{"type":"script","doc_desc":{"producers":[{"name":"Reproducibility WBG","abbr":"DECDI","affiliation":"World Bank - Development Impact Department","role":"Verification and preparation of metadata"}],"prod_date":"2026-10-23","version":"1"},"project_desc":{"authoring_entity":[{"name":"Filip Jolevski","affiliation":"World Bank","email":"fjolevski@worldbank.org"},{"name":"Gemechu A. Aga","affiliation":"World Bank","email":"gayanaaga@worldbank.org"}],"title_statement":{"title":"Reproducibility package for First Impressions Matter: Measuring And Correcting Position Bias In Business Environment Estimates","idno":"RR_WLD_2026_774"},"data_statement":"The reproducibility package relies on 2 type of data: Accessible and Open data. For the source, access type, file location, and citation of each dataset, refer to the Datasets section and the README file.","software":[{"name":"Stata","version":"19.0 MP"}],"scripts":[{"title":"Reproducibility package for First Impressions Matter: Measuring And Correcting Position Bias In Business Environment Estimates","date":"2026-10","notes":"Computational reproducibility verified by Development Impact (DECDI) Analytics team, World Bank.","instructions":"See README in reproducibility package.","file_name":"RR_WLD_2026_774","zip_package":"RR_WLD_2026_774.zip","dependencies":"Stata dependencies are listed in the ado folder."}],"repository_uri":[{"name":"Reproducible Research Repository (World Bank)","uri":"https:\/\/reproducibility.worldbank.org"}],"production_date":"2026-10-23","abstract":"Estimating the constraints in the business environment guides development policy and allocation of resources. This paper examines response order bias in survey questions on the biggest obstacle to operations with a lengthy list of response options in the World Bank Enterprise Surveys. Using over 200,000 interviews with firm managers from 178 economies with randomized response orders, estimates show that the first three positions have a 9 percent higher relative likelihood of being selected, with the very first position on the showcard being 22 percent more likely to be selected. The primacy bias, tendency to select an early response option, is significantly stronger in low-income economies (17 percent, whereas in high-income economies the bias is statistically non-existent), creating a troubling paradox: position effects distort estimates most severely where accurate constraint measurement matters most for development policy. Applying empirical Bayes-stabilized inverse probability weights to correct for these biases changes the rank order for 9 percent of the obstacles, affecting about half of the surveys.","geographic_units":[{"name":"World","code":"WLD"}],"keywords":[{"name":"Response Order Effects"},{"name":"Business Environment"},{"name":"Primacy Effects"},{"name":"Bias Correction"}],"topics":[{"id":"C14","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Semiparametric and Nonparametric Methods: General","parent_id":"C1"},{"id":" C81","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Methodology for Collecting, Estimating, and Organizing Microeconomic Data \u2022 Data Access","parent_id":"C8"},{"id":" C83","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Survey Methods \u2022 Sampling Methods","parent_id":"C8"},{"id":" O12","uri":"https:\/\/www.aeaweb.org\/econlit\/jelCodes.php?view=jel","vocabulary":"Journal of Economic Literature (JEL)","name":"Microeconomic Analyses of Economic Development","parent_id":"O1"}],"output":[{"type":"Working Paper","description":"Policy Research Working Paper (PRWP)","title":"First Impressions Matter: Measuring And Correcting Position Bias In Business Environment Estimates"}],"language":[{"name":"English","code":"EN"}],"technology_requirements":"Run time ~ 3 hours","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":"MIT License","uri":"https:\/\/opensource.org\/license\/mit"},{"name":"World Bank IGO Rider","uri":"https:\/\/github.com\/worldbank\/metadata-editor\/blob\/main\/WB-IGO-RIDER.md"}],"contacts":[{"name":"Filip Jolevski","affiliation":"World Bank","email":"fjolevski@worldbank.org"},{"name":"Reproducibility WBG","affiliation":"World Bank","email":"reproducibility@worldbank.org"}],"datasets":[{"name":"World Bank Enterprise Surveys - Comprehensive Data and Country-Specific Files","note":"Data accessed July 28, 2026. Includes the comprehensive WBES dataset and four country-specific survey files not included in the comprehensive file. (1) New_Comprehensive_July_28_2026.dta: comprehensive WBES dataset. Variables used: idstd, m1a (biggest obstacle), a16 (interviewer's view of truthfulness), wt (sampling weight). (2) Haiti-2019-full data.dta, Malaysia-2019-expansion.dta, Mozambique-2018-expansion.dta, Bosaso and Mogadishu-2019-full data.dta: individual country\/survey files not included in the comprehensive dataset. Variables used: idstd, m1a, a16, wmedian (sampling weight). File location: !Data\/_Raw Data\/New_Comprehensive_July_28_2026.dta; !Data\/_Raw Data\/WBES_Haiti2019_Data\/Haiti-2019-full data.dta; !Data\/_Raw Data\/WBES-OS_Malaysia2019_Data\/Malaysia-2019-expansion.dta; !Data\/_Raw Data\/WBES-OS_Mozambique2018_Data\/Mozambique-2018-expansion.dta; !Data\/_Raw Data\/WBES-OS_Somalia2019_Data\/Bosaso and Mogadishu-2019-full data.dta. To access these  go to the WBES website (https:\/\/www.enterprisesurveys.org\/en\/enterprisesurveys) and download them. You'll need to create an account to access them","access_type":"Data is publicly available but does not allow redistribution and is not included in the reproducibility package.","license":"Custom License","uri":"https:\/\/www.enterprisesurveys.org","citation":"World Bank. 2026. \"World Bank Enterprise Surveys\" [dataset]. https:\/\/www.enterprisesurveys.org. Accessed July 28, 2026."},{"name":"World Bank Enterprise Surveys - Showcard Positions","note":"File: `1_position data.dta` is constructed using the metadata which is not publically available, but can be requested from The World Bank Enterprise Surveys team (enterprisesurveys@worldbank.org). Permissions were obtained to make this dataset public. Variables used: idstd, survey, country_official, WBCode, region, year, method, m1a_ord, the 15 position variables (code_ord), m1d, a12, duration. File location: !Data\/_Raw Data\/1_position data.dta.","access_type":"Data is publicly available but does not allow redistribution and is not included in the reproducibility package.","license":"Custom License","citation":"Authors' compilation. 2026. \"World Bank Enterprise Surveys - Showcard Positions\" [dataset]. Constructed from World Bank Enterprise Surveys metadata. Accessed July 2026"},{"name":"World Bank Country and Lending Groups - Income Classifications","note":"Data accessed July 15, 2026. World Bank country and lending group income classifications. Sheet used: Country Analytical History from OGHIST_2026_07_15.xlsx. File location: !Data\/_Raw Data\/OGHIST_2026_07_15.xlsx.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Open data","uri":"https:\/\/ddh-openapi.worldbank.org\/resources\/DR0095334\/download","citation":"World Bank. 2026. \"World Bank Data Help Desk: World Bank Country and Lending Groups\" [dataset]. https:\/\/ddh-openapi.worldbank.org\/resources\/DR0095334\/download. Accessed July 15, 2026."},{"name":"World Development Indicators - GDP per Capita, PPP (Current International $)","note":"Data accessed October 1, 2026. Indicator NY.GDP.PCAP.PP.CD, downloaded by the code using wbopendata. Note: the code downloads the current WDI vintage each time it runs, so a later run may use revised figures. Three missing values are filled from the IMF World Economic Outlook (Taiwan, China; South Sudan 2024; Afghanistan 2025); the values and URLs are provided in the code.","access_type":"Data is publicly available and included in the reproducibility package.","license":"Creative Commons Attribution 4.0 International License (CC BY 4.0)","license_uri":"https:\/\/www.worldbank.org\/en\/about\/legal\/terms-of-use-for-datasets","uri":"https:\/\/data.worldbank.org\/indicator\/NY.GDP.PCAP.PP.CD","citation":"World Bank. 2026. \"World Development Indicators\" [dataset]. Indicator NY.GDP.PCAP.PP.CD. https:\/\/data.worldbank.org\/indicator\/NY.GDP.PCAP.PP.CD. Accessed October 1, 2026."}],"reproduction_instructions":"To reproduce the findings in this paper, a replicator must:\n1. Secure Access to Data: Access the datasets not included in the package. See the Datasets section for more details\n2. Open the master script `replication_first_impressions_matter.do`, update the directory on line 75, install the required packages and run the script.\n\nSince some of the data is excluded, the package includes the outputs produced by the replicators, which can be used to review the results presented in the paper","technology_environment":"Paper exhibits were reproduced on a computer with the following specifications:\n\u2022 OS: Windows 11 Enterprise\n\u2022 Processor: Intel(R) Xeon(R) Gold 5218 CPU @ 2.30GHz (2.30 GHz) (2 processors)\n\u2022 Memory available: 16 GB"},"datacite":{"creators":[{"givenName":"Filip","familyName":"Jolevski","nameType":"Personal","affiliation":[{"name":"World Bank","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]},{"givenName":"Gemechu A.","familyName":"Aga","nameType":"Personal","affiliation":[{"name":"World Bank","affiliationIdentifier":"https:\/\/ror.org\/00ae7jd04","affiliationIdentifierScheme":"ROR","schemeUri":"https:\/\/ror.org"}]}],"titles":[{"lang":"en","title":"Reproducibility package for First Impressions Matter: Measuring And Correcting Position Bias In Business Environment Estimates"},{"title":"RR_WLD_2026_774","titleType":"Other"}],"publisher":"World Bank","publicationYear":"2026","types":{"resourceType":"Reproducibility package","resourceTypeGeneral":"Other"},"url":"https:\/\/reproducibility.worldbank.org\/index.php\/catalog\/study\/RR_WLD_2026_774","language":"en"},"tags":[{"tag":"Accessible Data"},{"tag":"DOI"},{"tag":"Open Access"},{"tag":"Open Code"}],"schematype":"script"}