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Regime shifts in the Swedish housing market - A Markov-switching model analysis
KTH, School of Architecture and the Built Environment (ABE), Real Estate and Construction Management.
KTH, School of Architecture and the Built Environment (ABE), Real Estate and Construction Management.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Regimskiften pa den svenska bostadsmarknaden - En analys med Markov-switchingmodeller (Swedish)
Abstract [en]

Problem statement: Accurate and reliable forecasts of trends in the housing market can

be useful information for market participants as well as policy makers. This information may be useful to minimize risk related to market uncertainty. Since the burst of the housing bubble in the early 1990s the price level of single-family houses has risen sharply in Sweden. The Swedish housing market has experienced an unusually long period of high growth rates in transaction prices which has opened up for discussions about the risk of another housing bubble. Business and property cycles have shown to contain asymmetries, which linear models are unable to pick up and therefore inappropriate to analyze cycles.

Approach: Therefore, this study uses non-linear models which are able to pick up the asymmetries.

The estimated models are variations of the Markov-switching regression model, i.e. the

Markov-switching autoregressive (MS-AR) model and the Markov-switching dynamic regression (MS-DR) model.

Results: Our ndings show that the MS-AR(4) model allowing for varying variance across

regimes estimated using the growth rate of FASTPI produce superior forecasts over other MSAR models as well as variations of the MS-DR model. The average expected duration to remain in a positive growth regime is between 6.3 and 7.3 years and the average expected duration to remain in a negative growth regime is between 1.2 to 2.5 years.

Conclusion: The next regime shift in the Swedish housing market is projected to occur between 2018 and 2019, counting the contraction period in 2012 as the most recent negative regime. Our ndings support other studies ndings which indicate that the longer the market has remained in one state, the greater is the risk for a regime shift.

Abstract [sv]

Problemformulering: Noggranna och tillforlitliga prognoser om utvecklingen pa bostadsmarknaden kan vara anvandbar information for marknadsaktorer samt beslutsfattare. Denna information kan vara anvandbar for att minimera risken relaterad till osakerheten pa marknaden. Sen bostadsbubblan sprack i borjan av 1990-talet har prisnivan for smahus okat kraftigt i Sverige.

Den svenska bostadsmarknaden har upplevt en ovanligt lang period av hog tillvaxt i transaktionspriser som har oppnat upp for diskussioner om risken for en ny bostadsbubbla. Konjunkturoch fastighetscykler har visat sig innehalla asymmetrier som linjara modeller inte kan uppfanga och darfor visat sig vara olampliga for att analysera cykler.

Tillvagagangssatt: Darfor anvander den har studien icke-linjara modeller som kan uppfanga

dessa asymmetrier. De skattade modellerna ar variationer av Hamiltons Markov-switchingmodell, dvs. en autoregressiv Markov-switchingmodell (MS-AR) och en dynamisk Markov-switchingmodell (MS-DR).

Resultat: Resultatet visar att MS-AR(4)-modellen som tar hansyn till varierande varians over

regimerna estimerad med tillvaxten av FASTPI producerar overlagsna prognoser jamfort med

andra MS-AR-modeller samt variationer av MS-DR-modellen. Den genomsnittliga forvantade

varaktigheten att benna sig i en positiv regim ar mellan 6,3 och 7,3 ar och denĀ  genomsnittliga forvantade varaktigheten att benna sig i en negativ regim ar mellan 1,2 till 2,5 ar.

Slutsats: Nasta regimskifte pa den svenska bostadsmarknaden beraknas ske mellan 2018 och

2019, antaget att nedgangen under 2012 ar den senaste negativa regimen. Resultatet stodjer tidigare studier, som tyder pa att ju langre marknaden har varit i ett tillstand, desto storre ar risken for ett regimskifte.

Place, publisher, year, edition, pages
2016. , 34 p.
Series
TRITA-FOB, ByF-MASTER-2016:21
Keyword [en]
Housing cycles, Markov-switching, regime shifts, MS-AR, transition probabilities, regime-switching model, MS-DR, turning points, Swedish housing market, forecasting
Keyword [sv]
Bostadscykler, Markov-switching, regimskifte, MS-AR, overgangssannolikheter, vandpunktsmodell, MS-DR, vandpunkter, svenska bostadsmarknaden, prognos
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-190178Archive number: 427OAI: oai:DiVA.org:kth-190178DiVA: diva2:951883
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Available from: 2016-08-10 Created: 2016-08-10 Last updated: 2016-08-10Bibliographically approved

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