Comparing Models of Sustainable Development for the Arctic Region of the Russian Federation

Abstract

This paper outlines the concept of sustainability in regard to regional development, examines basic premises of modeling regional relations in the Arctic zone of the Russian Federation, describes the principles and investigates the specifics of building models for sustainable development in regions of the Arctic. It presents methods to build a model that can fully characterize sustainable regional development in the Russian Arctic and lays out requirements for such a model and its corresponding indicators. The paper also considers possibilities for using and adapting already existing mathematical models exemplified by an autoregressive distributed lag (ADL) model and a neural network model. The authors specify under what conditions these models can fully meet all the requirements, what statistical indicators are of key importance to a numerical representation of sustainable development, what factors can be prioritized to be incorporated in the models, what limitations they have and why these very models show the most promise in terms of both analyzing the current state of affairs and making forecasts. The paper presents the results of testing the models on the basis of real statistical data gathered across the Murmansk region and compares the derived outcomes to draw conclusions from the obtained data. It also summarizes the findings from the built models and assesses the prospects for their further application in forecasting sustainable regional development and utilizing projected outcomes in making management decisions to implement the strategy for the development of the Russian Arctic regions.