Gross Capital Stocks (Agriculture, Forestry and Fishing) — Value Standard Local Currency by country

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...

Countries reporting
26
Highest
106.73 million million SLC
Republic of Korea
Lowest
4,407 million SLC
Luxembourg
Median
101,120 million SLC
Years covered
28
1995–2022
Data points
670

What the numbers show

Gross Capital Stocks (Agriculture, Forestry and Fishing) — Value Standard Local Currency is currently reported for 26 countries. The highest value is 106.73 million million SLC in Republic of Korea; the lowest is 4,407 million SLC in Luxembourg.

The median across all reporting countries is 101,120 million SLC, and the mean is 5.01 million million SLC.

The gap between the highest and lowest reporting country is a factor of about 24,220.

Over the past decade 24 countries rose and 2 fell. The largest increase was in Estonia (up 96.4%), and the largest decrease in Greece (down 6.9%).

Gross Capital Stocks (Agriculture, Forestry and Fishing) — Value: full country ranking

#Country LatestYear 10-year changeTrend
1 Republic of Korea 106.73 million million SLC 2017 up 29.4% rising
2 Hungary 19.71 million million SLC 2021 up 74.6% rising
3 Czechia 892,573 million SLC 2022 up 71.1% rising
4 Denmark 475,723 million SLC 2022 up 27.7% rising
5 Germany 442,450 million SLC 2022 up 41.7% rising
6 Italy 396,536 million SLC 2022 down 1.0% rising
7 Poland 329,068 million SLC 2020 up 23.6% rising
8 France 253,235 million SLC 2022 up 10.6% rising
9 Canada 163,230 million SLC 2022 up 68.7% rising
10 Australia 155,178 million SLC 2016 up 31.7% rising
11 Austria 122,832 million SLC 2022 up 59.5% rising
12 Netherlands (Kingdom of the) 113,667 million SLC 2022 up 34.5% rising
13 United Kingdom of Great Britain and Northern Ireland 102,510 million SLC 2021 up 38.3% rising
14 Spain 99,731 million SLC 2020 up 44.5% rising
15 Israel 46,822 million SLC 2022 up 13.3% rising
16 Finland 46,315 million SLC 2022 up 13.6% rising
17 Greece 38,398 million SLC 2021 down 6.9% rising
18 Portugal 34,737 million SLC 2021 up 32.9% rising
19 Belgium 27,168 million SLC 2022 up 52.4% rising
20 Latvia 22,692 million SLC 2021 up 18.9% rising
21 Ireland 21,952 million SLC 2020 up 37.1% rising
22 Slovakia 17,869 million SLC 2021 up 27.8% rising
23 Lithuania 12,599 million SLC 2020 up 78.5% rising
24 Slovenia 8,234 million SLC 2022 up 45.3% rising
25 Estonia 4,675 million SLC 2021 up 96.4% volatile
26 Luxembourg 4,407 million SLC 2020 up 56.1% rising

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Gross Capital Stocks (Agriculture, Forestry and Fishing) — Value by country. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 08 September 2026, from https://environment.statizoid.com/stat/gross-capital-stocks-agriculture-forestry-and-fishing-value-standard-local-currency/

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About this data

Indicator
Gross Capital Stocks (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
26 places, 670 data points, 1995–2022
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.