Japan vs Net Food Importing Developing Countries (NFIDCs): Gross Fixed Capital Formation (Agriculture, Forestry and Fishing)

Japan
10,095 million USD
in 2023
Net Food Importing Developing Countries (NFIDCs)
46,024 million USD
in 2023
Japan rank
12th
Net Food Importing Developing Countries (NFIDCs) rank
12th

Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) over time

  • Japan
  • Net Food Importing Developing Countries (NFIDCs)
10.0k20.0k30.0k40.0k50.0k199520092023

How they compare

Net Food Importing Developing Countries (NFIDCs) currently reports 46,024 million USD against 10,095 million USD in Japan, a difference of 35,929 million USD.

That makes Net Food Importing Developing Countries (NFIDCs)'s figure about 4.6 times Japan's.

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

Japan ranks 12th and Net Food Importing Developing Countries (NFIDCs) ranks 12th of 182 countries.

Across the 4 decades both report, Japan averaged higher in 2 and Net Food Importing Developing Countries (NFIDCs) in 2.

Head to head by decade

Decade Japan Net Food Importing Developing Countries (NFIDCs) Difference Ahead
1990s 31,321 million USD 10,232 million USD 21,090 million USD Japan
2000s 17,680 million USD 13,766 million USD 3,915 million USD Japan
2010s 15,525 million USD 32,816 million USD 17,290 million USD Net Food Importing Developing Countries (NFIDCs)
2020s 11,960 million USD 43,001 million USD 31,041 million USD Net Food Importing Developing Countries (NFIDCs)

Averages of every year both report within each decade.

Frequently asked questions

Which has higher gross fixed capital formation (agriculture, forestry and fishing), Japan or Net Food Importing Developing Countries (NFIDCs)?
Net Food Importing Developing Countries (NFIDCs), at 46,024 million USD against 10,095 million USD in Japan as of 2023.
What is the difference in gross fixed capital formation (agriculture, forestry and fishing) between Japan and Net Food Importing Developing Countries (NFIDCs)?
35,929 million USD, with Net Food Importing Developing Countries (NFIDCs) ahead.
How many years of comparable data are there for Japan and Net Food Importing Developing Countries (NFIDCs)?
29 years are reported by both, from 1995 to 2023.
How do Japan and Net Food Importing Developing Countries (NFIDCs) rank globally for gross fixed capital formation (agriculture, forestry and fishing)?
Japan ranks 12th and Net Food Importing Developing Countries (NFIDCs) ranks 12th of 182 countries.
Where does this data come from?
Food and Agriculture Organization of the United Nations, published as Gross Fixed Capital Formation (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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Japan vs Net Food Importing Developing Countries (NFIDCs): Gross Fixed Capital Formation (Agriculture, Forestry and Fishing). Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 03 September 2026, from https://environment.statizoid.com/compare/gross-fixed-capital-formation-agriculture-forestry-and-fishing-value-us/japan/net-food-importing-developing-countries-nfidcs/

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About this data

Indicator
Gross Fixed Capital Formation (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, 6,512 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.