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How to identify downturns within an office submarke: A quantitative time series analysis of Stockholm CBD
KTH, School of Architecture and the Built Environment (ABE), Real Estate and Construction Management.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Hur man identifierar nedgångar inom en kontorsmarknad (Swedish)
Abstract [en]

The last couple of years there has been a significant increase in demand of attractive office locations in Stockholm consequently leading to all-time low office prime yields within the Central Business District (CBD), indicating warning signals regarding an overheated submarket. As the real estate market is crucial for the economy as a whole, it is essential to improve the understanding and predictability of future real estate cycles. This study produced three different logistic regression models with the purpose of identifying downturns in the office market of Stockholm CBD. The most successful model were able to predict 74 % of the actual downturns occurring throughout 114 observed quarters between Q3 1989 and Q4 2017. The dependent downturn variable consist of prime yield explained by variables on a national basis combined with submarket specific variables. Another produced model contained variables regarding confidence and expectations of tenants in Stockholm. However that model was unsatisfactory, leading to this study’s suggestion of further research on fluctuations of demand related to the current characteristics of Stockholm CBD. 

Abstract [sv]

Under de senaste åren har det skett en betydande ökning av efterfrågan på attraktiva kontorslokaler i Stockholm vilket resulterat i rekordlåga direktavkastningskrav inom Stockholm Central Business District (CBD), vilket indikerar på varningssignaler avseende en överhettad delmarknad. Eftersom fastighetsmarknaden är avgörande för ekonomin som helhet är det viktigt att förbättra förståelsen och förutsägbarheten för framtida fastighetscykler. Denna studie producerade tre olika logistiska regressionsmodeller med syfte att identifiera nedgångar i kontorsmarknaden inom Stockholm CBD. Den mest framgångsrika modellen kunde förutse 74 % av de faktiska nedgångarna som inträffade under 114 observerade kvartal mellan Q3 1989 och Q4 2017. Den beroende nedgångsvariabeln består av prime yield som förklaras av variabler på nationell basis i kombination med delmarknadsspecifika variabler. En annan producerad modell innehöll variabler avseende förtroende och förväntningar hos hyresgäster i Stockholm. Denna modell var dock otillfredsställande, vilket ledde till att denna studie föreslog ytterligare forskning om fluktuationer i efterfrågan relaterade till de nuvarande egenskaperna hos Stockholms centralbank

Place, publisher, year, edition, pages
2018. , p. 51
Series
TRITA-ABE-MBT ; 18194
Keywords [en]
Forecasting, Logistic regression, Real estate cycles, Office market, Yield, Stockholm CBD
Keywords [sv]
Prognoser, Logistisk regression, Fastighetscykler, Kontorsmarknad, Direktavkastningskrav, Stockholm CBD
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-230936OAI: oai:DiVA.org:kth-230936DiVA, id: diva2:1220389
Supervisors
Examiners
Available from: 2018-07-02 Created: 2018-06-18 Last updated: 2018-07-02Bibliographically approved

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CiteExportLink to record
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