Italy vs Melanesia: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$

Italy
176,700 million USD
in 2023
Melanesia
9,308 million USD
in 2023
Italy rank
7th
Melanesia rank
9th

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

  • Italy
  • Melanesia
050.0k100.0k150.0k200.0k250.0k199520092023

How they compare

Italy currently reports 176,700 million USD against 9,308 million USD in Melanesia, a difference of 167,392 million USD.

That makes Italy's figure about 19.0 times Melanesia's.

Across all 29 years both countries report, Italy has been ahead every year.

Italy ranks 7th and Melanesia ranks 9th of 180 countries.

Italy has averaged higher in every one of the 4 decades both report.

Head to head by decade

Decade Italy Melanesia Difference Ahead
1990s 155,772 million USD 1,574 million USD 154,198 million USD Italy
2000s 188,284 million USD 2,141 million USD 186,143 million USD Italy
2010s 201,064 million USD 5,276 million USD 195,787 million USD Italy
2020s 178,292 million USD 8,082 million USD 170,209 million USD Italy

Averages of every year both report within each decade.

Frequently asked questions

Which has higher net capital stocks (agriculture, forestry and fishing) — value us$, Italy or Melanesia?
Italy, at 176,700 million USD against 9,308 million USD in Melanesia as of 2023.
What is the difference in net capital stocks (agriculture, forestry and fishing) — value us$ between Italy and Melanesia?
167,392 million USD, with Italy ahead.
How many years of comparable data are there for Italy and Melanesia?
29 years are reported by both, from 1995 to 2023.
How do Italy and Melanesia rank globally for net capital stocks (agriculture, forestry and fishing) — value us$?
Italy ranks 7th and Melanesia ranks 9th of 180 countries.
Where does this data come from?
Food and Agriculture Organization of the United Nations, published as Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$. Statizoid refreshes it automatically from the source and publishes the full history for both places.

Individual pages

Share, cite or embed this page

Cite this page

Italy vs Melanesia: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 10 September 2026, from https://environment.statizoid.com/compare/net-capital-stocks-agriculture-forestry-and-fishing-value-us/italy/melanesia/

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/compare/net-capital-stocks-agriculture-forestry-and-fishing-value-us/italy/melanesia/">Italy vs Melanesia: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$</a> — Statizoid

About this data

Indicator
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$
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.