{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DIME","affiliation":"World Bank - Development Impact Department ","role":"Verification and preparation of metadata"}],"version":"1","prod_date":"2024-06-05"},"project_desc":{"authoring_entity":[{"name":"Unnada Chewpreecha","affiliation":"World Bank","email":"uchewpreecha@worldbank.org"},{"name":"Francis Dennig","affiliation":"United Nations Development Programme","email":"francis.dennig@undp.org"},{"name":"Ib Hansen","email":"ibhansen.iv@gmail.com"}],"output":[{"type":"Working paper","title":"FTT-FLEX: Flexible Technology Diffusion Analysis Tool for Data Poor Countries","description":"Policy Research Working Paper (PRWP) 10767","uri":" https:\/\/documents.worldbank.org\/curated\/en\/099735005082423970\/IDU117d8923a1226614d42196d115fb48f7c219b","doi":"https:\/\/doi.org\/10.1596\/1813-9450-10767"}],"software":[{"name":"EViews","version":"13 Enterprise Edition"}],"scripts":[{"file_name":"RR_GNB_2024_129-v02","zip_package":"RR_GNB_2024_129-v02.zip","title":"Reproducibility package (partial data and partial code) for FTT-FLEX: Flexible Technology Diffusion Analysis Tool for Data Poor Countries","dependencies":"No dependencies were used in this reproducibility package.","instructions":"See README in reproducibility package.","notes":"Computational reproducibility verified by Development Impact (DIME) Analytics team, World Bank."}],"title_statement":{"idno":"RR_GNB_2024_129","title":"Reproducibility package for FTT-FLEX: Flexible Technology Diffusion Analysis Tool for Data Poor Countries"},"production_date":"2024-05","abstract":"To achieve substantial emission reductions, widespread low-carbon technology adoption is vital. The process by which new technologies are developed and adopted and how their costs evolve is critical to understanding decarbonization. Modelling of this process requires a tool that realistically describes several phenomena related to technology adoption in different sectors, including technology diffusion, investment decisions, evolution of technology costs, and technology lock-in, among others.\nThis paper introduces FTT-FLEX, a simplification of the Future Technology Transformation (FTT) model (Mercure, 2012).  FTT-FLEX is suitable for application as a single-country standalone tool or in connection with a macro-economic model. FTT-FLEX captures the core country-level of features of FTT (knowledge spillovers as the driver of technology cost and inertia in the adoption of new technologies) as they pertain to an individual country and greatly reduces the data required as compared with the global FTT model. As presented, FTT-FLEX is a natural complement to country specific macroeconomic models that analyze the decarbonization of key emitting sectors in small developing countries. The utility of FTT-FLEX is demonstrated by a decarbonization analysis for the power-sector of Guinea-Bissau.","geographic_units":[{"name":"Guinea-Bissau","code":"GNB"}],"keywords":[{"name":"technology diffusion model"},{"name":"low carbon policies"},{"name":"macroeconomic model"}],"topics":[{"vocabulary":"Journal of Economic Literature (JEL)","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","id":"O33","parent_id":"O3","name":"Technological Change: Choices and Consequences \u2022 Diffusion Processes"},{"vocabulary":"Journal of Economic Literature (JEL)","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","id":"O38","parent_id":"O3","name":"Open Innovation"},{"vocabulary":"Journal of Economic Literature (JEL)","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","id":"E17","parent_id":"E1","name":"Forecasting and Simulation: Models and Applications"},{"vocabulary":"Journal of Economic Literature (JEL)","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","id":"Q55","parent_id":"Q5","name":"Technological Innovation"},{"vocabulary":"Journal of Economic Literature (JEL)","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","id":"Q42","name":"Alternative Energy Sources","parent_id":"Q4"},{"vocabulary":"Journal of Economic Literature (JEL)","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","id":"Q43","parent_id":"Q4","name":"Energy and the Macroeconomy"},{"vocabulary":"Journal of Economic Literature (JEL)","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","id":"Q48","parent_id":"Q4","name":"Energy - Government Policy"}],"data_statement":"Two datasets are restricted, two are public but not included in the reproducibility package, and two are public and included in the reproducibility package.","repository_uri":[{"uri":"https:\/\/reproducibility.worldbank.org","name":"Reproducible Research Repository (World Bank)"}],"technology_environment":"Paper exhibits were reproduced in a computer with the following specifications:\n\u2013 OS: Windows 11 Enterprise\n\u2013 Processor: Intel(R) Core(TM) i5-1145G7 CPU @ 2.60GHz\n\u2013 Memory available: 15.7 GB\n\u2013 Software version: EViews 13 Enterprise Edition - May 7 2024 build","technology_requirements":"Runtime: 1 minute","reproduction_instructions":"Users will not be able to reproduce the results of the paper, as access to some input data sources is restricted, and access to the intermediate dataset used to produce the results is also restricted. The included scripts document how outputs were created. The code used to create the intermediate dataset is currently embargoed.","disclaimer":"The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development\/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.","license":[{"name":"Modified BSD3 ","uri":"https:\/\/opensource.org\/license\/bsd-3-clause\/"}],"contacts":[{"name":"Unnada Chewpreecha","affiliation":"World Bank","email":"uchewpreecha@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"datasets":[{"name":"Levelised Cost of Electricity Calculator from the International Energy Agency (IEA)","uri":"https:\/\/www.iea.org\/data-and-statistics\/data-tools\/levelised-cost-of-electricity-calculator","access_type":"Data is public and included in the reproducibility package in tabs with the name \"LCOE [source] - IEA\" of the file \"FTTAssumptions.xlsx\".","note":"Variables: levelized cost of electricity. Variable names in EViews workfile: COST__(technology). Data was accessed in November 2023."},{"name":"Electricity production from Our World in Data","uri":"https:\/\/ourworldindata.org\/electricity-mix","access_type":"Data is public and included in the reproducibility package in the tab \"OWID\" of the file \"FTTAssumptions.xlsx\".","note":"Variables: global baseline cumulative power production by technology. Variable names in EViews workfile: ACCUMULATED_PRODUCTION__(technology). Data was accessed in November 2023."},{"uri":"https:\/\/www.iea.org\/data-and-statistics\/data-product\/world-energy-outlook-2022-extended-dataset","name":"Electricity production and fuel price scenarios from IEA's World Energy Outlook 2022 Extended Dataset","access_type":"Data is restricted. It should be purchased in the data URL.","note":"Variables used: energy production by technology, oil price increases, gas price increases, and coal price increases. Variable names in EViews workfile: ACCUMULATED_PRODUCTION__(technology), OIL_PRICE_STEPS, GAS_PRICE_STEP, COAL_PRICE_STEP.  Data was accessed in November 2023.","license_uri":"https:\/\/www.iea.org\/terms\/terms-of-use-for-non-cc-material"},{"name":"Main FTT-Power Database from Mercure (2012)","access_type":"Data is not publicly available but can be requested to the author of: Mercure, J-F. (2012), \u201cFTT:Power A global model of the power sector with induced technological change and natural resource depletion\u201d, Energy Policy, 48, pp. 799\u2013811 (https:\/\/doi.org\/10.1016\/j.enpol.2012.06.025).","note":"Variables: learning rate by technology, CO2 intensity by power generation technology, and lead and lifetime of power plant by technology. Variable names in EViews workfile: LEARNING__(technology), CO2_COEFF__(technology), LEAD__(technology), and TAU__(technology). Data was accessed in November 2023."},{"name":"Learning rate by technology from IRENA (2023)","uri":"https:\/\/www.irena.org\/Publications\/2023\/Aug\/Renewable-Power-Generation-Costs-in-2022","license":"Users must obtain the data directly from the Data URL provided below for the variables specified in the README.","note":"Variable names in EViews workfile: LEARNING__(technology). Data was manually compiled from the report: IRENA (2023), Renewable power generation costs in 2022, International Renewable Energy Agency, Abu Dhabi. Data was accessed in November 2023."},{"name":"Guinea-Bissau Macroeconomic and Fiscal Model (MFMod) Dataset from the World Bank","note":"Data for Guinea-Bissau was manually compiled from the data URL and complemented by Guinea-Bissau Country Economist\u2019s sources for electricity sector expansion and public investment assumptions. Data was accessed in November 2023. The current data available in the data URL might not match the version of the accessed data.","access_type":"Users must obtain the data directly from the Data URL provided below for the variables specified in the README. Data on electricity sector expansion and public investment assumptions is restricted and must be obtained from the Guinea-Bissau Country Economist.","uri":"https:\/\/www.worldbank.org\/en\/publication\/macro-poverty-outlook\/mpo_ssa"}]},"tags":[{"tag":"DOI"}],"schematype":"script"}