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Nationalekonomiska faktorers påverkan för priset på småhus
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2016 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Macroeconomic factors and the price of houses (English)
Abstract [sv]

Syftet med denna studie är att undersöka hur de nationalekonomiska faktorerna bostadsbestånd, befolkningsmängd, disponibla inkomster, styrränta och hushållens skulder påverkar bostadspriserna på småhus. Detta har gjorts med hjälp av ekonomisk teori i kombination med matematiska modeller. Regressionen är utförd med data från 2000 fram till och med 2013. Resultatet som utgörs av en regressionsmodell visar med god signifikansnivå hur mycket de olika variablerna påverkar bostadspriserna. Modellerna överensstämmer även med den ekonomiska teorin. Disponibla inkomsterna, hushållens skulder och befolkningsmängden har en positiv påverkan på bostadspriserna och bostadsbeståndet har en negativ. I de matematiska modellerna kunde inte styrräntan ge ett signifikant resultat. Resultatet i rapporten är relevant för samtliga institutioner som gör prognoser över bostadsmarknaden och fler liknande arbeten bör göras för att beslutsfattare ska få tydligare underlag för hur olika förändringar påverkar bostadspriserna.

Abstract [en]

The purpose of this study is to examine how the economic factors housing supply, population, disposable income, rates and household debt affects residential prices. This has been done by combining economics with mathematical models. The result is a regression model with a high level of significance that confirms the economic theory. For instance one can clearly conclude that the price of residential prices increases if the demand or disposable income increases. The regression is made based on data between the years 2000 until 2013. The result that consists of a regression model proves with a god level of significance how much the different factors affect the residential prices. The model also coordinates with the economic theory.  The disposable income, household debts and population have an increasing impact on the residential prices while an increasing amount in the housing supply (while keeping everything else fix) shows a decreasing effect on the price. In the mathematical model, the rate did not show enough significance. The result in this report is particularly meaningful for all institutions that provides forecasts concerning the housing market. More studies like this should be made, so that decision makers can get a better understanding how different changes can affect the housing market.

Place, publisher, year, edition, pages
2016.
Series
TRITA-MAT-K, 2016:08
National Category
Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-189006OAI: oai:DiVA.org:kth-189006DiVA: diva2:942660
Subject / course
Applied Mathematical Analysis
Educational program
Master of Science in Engineering - Industrial Engineering and Management
Supervisors
Examiners
Available from: 2016-06-26 Created: 2016-06-26 Last updated: 2016-06-26Bibliographically approved

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CiteExportLink to record
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