Germany vs Northern America: Consumption of Fixed Capital (Agriculture, Forestry and Fishing)

Germany
12,203 million USD
in 2023
Northern America
52,319 million USD
in 2023
Germany rank
9th
Northern America rank
6th

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

  • Germany
  • Northern America
020.0k40.0k60.0k199520092023

How they compare

Northern America currently reports 52,319 million USD against 12,203 million USD in Germany, a difference of 40,116 million USD.

That makes Northern America's figure about 4.3 times Germany's.

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

Germany ranks 9th and Northern America ranks 6th of 182 countries.

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

Head to head by decade

Decade Germany Northern America Difference Ahead
1990s 8,975 million USD 32,100 million USD 23,125 million USD Northern America
2000s 10,215 million USD 39,080 million USD 28,865 million USD Northern America
2010s 11,443 million USD 54,432 million USD 42,989 million USD Northern America
2020s 11,666 million USD 57,232 million USD 45,566 million USD Northern America

Averages of every year both report within each decade.

Frequently asked questions

Which has higher consumption of fixed capital (agriculture, forestry and fishing), Germany or Northern America?
Northern America, at 52,319 million USD against 12,203 million USD in Germany as of 2023.
What is the difference in consumption of fixed capital (agriculture, forestry and fishing) between Germany and Northern America?
40,116 million USD, with Northern America ahead.
How many years of comparable data are there for Germany and Northern America?
29 years are reported by both, from 1995 to 2023.
How do Germany and Northern America rank globally for consumption of fixed capital (agriculture, forestry and fishing)?
Germany ranks 9th and Northern America ranks 6th of 182 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$, 2015 prices. Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Germany vs Northern America: 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-2015-prices/germany/northern-america/

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<a href="https://environment.statizoid.com/compare/consumption-of-fixed-capital-agriculture-forestry-and-fishing-value-us-2015-prices/germany/northern-america/">Germany vs Northern America: Consumption of Fixed Capital (Agriculture, Forestry and Fishing)</a> — Statizoid

About this data

Indicator
Consumption of Fixed Capital (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
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.