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

Kyrgyzstan: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 79.82 million USD in 2023. ◆ Volatile

Latest (2023)
79.82 million USD
Change on year
up 12.2%
World rank
127th
of 182 countries
All-time high
79.82 million USD
in 2023
All-time low
3.33 million USD
in 2016
Years of data
24
2000–2023

Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Kyrgyzstan, 2000–2023

0204060802000201120232000: 10.9 million USD2001: 40.2 million USD2002: 41.5 million USD2003: 8.3 million USD2004: 9.8 million USD2005: 34.7 million USD2006: 33.3 million USD2007: 40.7 million USD2008: 43.3 million USD2009: 37.5 million USD2010: 37.8 million USD2011: 76.5 million USD2012: 68.1 million USD2013: 55 million USD2014: 44.5 million USD2015: 5.1 million USD2016: 3.3 million USD2017: 36.6 million USD2018: 63.7 million USD2019: 79.7 million USD2020: 55.2 million USD2021: 68.1 million USD2022: 71.1 million USD2023: 79.8 million USD

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

Analysis

In 2023, gross fixed capital formation (agriculture, forestry and fishing) in Kyrgyzstan stood at 79.82 million USD. That is the highest value across all 24 years on record.

The figure is up 12.2% on the previous year and up 45.1% over ten years.

Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Kyrgyzstan peaked at 79.82 million USD in 2023 and was at its lowest, 3.33 million USD, in 2016.

That places Kyrgyzstan 127th out of 182 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 Kyrgyzstan, year by year

Annual values for Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Value US$ in Kyrgyzstan, 2000 to 2023.
Year million USD Change
2000 10.93 million USD
2001 40.16 million USD +267.5%
2002 41.52 million USD +3.4%
2003 8.32 million USD -80.0%
2004 9.8 million USD +17.8%
2005 34.68 million USD +254.0%
2006 33.34 million USD -3.9%
2007 40.68 million USD +22.0%
2008 43.28 million USD +6.4%
2009 37.45 million USD -13.5%
2010 37.78 million USD +0.9%
2011 76.52 million USD +102.5%
2012 68.07 million USD -11.0%
2013 55.03 million USD -19.2%
2014 44.5 million USD -19.1%
2015 5.06 million USD -88.6%
2016 3.33 million USD -34.2%
2017 36.56 million USD +999.3%
2018 63.69 million USD +74.2%
2019 79.7 million USD +25.1%
2020 55.22 million USD -30.7%
2021 68.06 million USD +23.2%
2022 71.14 million USD +4.5%
2023 79.82 million USD +12.2%

Averages by decade

DecadeAverage LowestHighest Years
2000s 30.01 million USD 8.32 million USD 43.28 million USD 10
2010s 47.02 million USD 3.33 million USD 79.7 million USD 10
2020s 68.56 million USD 55.22 million USD 79.82 million USD 4

Countries ranked near Kyrgyzstan

  1. 124 Puerto Rico 100.39 million USD compare
  2. 125 Guyana 93.69 million USD compare
  3. 126 Gabon 87.13 million USD compare
  4. 128 Sierra Leone 78.36 million USD compare
  5. 129 North Macedonia 74.57 million USD compare
  6. 130 Cyprus 71.24 million USD compare

See the full ranking of 228 places →

More environment data for Kyrgyzstan

All data for Kyrgyzstan →

Frequently asked questions

What is gross fixed capital formation (agriculture, forestry and fishing) in Kyrgyzstan?
Gross fixed capital formation (agriculture, forestry and fishing) in Kyrgyzstan was 79.82 million USD 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 Kyrgyzstan?
The highest recorded value was 79.82 million USD in 2023.
What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Kyrgyzstan?
The lowest recorded value was 3.33 million USD in 2016.
How does Kyrgyzstan rank for gross fixed capital formation (agriculture, forestry and fishing)?
Kyrgyzstan ranks 127th out of 182 countries with data for 2023.
Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Kyrgyzstan?
Over the last ten years it is up 45.1%. The long-run trend across the full record is volatile.
Where does this Kyrgyzstan 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 US$. Statizoid updates them automatically from the source API.

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Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Kyrgyzstan. 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-value-us/kyrgyz-republic/

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About this data

Indicator
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Value US$
Unit
million USD
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.