{"doc_desc":{"title":"ETH_2022_FAT_v01_M","idno":"DDI_ETH_2022_FAT_v01_M_WB","producers":[{"name":"Development Data Group","abbr":"DECDG","affiliation":"World Bank","role":"Documentation of the study"}],"prod_date":"2026-03-05","version_statement":{"version":"Version 01 (2026-03-05)"}},"study_desc":{"title_statement":{"idno":"ETH_2022_FAT_v01_M","title":"The Firm Adoption of Technology (FAT) Survey, 2022","alternate_title":"FAT 2022"},"authoring_entity":[{"name":"Xavier Cirera","affiliation":"The World Bank"},{"name":"Diego Comin","affiliation":"Dartmouth College"},{"name":"Marcio Cruz","affiliation":"IFC"}],"production_statement":{"producers":[{"name":"World Bank Group"}],"funding_agencies":[{"name":"The World Bank Group","abbr":"WBG","role":"Financial Support"}]},"distribution_statement":{"contact":[{"name":"Marcio Cruz","affiliation":"DECPM","email":"marciocruz@ifc.org"},{"name":"Xavier Cirera","affiliation":"WKPTC","email":"xcirera@worldbank.org"},{"name":"Kyung Min Lee","affiliation":"WKPTC","email":"klee12@worldbank.org"}],"depositor":[{"name":"Financial and Private Sector Development Network (FPD)"}]},"series_statement":{"series_name":"Enterprise Survey [en\/oth]","series_info":"The Firm Adoption of Technology (FAT) Survey is a nationally representative firm-level survey for agriculture, manufacturing, and services, conducted and managed by the World Bank. The survey applies a standardized sampling methodology and survey questionnaire to generate data that are comparable across countries. Particularly, the FAT survey measures more than 300 granular levels of technologies across over 60 business functions. It also collects information about the firm and owner\/manager characteristics, subjective perceptions of firms regarding to the adoption of technology, and detailed financial information."},"version_statement":{"version_date":"2026-02-05","version_notes":"Edited, anonymised datasets for public distribution"},"study_info":{"abstract":"The Firm Adoption of Technology (FAT) Survey is a nationally representative firm-level survey for agriculture, manufacturing, and services. The survey covers a broad range of topics related to business, with a granular measures of technologies across business functions.","coll_dates":[{"start":"2022","end":"2022"}],"nation":[{"name":"Ethiopia","abbreviation":"ETH"}],"geog_coverage":"National","analysis_unit":"Establishment","data_kind":"Sample survey data [ssd]"},"method":{"data_collection":{"sampling_procedure":"Stratified random sampling; formal private sector establishments with 5+ employees; stratified by geography (Addis Ababa, Amhara, Oromia, and SNNPR-Sidama-Dire Dawa-Harari-Somali), firm size (small: 4\u201319, medium: 20\u201399, large: 100+ employees), and sector of activity (8 sectors: Agriculture ISIC 01, Food processing ISIC 10, Wearing apparel ISIC 14, Other manufacturing, Retail and wholesale ISIC 46 & 47, Land transport ISIC 49, Accommodation ISIC 55, and Other services) \n\nThe sampling frame was constructed using the Business Registry of the Ministry of Trade and Industry (MoTI), which provided information on establishment name, address, sector of activity, phone number, and capital size. However, the registry did not include data on the number of employees, which precluded direct stratification by firm size. To address this limitation, a proxy for firm size was developed by estimating the correlation between capital size and employment using data from the World Bank High-Frequency Phone Survey of Firms (HFPS-F). The resulting regression parameters were then applied to the registry data to predict the number of workers per establishment, enabling size-based stratification in line with the study's design.","sampling_deviation":"See methodology notes for sector and regional stratification or section 2 and Appendix A of Cirera, X., Comin, D., & Cruz, M. (2026) provide detailed information about the sample design.","coll_mode":["Computer-Assisted Personal Interview (CAPI)"],"research_instrument":"The standard FAT questionnaire provides a comprehensive assessment of technology adoption and firm performance through five integrated modules. These modules cover general firm characteristics (including ownership and management demographics), the use of general business function technologies common to all firms, and deep dives into sector-specific technologies for twelve distinct sub-sectors. Additionally, the questionnaire evaluates the primary drivers and barriers to technology adoption\u2014such as regulatory constraints and human capital\u2014alongside detailed information on labor composition, balance sheets, and overall firm performance. By measuring more than 300 granular technologies across 60 business functions, the survey captures the extensive margin of adoption, the intensive margin of use, and the duration of advanced technology implementation.","coll_situation":"The mode of data collection was primarily face-to-face before the pandemic and mostly via telephone and online during the pandemic.","act_min":"Survey supervision was implemented the core team: Xavier Cirera, Marcio Cruz, Kyung Min Lee, Caroline Nogueira, Shruti Lakhtakia and Steven Farji Weiss; Data cleaning: Charmaine Robles Crisostomo, Harneet Singh, Aman Mahajan and Yuheng Ding","weight":"Sampling weights are constructed in two steps. Design weights reflect selection probabilities under stratified random sampling by industry, size, and region, representing how many establishments each sampled unit stands for. These weights are then adjusted for non-response using response rates within strata. The final weights align the weighted respondent sample with the distribution of establishments in the sampling frame.  Details about how the FAT sampling weights are calculated are given in the FAT Methodology note."},"analysis_info":{"response_rate":"The response rate was 42%","data_appraisal":"Section 2 of Cirera, X., Comin, D., & Cruz, M. (2026) provides detailed information on several quality checks to validate the survey and the data, including comparability with official business statistics from external sources."}},"data_access":{"dataset_use":{"conf_dec":[[]],"contact":[{"name":"Marcio Cruz","affiliation":"DECPM"},{"name":"Xavier Cirera","affiliation":"WKPTC"},{"name":"Kyung Min Lee","affiliation":"WKPTC"}],"cit_req":"Use of the dataset must be acknowledged using a citation which would include:\n\n- the Identification of the Primary Investigator\n- the title of the survey (including country, acronym and year of implementation)\n- the survey reference number\n- the source and date of download\n\nIn addition to the dataset citation, users must also cite the journal publication for methodology and approach as follows:\nCirera, X., Comin, D., and Cruz, M. (2026). Technology Sophistication Across Establishments. The Quarterly Journal of Economics.","disclaimer":"The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses."}}},"tags":[{"tag":"DOI"}],"schematype":"survey"}