{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DIME","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2024-10-22","version":"1"},"project_desc":{"title_statement":{"idno":"RR_WLD_2024_184","title":"Reproducibility package for Development acupuncture: The network structure of multidimensional poverty and its implications"},"authoring_entity":[{"name":"Viktor Stojkoski","affiliation":"University Ss. Cyril and Methodius in Skopje, North Macedonia, and Center for Collective Learning, ANITI, IRIT, Universit\u00e9 de Toulouse & CIAS Corvinus University of Budapest","email":"viksabot@gmail.com"},{"name":"Luis F. Lopez-Calva","affiliation":"World Bank","email":"lflopezcalva@worldbank.org"},{"name":"Kimberly Bolch","affiliation":"World Bank","email":"kbolch@worldbank.org"},{"name":"Almudena Fernandez","affiliation":"United Nations Development Programme","email":"almudena.fernandez@undp.org"}],"output":[{"type":"Working Paper","description":"Policy Research Working Paper (PRWP) 10882","authors":"Viktor Stojkoski, Luis F. Lopez-Calva, Kimberly Bolch, and Almudena Fernandez","title":"Development acupuncture: The network structure of multidimensional poverty and its implications","uri":"http:\/\/documents.worldbank.org\/curated\/en\/099820408262426664\/IDU1e95eca6b13b7614632195121cca0629d0129","doi":"https:\/\/doi.org\/10.1596\/1813-9450-10882"}],"production_date":"2024-08","abstract":"While development literature has come a long way in conceptualizing and measuring poverty multidimensionally, policy interventions to address it remain trapped in fragmented sector-specific approaches. One of the main challenges in implementing integrated policy responses to multidimensional poverty reduction is understanding how the different dimensions are interlinked and how they jointly evolve over time. For example, disentangling how a person\u2019s health, education, and standards of living all interact in a dynamic sense. Motivated by economic complexity methods and applications, we use network science to propose two new measures to understand the interconnected structure of multidimensional poverty: the Poverty Space (a network that visualizes the interactions among different indicators of poverty) and Poverty Centrality (a measure of the relative importance of each indicator within this network). Applying these measures to 67 developing countries using data from the OPHI\/UNDP Global Multidimensional Poverty Index, we find that the structure of multidimensional poverty networks is similar across countries and stable over time. We also find that indicators that are more central in the Poverty Space witness a more significant reduction in the censored headcount ratio over time, compared to peripheral indicators. We then use these results to demonstrate how the Poverty Space can be applied in policy: using the forward-looking Policy Priority Inference framework to help guide policy choices. Overall, our research points to the relevance of using network science methods to help identify key \u201cnodes\u201d in the structure of multidimensional poverty where applied pressure (targeted interventions) could lead to a greater effect on the system as a whole.","keywords":[{"name":"Multidimensional poverty"},{"name":"network science"},{"name":"economic complexity"},{"name":"proximity metrics"},{"name":"dimensionality reduction"}],"topics":[{"id":"I31","vocabulary":"Journal of Economic Literature (JEL)","uri":" https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","parent_id":"I3","name":"General Welfare, Well-Being"},{"id":"I32","vocabulary":"Journal of Economic Literature (JEL)","uri":" https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","parent_id":"I3","name":"Measurement and Analysis of Poverty"},{"id":"C63","vocabulary":"Journal of Economic Literature (JEL)","uri":" https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","parent_id":"C6","name":"\tComputational Techniques \u2022 Simulation Modeling"}],"language":[{"name":"English","code":"EN"}],"data_statement":"All data sources are publicly available but not all are included in the reproducibility package. ","datasets":[{"name":"Demographic and Health Surveys (DHS)","uri":"https:\/\/dhsprogram.com\/data\/available-datasets.cfm","note":"Source: The Demographic and Health Surveys (DHS) Program.\nThe original data was downloaded from the official DHS website. However, due to DHS license terms, republication of the data is not permitted. The surveys were processed using the licensed do-files from the Global Multidimensional Poverty 2023 project by the Oxford Poverty & Human Development Initiative, available for download here: (https:\/\/ophi.org.uk\/global-mpi\/2023). The resulting data, generated by running these do-files, the global MPI indicators, serves as the starting point for this reproducibility package.\nThe data is organized in the data\/ folder using the format iso_dhs_year, where:\n- iso refers to the ISO3 country code.\n- year refers to the last two digits of the year (e.g., 19 for 2019).\nDetailed instructions on the datasets, including their full sources, names, download process, and data preparation steps, are provided in the accompanying README file.","access_type":"The data is publicly available but not included in this package. It can be downloaded from the provided data URL. ","license_uri":"https:\/\/dhsprogram.com\/data\/Terms-of-Use.cfm"},{"name":"Multiple Indicator Cluster Surveys (MICS)","uri":"https:\/\/mics.unicef.org\/surveys","note":"Source: UNICEF.\nThe original data was downloaded from the official MICS website. However, due to MICS license terms, republication of the data is not permitted. The surveys were processed using the licensed do-files from the Global Multidimensional Poverty 2023 project by the Oxford Poverty & Human Development Initiative, available for download here: (https:\/\/ophi.org.uk\/global-mpi\/2023). The resulting data, generated by running these do-files, serves as the starting point for this reproducibility package.\nThe data is organized in the data\/ folder using the format iso_mics_year, where:\n- iso refers to the ISO3 country code.\n- year refers to the last two digits of the year (e.g., 19 for 2019).\nDetailed instructions on the datasets, including their full sources, names, download process, and data preparation steps, are provided in the accompanying README file.","access_type":"The data is publicly available but not included in this package. It can be downloaded from the provided data URL. ","license_uri":"https:\/\/www.unicef.org\/legal#copyright"},{"name":"World Bank Country and Lending Groups","note":"Source: Author's calculation with information from the World Bank, available to download at the following link. \nLocated at: data\/OGHIST.xlsx. \n","access_type":"Published with the package","uri":"https:\/\/datahelpdesk.worldbank.org\/knowledgebase\/articles\/906519-world-bank-country-and-lending-groups"},{"name":"World Development Indicators","note":"Source: World Bank. Indicator used: General government final consumption expenditure (% of GDP), available to download at the following link. \nLocated at: data\/general-governmentdata.xlsx.","access_type":"Published with the package","uri":"https:\/\/data.worldbank.org\/indicator\/NE.CON.GOVT.ZS","license":"Creative Commons Attribution 4.0 (CC-BY 4.0)","license_uri":"https:\/\/datacatalog.worldbank.org\/int\/public-licenses"},{"name":"World Governance indicators","note":"Daniel Kaufmann and Aart Kraay (2023). Worldwide Governance Indicators, 2023 Update. Indicator used Rule of Law and Control of Corruption in 2011 and 2021. \nLocated at: data\/wgi-data.xlsx","access_type":"Published with the package","uri":"https:\/\/www.worldbank.org\/en\/publication\/worldwide-governance-indicators","license_uri":"https:\/\/www.worldbank.org\/en\/about\/legal\/terms-of-use-for-datasets","license":"Creative Commons Attribution 4.0 International License (CC BY 4.0)"}],"software":[{"name":"Python","version":"3.9.13"}],"scripts":[{"file_name":"RR_WLD_2024_184.zip","zip_package":"RR_WLD_2024_184.zip","title":"Reproducibility package (data and code) for Development acupuncture: The network structure of multidimensional poverty and its implications","date":"2024-10","dependencies":"All dependencies are stored in the requirements.txt.","notes":"Computational reproducibility verified by the Development Impact (DIME) Analytics team, World Bank."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"reproduction_instructions":"To reproduce the analysis provided in this package, new users need to do the following:\n1. **Register with MICS and DHS**  \n- Create accounts and register your project with both **MICS** and **DHS**.  \n- Refer to the README file for the list of required datasets.  \n- After obtaining the data, use the **OHPI do-files** to process it and generate the final dataset, which serves as the starting point for this research.  \n\n2. **Recover the Environment**  \n   To ensure the correct environment, follow these steps:  \n   `conda create --name rep-package `\n   `conda activate rep-package`  \n   `pip install -r requirements.txt`  \n\n3. **Run** the `complexity-mp-analysis.ipynb` Jupyter Notebook.\n\n *Note on OS Compatibility\n  - **Windows Users:** If you run the code in a **Windows environment**, the results for **Figure 3** won't align with the original paper. \n  - **macOS Users:** Running the code in a **macOS environment**, **Figure 3** will yield the same results as those reported in the original paper.  \n  - The package includes a folder named **`output_replicators`** with the results from both operating systems for transparency, and the reproducibility report included in the package contains more detailed information.\n","technology_environment":"Paper exhibits were reproduced in two computers with the following specifications:\nComputer 1:\n\u2022 OS: Mac OS 15.0.1\n\u2022 Processor: Apple M1 Pro\n\u2022 Memory available: 32 GB\n\u2022 Software version: Python version 3.13.\nComputer 2:\n\u2022 OS: Windows 10 Enterprise\n\u2022 Processor: Intel(R) Xeon(R) Gold 6226R CPU @ 2.90GHz, 2900 Mhz, 16 Core(s), 16 Logical Processor(s)\n\u2022 Memory available: 87.7 GB\n\u2022 Software version: Python version 3.9.13.\nAll the results were identical and reproducible in the two computers with exception of Figure 3, which was only reproducible in a MacOS environment. ","technology_requirements":"~60 minutes run time","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":[{"email":"viksabot@gmail.com","name":"Viktor Stojkoski","affiliation":"University Ss. Cyril and Methodius in Skopje, North Macedonia, and Center for Collective Learning, ANITI, IRIT, Universit\u00e9 de Toulouse & CIAS Corvinus University of Budapest"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"geographic_units":[{"name":"World","code":"WLD","type":"Region"}]},"tags":[{"tag":"DOI"}],"schematype":"script"}