FACTORS OF REGIONAL INDUSTRIAL DEVELOPMENT AND THEIR STATISTICAL ASSESSMENT (CASE OF NAVOI REGION)
DOI:
https://doi.org/10.55640/Keywords:
multifactor analysis, statistical modeling, industrial development, real economic growth, deflation, investment, industrial output, employment, number of enterprises, correlation, regression model, Navoi regionAbstract
This article assesses the economic development of industrial enterprises in the Navoi region based on a multifactor statistical analysis. Using official data for 2010–2024, the dynamics of industrial output, employment, investment in fixed capital, and the number of industrial enterprises are analyzed in real terms. Nominal indicators are deflated using price indices, and correlation and regression methods are applied to identify the key drivers of regional industrial growth.Downloads
References
1.Abduqodirov, B. (2018). Economic mechanisms for improving production efficiency in industrial enterprises (Doctor of Science [DSc] dissertation). Tashkent.
2.Umarov, A. M. (2019). Issues of modernization and diversification of industrial sectors in Uzbekistan. Economy and Innovative Technologies, (3).
3.Bakoev, H. N. (2021). Dispersion analysis of industrial production in cities and districts of the Navoi region. Multidisciplinary Journal of Educational Research, 11(3), 386–392.
4.Bakoev, H. N. (2022). Econometric modeling of production infrastructures’ effects on the industrial network in the Navoi region. Res Militaris Social Science Journal, 12(3), 4029–4041.
5.Bakoev, H. N. (2024). Econometric analysis of the development of the industrial sector in the Navoi region. In Comprehensive innovative development of the Zarafshan Valley: achievements, challenges, and prospects (pp. 307–308). Navoi.
6.National Statistics Committee of the Republic of Uzbekistan. (n.d.). Official website. Retrieved from https://www.stat.uz
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.

Germany
United States of America
Italy
United Kingdom
France
Canada
Uzbekistan
Japan
Republic of Korea
Australia
Spain
Switzerland
Sweden
Netherlands
China
India