Increasing the Efficiency of Using Data of the Russian Agricultural Census
Abstract
This article covers questions of enabling a better use of the data from national agricultural censuses, in particular, that of the 2016 Russian Agricultural Census (VSHP-2016). Analysis of programmes and materials for the VSHP regulatory and legal support and organizational and methodological documents that so far have been prepared for the FAO World Programme for the Census of Agriculture 2020, served as a basis for identifying groups of agricultural censuses data users. The author focuses on the need to apply international standards of various aspects of organization and carrying out of a such wide-scale statistical work to Russian conditions. The article formulates proposes on improving interactions between agricultural data producers and users, which in the author’s opinion should guarantee a more efficient use of the VSHP-2016.
About the Author
Ekaterina A. Gataulina
All-Russian Institute of Agrarian Problems and Informatics, named after A.A. Nikonov, Moscow
Russian Federation
Cand. Sci. (Econ.), Leading Researcher
Russian Federation
Cand. Sci. (Econ.), Leading Researcher
References
1. Gataulina E.A. Improving the Methodology of the All-Russian Agricultural Census. International Agricultural Journal. 2017;(6):39-41. (In Russ.)
2. Gataulina E.A. Agricultural Organizations: Preliminary Results of the 2016 Census. Economics of Agriculture of Russia. 2017;(12):66-72. (In Russ.)
3. Zinchenko A.P. What Should and Can be Obtained Conclusions after Analyzing the Outcome of the All-Russia Agricultural Census Year 2016. Economy of agricultural and processing enterprises. 2017;(1):2-8. (In Russ.)
4. Shashlova N.V. Review of 2016 Russian Agricultural Census Results. Voprosy statistiki. 2017;(2):17-19. (In Russ.)
5. Petrikov A.V. Results of the All-Russian Agricultural Census of 2016: the Main Structural Changes in Russia’s Agriculture in 10 years. Moscow Economic Journal. 2017;(4). (In Russ.) Available from: http://qje.su/selskohozyajstvennyenauki/moskovskij-ekonomicheskij-zhurnal-4-2017-64/.
6. Gataulina E.A. Methodology of the All-Russian Agricultural Census 2016: Issues of Improvement. Economics, Labor, Management in Agriculture. 2017;(4) (33):19-23. (In Russ.)
7. Korbut L.S. Agrarian Science and Agricultural Statistics: the World Agricultural Census of the Round of 2010. Nikonov’s Readings. 2013;(18):345-347.(In Russ.)
8. Korbut L.S. The Global Strategy to Improve Agricultural and Rural Statistics and the New 2020 Round of the World Census of Agriculture. Voprosy statistiki. 2016;(8): 7-13. (In Russ.)
9. Saraikin V.A. Economic Classification of Private Subsidiary Farms as a Basis for Improving Current Observation Method. Voprosy statistiki. 2018;25(2):73-80. (In Russ.)
10. Food and Agriculture Organization of the United Nations. World Programme for the Census of Agriculture 2020. Volume 1: Programme, Concepts and Definitions. Rome; 2016. 228 p. (In Russ.)
11. Uzun V.Ya., Saraykin V.A., Gataulina E.A. Classification of Agricultural Producers on the Basis of the Data of the All-Russian Agricultural Census of 2006. Moscow: VIAPI named after A.A. Nikonov: ERD; 2010. 229 p. (In Russ.)
12. Saraykin V.A., Gataulina E.A. Change in Population Density in Areas with Different Types of Agrarian Structures. Economics of Agriculture of Russia. 2016;(3):665-83. 65-89 р. (In Russ.)
13. Gataulina E.A. The Impact of Agrarian Structure on the Scale and Efficiency of Agricultural Production. Economics of Agriculture of Russia. 2015;(5): 43-47. (In Russ.)
Review
For citations:
Gataulina E.A. Increasing the Efficiency of Using Data of the Russian Agricultural Census. Voprosy statistiki. 2018;25(6):77-82. (In Russ.)
Views:
375
Email this article 