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

Polynesia
222.17 million USD
in 2023
Thailand
89,792 million USD
in 2023
Polynesia rank
15th
Thailand rank
13th

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

  • Polynesia
  • Thailand
020.0k40.0k60.0k80.0k199520092023

How they compare

Thailand currently reports 89,792 million USD against 222.17 million USD in Polynesia, a difference of 89,570 million USD.

That makes Thailand's figure about 404.2 times Polynesia's.

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

Polynesia ranks 15th and Thailand ranks 13th of 17 countries.

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

Head to head by decade

Decade Polynesia Thailand Difference Ahead
1990s 159.73 million USD 52,774 million USD 52,615 million USD Thailand
2000s 180.18 million USD 56,848 million USD 56,668 million USD Thailand
2010s 195.2 million USD 75,377 million USD 75,182 million USD Thailand
2020s 219.89 million USD 87,167 million USD 86,947 million USD Thailand

Averages of every year both report within each decade.

Frequently asked questions

Which has higher net capital stocks (agriculture, forestry and fishing) — value us$, Polynesia or Thailand?
Thailand, at 89,792 million USD against 222.17 million USD in Polynesia as of 2023.
What is the difference in net capital stocks (agriculture, forestry and fishing) — value us$ between Polynesia and Thailand?
89,570 million USD, with Thailand ahead.
How many years of comparable data are there for Polynesia and Thailand?
29 years are reported by both, from 1995 to 2023.
How do Polynesia and Thailand rank globally for net capital stocks (agriculture, forestry and fishing) — value us$?
Polynesia ranks 15th and Thailand ranks 13th of 17 countries.
Where does this data come from?
Food and Agriculture Organization of the United Nations, published as Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$, 2015 prices. Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Polynesia vs Thailand: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value US$. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 07 September 2026, from https://environment.statizoid.com/compare/net-capital-stocks-agriculture-forestry-and-fishing-value-us-2015-prices/polynesia/thailand/

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<a href="https://environment.statizoid.com/compare/net-capital-stocks-agriculture-forestry-and-fishing-value-us-2015-prices/polynesia/thailand/">Polynesia vs Thailand: 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.