6","date_modified":"2026-10-23"},{"text":"Mongolia's progress toward the UN Sustainable Development Goals is close to the East and South Asian regional average, but 8 of the 17 goals are classified as 'red' priorities, specifically SDGs 2 (zero hunger), 7 (affordable and clean energy), and 9 (industry, innovation and infrastructure).","ai_generated":true,"unit":"geconco-000111#insight-7","date_modified":"2026-10-23"}],"climate_tags":["green economy","climate finance","green job","air pollution","desertification","water scarcity","renewable energy","Sustainable Development Goals","greenhouse gas emissions","economic diversity","land degradation"],"geography_discussed":["Ulaanbaatar","Orkhon Province","Gobi Desert"],"frame_perspective":[],"analysis_type":["economic modelling","policy assessment","indicator analysis"]},{"id":"iisd-001942","url":"https://climateinsightsdirectory.org/document/iisd-001942","title":"Can We Measure Resilience?","publisher":{"name":"International Institute for Sustainable Development","organization":"international-institute-for-sustainable-development"},"document_type":"briefing","language":"en","date_published":"2017","source_url":"https://www.iisd.org/system/files/publications/reducing-agriculture-vulnerability-climate-change.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document proposes a framework for measuring agricultural resilience in eastern Ontario, Canada, moving beyond traditional risk-reduction to a holistic, system-based approach. It identifies 36 indicators across six themes—climate change, population, farmland production, market and economy, rural infrastructure, and natural environment—to track the capacity of rural systems to absorb shocks and adapt. The authors emphasize that while some data is readily available, significant gaps exist in detailed farm economic data. The briefing argues for cross-sectoral collaboration to break down government 'silos' and suggests that these indicators are transferable to other agricultural regions across Canada.","ai_generated":true,"unit":"iisd-001942#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Resilience is defined as the capacity of a system to absorb shocks and the ability to prepare for, cope with, adapt to, and potentially transform in response to stresses.","ai_generated":true,"unit":"iisd-001942#insight-1","date_modified":"2026-10-23"},{"text":"The study developed a suite of 36 resilience indicators categorized into six themes: climate change, population, farmland production activities, market and economy, rural infrastructure, and natural environment.","ai_generated":true,"unit":"iisd-001942#insight-2","date_modified":"2026-10-23"},{"text":"The indicators shift from traditional static measures, such as average rainfall, to those that capture regionally meaningful changes in the timing and features of impacts, such as the proportion of barns with air-conditioning to reflect heat coping capacity.","ai_generated":true,"unit":"iisd-001942#insight-3","date_modified":"2026-10-23"},{"text":"Data availability for the 36 indicators varies: approximately 50% are readily available, while others are missing, inaccessible, or require significant processing. A specific gap was noted in accessing detailed farm production and economic data.","ai_generated":true,"unit":"iisd-001942#insight-4","date_modified":"2026-10-23"},{"text":"The research indicates that resilience indicators for agriculture often overlap with other rural sectors, suggesting that a cross-sectoral approach is necessary to overcome traditional government 'silos' and optimize planning.","ai_generated":true,"unit":"iisd-001942#insight-5","date_modified":"2026-10-23"},{"text":"While developed for eastern Ontario, the indicators are considered highly relevant for other Canadian agricultural regions because they focus on broad natural and socioeconomic changes rather than highly specific regional indicators.","ai_generated":true,"unit":"iisd-001942#insight-6","date_modified":"2026-10-23"}],"climate_tags":["climate resilience","land-use change","biodiversity","water quality"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["framework development","indicator analysis","policy briefing"]},{"id":"fordecl-000028","url":"https://climateinsightsdirectory.org/document/fordecl-000028","title":"Progress on the New York Declaration on Forests","publisher":{"name":"Forest Declaration Assessment","organization":"forest-declaration-assessment"},"document_type":"report","language":"en","date_published":"2015-11","source_url":"https://forestdeclaration.org/wp-content/uploads/2020/11/2015Goal5.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document evaluates global forest restoration progress using two indicators: Bonn Challenge pledges and UNFCCC Intended Nationally Determined Contributions (INDCs). As of November 2015, Bonn Challenge commitments reached 62.6 million hectares (41.7% of the 2020 target), while UNFCCC INDCs included pledges for approximately 121.7 million hectares (35% of the 2030 target). The report notes that while commitments have increased, they are often clustered around major agreements and require a faster rate of pledging to meet targets. It also highlights significant data gaps in standardized global aggregates and the limitations of satellite imagery in detecting small-scale forest growth.","ai_generated":true,"unit":"fordecl-000028#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"As of the reporting period, 14 countries, three subnational regions, and two organizations have pledged to restore 62.6 million hectares of forest landscapes under the Bonn Challenge, representing 41.7% of the 150-million-hectare target for 2020.","ai_generated":true,"unit":"fordecl-000028#insight-1","date_modified":"2026-10-23"},{"text":"Projections for the COP-21 conference in Paris suggest that total Bonn Challenge commitments would increase to 83.8 million hectares, or 55.8% of the 2020 target.","ai_generated":true,"unit":"fordecl-000028#insight-2","date_modified":"2026-10-23"},{"text":"Analysis of 68 parties to the UNFCCC that submitted land-sector targets in their Intended Nationally Determined Contributions (INDCs) shows estimated pledges of 121.7 million hectares for restoration, reforestation, and afforestation, which is 35% of the 350-million-hectare target for 2030.","ai_generated":true,"unit":"fordecl-000028#insight-3","date_modified":"2026-10-23"},{"text":"The report identifies a lack of up-to-date standardized global aggregates for restoration activities, noting that current databases provide case studies but lack universal measurement indicators.","ai_generated":true,"unit":"fordecl-000028#insight-4","date_modified":"2026-10-23"},{"text":"Satellite imagery, specifically the Hansen/GFW dataset, is limited in its ability to monitor restoration because it cannot confirm activities directly and likely underestimates tree cover gain for trees under 5 meters high or those sparsely distributed.","ai_generated":true,"unit":"fordecl-000028#insight-5","date_modified":"2026-10-23"},{"text":"To facilitate the identification of feasible restoration areas at a fine scale, the IUCN and World Resources Institute (WRI) are implementing the Restoration Opportunities Assessment Methodology (ROAM).","ai_generated":true,"unit":"fordecl-000028#insight-6","date_modified":"2026-10-23"}],"climate_tags":["afforestation","reforestation","climate change mitigation","carbon capture and storage"],"geography_discussed":["Paris"],"frame_perspective":[],"analysis_type":["progress assessment","indicator analysis"]},{"id":"fordecl-000033","url":"https://climateinsightsdirectory.org/document/fordecl-000033","title":"Progress on the New York Declaration on Forests","publisher":{"name":"Forest Declaration Assessment","organization":"forest-declaration-assessment"},"document_type":"report","language":"en","date_published":"2015-11","source_url":"https://forestdeclaration.org/wp-content/uploads/2021/10/2015NYDFReport.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The report establishes a monitoring framework for the New York Declaration on Forests (NYDF), assessing ten goals related to halting deforestation, restoring landscapes, and improving governance. While it notes that 'overall progress remains slow', it identifies positive trends such as the inclusion of a deforestation target in the Sustainable Development Goals and an increase in clean cookstove distribution. The document highlights significant data gaps, particularly regarding non-agricultural drivers of deforestation and domestic public spending on forests, while noting that 'data are mostly trending in the right direction'.","ai_generated":true,"unit":"fordecl-000033#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Global natural forest loss shows diverging trends: while the annual net loss of natural forest area appears to be declining, there is no evidence that the annual rate of gross clearing or harvesting is slowing.","ai_generated":true,"unit":"fordecl-000033#insight-1","date_modified":"2026-10-23"},{"text":"Progress in eliminating deforestation from agricultural commodities varies by sector: certified sustainable palm oil reached 18% of the global market by 2013, and half of forests providing wood fiber for paper are certified, but certified sustainable soy represents only 2% of the global market.","ai_generated":true,"unit":"fordecl-000033#insight-2","date_modified":"2026-10-23"},{"text":"Non-agricultural drivers of tropical deforestation between 2000 and 2010 included infrastructure and human settlements (each responsible for 10%) and mining (7%), while timber extraction and logging caused approximately 52% of total forest degradation.","ai_generated":true,"unit":"fordecl-000033#insight-3","date_modified":"2026-10-23"},{"text":"Efforts to reduce deforestation driven by basic needs have seen rapid growth in clean cookstove distribution, with global investments peaking at US$260 million in 2014.","ai_generated":true,"unit":"fordecl-000033#insight-4","date_modified":"2026-10-23"},{"text":"Forest restoration pledges are currently below the 2020 and 2030 targets: the Bonn Challenge has commitments for 62.6 million hectares (about 42% of the 2020 target), and UNFCCC INDCs include about 122 million hectares (about 35% of the 2030 target).","ai_generated":true,"unit":"fordecl-000033#insight-5","date_modified":"2026-10-23"},{"text":"The Sustainable Development Goals (SDGs) adopted in September 2015 include a quantitative target to halt deforestation by 2020, but they lack a quantitative target for forest restoration.","ai_generated":true,"unit":"fordecl-000033#insight-6","date_modified":"2026-10-23"},{"text":"International financial support for reducing forest emissions has increased, with bilateral ODA for developing countries rising from an annual average of US$365 million (2002-07) to US$744 million (2008-13), with 2014 commitments potentially exceeding US$1 billion.","ai_generated":true,"unit":"fordecl-000033#insight-7","date_modified":"2026-10-23"},{"text":"Performance-based REDD+ payments saw over US$3 billion committed between 2008 and 2014, though actual disbursements lagged at just over US$1 billion.","ai_generated":true,"unit":"fordecl-000033#insight-8","date_modified":"2026-10-23"},{"text":"The forest carbon market peaked at US$237 million in 2011 before declining to approximately US$150 million in 2013.","ai_generated":true,"unit":"fordecl-000033#insight-9","date_modified":"2026-10-23"},{"text":"Recognized rights for indigenous peoples and local communities over forests increased by over one-third between 2002 and 2013, although the rate of legal recognition has slowed since 2008.","ai_generated":true,"unit":"fordecl-000033#insight-10","date_modified":"2026-10-23"}],"climate_tags":["deforestation","forest restoration","greenhouse gas emissions","Reducing emissions from deforestation and forest degradation","climate finance","Sustainable Development Goals","indigenous rights","land tenure","carbon emission trading"],"geography_discussed":["Brazil","Indonesia","Guyana","Norway","Germany"],"frame_perspective":[],"analysis_type":["progress assessment","framework development","indicator analysis"]}]}