Resilience Firm Survey 2018
Dar es Salaam, Tanga and Dodoma
Tanzania, 2018
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Reference ID
TZA_2018_RFS_v01_M
Producer(s)
Alvina Erman, Jun Rentschler, Julie Rozenberg, Stephane Hallegatte
Metadata
Created on
Jul 13, 2022
Last modified
Jul 13, 2022
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Identification
Survey ID Number
TZA_2018_RFS_v01_M
Title
Resilience Firm Survey 2018
Subtitle
Dar es Salaam, Tanga and Dodoma
Country/Economy
| Name | Country code |
|---|---|
| Tanzania | TZA |
Study type
Enterprise Survey [en/oth]
Series Information
The Resilience Firm Surveys (RFS) is a firm survey series designed to collect information from private businesses focusing on i) dependence on and reliability of critical and non-critical infrastructure, ii) use of suppliers and impacts of supply chain disruptions, iii) impacts of recent disasters – coping capacity and long-term effects, iv) firm level preparedness and management of shocks and interruptions caused by natural hazards. The survey is customized depending on the context, industry sector and research questions. The data can be used to explore policy-relevant research topics related to climate change adaptation, infrastructure resilience, private sector recovery, and more. explore the real costs of disasters on firms—both through direct damage to assets and operations, and the indirect costs of perpetuated economic inefficiencies and coping measures.
RFS data contain information on firm characteristics, use of suppliers, infrastructure dependency, firm experience with disasters and risk management and coping capacity. Firm characteristics include sector engagement, number of employees, number of clients, costs and sales information. Use of supplier information include location of suppliers, use of inputs, frequency of restocking, storage capacity, etc. Infrastructure dependency focuses on use of infrastructure, such as water, electricity and transport, frequency of disruptions, impacts of disruptions on demand and sales, use of backup infrastructure, etc. Firm experience with disasters captures both direct (damages to property) and indirect (infrastructure and supply chain disruptions) impacts of recent disasters, as well as coping behaviors and recovery of sales after a shock. Risk management and coping capacity capture information on use of hazard risk information, access to insurance and preparedness measures. The RFS can be customized to collect information on different sectors and type of disasters. So far, it has focused on the impacts of urban flooding (TZ) and hurricanes/storms (CAR).
The series was developed and financed by Global Facility for Disaster Reduction and Recovery (GFDRR) in collaboration with Disaster Risk Management, Resilience and Land Global Practice (GPURL), country counterparts, and selected survey firms.
RFS data contain information on firm characteristics, use of suppliers, infrastructure dependency, firm experience with disasters and risk management and coping capacity. Firm characteristics include sector engagement, number of employees, number of clients, costs and sales information. Use of supplier information include location of suppliers, use of inputs, frequency of restocking, storage capacity, etc. Infrastructure dependency focuses on use of infrastructure, such as water, electricity and transport, frequency of disruptions, impacts of disruptions on demand and sales, use of backup infrastructure, etc. Firm experience with disasters captures both direct (damages to property) and indirect (infrastructure and supply chain disruptions) impacts of recent disasters, as well as coping behaviors and recovery of sales after a shock. Risk management and coping capacity capture information on use of hazard risk information, access to insurance and preparedness measures. The RFS can be customized to collect information on different sectors and type of disasters. So far, it has focused on the impacts of urban flooding (TZ) and hurricanes/storms (CAR).
The series was developed and financed by Global Facility for Disaster Reduction and Recovery (GFDRR) in collaboration with Disaster Risk Management, Resilience and Land Global Practice (GPURL), country counterparts, and selected survey firms.
Abstract
The RFS In Tanzania was conducted in three major cities, Dar es Salaam, Tanga and Dodoma, between September and November 2018. The survey focused on firms in manufacturing and service industries and the data was collected via in-person interviews. The survey focused on how firms are affected by floods and which strategies they use to cope and adapt, Impact of flooding considers both direct damages and indirect effects through infrastructure systems, supply chains and workers.
This project was a collaborative effort between Global Facility for Disaster Reduction and Recovery (GFDRR) and Urban, Disaster Risk Management, Resilience and Land Global Practice (GPURL).
This project was a collaborative effort between Global Facility for Disaster Reduction and Recovery (GFDRR) and Urban, Disaster Risk Management, Resilience and Land Global Practice (GPURL).
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Firm level
Coverage
Geographic Coverage
Dar es Salaam, Dodoma, and Tanga
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Alvina Erman | World Bank |
| Jun Rentschler | World Bank |
| Julie Rozenberg | World Bank |
| Stephane Hallegatte | World Bank |
Funding Agency/Sponsor
| Name | Abbreviation |
|---|---|
| Global Facility for Disaster Risk Reduction | GFDRR |
Sampling
Sampling Procedure
The sampling frame consisted of the official business registry obtained from the National Bureau of Statistics' (NBS) in Tanzania. It contained a list of 58,959 firms in Dar es Salaam, Tanga, and Dodoma. Firms listed without a functioning telephone number were excluded from the sampling frame.
All registered firms were divided into five distinct strata, depending on their reliance on transport systems. Ordered from low to high transport reliance, these strata contain firms from the following sectors:
1 Accommodation and food service activities, Construction
2 Communication and other services
3 Manufacturing, Mining, Water, Energy, Agriculture
4 Transportation and storage
5 Wholesale and retail trade, Repair of motor vehicles and motorcycles
The sample selection was completed in one stage, with firms selected through a systematic random sampling method from each stratum. In terms of regional distribution, the sample contains 623 firms from Dar es Salaam, 101 from Dodoma, and 113 from Tanga. About 10 percent of listed firms were interviewed, with the main reasons for the low response rate being incorrect addresses, expectation of payment for survey participation, and concerns about disclosure of tax-relevant information.
All survey results, using the survey weights computed, should be interpreted as representative of private businesses located in the 3 cities Dar es Salaam, Dodoma, and Tanga and registered in the NBS business registry with phone access.
All registered firms were divided into five distinct strata, depending on their reliance on transport systems. Ordered from low to high transport reliance, these strata contain firms from the following sectors:
1 Accommodation and food service activities, Construction
2 Communication and other services
3 Manufacturing, Mining, Water, Energy, Agriculture
4 Transportation and storage
5 Wholesale and retail trade, Repair of motor vehicles and motorcycles
The sample selection was completed in one stage, with firms selected through a systematic random sampling method from each stratum. In terms of regional distribution, the sample contains 623 firms from Dar es Salaam, 101 from Dodoma, and 113 from Tanga. About 10 percent of listed firms were interviewed, with the main reasons for the low response rate being incorrect addresses, expectation of payment for survey participation, and concerns about disclosure of tax-relevant information.
All survey results, using the survey weights computed, should be interpreted as representative of private businesses located in the 3 cities Dar es Salaam, Dodoma, and Tanga and registered in the NBS business registry with phone access.
Response Rate
About 10 percent of listed firms were interviewed, with the main reasons for the low response rate being incorrect addresses, expectation of payment for survey participation, and concerns about disclosure of tax-relevant information.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2018-09 | 2018-11 |
Data Collection Mode
Computer Assisted Personal Interview [capi]
Supervision
The World Bank
Data Collectors
| Name | Abbreviation |
|---|---|
| UDA Consulting | UDA |
Questionnaires
Questionnaires
• Firm characteristics
o Sector
o Number of workers
• Infrastructure dependence and disruptions
o Water
o Electricity
o Communication (phone and internet)
• Suppliers
• Workers and transport disruptions
• Clients
• Most serious natural shock that affected the firm
• Operational costs
• Investments
o Sector
o Number of workers
• Infrastructure dependence and disruptions
o Water
o Electricity
o Communication (phone and internet)
• Suppliers
• Workers and transport disruptions
• Clients
• Most serious natural shock that affected the firm
• Operational costs
• Investments
Data Processing
Data Editing
The following data editing was done for anonymization purposes:
- Precise location data, such as GPS coordinates, and;
- Identifying information, such as firm names, respondent names, phone numbers and emails contacts, were dropped
- Precise location data, such as GPS coordinates, and;
- Identifying information, such as firm names, respondent names, phone numbers and emails contacts, were dropped
Access policy
Contacts
| Name | Affiliation | |
|---|---|---|
| Alvina Erman | GFDRR | aerman@worldbank.org |
Confidentiality
Confidentiality has been ensured through a process of anonymization (see Technical Document for details).
Access conditions
Data is accessible for licensed users only and further dissemination of data is not allowed.
Citation requirements
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
Example:
The World Bank. Tanzania - Resilience Firm Survey (RFS) 2018, Dar es Salaam, Tanga and Dodoma. Ref: TZA_2018_RFS_v01_M. Dataset downloaded from microdata.worldbank.org on [date].
- 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
Example:
The World Bank. Tanzania - Resilience Firm Survey (RFS) 2018, Dar es Salaam, Tanga and Dodoma. Ref: TZA_2018_RFS_v01_M. Dataset downloaded from microdata.worldbank.org on [date].
Disclaimer and copyrights
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.
Metadata production
DDI Document ID
DDI_TZA_2018_RFS_v01_M_WB
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Development Economics Data Group | DECDG | The World Bank | Documentation of the DDI |
Date of Metadata Production
2022-07-11
DDI Document version
Version 01 (July 2022)