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

Libya: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 1,003 million SLC in 2023. ◆ Volatile

Latest (2023)
1,003 million SLC
Change on year
up 39.1%
World rank
122nd
of 181 countries
All-time high
1,003 million SLC
in 2023
All-time low
64.05 million SLC
in 1995
Years of data
29
1995–2023

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

02004006008001.0k1995200920231995: 64.1 million SLC1996: 77.9 million SLC1997: 87.2 million SLC1998: 92.4 million SLC1999: 98.4 million SLC2000: 102 million SLC2001: 190.2 million SLC2002: 194 million SLC2003: 175 million SLC2004: 139 million SLC2005: 145.4 million SLC2006: 125.5 million SLC2007: 148.9 million SLC2008: 166.8 million SLC2009: 191.7 million SLC2010: 187.2 million SLC2011: 137.7 million SLC2012: 162.7 million SLC2013: 165.5 million SLC2014: 196.3 million SLC2015: 206.7 million SLC2016: 272.1 million SLC2017: 344.8 million SLC2018: 367.2 million SLC2019: 331.7 million SLC2020: 244.3 million SLC2021: 633 million SLC2022: 720.8 million SLC2023: 1.0k million SLC

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

Analysis

Libya recorded 1,003 million SLC for gross fixed capital formation (agriculture, forestry and fishing) in 2023. That is the highest value across all 29 years on record.

That represents a change of up 39.1% on the previous year and up 505.9% over ten years.

Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Libya peaked at 1,003 million SLC in 2023 and was at its lowest, 64.05 million SLC, in 1995.

That places Libya 122nd out of 181 countries with data for 2023, putting it in the middle of the range.

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 Libya, year by year

Annual values for Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Value Standard Local Currency in Libya, 1995 to 2023.
Year million SLC Change
1995 64.05 million SLC
1996 77.9 million SLC +21.6%
1997 87.21 million SLC +11.9%
1998 92.35 million SLC +5.9%
1999 98.4 million SLC +6.5%
2000 101.97 million SLC +3.6%
2001 190.16 million SLC +86.5%
2002 194 million SLC +2.0%
2003 174.98 million SLC -9.8%
2004 138.97 million SLC -20.6%
2005 145.39 million SLC +4.6%
2006 125.54 million SLC -13.7%
2007 148.94 million SLC +18.6%
2008 166.78 million SLC +12.0%
2009 191.73 million SLC +15.0%
2010 187.19 million SLC -2.4%
2011 137.75 million SLC -26.4%
2012 162.7 million SLC +18.1%
2013 165.48 million SLC +1.7%
2014 196.29 million SLC +18.6%
2015 206.7 million SLC +5.3%
2016 272.05 million SLC +31.6%
2017 344.76 million SLC +26.7%
2018 367.19 million SLC +6.5%
2019 331.66 million SLC -9.7%
2020 244.33 million SLC -26.3%
2021 632.99 million SLC +159.1%
2022 720.75 million SLC +13.9%
2023 1,003 million SLC +39.1%

Averages by decade

DecadeAverage LowestHighest Years
1990s 83.98 million SLC 64.05 million SLC 98.4 million SLC 5
2000s 157.85 million SLC 101.97 million SLC 194 million SLC 10
2010s 237.18 million SLC 137.75 million SLC 367.19 million SLC 10
2020s 650.18 million SLC 244.33 million SLC 1,003 million SLC 4

Countries ranked near Libya

  1. 119 Latvia 1,170 million SLC compare
  2. 120 New Caledonia 1,080 million SLC compare
  3. 121 Eswatini 1,024 million SLC compare
  4. 123 Suriname 935.88 million SLC compare
  5. 124 Slovak Republic 917.71 million SLC compare
  6. 125 Djibouti 854.37 million SLC compare

See the full ranking of 194 places →

More environment data for Libya

All data for Libya →

Frequently asked questions

What is gross fixed capital formation (agriculture, forestry and fishing) in Libya?
Gross fixed capital formation (agriculture, forestry and fishing) in Libya was 1,003 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 Libya?
The highest recorded value was 1,003 million SLC in 2023.
What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Libya?
The lowest recorded value was 64.05 million SLC in 1995.
How does Libya rank for gross fixed capital formation (agriculture, forestry and fishing)?
Libya ranks 122nd out of 181 countries with data for 2023.
Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Libya?
Over the last ten years it is up 505.9%. The long-run trend across the full record is volatile.
Where does this Libya 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. Statizoid updates them automatically from the source API.

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Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Libya. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 23 August 2026, from https://environment.statizoid.com/stat/gross-fixed-capital-formation-agriculture-forestry-and-fishing-value-standard-local/libya/

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About this data

Indicator
Gross Fixed Capital Formation (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
194 places, 5,531 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.