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

Comoros: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 23.03 % in 2023. ▲ Rising

Latest (2023)
23.03 %
Change on year
down 1.4%
World rank
3rd
of 182 countries
All-time high
25.87 %
in 2003
All-time low
9.04 %
in 2008
Years of data
29
1995–2023

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

101520251995200920231995: 10.3 %1996: 10.1 %1997: 12.8 %1998: 11.2 %1999: 13.6 %2000: 23.8 %2001: 20.6 %2002: 20.4 %2003: 25.9 %2004: 25 %2005: 17.8 %2006: 15.5 %2007: 10.3 %2008: 9 %2009: 11 %2010: 10.6 %2011: 11.8 %2012: 12 %2013: 13.3 %2014: 14 %2015: 16.1 %2016: 18 %2017: 17.7 %2018: 17 %2019: 21.7 %2020: 25.5 %2021: 21 %2022: 23.4 %2023: 23 %

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

Analysis

In 2023, gross fixed capital formation (agriculture, forestry and fishing) in Comoros stood at 23.03 %.

Compared with earlier readings it is down 1.4% on the previous year and up 72.9% over ten years.

Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Comoros peaked at 25.87 % in 2003 and was at its lowest, 9.04 %, in 2008.

That places Comoros 3rd out of 182 countries with data for 2023, putting it in the top 10%.

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

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

Annual values for Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Share of Gross Fixed Capital Formation US$ in Comoros, 1995 to 2023.
Year % Change
1995 10.3 %
1996 10.14 % -1.6%
1997 12.82 % +26.4%
1998 11.25 % -12.3%
1999 13.64 % +21.3%
2000 23.79 % +74.4%
2001 20.59 % -13.4%
2002 20.42 % -0.8%
2003 25.87 % +26.7%
2004 25.05 % -3.2%
2005 17.84 % -28.8%
2006 15.48 % -13.2%
2007 10.34 % -33.2%
2008 9.04 % -12.6%
2009 10.97 % +21.3%
2010 10.61 % -3.3%
2011 11.85 % +11.7%
2012 11.98 % +1.2%
2013 13.32 % +11.1%
2014 13.97 % +4.9%
2015 16.1 % +15.2%
2016 18.05 % +12.1%
2017 17.73 % -1.7%
2018 16.97 % -4.3%
2019 21.74 % +28.1%
2020 25.5 % +17.3%
2021 21.01 % -17.6%
2022 23.35 % +11.1%
2023 23.03 % -1.4%

Averages by decade

DecadeAverage LowestHighest Years
1990s 11.63 % 10.14 % 13.64 % 5
2000s 17.94 % 9.04 % 25.87 % 10
2010s 15.23 % 10.61 % 21.74 % 10
2020s 23.22 % 21.01 % 25.5 % 4

Countries ranked near Comoros

  1. 1 Guinea 28.93 % compare
  2. 2 Guinea-Bissau 25.21 % compare
  3. 4 Pakistan 21.87 % compare
  4. 5 Papua New Guinea 20.3 % compare
  5. 5 Timor-Leste 7.22 % compare
  6. 6 Belarus 17.56 % compare
  7. 6 Viet Nam 6.76 % compare

See the full ranking of 228 places →

More environment data for Comoros

All data for Comoros →

Frequently asked questions

What is gross fixed capital formation (agriculture, forestry and fishing) in Comoros?
Gross fixed capital formation (agriculture, forestry and fishing) in Comoros was 23.03 % 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 Comoros?
The highest recorded value was 25.87 % in 2003.
What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Comoros?
The lowest recorded value was 9.04 % in 2008.
How does Comoros rank for gross fixed capital formation (agriculture, forestry and fishing)?
Comoros ranks 3rd out of 182 countries with data for 2023.
Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Comoros?
Over the last ten years it is up 72.9%. The long-run trend across the full record is rising.
Where does this Comoros 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 Gross Fixed Capital Formation US$. 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 Comoros. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 03 September 2026, from https://environment.statizoid.com/stat/gross-fixed-capital-formation-agriculture-forestry-and-fishing-share-of-gross-fixed/comoros/

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-gross-fixed/comoros/">Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Comoros</a> — Statizoid

About this data

Indicator
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Share of Gross Fixed Capital Formation US$
Unit
%
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
228 places, 6,512 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.