SLE_2014-2015_HFCPS_v01_M
High Frequency Cell Phone Survey on the Socio-Economic Impacts of Ebola 2014-2015
Name | Country code |
---|---|
Sierra Leone | SLE |
Socio-Economic/Monitoring Survey [hh/sems]
Sample survey data [ssd]
v01 - edited, anonymous datasets for public distribution
The documented datasets - slhfcps_r1, slhfcps_r2, and slhfcps_r3 - correspond to each of the three survey rounds.
The scope of the study includes:
Due to differing characteristics between responding and non-responding households, the results should be considered “descriptive” rather than representative of the Sierra Leonean population. Overall the response rate was higher than expected given the nature of the survey and the difficult conditions under which it was conducted. In Sierra Leone, of the 4,199 households interviewed in the LFS, 65.8 percent (2,764 households) recorded a cell phone number for the household head, and, of those, 80.0 percent responded to at least one round of the cell phone survey. The unweighted sample was 59.1 percent urban (2,483 households) and 40.9 percent rural (1,716 households). Of urban households, 81.4 percent (2,021 households) listed a cell phone number for the household head, and, of those, 88.1 percent (1,780 households) responded in at least one of the three rounds of the cell phone survey. Of rural households, 43.1 percent (740 households) listed a cell phone number for the household head, and, of those, 58.1 percent (430 households) responded in at least one of the three rounds.
All households from the 2014 Sierra Leone Labor Force Survey which provided cell phone numbers.
Name | Affiliation |
---|---|
Statistics Sierra Leone | SSL |
Name | Role |
---|---|
Innovations for Poverty Action | Technical Assistance |
Name | Role |
---|---|
World Bank Group | Technical & Financial Assistance |
The sampling frame for the cell phone survey was the Sierra Leone Labor Force Survey (LFS) 2014. The LFS is a nationally representative stratified cluster sample survey conducted in July and August 2014, and includes the oversampling of urban areas. As part of the LFS, a total of 4199 households in 280 enumeration areas were interviewed. Interviewers collected the phone number, if available, for the head of household, and 2,764 households interviewed in the LFS included phone numbers. All available numbers from the LFS were included in the cell phone survey. The phone numbers were reported for 43 percent of rural households and 82 percent of urban households. Those households reporting numbers are unevenly distributed across the sample though there is at least partial coverage in all districts, ranging from 93 percent in Freetown (Western urban) to 30 percent in Kailahun district.
Overall the response rate was higher than expected given the nature of the survey and the difficult conditions under which it was conducted. In Sierra Leone, of the 4,199 households interviewed in the LFS, 65.8 percent (2,764 households) recorded a cell phone number for the household head, and, of those, 80.0 percent responded to at least one round of the cell phone survey.
The unweighted sample was 59.1 percent urban (2,483 households) and 40.9 percent rural (1,716 households). Of urban households, 81.4 percent (2,021 households) listed a cell phone number for the household head, and, of those, 88.1 percent (1,780 households) responded in at least one of the three rounds of the cell phone survey. Of rural households, 43.1 percent (740 households) listed a cell phone number for the household head, and, of those, 58.1 percent (430 households) responded in at least one of the three rounds.
The base weights for the cell phone survey were the probability weights from the Labor Force Survey (LFS). Sampling weights for the LFS households were calculated by,
Household weight = 1/(PEA,strata * PHH,EA)
where PEA,strata is probability of EA being selected within strata, and, PHH,EA is probability of household being selected within the EA.
To account for higher likelihood of more populated EA’s being selected, PEA,strata is calculated as,
PEA,strata = (nEA,strata * NHH,EA)/NHH,strara
where nEA,strata is number of EA’s selected within the strata, NHH,EA is the total number of households within that EA, and, NHH,strara is total number of households across all EAs in that strata.
Household selection probability was calculated using,
PHH,EA = nHH,EA /NHH,EA
To compensate as much as possible for non-response and low coverage rates, an attrition adjustment was applied. A propensity score adjustment, which uses the available characteristics of the household head from the LFS (age, gender, location, and employment sector) to calculate an aggregate probability of response, was calculated. These calculations need to be done separately for each combination of data sets, meaning the attrition calculations between the LFS and round 1 would be different than those between the LFS and round 2, which would also be different than those between the LFS and households that answered in both rounds 1 and 2. As an example the results of this analysis between the LFS and round 1 of the cell phone survey are presented in Table A1 in the appendix of the Basic Information Document. The inverse of this probability is then applied to the probability weights, therefore increasing the weight for underrepresented groups. As a final step, a post-stratification correction was applied, adjusting the weights to match known population totals at the district and urban/rural levels.
As the survey was administered by telephone, the length of the questionnaire was targeted as 20 to 25 minutes. In Round 1, the questionnaire focused on employment and labor market conditions, non-agricultural business operations, agricultural activity, food security, health responses (covering only fever and pregnancy), remittances, travel, trust and knowledge about Ebola. In Round 2, questions were added on social assistance and education on the radio, and there were small changes to the existing questions based on the results from Round 1.
Questions on earnings were revised to match the Labor Force Survey questions more closely, in particular to account for earnings that were expressed in time unit other than months, and questions on the incidence and treatment of child diarrhea were adding using identical wording to the Demographic and Health Survey (DHS). The most substantial changes were to the migration section as the Round 1 analysis found inconsistencies in the migration reporting. Details of these changes can be found in the Round 2 report. In Round 3, the agriculture, social assistance, and education sections were expanded while the trust section was dropped due to limited variation between Rounds 1 and 2.
The only questions on Ebola Virus Disease (EVD) specifically were in Round 1 and focused on whether the respondent had heard of Ebola and what were their main sources of information were. This section was placed at the end of the questionnaire in order to elicit unbiased responses in other sections, since people may be distrustful of the government especially regarding Ebola, at a time of such emergency.
Questions related directly to incidence of EVD within the household were excluded for two reasons. First EVD is a relatively rare event and the sample was unlikely to yield sufficient observations for meaningful analysis, and secondly, the respondents will be called repeatedly as part of the high frequency survey therefore it was necessary to avoid sensitive questions that may increase attrition in later rounds. The included questions were worded in such a way as to facilitate differences-in-differences comparisons. The vast majority of questions were identical in their wording to those asked during the LFS or other nationally representative surveys for which detailed data were available including the DHS, the National Public Services Survey (NPS) and the Agricultural Households Tracking Survey (AHTS).
In a few cases, the time period over which the questions were asked was shortened to make it relevant to the last few months during which the outbreak has been growing. For example, the NPS asked about remittances in the last year whereas in November 2014, respondents were asked about remittances received in the last month.
Start | End | Cycle |
---|---|---|
2014-11-12 | 2014-11-25 | Round 1 |
2015-01-22 | 2015-02-04 | Round 2 |
2015-05-01 | 2015-05-12 | Round 3 |
Name |
---|
Statistics Sierra Leone |
The survey was implemented by enumerators recruited by Statistics Sierra Leone (SSL) and Innovations for Poverty Action (IPA) from SSL's Freetown offices in three rounds. The first round was from November 12 - November 25, 2014; the second round was from January 22 - February 4, 2015; and the final round was from May 1 - May 12, 2015. The questionnaire was administered using computer assisted telephone interviewing from a CSPro application run on desktop computers. If respondents did not answer the phone after the initial attempts, a text message was sent to explain the purpose of the call. Respondents also received an incentive in the form of 50 phone units (valued up to 50 US cents) in cell phone credit for completed calls.
The datasets were cleaned and compiled by teams from Innovations for Poverty Action and the World Bank's Poverty Global Practice and Social Protection and Labor Global Practice.
Name | Affiliation |
---|---|
Kristen Himelein | World Bank |
Use of the dataset must be acknowledged using a citation which would include:
Example,
Statistics Sierra Leone. Sierra Leone High Frequency Cell Phone Survey on the Socio-Economic Impacts of Ebola 2014-2015, Ref. SLE_2014-2015_HFCPS_v01_M. Dataset downloaded from [URL] on [date].
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.
Name | Affiliation | |
---|---|---|
Kristen Himelein Kastelic | Poverty Global Practive, World Bank | khimelein@worldbank.org |
Nina Rosas Raffo | Social Protection and Labor Global Practice, World Bank | nrosas@worldbank.org |
DDI_SLE_2014-2015_HFCPS_v01_M_WB
Name | Affiliation | Role |
---|---|---|
Development Data Group | World Bank | Study documentation |
2016-10-03
v01 (October 2016)
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