Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Papua New Guinea
Papua New Guinea: Net Capital Stocks (Agriculture, Forestry and Fishing) — Value was 18,854 million SLC in 2023. ◆ Volatile
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Papua New Guinea, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million SLC.
Analysis
Papua New Guinea recorded 18,854 million SLC for net capital stocks (agriculture, forestry and fishing) — value in 2023. That is the highest value across all 29 years on record.
The figure is up 5.7% on the previous year and up 74.8% over ten years.
Over the whole period, net capital stocks (agriculture, forestry and fishing) — value in Papua New Guinea peaked at 18,854 million SLC in 2023 and was at its lowest, 2,356 million SLC, in 1995.
That places Papua New Guinea 105th out of 179 countries with data for 2023, putting it in the middle of the range.
The series is highly variable year to year, so single readings are best treated with caution.
Net Capital Stocks (Agriculture, Forestry and Fishing) — Value in Papua New Guinea, year by year
| Year | million SLC | Change |
|---|---|---|
| 1995 | 2,356 million SLC | — |
| 1996 | 2,540 million SLC | +7.8% |
| 1997 | 2,724 million SLC | +7.3% |
| 1998 | 2,949 million SLC | +8.2% |
| 1999 | 3,238 million SLC | +9.8% |
| 2000 | 3,597 million SLC | +11.1% |
| 2001 | 3,968 million SLC | +10.3% |
| 2002 | 4,393 million SLC | +10.7% |
| 2003 | 4,793 million SLC | +9.1% |
| 2004 | 5,162 million SLC | +7.7% |
| 2005 | 5,557 million SLC | +7.6% |
| 2006 | 5,939 million SLC | +6.9% |
| 2007 | 6,348 million SLC | +6.9% |
| 2008 | 6,815 million SLC | +7.4% |
| 2009 | 7,419 million SLC | +8.9% |
| 2010 | 8,115 million SLC | +9.4% |
| 2011 | 8,955 million SLC | +10.4% |
| 2012 | 9,847 million SLC | +10.0% |
| 2013 | 10,783 million SLC | +9.5% |
| 2014 | 11,750 million SLC | +9.0% |
| 2015 | 12,389 million SLC | +5.4% |
| 2016 | 13,078 million SLC | +5.6% |
| 2017 | 13,810 million SLC | +5.6% |
| 2018 | 14,518 million SLC | +5.1% |
| 2019 | 15,231 million SLC | +4.9% |
| 2020 | 16,079 million SLC | +5.6% |
| 2021 | 16,992 million SLC | +5.7% |
| 2022 | 17,834 million SLC | +5.0% |
| 2023 | 18,854 million SLC | +5.7% |
Papua New Guinea compared with similar countries
- Papua New Guinea's 18,854 million SLC is below the median for lower middle income countries, which is 149,162 million SLC, 13% of the median. (41 countries reporting)
- Papua New Guinea's 18,854 million SLC is below the median for East Asia & Pacific, which is 22,876 million SLC, 82% of the median. (23 countries reporting)
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 2,761 million SLC | 2,356 million SLC | 3,238 million SLC | 5 |
| 2000s | 5,399 million SLC | 3,597 million SLC | 7,419 million SLC | 10 |
| 2010s | 11,848 million SLC | 8,115 million SLC | 15,231 million SLC | 10 |
| 2020s | 17,440 million SLC | 16,079 million SLC | 18,854 million SLC | 4 |
Countries ranked near Papua New Guinea
- 102 Turkmenistan 23,402 million SLC compare
- 103 New Caledonia 22,876 million SLC compare
- 104 Namibia 19,982 million SLC compare
- 106 Zambia 18,456 million SLC compare
- 107 Finland 18,295 million SLC compare
- 108 Tajikistan 17,486 million SLC compare
More environment data for Papua New Guinea
- Historical exposure to drought — Land soil moisture anomaly 1.56 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly 2.24 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.183 °C (2025)
- Temperature change 0.834 °C (2025)
- Nutrient nitrogen N (total) — Export quantity, gaps filled 0 t (2024)
- Nutrient nitrogen N (total) — Agricultural Use, gaps filled 31,843 t (2024)
- Nutrient nitrogen N (total) — Agricultural Use, annual growth rate 26.29 % change on previous year (2024)
- Nutrient phosphate P2O5 (total) — Import quantity, gaps filled 4,359 t (2024)
- Nutrient phosphate P2O5 (total) — Import quantity, annual growth rate 80.27 % change on previous year (2024)
Frequently asked questions
- What is net capital stocks (agriculture, forestry and fishing) — value in Papua New Guinea?
- Net capital stocks (agriculture, forestry and fishing) — value in Papua New Guinea was 18,854 million SLC in 2023, according to Food and Agriculture Organization of the United Nations.
- What is the highest net capital stocks (agriculture, forestry and fishing) — value recorded in Papua New Guinea?
- The highest recorded value was 18,854 million SLC in 2023.
- What is the lowest net capital stocks (agriculture, forestry and fishing) — value recorded in Papua New Guinea?
- The lowest recorded value was 2,356 million SLC in 1995.
- How does Papua New Guinea rank for net capital stocks (agriculture, forestry and fishing) — value?
- Papua New Guinea ranks 105th out of 179 countries with data for 2023.
- Is net capital stocks (agriculture, forestry and fishing) — value rising or falling in Papua New Guinea?
- Over the last ten years it is up 74.8%. The long-run trend across the full record is volatile.
- 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 Net Capital Stocks (Agriculture, Forestry and Fishing) — Value Standard Local Currency, 2015 prices. Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 29 observations, free to reuse under CC BY-NC-SA 3.0 IGO (FAO).
About this data
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.