Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Hungary
Hungary: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 533,487 million SLC in 2023. ▲ Rising
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Hungary, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
The most recent figure for gross fixed capital formation (agriculture, forestry and fishing) in Hungary is 533,487 million SLC, measured in 2023. That is the highest value across all 29 years on record.
That represents a change of up 18.7% on the previous year and up 85.5% over ten years.
Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Hungary peaked at 533,487 million SLC in 2023 and was at its lowest, 204,247 million SLC, in 2006.
That places Hungary 18th out of 181 countries with data for 2023, putting it in the top 10%.
The long-run direction has been consistently rising across the 29 years of available data.
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Hungary, year by year
| Year | million SLC | Change |
|---|---|---|
| 1995 | 216,635 million SLC | — |
| 1996 | 207,343 million SLC | -4.3% |
| 1997 | 205,141 million SLC | -1.1% |
| 1998 | 232,175 million SLC | +13.2% |
| 1999 | 279,709 million SLC | +20.5% |
| 2000 | 265,519 million SLC | -5.1% |
| 2001 | 318,932 million SLC | +20.1% |
| 2002 | 312,177 million SLC | -2.1% |
| 2003 | 351,755 million SLC | +12.7% |
| 2004 | 243,737 million SLC | -30.7% |
| 2005 | 224,456 million SLC | -7.9% |
| 2006 | 204,247 million SLC | -9.0% |
| 2007 | 247,673 million SLC | +21.3% |
| 2008 | 272,706 million SLC | +10.1% |
| 2009 | 320,987 million SLC | +17.7% |
| 2010 | 256,412 million SLC | -20.1% |
| 2011 | 267,149 million SLC | +4.2% |
| 2012 | 281,958 million SLC | +5.5% |
| 2013 | 287,645 million SLC | +2.0% |
| 2014 | 345,950 million SLC | +20.3% |
| 2015 | 291,919 million SLC | -15.6% |
| 2016 | 260,960 million SLC | -10.6% |
| 2017 | 298,050 million SLC | +14.2% |
| 2018 | 346,867 million SLC | +16.4% |
| 2019 | 435,064 million SLC | +25.4% |
| 2020 | 358,191 million SLC | -17.7% |
| 2021 | 366,859 million SLC | +2.4% |
| 2022 | 449,629 million SLC | +22.6% |
| 2023 | 533,487 million SLC | +18.7% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 228,201 million SLC | 205,141 million SLC | 279,709 million SLC | 5 |
| 2000s | 276,219 million SLC | 204,247 million SLC | 351,755 million SLC | 10 |
| 2010s | 307,197 million SLC | 256,412 million SLC | 435,064 million SLC | 10 |
| 2020s | 427,042 million SLC | 358,191 million SLC | 533,487 million SLC | 4 |
Countries ranked near Hungary
More environment data for Hungary
- Historical exposure to drought — Land soil moisture anomaly -5.55 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly -5.61 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.63 °C (2025)
- Temperature change 2.01 °C (2025)
- Wood-based panels — Import quantity, annual growth rate 7.15 % change on previous year (2024)
- Wood-based panels — Import quantity, per unit of GDP 0 m3 per US$ of GDP (2024)
- Wood-based panels — Import quantity, per capita 0.0538 m3 per person (2024)
- Wood-based panels — Import value, annual growth rate -1.76 % change on previous year (2024)
- Wood-based panels — Import value, per unit of GDP 0 1000 USD per US$ of GDP (2024)
Frequently asked questions
- What is gross fixed capital formation (agriculture, forestry and fishing) in Hungary?
- Gross fixed capital formation (agriculture, forestry and fishing) in Hungary was 533,487 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 Hungary?
- The highest recorded value was 533,487 million SLC in 2023.
- What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Hungary?
- The lowest recorded value was 204,247 million SLC in 2006.
- How does Hungary rank for gross fixed capital formation (agriculture, forestry and fishing)?
- Hungary ranks 18th out of 181 countries with data for 2023.
- Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Hungary?
- Over the last ten years it is up 85.5%. The long-run trend across the full record is rising.
- Where does this Hungary 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, 2015 prices. Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 29 observations, free to reuse under CC BY-NC-SA 3.0 IGO (FAO).
About this data
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.