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

Sudan: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 9,390 million SLC in 2022. ▼ Falling

Latest (2022)
9,390 million SLC
Change on year
up 37.4%
World rank
81st
of 181 countries
All-time high
17,209 million SLC
in 2016
All-time low
5,845 million SLC
in 2018
Years of data
15
2008–2022

Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Sudan, 2008–2022

5.0k7.5k10.0k12.5k15.0k17.5k2008201520222008: 10.7k million SLC2009: 10.2k million SLC2010: 11.0k million SLC2011: 7.9k million SLC2012: 11.5k million SLC2013: 11.9k million SLC2014: 14.8k million SLC2015: 16.7k million SLC2016: 17.2k million SLC2017: 10.6k million SLC2018: 5.8k million SLC2019: 8.1k million SLC2020: 7.2k million SLC2021: 6.8k million SLC2022: 9.4k million SLC

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 Sudan is 9,390 million SLC, measured in 2022.

That represents a change of up 37.4% on the previous year and down 18.6% over ten years.

Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Sudan peaked at 17,209 million SLC in 2016 and was at its lowest, 5,845 million SLC, in 2018.

That places Sudan 81st out of 181 countries with data for 2022, putting it in the middle of the range.

The long-run direction has been consistently falling across the 15 years of available data.

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

Annual values for Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Value Standard Local Currency, 2015 prices in Sudan, 2008 to 2022.
Year million SLC Change
2008 10,712 million SLC
2009 10,202 million SLC -4.8%
2010 11,023 million SLC +8.0%
2011 7,945 million SLC -27.9%
2012 11,542 million SLC +45.3%
2013 11,862 million SLC +2.8%
2014 14,767 million SLC +24.5%
2015 16,720 million SLC +13.2%
2016 17,209 million SLC +2.9%
2017 10,634 million SLC -38.2%
2018 5,845 million SLC -45.0%
2019 8,124 million SLC +39.0%
2020 7,247 million SLC -10.8%
2021 6,836 million SLC -5.7%
2022 9,390 million SLC +37.4%

Averages by decade

DecadeAverage LowestHighest Years
2000s 10,457 million SLC 10,202 million SLC 10,712 million SLC 2
2010s 11,567 million SLC 5,845 million SLC 17,209 million SLC 10
2020s 7,824 million SLC 6,836 million SLC 9,390 million SLC 3

Countries ranked near Sudan

  1. 78 Germany 9,988 million SLC compare
  2. 79 Saudi Arabia 9,858 million SLC compare
  3. 80 Dominican Republic 9,819 million SLC compare
  4. 82 Nicaragua 8,852 million SLC compare
  5. 83 Ghana 8,699 million SLC compare
  6. 84 Canada 8,105 million SLC compare

See the full ranking of 194 places →

More environment data for Sudan

All data for Sudan →

Frequently asked questions

What is gross fixed capital formation (agriculture, forestry and fishing) in Sudan?
Gross fixed capital formation (agriculture, forestry and fishing) in Sudan was 9,390 million SLC in 2022, according to Food and Agriculture Organization of the United Nations.
What is the highest gross fixed capital formation (agriculture, forestry and fishing) recorded in Sudan?
The highest recorded value was 17,209 million SLC in 2016.
What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Sudan?
The lowest recorded value was 5,845 million SLC in 2018.
How does Sudan rank for gross fixed capital formation (agriculture, forestry and fishing)?
Sudan ranks 81st out of 181 countries with data for 2022.
Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Sudan?
Over the last ten years it is down 18.6%. The long-run trend across the full record is falling.
Where does this Sudan 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 — 15 observations, free to reuse under CC BY-NC-SA 3.0 IGO (FAO).

Share, cite or embed this page

Cite this page

Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Sudan. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 31 August 2026, from https://environment.statizoid.com/stat/gross-fixed-capital-formation-agriculture-forestry-and-fishing-value-standard-local-2/sudan/

Embed or link this data

Paste this into a page to link back to these figures. The data itself is free to reuse under CC BY-NC-SA 3.0 IGO (FAO); please keep the attribution.

<a href="https://environment.statizoid.com/stat/gross-fixed-capital-formation-agriculture-forestry-and-fishing-value-standard-local-2/sudan/">Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Sudan</a> — Statizoid

About this data

Indicator
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Value Standard Local Currency, 2015 prices
Unit
million SLC
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
194 places, 5,526 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.