Arctic Energy Resources as an Economic Growth Factor: Evidence from Alaska, USA

• Main Authors: Svetlana V. Bekareva, Ekaterina N. Meltenisova, Akim Guerreiro
• Format: Article in Journal/Newspaper
• Language: English
• Published: EconJournals 2018
• Subjects: Environmental sciences; GE1-350; Energy industries. Energy policy. Fuel trade; HD9502-9502.5; Arctic; Alaska North Slope; north slope; Alaska
• Online Access: https://doaj.org/article/6bc4461f275544fbb18d215045085d5b

Nowadays, the Arctic is referred to as a specific region rich in natural resources, including energy resources, with a severe climate and challenging conditions of doing business, connected not only with the climate itself but also with the existing legislative limitations. According to the researchers of the Arctic, together with the challenges, the Arctic offers huge development opportunities, including those in the oil and gas sector. Alaska is one of the territories of the region which has the richest energy resources. The objective of this study has been to estimate how the factor of the region's energy resources, which we have related to the oil production growth rates on the Alaska North Slope, affects the economic growth of Alaska. The study methodology is based on both the classical models of economic growth and their modification considering the factor of the energy resources. The vector error correction model was used for evaluating the proposed economic growth model modification. The influence of classical factors, the labor and the capital, on the economic growth of the region in the long-term perspective has been empirically proven. The factor of the energy resources has proved to be significant in the equation describing the economic growth only for the short-term perspective. We believe the influence of this variable on the long-term economic growth to be indirect, exercised through the parameter of capital investment. Keywords: Arctic region, Alaska, the Alaska North Slope, energy resources, economic growth, vector error correction model JEL Classifications: Q32, Q43