{"query_echo":{"q":"","filters":{"analysis_type":["quantitative evaluation"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'quantitative evaluation' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":3,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=quantitative+evaluation","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":"sei-000916","url":"https://climateinsightsdirectory.org/document/sei-000916","title":"Wind Power Curtailment China","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"research paper","language":"en","date_published":"2022-07-15","source_url":"https://www.sei.org/publications/wind-power-curtailment-china/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The study examines the drivers of wind power curtailment reduction in China using a logarithmic mean Divisia index approach. It identifies national contributors such as local power demand and power structures, while highlighting regional differences: power transmission is critical in northwest China, thermal power dominance hinders reduction in north China, and peak-shaving auxiliary service markets assist in northeast China. The paper argues for market-oriented energy structure reforms to ensure sustainable low-carbon development.","ai_generated":true,"unit":"sei-000916#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"At a national level, the primary factors contributing to the reduction of wind power curtailment are local power demand, power exports, and power structures.","ai_generated":true,"unit":"sei-000916#insight-1","date_modified":"2026-10-23"},{"text":"Wind power curtailment drivers vary significantly by region: northwest China relies on power transmission, north China is hindered by the dominance of thermal power for energy security, and northeast China utilizes a peak-shaving auxiliary service market to increase grid consumption of local wind power.","ai_generated":true,"unit":"sei-000916#insight-2","date_modified":"2026-10-23"},{"text":"Addressing wind power curtailment requires market-oriented energy structure reforms, technical transformations, and policy measures to improve power grid adaptability and support sustainable low-carbon development.","ai_generated":true,"unit":"sei-000916#insight-3","date_modified":"2026-10-23"}],"climate_tags":["energy transition","carbon neutrality"],"geography_discussed":["Northwestern China","North China","Northeast China"],"frame_perspective":[],"analysis_type":["regional analysis","quantitative evaluation"]},{"id":"clipolin-000471","url":"https://climateinsightsdirectory.org/document/clipolin-000471","title":"Apakah kredit mempengaruhi deforestasi? Bukti dari Kebijakan Kredit Pedesaan di Amazon, Brazil","publisher":{"name":"Climate Policy Initiative","organization":"climate-policy-initiative"},"document_type":"executive summary","language":"id","date_published":"2013-01","source_url":"https://www.climatepolicyinitiative.org/wp-content/uploads/2013/01/Does-Credit-Affect-Deforestation-Executive-Summary-Bahasa.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The study finds that Resolution 3.545, which conditioned rural credit on environmental compliance, significantly reduced deforestation in the Brazilian Amazon Biome. By restricting access to subsidized credit, the policy prevented the clearing of over 2,700 km2 of forest between 2009 and 2011, primarily affecting livestock-oriented regions where producers are more credit-constrained.","ai_generated":true,"unit":"clipolin-000471#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Resolution 3.545 led to a significant decrease in rural credit concessions in the Amazon Biome, with an estimated BRL 2.9 billion (USD 1.4 billion) in credit not contracted between 2008 and 2011. The majority of this reduction, approximately BRL 2.6 billion (USD 1.3 billion), was related to livestock contracts.","ai_generated":true,"unit":"clipolin-000471#insight-1","date_modified":"2026-10-23"},{"text":"The reduction in rural credit caused by the resolution prevented the deforestation of more than 2,700 km2 of forest from 2009 to 2011, representing a 15% decrease in deforestation during that period.","ai_generated":true,"unit":"clipolin-000471#insight-2","date_modified":"2026-10-23"},{"text":"The impact of the credit restriction on deforestation was primarily significant in municipalities where livestock farming is the main economic activity, suggesting that livestock producers are more credit-constrained than crop producers.","ai_generated":true,"unit":"clipolin-000471#insight-3","date_modified":"2026-10-23"},{"text":"In municipalities dominated by crop production, the reduction in credit did not lead to a decrease in deforestation, possibly because these producers are less credit-constrained or use credit for production intensification rather than expansion.","ai_generated":true,"unit":"clipolin-000471#insight-4","date_modified":"2026-10-23"},{"text":"The policy had a distributional effect on credit contracts: for livestock, there was a decrease in medium and large contracts and a slight increase in small contracts; for crops, there was a decrease in medium-scale contracts.","ai_generated":true,"unit":"clipolin-000471#insight-5","date_modified":"2026-10-23"},{"text":"Borrowers anticipated the 2008 credit restrictions by seeking loans before the resolution became mandatory, resulting in unusual credit peaks in April and June 2008.","ai_generated":true,"unit":"clipolin-000471#insight-6","date_modified":"2026-10-23"}],"climate_tags":["deforestation","environmental regulation","climate finance"],"geography_discussed":["Legal Amazon"],"frame_perspective":[],"analysis_type":["quantitative evaluation","counterfactual simulation"]},{"id":"clipolin-000472","url":"https://climateinsightsdirectory.org/document/clipolin-000472","title":"Does Credit Affect Deforestation? Evidence from a Rural Credit Policy in the Brazilian Amazon","publisher":{"name":"Climate Policy Initiative","organization":"climate-policy-initiative"},"document_type":"executive summary","language":"en","date_published":"2013-01","source_url":"https://www.climatepolicyinitiative.org/wp-content/uploads/2013/01/Does-Credit-Affect-Deforestation-Executive-Summary-English.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document assesses how Resolution 3,545, which conditioned rural credit on environmental compliance, reduced deforestation in the Brazilian Amazon. It finds that the policy led to a significant reduction in credit, particularly for cattle ranching, which in turn prevented over 2,700 km2 of forest clearing. The study highlights that cattle ranchers are more credit-constrained than crop farmers, suggesting that financial resource availability directly influences deforestation rates in the region.","ai_generated":true,"unit":"clipolin-000472#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"Resolution 3,545 led to a significant reduction in rural credit in the Amazon Biome, with an estimated BRL 2.9 billion (USD 1.4 billion) in credit not contracted between 2008 and 2011. The majority of this reduction, BRL 2.6 billion (USD 1.3 billion), was associated with cattle-specific contracts.","ai_generated":true,"unit":"clipolin-000472#insight-1","date_modified":"2026-10-23"},{"text":"The reduction in rural credit caused by the resolution prevented more than 2,700 km2 of forest area from being cleared between 2009 and 2011, representing a 15% decrease in deforestation for that period.","ai_generated":true,"unit":"clipolin-000472#insight-2","date_modified":"2026-10-23"},{"text":"The impact of the credit restriction on deforestation was primarily significant in municipalities where cattle ranching is the dominant economic activity; in contrast, deforestation in crop-oriented municipalities was not affected by Resolution 3,545.","ai_generated":true,"unit":"clipolin-000472#insight-3","date_modified":"2026-10-23"},{"text":"The policy altered the distribution of credit contracts, reducing the number of medium and large contracts for cattle while slightly increasing small contracts. For crops, there was a decrease in medium contracts with no significant impact on small ones.","ai_generated":true,"unit":"clipolin-000472#insight-4","date_modified":"2026-10-23"},{"text":"The results indicate that cattle ranchers in the Amazon are credit-constrained, meaning their deforestation activities are sensitive to the availability of subsidized credit. Crop farmers appear less dependent on these subsidies or use them to increase productivity rather than expand land use.","ai_generated":true,"unit":"clipolin-000472#insight-5","date_modified":"2026-10-23"},{"text":"The study warns that policies increasing financial resources for farmers, such as payments for environmental services, could potentially lead to higher deforestation rates if they do not account for existing credit constraints and avoid adverse rebound effects.","ai_generated":true,"unit":"clipolin-000472#insight-6","date_modified":"2026-10-23"}],"climate_tags":["deforestation","environmental regulation","climate finance","agricultural productivity"],"geography_discussed":["Legal Amazon","Brazil"],"frame_perspective":[],"analysis_type":["quantitative evaluation","counterfactual simulation"]}]}