Approach to Regionalization of Municipalities based on Panel Data Modeling (by example of Republic of Bashkortostan)
Irina Lakman, Railya Bakhitova, Elena Gafarova, Ramiz Gindullin
Available Online June 2017.
- https://doi.org/10.2991/ttiess-17.2017.65How to use a DOI?
- municipal formation; regionalization; panel data analysis; clusterization
- Social and economic development of sub-territories of the country or the region is heterogeneous. Because of that, the correct classification of territories into depressive, underdeveloped, developed and potentially growing is important. A relatively new approach that is used for regionalization of municipalities is the panel data analysis, the main benefit of which is the ability to analyze the development of municipalities taking into account spatio-temporal cross-sections. In this paper, the procedure of regionalization of municipalities of the Republic of Bashkortostan in terms of socio-economic development using panel data modeling is outlined. Firstly, the panel data model of economic growth for all municipalities of the Republic of Bashkortostan is evaluated. Then, clusters of municipalities are formed by grouping fixed individual effects obtained in the construction of the model at the first step. After that, all panel data models are restructured, according to the newly selected clusters of municipalities. Finally, partial coefficients of elasticity are analyzed for the factors influencing the economic growth for each selected cluster.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Irina Lakman AU - Railya Bakhitova AU - Elena Gafarova AU - Ramiz Gindullin PY - 2017/06 DA - 2017/06 TI - Approach to Regionalization of Municipalities based on Panel Data Modeling (by example of Republic of Bashkortostan) BT - International Conference on Trends of Technologies and Innovations in Economic and Social Studies 2017 PB - Atlantis Press SP - 392 EP - 398 SN - 2352-5428 UR - https://doi.org/10.2991/ttiess-17.2017.65 DO - https://doi.org/10.2991/ttiess-17.2017.65 ID - Lakman2017/06 ER -