Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Pakistan
Pakistan: Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) was 8,919 million USD in 2023. ▲ Rising
Gross Fixed Capital Formation (Agriculture, Forestry and Fishing) in Pakistan, 1995–2023
Source: Food and Agriculture Organization of the United Nations. Measured in million USD.
Analysis
Pakistan recorded 8,919 million USD for gross fixed capital formation (agriculture, forestry and fishing) in 2023.
That represents a change of down 7.8% on the previous year and up 13.0% over ten years.
Over the whole period, gross fixed capital formation (agriculture, forestry and fishing) in Pakistan peaked at 9,947 million USD in 2021 and was at its lowest, 4,899 million USD, in 2004.
Pakistan ranks 13th of 182 countries on this measure, 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 Pakistan, year by year
| Year | million USD | Change |
|---|---|---|
| 1995 | 7,908 million USD | — |
| 1996 | 7,619 million USD | -3.6% |
| 1997 | 5,043 million USD | -33.8% |
| 1998 | 5,134 million USD | +1.8% |
| 1999 | 6,286 million USD | +22.4% |
| 2000 | 6,228 million USD | -0.9% |
| 2001 | 5,334 million USD | -14.3% |
| 2002 | 5,339 million USD | +0.1% |
| 2003 | 5,583 million USD | +4.6% |
| 2004 | 4,899 million USD | -12.3% |
| 2005 | 6,903 million USD | +40.9% |
| 2006 | 6,455 million USD | -6.5% |
| 2007 | 6,665 million USD | +3.3% |
| 2008 | 6,402 million USD | -3.9% |
| 2009 | 6,636 million USD | +3.6% |
| 2010 | 7,295 million USD | +9.9% |
| 2011 | 7,541 million USD | +3.4% |
| 2012 | 7,608 million USD | +0.9% |
| 2013 | 7,891 million USD | +3.7% |
| 2014 | 7,653 million USD | -3.0% |
| 2015 | 8,491 million USD | +11.0% |
| 2016 | 8,938 million USD | +5.3% |
| 2017 | 9,210 million USD | +3.0% |
| 2018 | 9,549 million USD | +3.7% |
| 2019 | 9,174 million USD | -3.9% |
| 2020 | 9,125 million USD | -0.5% |
| 2021 | 9,947 million USD | +9.0% |
| 2022 | 9,670 million USD | -2.8% |
| 2023 | 8,919 million USD | -7.8% |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1990s | 6,398 million USD | 5,043 million USD | 7,908 million USD | 5 |
| 2000s | 6,044 million USD | 4,899 million USD | 6,903 million USD | 10 |
| 2010s | 8,335 million USD | 7,295 million USD | 9,549 million USD | 10 |
| 2020s | 9,415 million USD | 8,919 million USD | 9,947 million USD | 4 |
Countries ranked near Pakistan
- 10 Germany 11,082 million USD compare
- 11 Bolivia (Plurinational State of) 698.09 million USD compare
- 11 Japan 10,400 million USD compare
- 12 Nigeria 9,663 million USD compare
- 12 Melanesia 567.17 million USD compare
- 13 Lao People's Democratic Republic 528.72 million USD compare
- 14 Brazil 8,865 million USD compare
- 14 Timor-Leste 24.48 million USD compare
- 15 Thailand 7,669 million USD compare
- 15 Polynesia 16.25 million USD compare
- 16 Canada 6,338 million USD compare
- 16 Micronesia 13.77 million USD compare
More environment data for Pakistan
- Historical exposure to drought — Land soil moisture anomaly -10.53 Percentage change (2025)
- Historical exposure to drought — Cropland soil moisture anomaly -7.64 Percentage change (2025)
- Standard Deviation, annual growth rate 0 % change on previous year (2025)
- Standard Deviation 0.373 °C (2025)
- Temperature change 1.58 °C (2025)
- Sawnwood — Export quantity, per unit of GDP 0 m3 per US$ of GDP (2024)
- Sawnwood — Export quantity, per capita 0 m3 per person (2024)
- Sawnwood — Export value, annual growth rate 0 % change on previous year (2024)
- Sawnwood — Export value, per unit of GDP 0 1000 USD per US$ of GDP (2024)
- Sawnwood — Export value, per capita 0 1000 USD per person (2024)
Frequently asked questions
- What is gross fixed capital formation (agriculture, forestry and fishing) in Pakistan?
- Gross fixed capital formation (agriculture, forestry and fishing) in Pakistan was 8,919 million USD 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 Pakistan?
- The highest recorded value was 9,947 million USD in 2021.
- What is the lowest gross fixed capital formation (agriculture, forestry and fishing) recorded in Pakistan?
- The lowest recorded value was 4,899 million USD in 2004.
- How does Pakistan rank for gross fixed capital formation (agriculture, forestry and fishing)?
- Pakistan ranks 13th out of 182 countries with data for 2023.
- Is gross fixed capital formation (agriculture, forestry and fishing) rising or falling in Pakistan?
- Over the last ten years it is up 13.0%. The long-run trend across the full record is rising.
- Where does this Pakistan 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) — Value US$, 2015 prices. Statizoid updates them automatically from the source API.
Download this data
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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.