New domestic agricultural machinery acquired over the year (continued)
Annually, agricultural producers acquire new domestically produced machinery, including combine harvesters and windrowers. The table provides a breakdown by specific types of equipment, with rows categorizing data for the Russian Federation as a whole and by individual federal districts. The information covers a wide range of items, from combines to harvesters, enabling an assessment of procurement structure
Chart of new domestic agricultural machinery purchase volumes by type and region
Set in numbers
Rosstat data. Rows: 57, indicators: 7. The breakdown is by positions: Russian Federation; Volga Federal District; Central Federal District; Voronezh Oblast; Moscow Oblast and others
The five largest values: Russian Federation (1 230), Volga Federal District (319), Central Federal District (271), Siberian Federal District (239), Southern Federal District (188). The gap between the largest and the smallest is 246 times. The top five account for 78.2% of the total for all positions — the distribution is heavily skewed towards the top
All table numbers are series: 57
| Series | Комбайны: — зерноуборочные | Комбайны: — кукурузоуборочные | Комбайны: — кормоуборочные | Комбайны: — льноуборочные | Комбайны: — картофелеуборочные | Свеклоуборочные машины (без ботвоуборочных) | Жатки валковые |
|---|---|---|---|---|---|---|---|
| Российская Федерация | 1 230,00 | 13,00 | 188,00 | — | 8,00 | 7,00 | 682,00 |
| Центральный федеральный округ | 271,00 | — | 35,00 | — | — | — | 125,00 |
| Белгородская область | 48,00 | — | — | — | — | — | 14,00 |
| Брянская область | 4,00 | — | — | — | — | — | — |
| Владимирская область | 6,00 | — | — | — | — | — | — |
| Воронежская область | 55,00 | — | 6,00 | — | — | — | 22,00 |
| Калужская область | — | — | — | — | — | — | 4,00 |
| Костромская область | — | — | 4,00 | — | — | — | — |
| Курская область | 10,00 | — | — | — | — | — | — |
| Липецкая область | 11,00 | — | — | — | — | — | — |
| Московская область | 5,00 | — | 3,00 | — | — | — | 8,00 |
| Орловская область | 33,00 | — | — | — | — | — | 17,00 |
| Рязанская область | 18,00 | — | 4,00 | — | — | — | 12,00 |
| Тамбовская область | 44,00 | — | 3,00 | — | — | — | 33,00 |
| Тульская область | 24,00 | — | — | — | — | — | — |
| Ярославская область | 3,00 | — | 5,00 | — | — | — | — |
| Северо-Западный федеральный округ | — | — | 18,00 | — | — | — | 4,00 |
| Вологодская область | — | — | 9,00 | — | — | — | 4,00 |
| Ленинградская область | — | — | 7,00 | — | — | — | — |
| Южный федеральный округ | 188,00 | — | 8,00 | — | — | — | 65,00 |
| Республика Калмыкия | 3,00 | — | — | — | — | — | — |
| Краснодарский край | 57,00 | — | 5,00 | — | — | — | 11,00 |
| Волгоградская область | 28,00 | — | — | — | — | — | 20,00 |
| Ростовская область | 95,00 | — | — | — | — | — | 30,00 |
| Северо-Кавказский федеральный округ | 93,00 | — | — | — | — | — | 34,00 |
| Ставропольский край | — | — | — | — | — | — | 27,00 |
| Приволжский федеральный округ | 319,00 | 9,00 | 76,00 | — | — | 3,00 | 201,00 |
| Республика Башкортостан | 43,00 | — | 9,00 | — | — | — | 24,00 |
| Республика Марий Эл | — | — | 4,00 | — | — | — | — |
| Республика Мордовия | 42,00 | — | — | — | — | — | 4,00 |
| Республика Татарстан | 12,00 | — | 9,00 | — | — | — | — |
| Удмуртская Республика | 14,00 | — | 22,00 | — | — | — | 13,00 |
| Чувашская Республика | 11,00 | — | 4,00 | — | — | — | 5,00 |
| Пермский край | — | — | 5,00 | — | — | — | 4,00 |
| Кировская область | 9,00 | — | 6,00 | — | — | — | 7,00 |
| Нижегородская область | 22,00 | — | 12,00 | — | — | — | 12,00 |
| Оренбургская область | 30,00 | — | — | — | — | — | 49,00 |
| Пензенская область | 19,00 | — | — | — | — | — | 4,00 |
| Самарская область | 37,00 | — | — | — | — | — | 36,00 |
| Саратовская область | 44,00 | — | — | — | — | — | 25,00 |
| Ульяновская область | 29,00 | — | — | — | — | — | 13,00 |
| Уральский федеральный округ | 49,00 | — | 13,00 | — | — | — | 39,00 |
| Курганская область | 16,00 | — | — | — | — | — | 17,00 |
| Свердловская область | 13,00 | — | 7,00 | — | — | — | 14,00 |
| Тюменская область | 12,00 | — | — | — | — | — | 4,00 |
| Тюменская область (без автономных округов) | 12,00 | — | — | — | — | — | 4,00 |
| Челябинская область | 8,00 | — | 4,00 | — | — | — | 4,00 |
| Сибирский федеральный округ | 239,00 | — | 32,00 | — | — | — | 175,00 |
| Алтайский край | 81,00 | — | 8,00 | — | — | — | 84,00 |
| Красноярский край | 27,00 | — | 6,00 | — | — | — | — |
| Кемеровская область | 25,00 | — | — | — | — | — | 15,00 |
| Новосибирская область | 60,00 | — | 9,00 | — | — | — | 48,00 |
| Омская область | 20,00 | — | 3,00 | — | — | — | 16,00 |
| Томская область | 6,00 | — | — | — | — | — | — |
| Дальневосточный федеральный округ | 67,00 | — | — | — | — | — | 39,00 |
| Приморский край | 23,00 | — | — | — | — | — | — |
| Амурская область | 29,00 | — | — | — | — | — | 10,00 |
How to read this table
The rows allow for a comparison of acquisition volumes nationwide versus the Volga or Central Federal Districts. By comparing different items, one can identify which equipment is in higher demand: for example, the number of combine harvesters is 1230 units, while windrowers total 682 units. This helps illustrate the distribution of demand for various types of machinery within a single year
What is visible in these numbers
Indicators in the set: Combines: — grain harvesters; Combines: — corn harvesters; Combines: — forage harvesters; Combines: — flax harvesters; Combines: — potato harvesters; Beet harvesters (excluding haulm harvesters); Windrow headers
There are 76 values in the table out of 175 possible, which is 43.4%. The data is sparse — for many positions, observations were not conducted for the entire period, and summary totals for them should not be calculated
The same indicator in other breakdowns (3)
More in the section Bulletins on the state of agriculture (electronic versions)»
Period and application
This information is published as part of agricultural status bulletins. The data is presented as a single cross-section without time-series links, facilitating current situation analysis. The information is useful for agricultural specialists, machinery manufacturing enterprise representatives, and economists assessing the domestic equipment market
How it is calculated
The harvest and livestock population of the current year determine the purchase prices of the next: a processor needs such series earlier than a supplier's price list
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