Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Lebanon
Lebanon: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 2.77 million million SLC in 2023. ◆ Volatile
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Lebanon, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
Lebanon recorded 2.77 million million SLC for gross fixed capital formation (agriculture, forestry and fishing) in 2023. That is the highest value across all 29 years on record.
Compared with earlier readings it is up 60.1% on the previous year and up 767.3% over ten years.
Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Lebanon peaked at 2.77 million million SLC in 2023 and was at its lowest, 88,560 million SLC, in 2001.
Lebanon ranks 12th 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 Lebanon, year by year
| Year | million SLC | Change |
|---|---|---|
| 1995 | 108,441 million SLC | — |
| 1996 | 108,438 million SLC | -0.0% |
| 1997 | 108,699 million SLC | +0.2% |
| 1998 | 104,532 million SLC | -3.8% |
| 1999 | 95,672 million SLC | -8.5% |
| 2000 | 92,097 million SLC | -3.7% |
| 2001 | 88,560 million SLC | -3.8% |
| 2002 | 94,249 million SLC | +6.4% |
| 2003 | 95,684 million SLC | +1.5% |
| 2004 | 108,903 million SLC | +13.8% |
| 2005 | 105,784 million SLC | -2.9% |
| 2006 | 136,488 million SLC | +29.0% |
| 2007 | 182,698 million SLC | +33.9% |
| 2008 | 221,780 million SLC | +21.4% |
| 2009 | 238,841 million SLC | +7.7% |
| 2010 | 244,053 million SLC | +2.2% |
| 2011 | 242,094 million SLC | -0.8% |
| 2012 | 268,641 million SLC | +11.0% |
| 2013 | 319,104 million SLC | +18.8% |
| 2014 | 304,569 million SLC | -4.6% |
| 2015 | 272,394 million SLC | -10.6% |
| 2016 | 226,608 million SLC | -16.8% |
| 2017 | 216,851 million SLC | -4.3% |
| 2018 | 257,673 million SLC | +18.8% |
| 2019 | 200,452 million SLC | -22.2% |
| 2020 | 530,655 million SLC | +164.7% |
| 2021 | 635,550 million SLC | +19.8% |
| 2022 | 1.73 million million SLC | +171.9% |
| 2023 | 2.77 million million SLC | +60.1% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 105,156 million SLC | 95,672 million SLC | 108,699 million SLC | 5 |
| 2000s | 136,508 million SLC | 88,560 million SLC | 238,841 million SLC | 10 |
| 2010s | 255,244 million SLC | 200,452 million SLC | 319,104 million SLC | 10 |
| 2020s | 1.42 million million SLC | 530,655 million SLC | 2.77 million million SLC | 4 |
Countries ranked near Lebanon
- 9 Timor-Leste 26.08 million SLC compare
- 9 Uganda 5.05 million million SLC compare
- 10 Paraguay 3.68 million million SLC compare
- 11 Myanmar 2.83 million million SLC compare
- 13 Cambodia 2.62 million million SLC compare
- 14 Pakistan 2.23 million million SLC compare
- 15 China, mainland 1.48 million million SLC compare
More environment data for Lebanon
- Historical exposure to drought — Land soil moisture anomaly -12.11 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly -12.31 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.5 °C (2025)
- Temperature change 1.89 °C (2025)
- Sawnwood, non-coniferous — Production, annual growth rate 0 % change on previous year (1982)
- Sawnwood, non-coniferous — Production, per unit of GDP 0 m3 per US$ of GDP (2024)
- Sawnwood, non-coniferous — Production, per capita 0 m3 per person (2024)
- Sawnwood, non-coniferous — Import quantity, annual growth rate -15.47 % change on previous year (2024)
- Sawnwood, non-coniferous — Import quantity, per unit of GDP 0 m3 per US$ of GDP (2024)
Frequently asked questions
- What is gross fixed capital formation (agriculture, forestry and fishing) in Lebanon?
- Gross fixed capital formation (agriculture, forestry and fishing) in Lebanon was 2.77 million 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 Lebanon?
- The highest recorded value was 2.77 million million SLC in 2023.
- What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Lebanon?
- The lowest recorded value was 88,560 million SLC in 2001.
- How does Lebanon rank for gross fixed capital formation (agriculture, forestry and fishing)?
- Lebanon ranks 12th out of 181 countries with data for 2023.
- Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Lebanon?
- Over the last ten years it is up 767.3%. The long-run trend across the full record is volatile.
- Where does this Lebanon 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.
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.