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dc.contributor.advisorEgging, Ruud
dc.contributor.advisorTomasgard, Asgeir
dc.contributor.advisorIvanova, Olga
dc.contributor.authorJohansen, Ulf
dc.date.accessioned2019-09-30T11:28:38Z
dc.date.available2019-09-30T11:28:38Z
dc.date.issued2019
dc.identifier.isbn978-82-326-3889-5
dc.identifier.issn1503-8181
dc.identifier.urihttp://hdl.handle.net/11250/2619361
dc.description.abstractThis thesis explores various regional policy effects in Norway. Studying such effects is interesting for several reasons. First, Norway is a large country with a relatively small, diverse, and geographically spread population. Second, a very large share of the total value creation happens in rural areas, because several key industries, such as fishery, aquaculture and oil and gas, depend on location-fixed natural resources outside the central areas. Third, Norway uses various public policy instruments to balance the regional development – to maximize the total value creation but also to preserve the population settlement pattern. To evaluate regional policy effects in Norway Input-Output analysis, operations research, a computable general equilibrium model and econometrics have been applied. Input-Output (I-O) models can be used to assess a sector’s ripple effects by quantifying the value-added of the sector activities including its interactions with the wider economy. The I-O methodology can address potential wider economic effects from increasing production in, for instance, the forestry industry, but it does not give any guidance to the industry where to invest, what to produce or where to transport the products. A more appropriate methodology to answer these questions is value chain optimization. Existing methods in the literature fall short in connecting wider economic impacts from actors in a value chain to an optimization problem. The thesis presents one of the first approaches to close this gap, combining value chain optimization and regional macroeconomic theory by way of I-O analysis methods. Computable general equilibrium (CGE) models are widely utilized to assess effects from economic policy. In contrast to I-O models, CGE models focus on prices, taxes, transfers and constraints in capital and labour supply. Regional CGE models have been adopted very slowly because they are more data intensive than their I-O counterpart. A fully operational regional CGE model needs regional data of industry output, production technology, intra-regional and international trade, consumption, investment patterns, government expenditures, taxes, and factor ownership. Still, they are well-suited to analyse regional effects of various policy instruments, as demonstrated in this thesis. Finally, econometrics comprises statistical methods for estimating economic relationships, testing theories, evaluating policy, and should be considered as a complement to modelling approaches. In this work, micro data of all employees in Norway is used to address policy effects on the regional labour market in Norway. In sum, the thesis aims to give a holistic picture of various regional policy effects, making use of different perspectives in the applied methodologies. This contributes to creating new insights for policy makers and, thus, designing more effective and consistent policy instruments.nb_NO
dc.language.isoengnb_NO
dc.publisherNTNUnb_NO
dc.relation.ispartofseriesDoctoral theses at NTNU;2019:145
dc.titleRegional policy effects in Norwaynb_NO
dc.typeDoctoral thesisnb_NO
dc.subject.nsiVDP::Samfunnsvitenskap: 200::Økonomi: 210::Samfunnsøkonomi: 212nb_NO
dc.description.localcodeDigital full text not availablenb_NO


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