GDP from Manufacturing in Nigeria increased to 1651873.40 NGN Million in the third quarter of 2024 from 1547525.55 NGN Million in the second quarter of 2024. This dataset provides the latest reported value for - Nigeria Gdp From Manufacturing - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Nigeria NG: GDP: % of GDP: Gross Value Added: Industry data was reported at 22.320 % in 2017. This records an increase from the previous number of 18.173 % for 2016. Nigeria NG: GDP: % of GDP: Gross Value Added: Industry data is updated yearly, averaging 43.485 % from Dec 1981 (Median) to 2017, with 37 observations. The data reached an all-time high of 104.637 % in 1981 and a record low of 18.173 % in 2016. Nigeria NG: GDP: % of GDP: Gross Value Added: Industry data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Gross Domestic Product: Share of GDP. Industry corresponds to ISIC divisions 10-45 and includes manufacturing (ISIC divisions 15-37). It comprises value added in mining, manufacturing (also reported as a separate subgroup), construction, electricity, water, and gas. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3 or 4.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted average; Note: Data for OECD countries are based on ISIC, revision 4.

Nigeria NG: GDP: Growth: Gross Value Added: Industry: Manufacturing data was reported at -0.212 % in 2017. This records an increase from the previous number of -4.318 % for 2016. Nigeria NG: GDP: Growth: Gross Value Added: Industry: Manufacturing data is updated yearly, averaging 4.524 % from Dec 1982 (Median) to 2017, with 36 observations. The data reached an all-time high of 39.050 % in 1985 and a record low of -33.827 % in 1983. Nigeria NG: GDP: Growth: Gross Value Added: Industry: Manufacturing data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank: Gross Domestic Product: Annual Growth Rate. Annual growth rate for manufacturing value added based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted Average; Note: Data for OECD countries are based on ISIC, revision 4.

Nigeria NG: GDP: Real: Gross Value Added at Factor Cost: Industry: Manufacturing data was reported at 6,288,896.797 NGN mn in 2017. This records a decrease from the previous number of 6,302,232.447 NGN mn for 2016. Nigeria NG: GDP: Real: Gross Value Added at Factor Cost: Industry: Manufacturing data is updated yearly, averaging 1,758,605.717 NGN mn from Dec 1981 (Median) to 2017, with 37 observations. The data reached an all-time high of 6,684,217.739 NGN mn in 2014 and a record low of 1,018,906.865 NGN mn in 1984. Nigeria NG: GDP: Real: Gross Value Added at Factor Cost: Industry: Manufacturing data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank: Gross Domestic Product: Real. Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in constant local currency.; ; World Bank national accounts data, and OECD National Accounts data files.; ; Note: Data for OECD countries are based on ISIC, revision 4.

Nigeria GDP: Basic Prices: 2010p: Industry: Mfg: Other Manufacturing data was reported at 282,946.706 NGN mn in 2017. This records a decrease from the previous number of 304,222.484 NGN mn for 2016. Nigeria GDP: Basic Prices: 2010p: Industry: Mfg: Other Manufacturing data is updated yearly, averaging 112,271.907 NGN mn from Dec 1981 (Median) to 2017, with 37 observations. The data reached an all-time high of 367,840.934 NGN mn in 2014 and a record low of 108,663.941 NGN mn in 1984. Nigeria GDP: Basic Prices: 2010p: Industry: Mfg: Other Manufacturing data remains active status in CEIC and is reported by National Bureau of Statistics of the Federal Republic of Nigeria. The data is categorized under Global Database’s Nigeria – Table NG.A010: GDP: by Industry: 2010 Price: Annual.

Nigeria GDP: Basic Prices: Industry: Manufacturing (Mfg) data was reported at 10,881,835.710 NGN mn in Dec 2024. This records an increase from the previous number of 10,172,988.397 NGN mn for Sep 2024. Nigeria GDP: Basic Prices: Industry: Manufacturing (Mfg) data is updated quarterly, averaging 2,479,374.420 NGN mn from Mar 2010 (Median) to Dec 2024, with 60 observations. The data reached an all-time high of 10,881,835.710 NGN mn in Dec 2024 and a record low of 875,408.171 NGN mn in Mar 2010. Nigeria GDP: Basic Prices: Industry: Manufacturing (Mfg) data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under Global Database’s Nigeria – Table NG.A005: SNA 2008: GDP: by Industry: Current Price.

Abstract

The main objectives of the 2018/19 NLSS are: i) to provide critical information for production of a wide range of socio-economic and demographic indicators, including for benchmarking and monitoring of SDGs; ii) to monitor progress in population’s welfare; iii) to provide statistical evidence and measure the impact on households of current and anticipated government policies. In addition, the 2018/19 NLSS could be utilized to improve other non-survey statistical information, e.g. to determine and calibrate the contribution of final consumption expenditures of households to GDP; to update the weights and determine the basket for the national Consumer Price Index (CPI); to improve the methodology and dissemination of micro-economic and welfare statistics in Nigeria.

The 2018/19 NLSS collected a comprehensive and diverse set of socio-economic and demographic data pertaining to the basic needs and conditions under which households live on a day to day basis. The 2018/19 NLSS questionnaire includes wide-ranging modules, covering demographic indicators, education, health, labour, expenditures on food and non-food goods, non-farm enterprises, household assets and durables, access to safety nets, housing conditions, economic shocks, exposure to crime and farm production indicators.

Geographic coverage

National coverage

Analysis unit

• Households
• Individuals
• Communities

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The 2018/19 NLSS sample is designed to provide representative estimates for the 36 states and the Federal Capital Territory (FCT), Abuja. By extension. The sample is also representative at the national and zonal levels. Although the sample is not explicitly stratified by urban and rural areas, it is possible to obtain urban and rural estimates from the NLSS data at the national level. At all stages, the relative proportion of urban and rural EAs as has been maintained.

Before designing the sample for the 2018/19 NLSS, the results from the 2009/10 HNLSS were analysed to extract the sampling properties (variance, design effect, etc.) and estimate the required sample size to reach a desired precision for poverty estimates in the 2018/19 NLSS.

EA SELECTION: The sampling frame for the 2018/19 NLSS was based on the national master sample developed by the NBS, referred to as the NISH2 (Nigeria Integrated Survey of Households 2). This master sample was based on the enumeration areas (EAs) defined for the 2006 Nigeria Census Housing and Population conducted by National Population Commission (NPopC). The NISH2 was developed by the NBS to use as a frame for surveys with state-level domains. NISH2 EAs were drawn from another master sample that NBS developed for surveys with LGA-level domains (referred to as the “LGA master sample”). The NISH2 contains 200 EAs per state composed of 20 replicates of 10 sample EAs for each state, selected systematically from the full LGA master sample. Since the 2018/19 NLSS required domains at the state-level, the NISH2 served as the sampling frame for the survey.

Since the NISH2 is composed of state-level replicates of 10 sample EAs, a total of 6 replicates were selected from the NISH2 for each state to provide a total sample of 60 EAs per state. The 6 replicates selected for the 2018/19 NLSS in each state were selected using random systematic sampling. This sampling procedure provides a similar distribution of the sample EAs within each state as if one systematic sample of 60 EAs had been selected directly from the census frame of EAs.

A fresh listing of households was conducted in the EAs selected for the 2018/19 NLSS. Throughout the course of the listing, 139 of the selected EAs (or about 6%) were not able to be listed by the field teams. The primary reason the teams were not able to conduct the listing in these EAs was due to security issues in the country. The fieldwork period of the 2018/19 NLSS saw events related to the insurgency in the north east of the country, clashes between farmers and herdsman, and roving groups of bandits. These events made it impossible for the interviewers to visit the EAs in the villages and areas affected by these conflict events. In addition to security issues, some EAs had been demolished or abandoned since the 2006 census was conducted. In order to not compromise the sample size and thus the statistical power of the estimates, it was decided to replace these 139 EAs. Additional EAs from the same state and sector were randomly selected from the remaining NISH2 EAs to replace each EA that could not be listed by the field teams. This necessary exclusion of conflict affected areas implies that the sample is representative of areas of Nigeria that were accessible during the 2018/19 NLSS fieldwork period. The sample will not reflect conditions in areas that were undergoing conflict at that time. This compromise was necessary to ensure the safety of interviewers.

HOUSEHOLD SELECTION: Following the listing, the 10 households to be interviewed were selected from the listed households. These households were selected systemically after sorting by the order in which the households were listed. This systematic sampling helped to ensure that the selected households were well dispersed across the EA and thereby limit the potential for clustering of the selected households within an EA.

Occasionally, interviewers would encounter selected households that were not able to be interviewed (e.g. due to migration, refusal, etc.). In order to preserve the sample size and statistical power, households that could not be interviewed were replaced with an additional randomly selected household from the EA. Replacement households had to be requested by the field teams on a case-by-case basis and the replacement household was sent by the CAPI managers from NBS headquarters. Interviewers were required to submit a record for each household that was replaced, and justification given for their replacement. These replaced households are included in the disseminated data. However, replacements were relatively rare with only 2% of sampled households not able to be interviewed and replaced.

Sampling deviation

Although a sample was initially drawn for Borno state, the ongoing insurgency in the state presented severe challenges in conducting the survey there. The situation in the state made it impossible for the field teams to reach large areas of the state without compromising their safety. Given this limitation it was clear that a representative sample for Borno was not possible. However, it was decided to proceed with conducting the survey in areas that the teams could access in order to collect some information on the parts of the state that were accessible.

The limited area that field staff could safely operate in in Borno necessitated an alternative sample selection process from the other states. The EA selection occurred in several stages. Initially, an attempt was made to limit the frame to selected LGAs that were considered accessible. However, after selection of the EAs from the identified LGAs, it was reported by the NBS listing teams that a large share of the selected EAs were not safe for them to visit. Therefore, an alternative approach was adopted that would better ensure the safety of the field team but compromise further the representativeness of the sample. First, the list of 788 EAs in the LGA master sample for Borno were reviewed by NBS staff in Borno and the EAs they deemed accessible were identified. The team identified 359 EAs (46%) that were accessible. These 359 EAs served as the frame for the Borno sample and 60 EAs were randomly selected from this frame. However, throughout the course of the NLSS fieldwork, additional insurgency related events occurred which resulted in 7 of the 60 EAs being inaccessible when they were to be visited. Unlike for the main sample, these EAs were not replaced. Therefore, 53 EAs were ultimately covered from the Borno sample. The listing and household selection process that followed was the same as for the rest of the states.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Two sets of questionnaires – household and community – were used to collect information in the NLSS2018/19. The Household Questionnaire was administered to all households in the sample. The Community Questionnaire was administered to the community to collect information on the socio-economic indicators of the enumeration areas where the sample households reside.

Household Questionnaire: The Household Questionnaire provides information on demographics; education; health; labour; food and non-food expenditure; household nonfarm income-generating activities; food security and shocks; safety nets; housing conditions; assets; information and communication technology; agriculture and land tenure; and other sources of household income.

Community Questionnaire: The Community Questionnaire solicits information on access to transported and infrastructure; community organizations; resource management; changes in the community; key events; community needs, actions and achievements; and local retail price information.

Cleaning operations

CAPI: The 2018/19 NLSS was conducted using the Survey Solutions Computer Assisted Person Interview (CAPI) platform. The Survey Solutions software was developed and maintained by the Development Economics Data Group (DECDG) at the World Bank. Each interviewer and supervisor was given a tablet

Nigeria NG: GDP: Gross Value Added at Factor Cost: Industry: Manufacturing data was reported at 10,044,484.949 NGN mn in 2017. This records an increase from the previous number of 8,903,236.284 NGN mn for 2016. Nigeria NG: GDP: Gross Value Added at Factor Cost: Industry: Manufacturing data is updated yearly, averaging 713,821.650 NGN mn from Dec 1981 (Median) to 2017, with 37 observations. The data reached an all-time high of 10,044,484.949 NGN mn in 2017 and a record low of 26,885.964 NGN mn in 1981. Nigeria NG: GDP: Gross Value Added at Factor Cost: Industry: Manufacturing data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank: Gross Domestic Product: Nominal. Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current local currency.; ; World Bank national accounts data, and OECD National Accounts data files.; ; Note: Data for OECD countries are based on ISIC, revision 4.

Nigeria NG: GDP: USD: Gross Value Added at Factor Cost: Industry: Manufacturing data was reported at 32.848 USD bn in 2017. This records a decrease from the previous number of 35.123 USD bn for 2016. Nigeria NG: GDP: USD: Gross Value Added at Factor Cost: Industry: Manufacturing data is updated yearly, averaging 11.408 USD bn from Dec 1981 (Median) to 2017, with 37 observations. The data reached an all-time high of 54.779 USD bn in 2014 and a record low of 4.884 USD bn in 1993. Nigeria NG: GDP: USD: Gross Value Added at Factor Cost: Industry: Manufacturing data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Gross Domestic Product: Nominal. Manufacturing refers to industries belonging to ISIC divisions 15-37. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in current U.S. dollars.; ; World Bank national accounts data, and OECD National Accounts data files.; Gap-filled total; Note: Data for OECD countries are based on ISIC, revision 4.

Nigeria NG: GDP: Growth: Gross Value Added: Industry data was reported at 2.186 % in 2017. This records an increase from the previous number of -8.850 % for 2016. Nigeria NG: GDP: Growth: Gross Value Added: Industry data is updated yearly, averaging 1.893 % from Dec 1982 (Median) to 2017, with 36 observations. The data reached an all-time high of 19.286 % in 1990 and a record low of -15.544 % in 1983. Nigeria NG: GDP: Growth: Gross Value Added: Industry data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank: Gross Domestic Product: Annual Growth Rate. Annual growth rate for industrial value added based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. Industry corresponds to ISIC divisions 10-45 and includes manufacturing (ISIC divisions 15-37). It comprises value added in mining, manufacturing (also reported as a separate subgroup), construction, electricity, water, and gas. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3.; ; World Bank national accounts data, and OECD National Accounts data files.; Weighted Average; Note: Data for OECD countries are based on ISIC, revision 4.

Nigeria NG: GDP: 2015 Price: USD: Gross Value Added Per Worker: Industry data was reported at 0.005 USD mn in 2023. This records a decrease from the previous number of 0.005 USD mn for 2022. Nigeria NG: GDP: 2015 Price: USD: Gross Value Added Per Worker: Industry data is updated yearly, averaging 0.011 USD mn from Dec 1991 (Median) to 2023, with 33 observations. The data reached an all-time high of 0.014 USD mn in 1992 and a record low of 0.005 USD mn in 2023. Nigeria NG: GDP: 2015 Price: USD: Gross Value Added Per Worker: Industry data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Gross Domestic Product: Real. Value added per worker is a measure of labor productivity—value added per unit of input. Value added denotes the net output of a sector after adding up all outputs and subtracting intermediate inputs. Data are in constant 2015 U.S. dollars. Industry corresponds to the International Standard Industrial Classification (ISIC) tabulation categories C-F (revision 3) or tabulation categories B-F (revision 4), and includes mining and quarrying (including oil production), manufacturing, construction, and public utilities (electricity, gas, and water).;Derived using World Bank national accounts data and OECD National Accounts data files, and employment data from International Labour Organization, ILOSTAT database.;Weighted average;

Nigeria NG: GDP: 2010 Price: USD: Gross Value Added at Factor Cost: Industry data was reported at 101.427 USD bn in 2017. This records an increase from the previous number of 99.257 USD bn for 2016. Nigeria NG: GDP: 2010 Price: USD: Gross Value Added at Factor Cost: Industry data is updated yearly, averaging 60.930 USD bn from Dec 1981 (Median) to 2017, with 37 observations. The data reached an all-time high of 111.393 USD bn in 2014 and a record low of 39.162 USD bn in 1983. Nigeria NG: GDP: 2010 Price: USD: Gross Value Added at Factor Cost: Industry data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank: Gross Domestic Product: Real. Industry corresponds to ISIC divisions 10-45 and includes manufacturing (ISIC divisions 15-37). It comprises value added in mining, manufacturing (also reported as a separate subgroup), construction, electricity, water, and gas. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Data are in constant 2010 U.S. dollars.; ; World Bank national accounts data, and OECD National Accounts data files.; Gap-filled total; Note: Data for OECD countries are based on ISIC, revision 4.

Nigeria NG: GDP: 2010 Price: USD: Gross Value Added Per Worker: Industry data was reported at 0.016 USD mn in 2017. This records an increase from the previous number of 0.016 USD mn for 2016. Nigeria NG: GDP: 2010 Price: USD: Gross Value Added Per Worker: Industry data is updated yearly, averaging 0.020 USD mn from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 0.024 USD mn in 2005 and a record low of 0.014 USD mn in 2010. Nigeria NG: GDP: 2010 Price: USD: Gross Value Added Per Worker: Industry data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank: Gross Domestic Product: Real. Value added per worker is a measure of labor productivity—value added per unit of input. Value added denotes the net output of a sector after adding up all outputs and subtracting intermediate inputs. Data are in constant 2010 U.S. dollars. Industry corresponds to the International Standard Industrial Classification (ISIC) tabulation categories C-F (revision 3) or tabulation categories B-F (revision 4), and includes mining and quarrying (including oil production), manufacturing, construction, and public utilities (electricity, gas, and water).; ; Derived using World Bank national accounts data and OECD National Accounts data files, and employment data from International Labour Organization, ILOSTAT database.; Weighted Average;