The Firm Adoption of Technology (FAT) Survey, 2019
Senegal, 2019
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SEN_2019_FAT_v01_M
The Firm Adoption of Technology (FAT) Survey, 2019
FAT 2019
| Name | Country code |
|---|---|
| Senegal | SEN |
Enterprise Survey [en/oth]
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.
Sample survey data [ssd]
Establishment
Version
2026-02-05
Edited, anonymised datasets for public distribution
Coverage
National
Producers and sponsors
| Name | Affiliation |
|---|---|
| Xavier Cirera | The World Bank |
| Diego Comin | Dartmouth College |
| Marcio Cruz | IFC |
| Name |
|---|
| World Bank Group |
| Name | Abbreviation | Role |
|---|---|---|
| Competitive Industries and Innovation Program | CIIP | Financial Support |
Sampling
The Firm-level Adoption of Technology (FAT) survey employs a stratified random sampling design to ensure a nationally representative sample of formal private sector establishments. The universe of study was restricted to formal establishments with five or more employees across the stratified sectors. Micro-firms with fewer than five employees were excluded to ensure consistency in the sampling frame and to mitigate the complexities associated with surveying informal entities in developing economies. To achieve statistical precision across key economic dimensions, the population was stratified by geography, firm size, and sector of activity. Details about the stratifications are provided in the FAT Methodology note.
In Senegal, the census includes informal firms as well, as a type of firms with a basic registration. As a result, we stratify for formal and informal firms. Data collection was collected via face-to-face interviews.
For geographic stratification, we used the following regions: Dakar, Diourbel, Kaolack, Kolda, St. Louis, Thies, and Ziguinchor. As firm size stratification, we used three strata: small firms (4-19 employees), medium firms (20-99 employees), large firms (more than 100 employees). Regarding sector startification, in Senegal the survey stratifies in nine sectors: agriculture (ISIC 01), food processing (ISIC 10), wearing apparel (ISIC 14), "other manufacturing", retail and wholesale (ISIC 46 and 47), land transportation (ISIC 49), finance (ISIC 64), health (ISIC 86), and "other services".
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.
The response rate was 39%
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.
Survey 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—such as regulatory constraints and human capital—alongside 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.
Data collection
| Start | End |
|---|---|
| 2019 | 2019 |
- Computer-Assisted Personal Interview (CAPI)
Survey supervision was implemented by Xavier Cirera, Marcio Cruz and Kyung Min Lee.
The mode of data collection was primarily face-to-face before the pandemic and mostly via telephone and online during the pandemic.
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.
Depositor information
| Name |
|---|
| Financial and Private Sector Development Network (FPD) |
Data Access
| Name | Affiliation |
|---|---|
| Marcio Cruz | DECPM |
| Xavier Cirera | WKPTC |
| Kyung Min Lee | WKPTC |
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
In addition to the dataset citation, users must also cite the journal publication for methodology and approach as follows:
Cirera, X., Comin, D., and Cruz, M. (2026). Technology Sophistication Across Establishments. The Quarterly Journal of Economics.
Disclaimer and copyrights
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.
Contacts
| Name | Affiliation | |
|---|---|---|
| Marcio Cruz | DECPM | marciocruz@ifc.org |
| Xavier Cirera | WKPTC | xcirera@worldbank.org |
| Kyung Min Lee | WKPTC | klee12@worldbank.org |
Metadata production
DDI_SEN_2019_FAT_v01_M_WB
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Data Group | DECDG | World Bank | Documentation of the study |
2026-03-05
Metadata version
Version 01 (2026-03-05)