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

Singapore: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 94.98 million SLC in 2023. ▲ Rising

Latest (2023)
94.98 million SLC
Change on year
up 8.7%
World rank
149th
of 181 countries
All-time high
94.98 million SLC
in 2023
All-time low
46.14 million SLC
in 2003
Years of data
29
1995–2023

Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Singapore, 1995–2023

0204060801001995200920231995: 67.5 million SLC1996: 78.6 million SLC1997: 78.2 million SLC1998: 64.7 million SLC1999: 65.7 million SLC2000: 62.8 million SLC2001: 56 million SLC2002: 51.3 million SLC2003: 46.1 million SLC2004: 48.6 million SLC2005: 52.4 million SLC2006: 52.3 million SLC2007: 54.2 million SLC2008: 54.6 million SLC2009: 55.2 million SLC2010: 57 million SLC2011: 59 million SLC2012: 59.6 million SLC2013: 64.4 million SLC2014: 67.4 million SLC2015: 67.7 million SLC2016: 68.3 million SLC2017: 71.6 million SLC2018: 74.2 million SLC2019: 79.6 million SLC2020: 75.5 million SLC2021: 84.4 million SLC2022: 87.4 million SLC2023: 95 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 Singapore stood at 94.98 million SLC. That is the highest value across all 29 years on record.

That represents a change of up 8.7% on the previous year and up 47.5% over ten years.

Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Singapore peaked at 94.98 million SLC in 2023 and was at its lowest, 46.14 million SLC, in 2003.

Singapore ranks 149th of 181 countries on this measure, in the bottom quarter.

The long-run direction has been consistently rising across the 29 years of available data.

Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Singapore, year by year

Annual values for Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Value Standard Local Currency in Singapore, 1995 to 2023.
Year million SLC Change
1995 67.5 million SLC
1996 78.63 million SLC +16.5%
1997 78.19 million SLC -0.6%
1998 64.67 million SLC -17.3%
1999 65.7 million SLC +1.6%
2000 62.81 million SLC -4.4%
2001 55.98 million SLC -10.9%
2002 51.32 million SLC -8.3%
2003 46.14 million SLC -10.1%
2004 48.64 million SLC +5.4%
2005 52.36 million SLC +7.7%
2006 52.28 million SLC -0.2%
2007 54.22 million SLC +3.7%
2008 54.56 million SLC +0.6%
2009 55.24 million SLC +1.2%
2010 56.98 million SLC +3.2%
2011 58.99 million SLC +3.5%
2012 59.64 million SLC +1.1%
2013 64.41 million SLC +8.0%
2014 67.42 million SLC +4.7%
2015 67.69 million SLC +0.4%
2016 68.3 million SLC +0.9%
2017 71.56 million SLC +4.8%
2018 74.18 million SLC +3.7%
2019 79.62 million SLC +7.3%
2020 75.52 million SLC -5.2%
2021 84.39 million SLC +11.8%
2022 87.36 million SLC +3.5%
2023 94.98 million SLC +8.7%

Averages by decade

DecadeAverage LowestHighest Years
1990s 70.94 million SLC 64.67 million SLC 78.63 million SLC 5
2000s 53.35 million SLC 46.14 million SLC 62.81 million SLC 10
2010s 66.88 million SLC 56.98 million SLC 79.62 million SLC 10
2020s 85.56 million SLC 75.52 million SLC 94.98 million SLC 4

Countries ranked near Singapore

  1. 146 Liberia 109.62 million SLC compare
  2. 147 Puerto Rico 100.39 million SLC compare
  3. 148 Sao Tome and Principe 98.14 million SLC compare
  4. 150 Trinidad and Tobago 74.23 million SLC compare
  5. 151 Fiji 67.75 million SLC compare
  6. 152 Cyprus 65.88 million SLC compare

See the full ranking of 194 places →

More environment data for Singapore

All data for Singapore →

Frequently asked questions

What is gross fixed capital formation (agriculture, forestry and fishing) in Singapore?
Gross fixed capital formation (agriculture, forestry and fishing) in Singapore was 94.98 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 Singapore?
The highest recorded value was 94.98 million SLC in 2023.
What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Singapore?
The lowest recorded value was 46.14 million SLC in 2003.
How does Singapore rank for gross fixed capital formation (agriculture, forestry and fishing)?
Singapore ranks 149th out of 181 countries with data for 2023.
Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Singapore?
Over the last ten years it is up 47.5%. The long-run trend across the full record is rising.
Where does this Singapore 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 Singapore. 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/singapore/

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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.