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

Latvia: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 111.08 % in 2023. ◆ Volatile

Latest (2023)
111.08 %
Change on year
up 71.6%
World rank
3rd
of 181 countries
All-time high
111.08 %
in 2023
All-time low
4.69 %
in 1995
Years of data
29
1995–2023

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

02550751001995200920231995: 4.7 %1996: 6.5 %1997: 6.7 %1998: 10.9 %1999: 12.4 %2000: 13.1 %2001: 10.6 %2002: 17.9 %2003: 33.4 %2004: 43.8 %2005: 74.5 %2006: 60.6 %2007: 60.4 %2008: 64.6 %2009: 31.3 %2010: 39.6 %2011: 57 %2012: 68.4 %2013: 51.6 %2014: 36.1 %2015: 39.1 %2016: 54.7 %2017: 57 %2018: 74.7 %2019: 41.1 %2020: 43.8 %2021: 46.4 %2022: 64.7 %2023: 111.1 %

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

Analysis

Latvia recorded 111.08 % 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 71.6% on the previous year and up 115.2% over ten years.

Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Latvia peaked at 111.08 % in 2023 and was at its lowest, 4.69 %, in 1995.

Latvia ranks 3rd of 181 countries on this measure, in the top 10%.

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 Latvia, year by year

Annual values for Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Share of Value Added Standard Local Currency, 2015 prices in Latvia, 1995 to 2023.
Year % Change
1995 4.69 %
1996 6.49 % +38.3%
1997 6.74 % +3.9%
1998 10.89 % +61.6%
1999 12.44 % +14.2%
2000 13.05 % +4.9%
2001 10.59 % -18.9%
2002 17.87 % +68.7%
2003 33.43 % +87.1%
2004 43.84 % +31.1%
2005 74.47 % +69.9%
2006 60.59 % -18.6%
2007 60.44 % -0.3%
2008 64.6 % +6.9%
2009 31.32 % -51.5%
2010 39.65 % +26.6%
2011 56.95 % +43.6%
2012 68.42 % +20.1%
2013 51.61 % -24.6%
2014 36.14 % -30.0%
2015 39.09 % +8.2%
2016 54.74 % +40.0%
2017 57.04 % +4.2%
2018 74.73 % +31.0%
2019 41.06 % -45.1%
2020 43.75 % +6.6%
2021 46.41 % +6.1%
2022 64.72 % +39.5%
2023 111.08 % +71.6%

Averages by decade

DecadeAverage LowestHighest Years
1990s 8.25 % 4.69 % 12.44 % 5
2000s 41.02 % 10.59 % 74.47 % 10
2010s 51.94 % 36.14 % 74.73 % 10
2020s 66.49 % 43.75 % 111.08 % 4

Countries ranked near Latvia

  1. 1 Estonia 214.42 % compare
  2. 1 Syrian Arab Republic 37.23 % compare
  3. 2 Côte d'Ivoire 13.17 % compare
  4. 2 Democratic Republic of the Congo 22.68 % compare
  5. 2 Luxembourg 165.6 % compare
  6. 3 Cabo Verde 11.01 % compare
  7. 3 Viet Nam 18.33 % compare
  8. 4 Denmark 74.93 % compare
  9. 4 Lao People's Democratic Republic 17.31 % compare
  10. 5 Lithuania 69.87 % compare
  11. 5 Türkiye 15.67 % compare
  12. 6 Bolivia (Plurinational State of) 14.79 % compare
  13. 6 United Kingdom of Great Britain and Northern Ireland 61.06 % compare

See the full ranking of 194 places →

More environment data for Latvia

All data for Latvia →

Frequently asked questions

What is gross fixed capital formation (agriculture, forestry and fishing) in Latvia?
Gross fixed capital formation (agriculture, forestry and fishing) in Latvia was 111.08 % 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 Latvia?
The highest recorded value was 111.08 % in 2023.
What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Latvia?
The lowest recorded value was 4.69 % in 1995.
How does Latvia rank for gross fixed capital formation (agriculture, forestry and fishing)?
Latvia ranks 3rd out of 181 countries with data for 2023.
Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Latvia?
Over the last ten years it is up 115.2%. The long-run trend across the full record is volatile.
Where does this Latvia 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, 2015 prices. Statizoid updates them automatically from the source API.

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Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Latvia. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 06 September 2026, from https://environment.statizoid.com/stat/gross-fixed-capital-formation-agriculture-forestry-and-fishing-share-of-value-added-2/latvia/

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About this data

Indicator
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Share of Value Added Standard Local Currency, 2015 prices
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.