Seychelles vs Saint Lucia: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$

Seychelles
29.76 million USD
in 2023
Saint Lucia
38.13 million USD
in 2023
Seychelles rank
166th
Saint Lucia rank
165th

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

  • Seychelles
  • Saint Lucia
010203040199520092023

How they compare

Saint Lucia currently reports 38.13 million USD against 29.76 million USD in Seychelles, a difference of 8.37 million USD.

That makes Saint Lucia's figure about 1.3 times Seychelles's.

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

Seychelles ranks 166th and Saint Lucia ranks 165th of 180 countries.

Across the 4 decades both report, Seychelles averaged higher in 1 and Saint Lucia in 3.

Head to head by decade

Decade Seychelles Saint Lucia Difference Ahead
1990s 34.39 million USD 32.67 million USD 1.72 million USD Seychelles
2000s 34.56 million USD 39.35 million USD 4.79 million USD Saint Lucia
2010s 30.84 million USD 43.78 million USD 12.94 million USD Saint Lucia
2020s 30.27 million USD 39.41 million USD 9.14 million USD Saint Lucia

Averages of every year both report within each decade.

Frequently asked questions

Which has higher net capital stocks (agriculture, forestry and fishing) — value us$, Seychelles or Saint Lucia?
Saint Lucia, at 38.13 million USD against 29.76 million USD in Seychelles as of 2023.
What is the difference in net capital stocks (agriculture, forestry and fishing) — value us$ between Seychelles and Saint Lucia?
8.37 million USD, with Saint Lucia ahead.
How many years of comparable data are there for Seychelles and Saint Lucia?
29 years are reported by both, from 1995 to 2023.
How do Seychelles and Saint Lucia rank globally for net capital stocks (agriculture, forestry and fishing) — value us$?
Seychelles ranks 166th and Saint Lucia ranks 165th of 180 countries.
Where does this data come from?
Food and Agriculture Organization of the United Nations, published as Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$, 2015 prices. Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Seychelles vs Saint Lucia: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 12 September 2026, from https://environment.statizoid.com/compare/net-capital-stocks-agriculture-forestry-and-fishing-value-us-2015-prices/seychelles/st-lucia/

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<a href="https://environment.statizoid.com/compare/net-capital-stocks-agriculture-forestry-and-fishing-value-us-2015-prices/seychelles/st-lucia/">Seychelles vs Saint Lucia: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$</a> — Statizoid

About this data

Indicator
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$, 2015 prices
Unit
million USD
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
226 places, 6,479 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.