Micronesia vs Republic of Korea: Consumption of Fixed Capital (Agriculture, Forestry and Fishing)

Micronesia
15.34 million USD
in 2023
Republic of Korea
6,736 million USD
in 2023
Micronesia rank
16th
Republic of Korea rank
13th

Consumption of Fixed Capital (Agriculture, Forestry and Fishing) over time

  • Micronesia
  • Republic of Korea
02.0k4.0k6.0k199520092023

How they compare

Republic of Korea currently reports 6,736 million USD against 15.34 million USD in Micronesia, a difference of 6,721 million USD.

That makes Republic of Korea's figure about 439.1 times Micronesia's.

Across all 29 years both countries report, Republic of Korea has been ahead every year.

Micronesia ranks 16th and Republic of Korea ranks 13th of 17 countries.

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

Head to head by decade

Decade Micronesia Republic of Korea Difference Ahead
1990s 4.37 million USD 3,697 million USD 3,692 million USD Republic of Korea
2000s 6.11 million USD 4,295 million USD 4,289 million USD Republic of Korea
2010s 10.33 million USD 4,385 million USD 4,374 million USD Republic of Korea
2020s 13.69 million USD 5,292 million USD 5,278 million USD Republic of Korea

Averages of every year both report within each decade.

Frequently asked questions

Which has higher consumption of fixed capital (agriculture, forestry and fishing), Micronesia or Republic of Korea?
Republic of Korea, at 6,736 million USD against 15.34 million USD in Micronesia as of 2023.
What is the difference in consumption of fixed capital (agriculture, forestry and fishing) between Micronesia and Republic of Korea?
6,721 million USD, with Republic of Korea ahead.
How many years of comparable data are there for Micronesia and Republic of Korea?
29 years are reported by both, from 1995 to 2023.
How do Micronesia and Republic of Korea rank globally for consumption of fixed capital (agriculture, forestry and fishing)?
Micronesia ranks 16th and Republic of Korea ranks 13th of 17 countries.
Where does this data come from?
Food and Agriculture Organization of the United Nations, published as Consumption of Fixed Capital (Agriculture, Forestry and Fishing) — Value US$. Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Micronesia vs Republic of Korea: Consumption of Fixed Capital (Agriculture, Forestry and Fishing). Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 14 September 2026, from https://environment.statizoid.com/compare/consumption-of-fixed-capital-agriculture-forestry-and-fishing-value-us/micronesia/republic-of-korea/

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<a href="https://environment.statizoid.com/compare/consumption-of-fixed-capital-agriculture-forestry-and-fishing-value-us/micronesia/republic-of-korea/">Micronesia vs Republic of Korea: Consumption of Fixed Capital (Agriculture, Forestry and Fishing)</a> — Statizoid

About this data

Indicator
Consumption of Fixed Capital (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
228 places, 6,497 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.