Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Papua New Guinea

Papua New Guinea: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 20.3 % in 2023. ▲ Rising

Latest (2023)
20.3 %
Change on year
up 17.3%
World rank
5th
of 182 countries
All-time high
20.3 %
in 2023
All-time low
7.5 %
in 2012
Years of data
29
1995–2023

Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Papua New Guinea, 1995–2023

051015201995200920231995: 9.3 %1996: 10 %1997: 12.1 %1998: 12.1 %1999: 13.8 %2000: 9.6 %2001: 9.4 %2002: 10.3 %2003: 11.5 %2004: 10.8 %2005: 10.8 %2006: 11.8 %2007: 11.4 %2008: 12.2 %2009: 9.8 %2010: 8.2 %2011: 7.7 %2012: 7.5 %2013: 7.9 %2014: 8.1 %2015: 16.7 %2016: 17.4 %2017: 17.6 %2018: 16.7 %2019: 16.3 %2020: 18.7 %2021: 19.4 %2022: 17.3 %2023: 20.3 %

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

Analysis

Papua New Guinea recorded 20.3 % for gross fixed capital formation (agriculture, forestry and fishing) in 2023. That is the highest value across all 29 years on record.

Compared with earlier readings it is up 17.3% on the previous year and up 157.8% over ten years.

Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Papua New Guinea peaked at 20.3 % in 2023 and was at its lowest, 7.5 %, in 2012.

That places Papua New Guinea 5th out of 182 countries with data for 2023, putting it in the top 10%.

The long-run direction has been consistently rising across the 29 years of available data.

Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Papua New Guinea, year by year

Annual values for Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Share of Gross Fixed Capital Formation US$ in Papua New Guinea, 1995 to 2023.
Year % Change
1995 9.3 %
1996 10 % +7.5%
1997 12.12 % +21.2%
1998 12.1 % -0.2%
1999 13.77 % +13.8%
2000 9.65 % -29.9%
2001 9.41 % -2.4%
2002 10.34 % +9.9%
2003 11.47 % +10.9%
2004 10.78 % -6.0%
2005 10.78 % +0.0%
2006 11.77 % +9.1%
2007 11.4 % -3.2%
2008 12.16 % +6.7%
2009 9.78 % -19.6%
2010 8.16 % -16.5%
2011 7.73 % -5.3%
2012 7.5 % -3.0%
2013 7.87 % +5.0%
2014 8.14 % +3.4%
2015 16.68 % +104.9%
2016 17.37 % +4.2%
2017 17.56 % +1.1%
2018 16.74 % -4.7%
2019 16.26 % -2.8%
2020 18.68 % +14.9%
2021 19.41 % +3.9%
2022 17.31 % -10.8%
2023 20.3 % +17.3%

Averages by decade

DecadeAverage LowestHighest Years
1990s 11.46 % 9.3 % 13.77 % 5
2000s 10.75 % 9.41 % 12.16 % 10
2010s 12.4 % 7.5 % 17.56 % 10
2020s 18.93 % 17.31 % 20.3 % 4

Countries ranked near Papua New Guinea

  1. 2 Bolivia (Plurinational State of) 9.28 % compare
  2. 2 Guinea-Bissau 25.21 % compare
  3. 3 Comoros 23.03 % compare
  4. 3 Lao People's Democratic Republic 8.63 % compare
  5. 4 Côte d'Ivoire 7.35 % compare
  6. 4 Pakistan 21.87 % compare
  7. 4 Melanesia 8.58 % compare
  8. 5 Timor-Leste 7.22 % compare
  9. 6 Belarus 17.56 % compare
  10. 6 Viet Nam 6.76 % compare
  11. 7 Ghana 16.42 % compare
  12. 7 Micronesia (Federated States of) 6.56 % compare
  13. 8 Afghanistan 16.17 % compare

See the full ranking of 228 places →

More environment data for Papua New Guinea

All data for Papua New Guinea →

Frequently asked questions

What is gross fixed capital formation (agriculture, forestry and fishing) in Papua New Guinea?
Gross fixed capital formation (agriculture, forestry and fishing) in Papua New Guinea was 20.3 % in 2023, according to Food and Agriculture Organization of the United Nations.
What is the highest gross fixed capital formation (agriculture, forestry and fishing) recorded in Papua New Guinea?
The highest recorded value was 20.3 % in 2023.
What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Papua New Guinea?
The lowest recorded value was 7.5 % in 2012.
How does Papua New Guinea rank for gross fixed capital formation (agriculture, forestry and fishing)?
Papua New Guinea ranks 5th out of 182 countries with data for 2023.
Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Papua New Guinea?
Over the last ten years it is up 157.8%. The long-run trend across the full record is rising.
Where does this Papua New Guinea data come from?
The figures come from Food and Agriculture Organization of the United Nations, published as part of Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Share of Gross Fixed Capital Formation US$. Statizoid updates them automatically from the source API.

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Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Papua New Guinea. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 10 September 2026, from https://environment.statizoid.com/stat/gross-fixed-capital-formation-agriculture-forestry-and-fishing-share-of-gross-fixed/papua-new-guinea/

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About this data

Indicator
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) — Share of Gross Fixed Capital Formation US$
Unit
%
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.