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

Kazakhstan: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 583,633 million SLC in 2023. ◆ Volatile

Latest (2023)
583,633 million SLC
Change on year
up 26.0%
World rank
26th
of 181 countries
All-time high
583,633 million SLC
in 2023
All-time low
15,129 million SLC
in 2000
Years of data
24
2000–2023

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

0200.0k400.0k600.0k2000201120232000: 15.1k million SLC2001: 23.1k million SLC2002: 25.0k million SLC2003: 29.7k million SLC2004: 36.7k million SLC2005: 44.9k million SLC2006: 54.7k million SLC2007: 69.9k million SLC2008: 79.6k million SLC2009: 95.4k million SLC2010: 89.4k million SLC2011: 113.2k million SLC2012: 121.4k million SLC2013: 141.4k million SLC2014: 150.2k million SLC2015: 172.0k million SLC2016: 187.8k million SLC2017: 209.3k million SLC2018: 228.6k million SLC2019: 279.1k million SLC2020: 342.7k million SLC2021: 375.5k million SLC2022: 463.1k million SLC2023: 583.6k 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 Kazakhstan stood at 583,633 million SLC. That is the highest value across all 24 years on record.

That represents a change of up 26.0% on the previous year and up 312.7% over ten years.

Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Kazakhstan peaked at 583,633 million SLC in 2023 and was at its lowest, 15,129 million SLC, in 2000.

That places Kazakhstan 26th out of 181 countries with data for 2023, putting it in the top 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 Kazakhstan, year by year

Annual values for Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Value Standard Local Currency in Kazakhstan, 2000 to 2023.
Year million SLC Change
2000 15,129 million SLC
2001 23,070 million SLC +52.5%
2002 24,977 million SLC +8.3%
2003 29,723 million SLC +19.0%
2004 36,709 million SLC +23.5%
2005 44,923 million SLC +22.4%
2006 54,659 million SLC +21.7%
2007 69,854 million SLC +27.8%
2008 79,560 million SLC +13.9%
2009 95,406 million SLC +19.9%
2010 89,446 million SLC -6.2%
2011 113,206 million SLC +26.6%
2012 121,424 million SLC +7.3%
2013 141,406 million SLC +16.5%
2014 150,216 million SLC +6.2%
2015 172,017 million SLC +14.5%
2016 187,751 million SLC +9.1%
2017 209,266 million SLC +11.5%
2018 228,614 million SLC +9.2%
2019 279,121 million SLC +22.1%
2020 342,746 million SLC +22.8%
2021 375,516 million SLC +9.6%
2022 463,105 million SLC +23.3%
2023 583,633 million SLC +26.0%

Averages by decade

DecadeAverage LowestHighest Years
2000s 47,401 million SLC 15,129 million SLC 95,406 million SLC 10
2010s 169,247 million SLC 89,446 million SLC 279,121 million SLC 10
2020s 441,250 million SLC 342,746 million SLC 583,633 million SLC 4

Countries ranked near Kazakhstan

  1. 23 Madagascar 767,254 million SLC compare
  2. 24 Iraq 640,590 million SLC compare
  3. 25 Bangladesh 607,853 million SLC compare
  4. 27 Cameroon 488,416 million SLC compare
  5. 28 Senegal 402,034 million SLC compare
  6. 29 Algeria 392,733 million SLC compare

See the full ranking of 194 places →

More environment data for Kazakhstan

All data for Kazakhstan →

Frequently asked questions

What is gross fixed capital formation (agriculture, forestry and fishing) in Kazakhstan?
Gross fixed capital formation (agriculture, forestry and fishing) in Kazakhstan was 583,633 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 Kazakhstan?
The highest recorded value was 583,633 million SLC in 2023.
What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Kazakhstan?
The lowest recorded value was 15,129 million SLC in 2000.
How does Kazakhstan rank for gross fixed capital formation (agriculture, forestry and fishing)?
Kazakhstan ranks 26th out of 181 countries with data for 2023.
Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Kazakhstan?
Over the last ten years it is up 312.7%. The long-run trend across the full record is volatile.
Where does this Kazakhstan 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 Kazakhstan. 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-value-standard-local/kazakhstan/

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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.