NGA-NBS-CVN-2017-v1.0
Conflict and Violence in Nigeria 2017
First Round
CVN 2017
No Translation
Name | Country code |
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Nigeria | NGA |
Other Household Survey [hh/oth]
The Conflict and Violence in Nigeria Survey is the first round of a telephone survey using a sub-set of the sample of GHS (General Household Survey) households which started in 2017. It is designed by World Bank, and implemented by is a collaborative effort of the National Bureau of Statistics, and Poverty and LSMS teams of the World Bank. The first round focused on conflict exposure in conflict affected regions. This first round of the telephone interview had 717 completed interviews with the following geographical distribution: 175 interviews in the North East, 276 in North Central and 266 in South South.
This survey focuses on conflict in North East, North Central, and South South Nigeria. Each of these three geopolitical zones has a unique history and context of conflict.
North East Nigeria comprises six states: Adamawa, Bauchi, Borno, Gombe, Taraba, and Yobe.
North Central Nigeria consists of the states of Benue, Kogi, Kwara, Nasarawa, Niger, and Plateau, as well as the Federal Capital Territory (FCT).
South South Nigeria is made up of Akwa Ibom, Bayelsa, Cross River, Delta, Edo, and Rivers states.
This document reports on the prevalence of conflict and violence, and how these affect Nigerian households, between 2010 and 2017. The report takes into account conflict- and violence-related events of all types, independent of the cause or perpetrator of the event. This approach seeks to provide a better understanding of the extent to which households are affected by violence and conflict, as well as their perceived risk of exposure to conflict. It assumes that the economic and social impacts of violence are meaningful no matter what the cause. The report also provides context on the perceived causes and perpetrators of the conflict and violence. This data can be useful in informing response to and prevention of these events.This report seeks to explain the prevalence of conflict and violence, and how these affect Nigerian households, between 2010 and 2017. The report takes into account conflict- and violence-related events of all types, independent of the cause or perpetrator of the event. This approach seeks to provide a better understanding of the extent to which households are affected by violence and conflict.
Conflict in Nigeria
· Conflict was higher in 2016 than in 2010 in each of the three zones
· Households in North East Nigeria are the most exposed to all types of conflict events
· Each of the three geopolitical zones surveyed has a distinct principal cause of conflict
· A small minority of conflict-affected households in any of Nigeria's geopolitical zones receive any form of assistance
Key Lessons
· Overall levels of conflict have risen between 2010 and 2016
· Sustained conflict is known to be both caused by and contribute to poverty; however, according to our findings wealth does not protect households from exposure to conflict and violence in Nigeria
· Many conflict events are never reported to authorities; engaging community and religious leaders in surveillance may improve rates of reporting events and improve overall understanding of the changing context of conflict and violence across Nigeria
· Only a small minority of conflict-affected households receive any type of assistance in support of their recovery - increased reporting and a stronger response system may aid in post-conflict rehabilitation
· Phone-based data collection can improve understanding of conflict and violence, especially in areas where insecurity prevents face-to-face access to community members
Sample survey data [ssd]
Individuals, Households and Communities
Version 1.0(April, 2018).
2018-01-17
Version 1.0(April, 2018). The first version to be released.
The questionnaire is divided into sections with a household roster. Information on Conflict and Violence from the year 2010 to 2017, Causes and perpetrators.
Topic | Vocabulary |
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Environment | World Bank |
Gender | World Bank |
Resettlement | World Bank |
Fragile & Conflict-affected States | World Bank |
Zones States Local Government Areas (LGAs) Households
The Survey covered all household members. The questionnaire was administered to only one respondent per household - most often a male household head.
Name | Affiliation |
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National Bureau of Statistics (NBS) | Federal Government of Nigeria (FGN) |
World Bank | Federal Government of Nigeria (FGN) |
Name | Affiliation | Role |
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World Bank | IDA | Technical Assistance in Questionnaire design, Sampling methodology, Data Processing and Analysis |
National Bureau of Statistics (NBS) | Federal Government of Nigeria(FGN) | Technical Assistance in Questionnaire design, Sampling methodology, Data Processing and Analysis |
Name | Abbreviation | Role |
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World Bank | WB | Funding |
The survey was a telephone based survey conducted between March 22 and May 10th, 2017. The interview was the first round of a telephone survey using a sub-set of the sample of GHS (General Household Survey) households. The first round was focused on conflict exposure, while the second round not discussed in this report focused on food insecurity in conflict affected regions. This first round of the telephone interview had 717 completed interviews with the following geographical distribution: 175 interviews in the North East, 276 in North Central and 266 in South South.
In the three conflict affected geographical zones comprising of 16 states of Nigeria, households from LGS's that had high conflict exposure were oversampled chosen for a pilot sample, conducted before the telephone surveys. These LGS's were chosen based on the following criteria: The oversampled LGS's needed to have over 10 conflict events during 2012-14 recorded in the Armed Conflict Location & Event Data Project (ACLED) database.
The first round of the telephone survey (which took place after the pilot), first attempted to reach 742 households from the GHS panel, of which 529 could be reached and interviewed. The rest did not have phone numbers or functioning phone numbers (only 2.7 per cent refused to answer). In order to increase the sample size to a level that was considered adequate for the survey, an additional 288 replacement households were included in the sample also from the GHS panel. Out of these replacement households 188 could be interviewed. Therefore altogether 1030 households were attempted to be reached, with a final sample size of 717 completed interviews.
Conflict affected areas were oversampled in order to have a large enough sample of individuals that in fact experienced conflict events in order to shed light on the type of events that have happened. A random sample of the zones might have given too small sample of conflict affected households and therefore restricted the analysis of the various types of conflict events. Due to the oversampling however, the sample drawn was not representative at the level of the geographical zone, as is the case in the GHS. Therefore in the analysis we use probability weights that adjust for the propensity of being in a conflict affected LGA in order to ensure that the sample is representative at the level of the geographical zone.
During the second round of the survey 582 of the 717 households were re-interviewed on food security related issues (only the 717 were attempted to be reached). The data on the second telephone interview on food security as well as issues related to attrition in reaching the households are discussed in a separate report.
No deviation
The first round of the telephone survey (which took place after the pilot), first attempted to reach 742 households from the GHS panel, of which 529 could be reached and interviewed. The rest did not have phone numbers or functioning phone numbers (only 2.7 per cent refused to answer). In order to increase the sample size to a level that was considered adequate for the survey, an additional 288 replacement households were included in the sample also from the GHS panel. Out of these replacement households 188 could be interviewed. Therefore altogether 1030 households were attempted to be reached, with a final sample size of 717 completed interviews.
The response rate is 96%
In the analysis, probability weights that adjust for the propensity of being in a conflict affected LGA in order to ensure that the sample is representative at the level of the geographical zone was used.
The questionnaire is divided into sections with a household roster. Information on Conflict and Violence from the year 2010 to 2017, Causes and perpetrators.
Data collection on mobile devices provided many advantages. As data quality was reviewed during the data collection and supervision, strong rigor was ensured for the survey data. The double data entry steps were eliminated and the time needed to process the data after fieldwork was reduced
Start | End | Cycle |
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2017-03-22 | 2017-05-10 | 18 Days |
Name | Affiliation | Abbreviation |
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National Bureau of Statistics | Federal Government of Nigeria(FGN) | NBS |
World Bank | IDA | WB |
The survey was a telephone based survey comprising of 3 Interviewers(out-sourced) and a Supervisors from the National Bureau of Statistics. The role of the supervisor was to a supervisor was engaged to monitor the data collection effort and also to verify responses before uploading them to the server.
NBS in collaboration with the World Bank carried out the survey using mobile phones and captured data in tablet, which was later uploaded to the server after verification. Both teams worked together to design and program the instrument in Survey Solutions, and put in place two layers of quality control measures. The first layer incorporated measures into the programing to ensure data accuracy, and metadata was followed closely to flag questionable entries. In the second layer, a supervisor was engaged to monitor the data collection effort and also to verify responses before uploading them to the server.
The data collection effort took three enumerators and a supervisor, who went through a two-day training in survey protocols, data capturing and uploading, and the questionnaire itself. The instrument was tested in house before the data collection started. The entire data collection process including the training took two and half weeks.
Data was analyzed using descriptive statistics in Stata 15. All data analysis was tracked using comprehensive do files to ensure reproducibility. All statistics presented in this report have been adjusted with probability weights, when possible, to be representative at the level of the geopolitical zone.
Demographics for each geopolitical zone were analyzed based on the complete GHS 2016 dataset.
No Sampling Error
Limitations
Recall Bias
In the pilot data collection, respondents were asked to report on conflict events that had taken place in their family and their community over the last six years. This extremely long recall period must be considered when drawing inferences from the data. People are likely to under-report less severe (and therefore less memorable) events, particularly those that happened to community members in larger communities. Respondents are also more likely to recall events that happened to family members than those that happened to community members. Other biases may also be at play - for example, those who have been most highly affected by conflict over the last six years may have moved to another community. These factors demonstrate the importance of implementing a regular data collection schedule, which would allow far more accurate data to be collected.
Sampling Bias
The GHS is a panel survey taking place over multiple rounds through a period of time. Therefore, households that are more mobile or households that are nomadic are less likely to be represented in this sample. This may be particularly relevant in circumstances where nomadic groups are named as perpetrators of conflict events.
Power Dynamics
There are some disadvantages to the phone system, and for this reason it should be supplemented by additional types of data collection wherever possible. In a mobile phone survey, the respondent is the person who owns a mobile phone. In many areas, particularly those highly affected by poverty and those located in rural areas, only one family member owns a mobile phone. This is generally the household head, who is most likely male. Furthermore, in many of these communities, women are not allowed to have access to mobile phones and are forbidden from speaking to outsiders, which can prohibit mobile phone-based data collection.
Gender Dynamics
The questionnaire was administered to only one respondent per household - most often a male household head. This means that crimes that carry stigma, especially sexual violence, are less likely to be reported. In this dataset, no sexual assault was reported despite data collected elsewhere that indicate that rape was used as a weapon by Boko Haram and elsewhere. This also means that violence that affects members of the household with less power (such as women, children, and employees), is less likely to be reported. This may be particularly important when considering violence not related to ongoing external conflict, such as domestic violence.
Name | Affiliation | URL | |
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National Bureau of Statistics (NBS) | Federal Government of Nigeria (FGN) | www.nigerianstat.gov.ng | feedback@nigerianstat.gov.ng |
Is signing of a confidentiality declaration required? | Confidentiality declaration text |
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yes | The confidentiality of the individual respondent is protected by law (Statistical Act 2007) This is published in the Official Gazette of the Federal republic of Nigeria No. 60 vol. 94 of 11th June 2007. See section 26 para.2. Punitive measures for breeches of confidentiality are outlined in section 28 of the same Act. |
A comprehensive data access policy is been developed by NBS, however section 27 of the Statistical Act 2007 outlines the data access obligation of data producers which includes the realease of properly anonymized micro data.
National Bureau of Statistics, Nigeria, Conflict and Violence in Nigeria-v1.0
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.
© NBS 2018
Name | Affiliation | URL | |
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Dr. Yemi Kale (Statistician-General) | National Bureau of Statistics (NBS) | yemikale@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
Mr. M Abul Kalam Azad | World Bank | mazad@worldbank.org | |
Mr. Fafunmi E.A (Head, ICT Department) | National Bureau of Statistics (NBS) | biyifafunmi@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
Mr. Esiri Ojo | National Bureau of Statistics (NBS) | eojo@nigerianstat.gov.ng | http://www.nigerianstat.gov.ng |
Nemi Okujagu | nemiere@gmail.com | ||
Irenonse Victoria (Data Archivist) | National Bureau of Statistics (NBS) | irenonsevic@yahoo.com | http://www.nigerianstat.gov.ng |
Oke Florence | National Bureau of Statistics (NBS) | Okeoriginal@gmail.com | http://www.nigerianstat.gov.ng |
DDI-NGA-NBS-CVN-2017-v1.0
Name | Abbreviation | Affiliation | Role |
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National Bureau of Statistics | NBS | Federal Government of Nigeria (FGN) | Metadata Producer |
2018-04-10
Version 1.0 (April, 2018).