Eritrea vs Hungary: Cereals n.e.c. — Gross Production Value
Eritrea
829,608 1000 SLC
in 2024
Hungary
1.01 million 1000 SLC
in 2017
Eritrea rank
11th
Hungary rank
10th
Cereals n.e.c. — Gross Production Value over time
- Eritrea
- Hungary
How they compare
Hungary currently reports 1.01 million 1000 SLC against 829,608 1000 SLC in Eritrea, a difference of 175,832 1000 SLC.
That makes Hungary's figure about 1.2 times Eritrea's.
The two have swapped places 2 times across 18 shared years of data; in 1993 it was Hungary ahead.
Eritrea ranks 11th and Hungary ranks 10th of 43 countries.
Across the 3 decades both report, Eritrea averaged higher in 2 and Hungary in 1.
Head to head by decade
| Decade | Eritrea | Hungary | Difference | Ahead |
|---|---|---|---|---|
| 1990s | 208,891 1000 SLC | 504,456 1000 SLC | 295,564 1000 SLC | Hungary |
| 2000s | 498,887 1000 SLC | 115,370 1000 SLC | 383,517 1000 SLC | Eritrea |
| 2010s | 768,278 1000 SLC | 431,838 1000 SLC | 336,440 1000 SLC | Eritrea |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher cereals n.e.c. — gross production value, Eritrea or Hungary?
- Hungary, at 1.01 million 1000 SLC against 829,608 1000 SLC in Eritrea as of 2017.
- What is the difference in cereals n.e.c. — gross production value between Eritrea and Hungary?
- 175,832 1000 SLC, with Hungary ahead.
- How many years of comparable data are there for Eritrea and Hungary?
- 18 years are reported by both, from 1993 to 2017.
- How do Eritrea and Hungary rank globally for cereals n.e.c. — gross production value?
- Eritrea ranks 11th and Hungary ranks 10th of 43 countries.
- Where does this data come from?
- Food and Agriculture Organization of the United Nations, published as Cereals n.e.c. — Gross Production Value (constant 2014-2016 thousand SLC). Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
The domain provides detailed data on the value of agricultural production that is calculated by the agricultural production data and the price data at farm gate. Thus, the value of production measures the agricultural production in monetary terms at the farm gate level.