Central African Republic vs Morocco: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value

Central African Republic
281,532 million SLC
in 2023
Morocco
337,264 million SLC
in 2023
Central African Republic rank
64th
Morocco rank
63rd

Net Capital Stocks (Agriculture, Forestry and Fishing) — Value over time

  • Central African Republic
  • Morocco
100.0k200.0k300.0k400.0k199520092023

How they compare

Morocco currently reports 337,264 million SLC against 281,532 million SLC in Central African Republic, a difference of 55,732 million SLC.

That makes Morocco's figure about 1.2 times Central African Republic's.

The two have swapped places 1 time across 29 shared years of data; in 1995 it was Central African Republic ahead.

Central African Republic ranks 64th and Morocco ranks 63rd of 179 countries.

Across the 4 decades both report, Central African Republic averaged higher in 3 and Morocco in 1.

Head to head by decade

Decade Central African Republic Morocco Difference Ahead
1990s 164,646 million SLC 105,241 million SLC 59,405 million SLC Central African Republic
2000s 206,142 million SLC 139,873 million SLC 66,268 million SLC Central African Republic
2010s 340,861 million SLC 224,375 million SLC 116,486 million SLC Central African Republic
2020s 270,041 million SLC 312,008 million SLC 41,967 million SLC Morocco

Averages of every year both report within each decade.

Frequently asked questions

Which has higher net capital stocks (agriculture, forestry and fishing) — value, Central African Republic or Morocco?
Morocco, at 337,264 million SLC against 281,532 million SLC in Central African Republic as of 2023.
What is the difference in net capital stocks (agriculture, forestry and fishing) — value between Central African Republic and Morocco?
55,732 million SLC, with Morocco ahead.
How many years of comparable data are there for Central African Republic and Morocco?
29 years are reported by both, from 1995 to 2023.
How do Central African Republic and Morocco rank globally for net capital stocks (agriculture, forestry and fishing) — value?
Central African Republic ranks 64th and Morocco ranks 63rd of 179 countries.
Where does this data come from?
Food and Agriculture Organization of the United Nations, published as Net Capital Stocks (Agriculture, Forestry and Fishing) — Value Standard Local Currency. Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Central African Republic vs Morocco: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 15 September 2026, from https://environment.statizoid.com/compare/net-capital-stocks-agriculture-forestry-and-fishing-value-standard-local-currency/central-african-republic/morocco/

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About this data

Indicator
Net Capital Stocks (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
192 places, 5,493 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.