FORECAST MODELING OF FOREIGN TRADE IN AGRICULTURAL COMPLEX PRODUCTS BETWEEN UKRAINE AND ROMANIA
The article presents forecast modeling of foreign trade between Ukraine and Romania by separate groups of agro-industrial goods. Indicators were forecast for three years (2022-2024) based on actual data for eleven years (2011-2021). Five trend models (exponential, linear, logarithmic, polynomial, an...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
University of Agricultural Sciences and Veterinary Medicine, Bucharest
2022-01-01
|
| Series: | Scientific Papers Series : Management, Economic Engineering in Agriculture and Rural Development |
| Online Access: | https://managementjournal.usamv.ro/pdf/vol.22_3/Art86.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The article presents forecast modeling of foreign trade between Ukraine and Romania by separate groups of agro-industrial goods. Indicators were forecast for three years (2022-2024) based on actual data for eleven years (2011-2021). Five trend models (exponential, linear, logarithmic, polynomial, and power) were constructed for each indicator and only one with the highest value of the reliability of the approximation R² was selected. The constructed trend models indicate a positive trend in 2022-2024 for preparations of grains, cocoa and cocoa preparations, sugar and sugar confectionery, animal or plant fats and oils; in 2023-2024 – for meat and meat preparations, alcoholic and non-alcoholic beverages, vinegar. At the same time, the forecast models indicate an increase in imports of tobacco and its industrial substitutes in 2023-2024, a decrease in imports of cereals over the same period, an increase in imports of other mixed foodstuffs in 2022-2024. Of the nine selected models, six are polynomial, one is power, one is logarithmic, and one is exponential. Two of them have a very high degree of reliability of the approximation R² (>0.9) and, accordingly, a high probability of forecast prediction. |
|---|---|
| ISSN: | 2284-7995 2285-3952 |