Research Article Open Access

Improving the Approaches to Planning the Electricity Consumption in Budget Institutions

Nailya Malikovna Yakupova1, Rezeda Muhtarovna Kundakchyan1, Roza Nuriahmetovna Andreeva1 and Aleksey Vladimirovich Andreev1
  • 1 The Institute of Management, Economics and Finance, Kazan (Volga region) Federal University, Kazan, Russia

Abstract

The technique of predicting the budget organizations' electrical power demands, which is currently used in Tatarstan Republic, based on the averaged norms for all educational establishments, does not reflect the impact of certain external and internal factors of environment influencing the volume of energy consumption, which results in the inefficient expenditure of the budget. This problem is especially topical for the local budgets, as a broad network of educational establishments is financed from these budgets. The article analyzes the impact of certain external and internal factors of environment on energy consumption in educational establishments by the example of municipal districts of Tatarstan Republic. The research allowed to conclude that electrical energy consumption in educational establishments is characterized by expressed seasonality, thus the model is presented as a multiplicative trend-season model, for which the component values are defined basing on correlation-regression analysis. Similar calculations were carried out for other municipal districts of Tatarstan Republic and trend-season models were constructed for each district under analysis.

American Journal of Applied Sciences
Volume 12 No. 12, 2015, 962-966

DOI: https://doi.org/10.3844/ajassp.2015.962.966

Submitted On: 8 November 2015 Published On: 26 November 2015

How to Cite: Yakupova, N. M., Kundakchyan, R. M., Andreeva, R. N. & Andreev, A. V. (2015). Improving the Approaches to Planning the Electricity Consumption in Budget Institutions. American Journal of Applied Sciences, 12(12), 962-966. https://doi.org/10.3844/ajassp.2015.962.966

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Keywords

  • Public Sphere
  • Budget
  • Correlation Analysis
  • Educational Establishments
  • Regression Analysis