{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DIME","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2024-02-26","version":"1"},"project_desc":{"output":[{"type":"Working paper","title":"Lives, Livelihoods, and Learning: A Global Perspective on the Wellbeing Impacts of the COVID-19 Pandemic","authors":"Benoit Decerf, Jed Friedman, Arthur Mendes, Steven Pennings, Nishant Yonzan","description":"Policy Research Working Paper (PRWP)"}],"datasets":[{"name":"WHO Estimates of Excess Mortality Associated With COVID-19 Pandemic","access_type":"Data is public and included in the reproducibility package","note":"WHO dataset on global excess deaths, used to create YLL. Data was accessed on May 2022. Please refer to \u201cPrevious releases\u201d at the bottom of the website provided to download the May 2022 vintage. Download is a zip file. Excel file used is \"WHO_COVID_Excess_Deaths_EstimatesByCountry.xlsx\", only the tab  Country by year, sex and age. Please delete rows 1 to 11, rows 5434 to 5439, and change the file name to \"Excess deaths WHO.xlsx\".","uri":"https:\/\/www.who.int\/data\/sets\/global-excess-deaths-associated-with-covid-19-modelled-estimates"},{"name":"Country-level Mortality data from: \"Too Young to Die\": Deprivation Measures Combining Poverty and Premature Mortality\" ","note":"Mortality data, used to create YLL. No cleaning took place. Data was accessed on February 2023. Dataset can be found inside the folder Replication\/Data\/GBD in the Data URL with the name IHME-GBD_2017_DATA-f89cefb0-1.csv.","access_type":"Data is public and included in the reproducibility package","uri":"https:\/\/www.openicpsr.org\/openicpsr\/project\/119941\/version\/V1\/view"},{"name":"Historical country income group classification from Daniel Mahler","note":"Historical country income group classification. No cleaning took place. Dataset was accessed on November 2023. Dataset can be found inside the folder OutputData of the Data URL, in a file named CLASS.dta. Please change its name to CLASS_historical.dta","uri":"https:\/\/github.com\/PovcalNet-Team\/Class","access_type":"Data is public and included in the reproducibility package"},{"name":"Global binned income distribution per country and year from: The Impact of COVID-19 on Global Inequality and Poverty","access_type":"Data is public and included in the reproducibility package","note":"Global binned income distribution per country and year. Version accessed was 20230919_2017_01_02_PROD. To generate the database, run the do files of the Data URL. This code queries updated poverty lines from the Poverty and Inequality Platform (PIP, World Bank) publicly available at https:\/\/pip.worldbank.org\/home. If the code provided produces updated data that differs from the data used in this paper, please refer to the dataset authors. After running the code, change the name of the variable region_code to region_pip, and obs to quantile and save the dataset as GlobalDist_1000bins_2019-2023_sep23.dta","uri":"https:\/\/github.com\/worldbank\/covid-impact-on-inequality-and-poverty\/tree\/main"},{"name":"Welfare vectors from: The Impact of COVID-19 on Global Inequality and Poverty","access_type":"Dataset is restricted. Replicators seeking to access the data should contact the authors of \"The Impact of COVID-19 on Global Inequality and Poverty\" (World Bank Policy Research Working Paper 10198, http:\/\/hdl.handle.net\/10986\/38114). Dataset file name is \"GlobalDist_1000bins_MYLseptember23_limitedvars.dta\" in the code reading the data. The data is not included in the reproducibility package.\n","note":"Welfare vectors, used to create CPY. No cleaning took place. Version accessed was 20230919_2017_01_02_PROD."},{"name":"World Economic Outlook (WEO) database by the International Monetary Fund","note":"WEO Database, macroeconomic data series produced by the International Monetary Fund. Dataset was accessed in October 2022. Please click on the button \u201cBy Countries\u201d to download the dataset and name it WEOOct2022all.xls.","access_type":"Data is public and included in the reproducibility package","uri":"https:\/\/www.imf.org\/en\/Publications\/WEO\/weo-database\/2022\/October\/download-entire-database"},{"name":"World Bank's World Development Indicators (WDI) Database","access_type":"Data is public and included in the reproducibility package","uri":"https:\/\/datatopics.worldbank.org\/world-development-indicators\/","note":"World Bank's WDI. Dataset was accessed in September 2023. Click on \u201cCSV download\u201d under Bulk Downloads in the Data URL . Open WDI_CSV.zip. Change the name of WDIData.csv to WDIEXCEL_extracted0923.csv"},{"name":"Penn World Table 10.01","note":"PWT version 10.01 is a database with information on relative levels of income, output, input and productivity, covering 183 countries between 1950 and 2019. We use data from PWT 10 to calibrate the labor share, initial capital to output ratio, depreciation rate and TFP. Labor share: The labor share is a key parameter for the impact of human capital on growth and is taken from Penn World Table 10 (PWT10) for 2019 (most recent observation) under \u201clabsh\u201d \u201cShare of labour compensation in GDP at current national prices\u201d. Depreciation rate is taken from \u201cdelta\u201d the \u201caverage depreciation rate of the capital stock\u201d. Initial capital-to-GDP ratio: The initial capital-to-GDP ratio is calculated using the 2019 observations on physical capital stock and GDP from PWT 10. More specifically, we compute KY= rnna\/rgdpna where \u201crnna\u201d is \u201cCapital stock at constant 2017 national prices (in mil. 2017US$)\u201d and \u201crgdpna\u201d is \u201cReal GDP at constant 2017 national prices (in mil. 2017US$)\u201d. These data was copied to columns G, H, I of the tab \"Summary\" of the file OUTPUT_default_nolinks_31March2023.xlsx.","uri":"https:\/\/www.rug.nl\/ggdc\/productivity\/pwt\/?lang=en","access_type":"Data is public and included in the reproducibility package"},{"note":"Total investment by country for 2020-2027, expressed as a ratio of total investment in current local currency and GDP in current local currency was taken from the IMF's World Economic Outlook report  for October 2022. The corresponding variable name in the original data is \u201cNID_NGDP\u201d. Data was copied and pasted manually in columns AR-AY (2020-2027) of the tab \"WEO_investment\" in the file OUTPUT_default_nolinks_31March2023.xlsx.","name":"Total investment from the World Economic Outlook report  for October 2022","uri":"https:\/\/www.imf.org\/en\/Publications\/WEO\/Issues\/2022\/10\/11\/world-economic-outlook-october-2022","access_type":"Data is public and included in the reproducibility package"},{"name":"World Bank\u2019s Human Capital Project","note":"The data for the HCI of young cohorts (5-19 year-olds in 2020-2021 and future cohorts) are taken from the World Bank\u2019s Human Capital Project, (which measures the expected LAYS a child born today is expected to attain by her 18th birthday, including quantity and quality of education, S_c and Q_c). The HCI data can be downloaded in the Data URL provided under \u201cExpected Years of School\u201d and \u201cTest Scores\u201d. Data was copied and pasted manually in columns J and K of the tab \"Summary\" in the file OUTPUT_default_nolinks_31March2023.xlsx.","uri":"https:\/\/www.worldbank.org\/en\/publication\/human-capital","access_type":"Data is public and included in the reproducibility package"},{"name":"Barro-Lee Educational Attainment Database","note":"Data for the years of schooling of older generations is from the Barro-Lee Educational Attainment Database. Data was copied and pasted manually in column E of the tab \"BARROLEE\" in the file OUTPUT_default_nolinks_31March2023.xlsx.","uri":"http:\/\/www.barrolee.com","access_type":"Data is public and included in the reproducibility package"},{"name":"National Accounts Data from the UN\u2019s Statistical Division (UNSD)","note":"Data as of January 2024 on the share of agriculture in total Gross Value Added reported by the UNSD was used to simulate future total factor productivity (TFP) growth paths. We used the ISIC3 classification of economic activities. The data can be downloaded in the link below under National Accounts Estimates of Main Aggregates, variable \u201cGross Value Added by kind of Economic Activity at current prices\u201d. Data was copied and manually pasted in column C of the tab \"Data_agriculture\" in the file OUTPUT_default_nolinks_31March2023.xlsx.","uri":"http:\/\/data.un.org\/Explorer.aspx?d=SNAAMA","access_type":"Data is public and included in the reproducibility package"},{"name":"UN\u2019s World Population Prospects","note":"We use the UN\u2019s World Population Prospects forecasts for total population growth and the working-age population from 2021 to 2100. The forecasts for total population growth from 2021 to 2100 were downloaded from https:\/\/population.un.org\/wpp\/Download\/Standard\/MostUsed\/ and manually pasted to column G of the tab \"Data_agriculture\" in the file OUTPUT_default_nolinks_31March2023.xlsx. The forecasts for working-age population from 2021 to 2100 were downloaded from https:\/\/population.un.org\/wpp\/Download\/Standard\/Population\/ and manually pasted to column H of the same tab.","uri":"https:\/\/population.un.org\/wpp\/","access_type":"Data is public and included in the reproducibility package"},{"name":"World Bank\u2019s World Development Indicators (WDI) - GDP per capita and labor force participation","note":"The labor force participation rate is taken from the World Bank\u2019s WDI under  \u201cLabor force participation rate, total (% of total population ages 15-64) (modeled ILO estimate)\u201d, code SL.TLF.ACTI.ZS, and was manually copied to column E of the tab \"WDI\" in the file OUTPUT_default_nolinks_31March2023.xlsx. GDP per capita is taken from the WDI under \u201cGDP per capita, constant 2015 US$\u201d code NY.GDP.PCAP.KD., and was manually copied to column D of the same tab.\n","access_type":"Data is public and included in the reproducibility package","uri":"https:\/\/datatopics.worldbank.org\/world-development-indicators\/"},{"name":"Global Monitoring of School Closures Caused by the COVID-19 Pandemic from UNESCO","note":"The UNESCO data records for each day of 2020 and 2021 whether schools are fully closed, partially closed, or open. UNESCO codes days into \u201cFully Closed\u201d and \u201cPartially Closed\u201d with the latter getting a weight of 0.5. You can download variables Fully Closed\u201d and \u201cPartially Closed\u201d at UNESCO\u2019s dashboard on the global monitoring of school closures caused by the COVID-19 pandemic. Data was manually pasted to the column C of the tab \"UNESCO-COVID\" in the file OUTPUT_default_nolinks_31March2023.xlsx.","uri":"https:\/\/covid19.uis.unesco.org\/global-monitoring-school-closures-covid19\/","access_type":"Data is public and included in the reproducibility package"}],"title_statement":{"idno":"RR_WLD_2024_74-v03","title":"[WORKING PAPER VERSION] Reproducibility package for Lives, Livelihoods, and Learning: A Global Perspective on the Wellbeing Impacts of the COVID-19 Pandemic"},"production_date":"2024-02","abstract":"[PLEASE NOTE THAT THIS REPRODUCIBILITY PACKAGE CORRESPONDS TO THE WORKING PAPER VERSION. THE JOURNAL VERSION IS AVAILABLE AT THIS LINK: ]https:\/\/reproducibility.worldbank.org\/catalog\/516]. This study compares the magnitude of the losses that the COVID-19 pandemic inflicted across three critical dimensions: loss of life, loss of income, and loss of learning. The wellbeing consequences of excess mortality are expressed in years of life lost while those of income losses and school closures are expressed in additional years spent in poverty (as measured by national poverty lines), either currently or in the future. While the 2020-2021 period witnessed a global drop in life expectancy and the largest one-year increase in global poverty in many decades, widespread school closure may cause an increase in future poverty almost twice as large. The estimates of wellbeing loss for the average global citizen include a loss of almost 3 weeks of life (19 days), an additional two and half weeks spent in poverty in the years 2020 and 2021 (17 days), and the possibility of an additional month of life in poverty in the future due to school closures (31 days). Wellbeing losses are also not equitably distributed across countries. The typical high-income country suffered more total years of life lost than additional years in poverty, while the opposite holds for the typical low- or middle-income country. Aggregating total losses requires a valuation for a year of life lost vis-\u00e0-vis an additional year spent in poverty. If a year of life lost is valued at six or fewer additional years spent in poverty, low-income countries suffered greater total wellbeing loss than high-income countries. However, for a wide range of valuations, the greatest wellbeing losses fell on upper-middle-income countries and for countries in the Latin America region. This set of countries suffered the largest mortality costs as well as large losses in learning and sharp increases in poverty.","geographic_units":[{"name":"World","code":"WLD"}],"keywords":[{"name":"covid"},{"name":"welfare"},{"name":"poverty"},{"name":"mortality"},{"name":"learning"}],"topics":[{"vocabulary":"Journal of Economic Literature (JEL)","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","name":"Equity, Justice, Inequality, and Other Normative Criteria and Measurement","id":"D63"},{"vocabulary":"Journal of Economic Literature (JEL)","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","name":"Health and Economic Development","id":"I15"},{"vocabulary":"Journal of Economic Literature (JEL)","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","name":"General Welfare, Well-Being","id":"I31"},{"vocabulary":"Journal of Economic Literature (JEL)","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","name":"Measurement and Analysis of Poverty","id":"I32"},{"vocabulary":"Journal of Economic Literature (JEL)","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","id":"O15","name":"Human Resources \u2022 Human Development \u2022 Income Distribution \u2022 Migration"}],"data_statement":"All datasets used are public and included in the reproducibility package except for the Welfare Vectors dataset. Replicators can contact the dataset authors (specified in the datasets section) for access.","software":[{"name":"Stata","version":"17"}],"scripts":[{"file_name":"RR_WLD_2024_74-v3","zip_package":"RR_WLD_2024_74-v3.zip","title":"Reproducibility package (code and partial data) for Lives, Livelihoods, and Learning: A Global Perspective on the Well-being Impacts of the Covid-19 Pandemic","date":"2024-02","dependencies":"All dependencies are stored in the folder \"DoFiles\/ado\"","instructions":"See README in reproducibility package","notes":"Computational reproducibility verified by Development Impact (DIME) Analytics team, World Bank. A separate reproducibility package for the journal version is available and can be accessed here: https:\/\/reproducibility.worldbank.org\/catalog\/516."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"technology_environment":"The code was run in a computer with the following specifications:\n- OS: Windows 10 Enterprise, version 21H2\n- Processor: Intel(R) Xeon(R) CPU E7-4890 v2 @ 2.80GHz 2.80 GHz\n- Memory available: 5.9 GB\n- Software version: Stata 17","technology_requirements":"Runtime: 40 minutes","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":[{"affiliation":"World Bank","name":"Benoit Decerf","email":"bdecerf@worldbank.org"},{"name":"Reproducibility WB","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"authoring_entity":[{"name":"Benoit Decerf","affiliation":"World Bank","email":"bdecerf@worldbank.org"},{"name":"Jed Friedman","affiliation":"World Bank","email":"jfriedman@worldbank.org"},{"name":"Arthur Mendes","affiliation":"World Bank","email":"agalegomendes@worldbank.org"},{"name":"Steven Pennings","affiliation":"World Bank","email":"spennings@worldbank.org"},{"name":"Nishant Yonzan","affiliation":"World Bank","email":"nyonzan@worldbank.org"}]},"tags":[{"tag":"DOI"}],"schematype":"script"}