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

Anguilla: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 0.09 million SLC in 2023. ◆ Volatile

Latest (2023)
0.09 million SLC
Change on year
down 35.6%
World rank
181st
of 181 countries
All-time high
3.42 million SLC
in 2008
All-time low
0.0742 million SLC
in 2016
Years of data
29
1995–2023

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

01231995200920231995: 0.287 million SLC1996: 0.351 million SLC1997: 0.19 million SLC1998: 0.661 million SLC1999: 1.2 million SLC2000: 1.3 million SLC2001: 0.862 million SLC2002: 0.423 million SLC2003: 0.483 million SLC2004: 0.993 million SLC2005: 1.5 million SLC2006: 2 million SLC2007: 2.9 million SLC2008: 3.4 million SLC2009: 1.3 million SLC2010: 0.921 million SLC2011: 0.13 million SLC2012: 0.086 million SLC2013: 0.44 million SLC2014: 0.839 million SLC2015: 0.873 million SLC2016: 0.074 million SLC2017: 0.626 million SLC2018: 0.326 million SLC2019: 0.466 million SLC2020: 0.167 million SLC2021: 0.167 million SLC2022: 0.14 million SLC2023: 0.09 million SLC

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

Analysis

In 2023, gross fixed capital formation (agriculture, forestry and fishing) in Anguilla stood at 0.09 million SLC.

The figure is down 35.6% on the previous year and down 79.5% over ten years.

Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Anguilla peaked at 3.42 million SLC in 2008 and was at its lowest, 0.0742 million SLC, in 2016.

That places Anguilla 181st out of 181 countries with data for 2023, putting it in the bottom quarter.

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

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

Annual values for Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Value Standard Local Currency, 2015 prices in Anguilla, 1995 to 2023.
Year million SLC Change
1995 0.287 million SLC
1996 0.3509 million SLC +22.3%
1997 0.1902 million SLC -45.8%
1998 0.6612 million SLC +247.7%
1999 1.25 million SLC +88.8%
2000 1.27 million SLC +1.7%
2001 0.862 million SLC -32.1%
2002 0.4234 million SLC -50.9%
2003 0.4828 million SLC +14.0%
2004 0.9929 million SLC +105.7%
2005 1.49 million SLC +50.1%
2006 1.99 million SLC +33.9%
2007 2.87 million SLC +43.7%
2008 3.42 million SLC +19.5%
2009 1.29 million SLC -62.2%
2010 0.9213 million SLC -28.9%
2011 0.1303 million SLC -85.9%
2012 0.0861 million SLC -33.9%
2013 0.4398 million SLC +410.9%
2014 0.8386 million SLC +90.7%
2015 0.8726 million SLC +4.1%
2016 0.0742 million SLC -91.5%
2017 0.6259 million SLC +743.8%
2018 0.3258 million SLC -47.9%
2019 0.4656 million SLC +42.9%
2020 0.167 million SLC -64.1%
2021 0.1666 million SLC -0.3%
2022 0.1398 million SLC -16.1%
2023 0.09 million SLC -35.6%

Averages by decade

DecadeAverage LowestHighest Years
1990s 0.5476 million SLC 0.1902 million SLC 1.25 million SLC 5
2000s 1.51 million SLC 0.4234 million SLC 3.42 million SLC 10
2010s 0.478 million SLC 0.0742 million SLC 0.9213 million SLC 10
2020s 0.1409 million SLC 0.09 million SLC 0.167 million SLC 4

Countries ranked near Anguilla

  1. 179 British Virgin Islands 0.3 million SLC compare
  2. 180 Nauru 0.21 million SLC compare

See the full ranking of 194 places →

More environment data for Anguilla

All data for Anguilla →

Frequently asked questions

What is gross fixed capital formation (agriculture, forestry and fishing) in Anguilla?
Gross fixed capital formation (agriculture, forestry and fishing) in Anguilla was 0.09 million SLC 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 Anguilla?
The highest recorded value was 3.42 million SLC in 2008.
What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Anguilla?
The lowest recorded value was 0.0742 million SLC in 2016.
How does Anguilla rank for gross fixed capital formation (agriculture, forestry and fishing)?
Anguilla ranks 181st out of 181 countries with data for 2023.
Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Anguilla?
Over the last ten years it is down 79.5%. The long-run trend across the full record is volatile.
Where does this Anguilla 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) — Value Standard Local Currency, 2015 prices. Statizoid updates them automatically from the source API.

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Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Anguilla. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 01 September 2026, from https://environment.statizoid.com/stat/gross-fixed-capital-formation-agriculture-forestry-and-fishing-value-standard-local-2/anguilla/

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About this data

Indicator
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Value Standard Local Currency, 2015 prices
Unit
million SLC
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.