This paper investigates which factors best predict the economic state of a Swedish municipality after the 2008 crisis by constructing a linear model that regresses the change in the unemployment rate on a set of variables. The variables used for the model were from a dataset put together using data from a government service and were selected for the model using Bayesian information criterion. From this procedure, a model with six independent variables was estimated. The model’s statistics were examined, and the model was subsequentially tried against the five multiple linear regression assumptions. It was concluded that the model did not fulfil the assumption of homoscedasticity, and because of this, the dependent variable was transformed into a logarithm, thus yielding a log-lin model. This model ended up fulfilling every assumption and had higher explanatory power than the previous model. It is concluded that the variables that denote the number of newly registered businesses per 1000 residents, the share of residents with a high education, the fraction of net-commuters, the number of refugees received with a residence permit per 1000 residents, total net investments per person, the share of long term unemployed residents and the population size all prove significant when included together in a log-lin model of the change in the unemployment rate.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-413825 |
| Date | January 2020 |
| Creators | Artman, Arvid |
| Publisher | Uppsala universitet, Statistiska institutionen |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | Studia statistica Upsaliensia, 1104-1560 |
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