Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Montenegro

Montenegro: Consumption of Fixed Capital (Agriculture, Forestry and Fishing) was 42.28 million USD in 2023. ▲ Rising

Latest (2023)
42.28 million USD
Change on year
up 20.9%
World rank
133rd
of 182 countries
All-time high
42.28 million USD
in 2023
All-time low
10.53 million USD
in 2002
Years of data
24
2000–2023

Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Montenegro, 2000–2023

102030402000201120232000: 14.1 million USD2001: 13.8 million USD2002: 10.5 million USD2003: 15.5 million USD2004: 22.7 million USD2005: 22.9 million USD2006: 24 million USD2007: 26.3 million USD2008: 30.4 million USD2009: 28.2 million USD2010: 27.9 million USD2011: 30.2 million USD2012: 28.6 million USD2013: 29.2 million USD2014: 29.6 million USD2015: 25.3 million USD2016: 24.8 million USD2017: 26.1 million USD2018: 29 million USD2019: 28.6 million USD2020: 29.5 million USD2021: 33.4 million USD2022: 35 million USD2023: 42.3 million USD

Source: Food and Agriculture Organization of the United Nations. Measured in million USD.

Analysis

The most recent figure for consumption of fixed capital (agriculture, forestry and fishing) in Montenegro is 42.28 million USD, measured in 2023. That is the highest value across all 24 years on record.

The figure is up 20.9% on the previous year and up 44.7% over ten years.

Over the whole period, consumption of fixed capital (agriculture, forestry and fishing) in Montenegro peaked at 42.28 million USD in 2023 and was at its lowest, 10.53 million USD, in 2002.

Montenegro ranks 133rd of 182 countries on this measure, in the middle of the range.

The long-run direction has been consistently rising across the 24 years of available data.

Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Montenegro, year by year

Annual values for Consumption of Fixed Capital (Agriculture, Forestry and Fishing) — Value US$ in Montenegro, 2000 to 2023.
Year million USD Change
2000 14.06 million USD
2001 13.84 million USD -1.6%
2002 10.53 million USD -23.9%
2003 15.54 million USD +47.5%
2004 22.69 million USD +46.0%
2005 22.87 million USD +0.8%
2006 24 million USD +4.9%
2007 26.33 million USD +9.7%
2008 30.4 million USD +15.4%
2009 28.21 million USD -7.2%
2010 27.91 million USD -1.1%
2011 30.21 million USD +8.3%
2012 28.6 million USD -5.3%
2013 29.23 million USD +2.2%
2014 29.59 million USD +1.2%
2015 25.27 million USD -14.6%
2016 24.84 million USD -1.7%
2017 26.08 million USD +5.0%
2018 28.99 million USD +11.1%
2019 28.63 million USD -1.2%
2020 29.47 million USD +2.9%
2021 33.41 million USD +13.4%
2022 34.96 million USD +4.6%
2023 42.28 million USD +20.9%

Averages by decade

DecadeAverage LowestHighest Years
2000s 20.85 million USD 10.53 million USD 30.4 million USD 10
2010s 27.93 million USD 24.84 million USD 30.21 million USD 10
2020s 35.03 million USD 29.47 million USD 42.28 million USD 4

Countries ranked near Montenegro

  1. 130 Honduras 47.24 million USD compare
  2. 131 Egypt 46.99 million USD compare
  3. 132 Eswatini 44.73 million USD compare
  4. 134 Burundi 35.22 million USD compare
  5. 134 Gabon 35.22 million USD compare
  6. 136 Solomon Islands 35.12 million USD compare

See the full ranking of 228 places →

More environment data for Montenegro

All data for Montenegro →

Frequently asked questions

What is consumption of fixed capital (agriculture, forestry and fishing) in Montenegro?
Consumption of fixed capital (agriculture, forestry and fishing) in Montenegro was 42.28 million USD in 2023, according to Food and Agriculture Organization of the United Nations.
What is the highest consumption of fixed capital (agriculture, forestry and fishing) recorded in Montenegro?
The highest recorded value was 42.28 million USD in 2023.
What is the lowest consumption of fixed capital (agriculture, forestry and fishing) recorded in Montenegro?
The lowest recorded value was 10.53 million USD in 2002.
How does Montenegro rank for consumption of fixed capital (agriculture, forestry and fishing)?
Montenegro ranks 133rd out of 182 countries with data for 2023.
Is consumption of fixed capital (agriculture, forestry and fishing) rising or falling in Montenegro?
Over the last ten years it is up 44.7%. The long-run trend across the full record is rising.
Where does this Montenegro data come from?
The figures come from Food and Agriculture Organization of the United Nations, published as part of Consumption of Fixed Capital (Agriculture, Forestry and Fishing) — Value US$. Statizoid updates them automatically from the source API.

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Consumption of Fixed Capital (Agriculture, Forestry and Fishing) in Montenegro. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 04 September 2026, from https://environment.statizoid.com/stat/consumption-of-fixed-capital-agriculture-forestry-and-fishing-value-us/montenegro/

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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.