Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Nigeria

Nigeria: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 19.38 % in 2023. ▲ Rising

Latest (2023)
19.38 %
Change on year
up 9.9%
World rank
43rd
of 181 countries
All-time high
19.38 %
in 2023
All-time low
15.84 %
in 1999
Years of data
29
1995–2023

Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Nigeria, 1995–2023

051015201995200920231995: 16 %1996: 16.1 %1997: 16 %1998: 16 %1999: 15.8 %2000: 16 %2001: 16.2 %2002: 16.1 %2003: 16.3 %2004: 16.6 %2005: 16.8 %2006: 16.9 %2007: 17 %2008: 17.2 %2009: 17.5 %2010: 17.8 %2011: 17.9 %2012: 17.9 %2013: 18.2 %2014: 18.4 %2015: 18.3 %2016: 18 %2017: 17.9 %2018: 17.8 %2019: 17.8 %2020: 17.5 %2021: 17.6 %2022: 17.6 %2023: 19.4 %

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

Analysis

Nigeria recorded 19.38 % for gross fixed capital formation (agriculture, forestry and fishing) in 2023. That is the highest value across all 29 years on record.

The figure is up 9.9% on the previous year and up 6.7% over ten years.

Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Nigeria peaked at 19.38 % in 2023 and was at its lowest, 15.84 %, in 1999.

Nigeria ranks 43rd of 181 countries on this measure, in the top quarter.

The long-run direction has been consistently rising across the 29 years of available data.

Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Nigeria, year by year

Annual values for Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Share of Value Added Standard Local Currency in Nigeria, 1995 to 2023.
Year % Change
1995 15.99 %
1996 16.06 % +0.4%
1997 16.04 % -0.1%
1998 16 % -0.3%
1999 15.84 % -1.0%
2000 15.98 % +0.9%
2001 16.16 % +1.1%
2002 16.12 % -0.3%
2003 16.3 % +1.1%
2004 16.62 % +2.0%
2005 16.76 % +0.9%
2006 16.87 % +0.6%
2007 17.04 % +1.0%
2008 17.22 % +1.1%
2009 17.47 % +1.5%
2010 17.75 % +1.6%
2011 17.91 % +0.9%
2012 17.93 % +0.1%
2013 18.17 % +1.4%
2014 18.37 % +1.1%
2015 18.34 % -0.1%
2016 18.02 % -1.8%
2017 17.88 % -0.8%
2018 17.83 % -0.3%
2019 17.79 % -0.2%
2020 17.5 % -1.6%
2021 17.57 % +0.4%
2022 17.64 % +0.4%
2023 19.38 % +9.9%

Averages by decade

DecadeAverage LowestHighest Years
1990s 15.99 % 15.84 % 16.06 % 5
2000s 16.65 % 15.98 % 17.47 % 10
2010s 18 % 17.75 % 18.37 % 10
2020s 18.02 % 17.5 % 19.38 % 4

Countries ranked near Nigeria

  1. 40 Kuwait 20.94 % compare
  2. 41 British Virgin Islands 20.61 % compare
  3. 42 Honduras 19.96 % compare
  4. 44 Republic of Korea 19.22 % compare
  5. 45 Palestine, State of 19.2 % compare
  6. 46 Grenada 19.05 % compare

See the full ranking of 194 places →

More environment data for Nigeria

All data for Nigeria →

Frequently asked questions

What is gross fixed capital formation (agriculture, forestry and fishing) in Nigeria?
Gross fixed capital formation (agriculture, forestry and fishing) in Nigeria was 19.38 % in 2023, according to Food and Agriculture Organization of the United Nations.
What is the highest gross fixed capital formation (agriculture, forestry and fishing) recorded in Nigeria?
The highest recorded value was 19.38 % in 2023.
What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Nigeria?
The lowest recorded value was 15.84 % in 1999.
How does Nigeria rank for gross fixed capital formation (agriculture, forestry and fishing)?
Nigeria ranks 43rd out of 181 countries with data for 2023.
Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Nigeria?
Over the last ten years it is up 6.7%. The long-run trend across the full record is rising.
Where does this Nigeria data come from?
The figures come from Food and Agriculture Organization of the United Nations, published as part of Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Share of Value Added Standard Local Currency. Statizoid updates them automatically from the source API.

Download this data

CSV · JSON — 29 observations, free to reuse under CC BY-NC-SA 3.0 IGO (FAO).

Share, cite or embed this page

Cite this page

Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Nigeria. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 08 September 2026, from https://environment.statizoid.com/stat/gross-fixed-capital-formation-agriculture-forestry-and-fishing-share-of-value-added/nigeria/

Embed or link this data

Paste this into a page to link back to these figures. The data itself is free to reuse under CC BY-NC-SA 3.0 IGO (FAO); please keep the attribution.

<a href="https://environment.statizoid.com/stat/gross-fixed-capital-formation-agriculture-forestry-and-fishing-share-of-value-added/nigeria/">Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Nigeria</a> — Statizoid

About this data

Indicator
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Share of Value Added Standard Local Currency
Unit
%
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
194 places, 5,526 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.