Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Malaysia
Malaysia: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 11,699 million SLC in 2023. ▲ Rising
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Malaysia, 1995–2023
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 Malaysia stood at 11,699 million SLC. That is the highest value across all 29 years on record.
That represents a change of up 6.0% on the previous year and up 28.1% over ten years.
Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Malaysia peaked at 11,699 million SLC in 2023 and was at its lowest, 3,403 million SLC, in 2001.
That places Malaysia 76th out of 181 countries with data for 2023, putting it in the middle of the range.
The long-run direction has been consistently rising across the 29 years of available data.
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Malaysia, year by year
| Year | million SLC | Change |
|---|---|---|
| 1995 | 5,704 million SLC | — |
| 1996 | 5,635 million SLC | -1.2% |
| 1997 | 5,901 million SLC | +4.7% |
| 1998 | 4,665 million SLC | -20.9% |
| 1999 | 3,900 million SLC | -16.4% |
| 2000 | 3,683 million SLC | -5.5% |
| 2001 | 3,403 million SLC | -7.6% |
| 2002 | 3,972 million SLC | +16.7% |
| 2003 | 4,298 million SLC | +8.2% |
| 2004 | 4,577 million SLC | +6.5% |
| 2005 | 4,206 million SLC | -8.1% |
| 2006 | 4,672 million SLC | +11.1% |
| 2007 | 6,015 million SLC | +28.8% |
| 2008 | 6,392 million SLC | +6.3% |
| 2009 | 5,612 million SLC | -12.2% |
| 2010 | 7,062 million SLC | +25.8% |
| 2011 | 8,271 million SLC | +17.1% |
| 2012 | 8,888 million SLC | +7.5% |
| 2013 | 9,134 million SLC | +2.8% |
| 2014 | 9,785 million SLC | +7.1% |
| 2015 | 10,324 million SLC | +5.5% |
| 2016 | 10,597 million SLC | +2.6% |
| 2017 | 10,758 million SLC | +1.5% |
| 2018 | 10,672 million SLC | -0.8% |
| 2019 | 10,752 million SLC | +0.8% |
| 2020 | 9,824 million SLC | -8.6% |
| 2021 | 10,527 million SLC | +7.2% |
| 2022 | 11,040 million SLC | +4.9% |
| 2023 | 11,699 million SLC | +6.0% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 5,161 million SLC | 3,900 million SLC | 5,901 million SLC | 5 |
| 2000s | 4,683 million SLC | 3,403 million SLC | 6,392 million SLC | 10 |
| 2010s | 9,624 million SLC | 7,062 million SLC | 10,758 million SLC | 10 |
| 2020s | 10,772 million SLC | 9,824 million SLC | 11,699 million SLC | 4 |
Countries ranked near Malaysia
- 73 Equatorial Guinea 13,266 million SLC compare
- 74 Guinea-Bissau 13,183 million SLC compare
- 75 Italy 12,626 million SLC compare
- 77 Mozambique 11,022 million SLC compare
- 78 Germany 9,988 million SLC compare
- 79 Saudi Arabia 9,858 million SLC compare
More environment data for Malaysia
- Historical exposure to drought — Land soil moisture anomaly -1.65 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly -1.9 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.179 °C (2025)
- Temperature change 1.25 °C (2025)
- Wood-based panels — Import quantity, annual growth rate 20.22 % 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 0.0728 m3 per person (2024)
- Wood-based panels — Import value, annual growth rate 10.62 % 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 Malaysia?
- Gross fixed capital formation (agriculture, forestry and fishing) in Malaysia was 11,699 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 Malaysia?
- The highest recorded value was 11,699 million SLC in 2023.
- What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Malaysia?
- The lowest recorded value was 3,403 million SLC in 2001.
- How does Malaysia rank for gross fixed capital formation (agriculture, forestry and fishing)?
- Malaysia ranks 76th out of 181 countries with data for 2023.
- Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Malaysia?
- Over the last ten years it is up 28.1%. The long-run trend across the full record is rising.
- Where does this Malaysia 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.