Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Nigeria

Nigeria: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value was 155.61 million million SLC in 2023. ◆ Volatile

Latest (2023)
155.61 million million SLC
Change on year
down 1.5%
World rank
3rd
of 179 countries
All-time high
157.94 million million SLC
in 2022
All-time low
1.13 million million SLC
in 1995
Years of data
29
1995–2023

Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Nigeria, 1995–2023

050.0M100.0M150.0M1995200920231995: 1.1M million SLC1996: 1.5M million SLC1997: 1.7M million SLC1998: 2.0M million SLC1999: 2.2M million SLC2000: 2.4M million SLC2001: 3.4M million SLC2002: 4.2M million SLC2003: 4.8M million SLC2004: 7.8M million SLC2005: 9.7M million SLC2006: 10.2M million SLC2007: 12.2M million SLC2008: 14.3M million SLC2009: 16.9M million SLC2010: 17.5M million SLC2011: 21.8M million SLC2012: 23.5M million SLC2013: 25.8M million SLC2014: 28.6M million SLC2015: 31.2M million SLC2016: 37.4M million SLC2017: 44.7M million SLC2018: 60.3M million SLC2019: 82.0M million SLC2020: 109.1M million SLC2021: 147.1M million SLC2022: 157.9M million SLC2023: 155.6M million SLC

Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.

Analysis

Nigeria recorded 155.61 million million SLC for net capital stocks (agriculture, forestry and fishing) — value in 2023.

The figure is down 1.5% on the previous year and up 502.4% over ten years.

Over the whole period, net capital stocks (agriculture, forestry and fishing) — value in Nigeria peaked at 157.94 million million SLC in 2022 and was at its lowest, 1.13 million million SLC, in 1995.

That places Nigeria 3rd out of 179 countries with data for 2023, putting it in the top 10%.

The series is highly variable year to year, so single readings are best treated with caution.

Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Nigeria, year by year

Annual values for Net Capital Stocks (Agriculture, Forestry and Fishing) — Value Standard Local Currency in Nigeria, 1995 to 2023.
Year million SLC Change
1995 1.13 million million SLC
1996 1.46 million million SLC +28.8%
1997 1.66 million million SLC +13.8%
1998 1.97 million million SLC +19.0%
1999 2.16 million million SLC +9.7%
2000 2.41 million million SLC +11.2%
2001 3.37 million million SLC +39.9%
2002 4.24 million million SLC +25.9%
2003 4.83 million million SLC +13.8%
2004 7.75 million million SLC +60.7%
2005 9.68 million million SLC +24.9%
2006 10.16 million million SLC +4.9%
2007 12.18 million million SLC +19.9%
2008 14.34 million million SLC +17.8%
2009 16.90 million million SLC +17.9%
2010 17.53 million million SLC +3.7%
2011 21.80 million million SLC +24.3%
2012 23.51 million million SLC +7.8%
2013 25.83 million million SLC +9.9%
2014 28.57 million million SLC +10.6%
2015 31.20 million million SLC +9.2%
2016 37.38 million million SLC +19.8%
2017 44.71 million million SLC +19.6%
2018 60.34 million million SLC +35.0%
2019 82.02 million million SLC +35.9%
2020 109.08 million million SLC +33.0%
2021 147.10 million million SLC +34.9%
2022 157.94 million million SLC +7.4%
2023 155.61 million million SLC -1.5%

Averages by decade

DecadeAverage LowestHighest Years
1990s 1.68 million million SLC 1.13 million million SLC 2.16 million million SLC 5
2000s 8.59 million million SLC 2.41 million million SLC 16.90 million million SLC 10
2010s 37.29 million million SLC 17.53 million million SLC 82.02 million million SLC 10
2020s 142.43 million million SLC 109.08 million million SLC 157.94 million million SLC 4

Countries ranked near Nigeria

  1. 1 Côte d'Ivoire 7.28 million million SLC compare
  2. 1 Indonesia 3.81 billion million SLC compare
  3. 1 Iran (Islamic Republic of) 15.40 billion million SLC compare
  4. 2 Uzbekistan 157.18 million million SLC compare
  5. 2 Viet Nam 1.50 billion million SLC compare
  6. 3 Cabo Verde 19,616 million SLC compare
  7. 3 Lao People's Democratic Republic 36.12 million million SLC compare
  8. 4 Colombia 82.95 million million SLC compare
  9. 4 United Republic of Tanzania 29.20 million million SLC compare
  10. 5 Republic of Korea 80.65 million million SLC compare
  11. 5 Syrian Arab Republic 13.90 million million SLC compare
  12. 6 Democratic Republic of the Congo 6.11 million million SLC compare
  13. 6 Somalia 78.92 million million SLC compare

See the full ranking of 192 places →

More environment data for Nigeria

All data for Nigeria →

Frequently asked questions

What is net capital stocks (agriculture, forestry and fishing) — value in Nigeria?
Net capital stocks (agriculture, forestry and fishing) — value in Nigeria was 155.61 million million SLC in 2023, according to Food and Agriculture Organization of the United Nations.
What is the highest net capital stocks (agriculture, forestry and fishing) — value recorded in Nigeria?
The highest recorded value was 157.94 million million SLC in 2022.
What is the lowest net capital stocks (agriculture, forestry and fishing) — value recorded in Nigeria?
The lowest recorded value was 1.13 million million SLC in 1995.
How does Nigeria rank for net capital stocks (agriculture, forestry and fishing) — value?
Nigeria ranks 3rd out of 179 countries with data for 2023.
Is net capital stocks (agriculture, forestry and fishing) — value rising or falling in Nigeria?
Over the last ten years it is up 502.4%. The long-run trend across the full record is volatile.
Where does this Nigeria data come from?
The figures come from Food and Agriculture Organization of the United Nations, published as part of Net Capital Stocks (Agriculture, Forestry and Fishing) — Value Standard Local Currency. Statizoid updates them automatically from the source API.

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Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Nigeria. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 12 September 2026, from https://environment.statizoid.com/stat/net-capital-stocks-agriculture-forestry-and-fishing-value-standard-local-currency/nigeria/

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About this data

Indicator
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value Standard Local Currency
Unit
million SLC
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
192 places, 5,493 data points, 1995–2023
Last refreshed

As part of the FAO Agriculture Capital Stock (ACS) database, the Statistics Division of FAO publishes country-by-country data on physical investment in agriculture, forestry and fishing as measured by the System of National Accounts (SNA) concept of Gross Fixed Capital Formation (GFCF). Additional variables included in the ACS are Net and Gross Capital Stock, Consumption of Fixed Capital, the Agriculture Investment ratio, and the Gross Fixed Capital Formation Agriculture Orientation Index. The FAO Agriculture Capital Stock Database is an analytical database: whenever available, the database integrates official National Accounts data harvested from the UNSD National Accounts Main Aggregates Database (UNSD AMA) and the OECD Annual National Accounts Database (OECD ANA). The database is further supplemented by OECD Structural Analysis database (OECD STAN) and, in a few cases, data from country’s statistics websites. If the full set of official data is not available for any specific country, imputation methods are applied to obtain estimates over the complete time series. Many data points in ACS are estimated and are flagged as such; they do not represent official submissions by Member Countries. With a view of producing internationally comparable net capital stock estimates, the Perpetual Inventory Method (PIM) with a constant geometric depreciation rate is employed to impute missing data. The Perpetual Inventory Method is a well-established economic model to calculate Net Capital Stocks (NCS) and Consumption of Fixed Capital (CFC) from time series of Gross Fixed Capital Formation (GFCF). Specifically, annual measures of the NCS are obtained from cumulating historical series on physical investment flows and deducting the part of assets that are depreciated (the Consumption of Fixed Capital that occurs in every period). In order to implement the PIM, long time series on aggregate GFCF in agriculture, forestry and fishing is required.An attempt is made to rely as much as possible on National Accounts data published by the OECD and UNSD. When country data are partially or fully missing, econometric techniques to impute missing observations are employed. Depending on the pattern of data missingness for the countries, different imputation methods are applied (from among the ARIMAX, PANEL regression, and OLS approaches) for the data series from 1995 to 2022. The values of Agriculture Capital Stock related indicators for 2023, including Agriculture Investment Ratio, Agriculture Orientation Index, Net Capital Stock, Gross Fixed Capital Formation and Consumption of Fixed Capital, are estimated using the Holt-Winters (HW) method (Cipra et al., 1995). The HW method is an exponential smoothing method for forecasting the annual values of economic variables. In this context, the HW method relies on existing (historical) values of the Agriculture Capital Stock. The predicted value is an extrapolation of the historical values to the specified target date, which extends the timeline without considering seasonality in the annual series.All data series in the database are provided both in national currencies and in US dollars as well as in current prices and constant prices with base year 2015.