Forecasting real estate prices in Germany: the role of consumer confidence

Meulen, Philipp an de; Micheli, Martin; Schmidt, Torsten

doi:10.1080/09599916.2014.940059

Cited by 10 publications

(4 citation statements)

References 32 publications

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“…The persistent negative response of house prices to interest rate shocks indicates that falling interest rates have substantially contributed to the sudden increase in house prices. It cannot even be ruled out that these have caused the increase in connection with Germany's robust economic recovery and positive expectations from agents, see an de Meulen et al (2014). A counterfactual analysis shows that a permanent increase of interest rates to 4% would be sufficient to stop the increase of house prices.…”

Section: Resultsmentioning

confidence: 99%

House prices and interest rates: Bayesian evidence from Germany

Hanck

Prüser

2020

Applied Economics

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This study uses a Bayesian VAR to demonstrate that the recent house price boom in Germany can be explained by falling interest rates and that higher interest rates are likely suciffi ent to stop the increase of German house prices. The latter suggests a potential drawback of the current monetary policy of the ECB. The BVAR's prior information shrinks the model parameters towards a parsimonious benchmark. We provide a simulation study to compare the frequentist properties of two useful strategies to select the informativeness of the prior. The study reveals that prior information helps to obtain more precise estimates of impulse response functions in small samples. To choose relevant control variables, we use a new Bayesian variable selection approach by Ding and Karlsson (2014). In addition to impulse responses and variance decompositions, we use a Bayesian conditional forecast to test the hypothetical eff ect of an increase of interest rates on house prices. This approach has the crucial advantage that it is invariant to the ordering of the variables.

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Section: Resultsmentioning

confidence: 99%

House prices and interest rates: Bayesian evidence from Germany

Hanck

Prüser

2020

Applied Economics

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“…The ARDL has been used by various researchers in real estate for studying housing prices (Arestis et al , 2017; Teye et al , 2017; Ozun et al , 2018); assessing housing related taxation receipts (Smyth and McQuinn, 2016); identifying macro drivers of housing affordability (Worthington and Higgs, 2013); determinants of mortgage defaults (Ngene et al , 2016); studying linkages (volatility spillover effects) between various markets (Liow, 2014; Liow and Schindler, 2017); studying the relationship between residential property and the stock market (Lee, 2017); comparing real estate with other asset classes like bonds and shares (Szumilo et al , 2018); modeling office rents of various markets to understand the intra-market dependence and speed of adjustment toward long-run equilibrium (Mouzakis and Richards, 2007); studying the rental rate for pricing Islamic mortgage rates (Mohd Yusof, Bahlous and Haniffa, 2016) and forecasting real estate pricing (An de Meulen, Micheli and Schmidt, 2014).…”

Section: Empirical Methods and Estimationsmentioning

confidence: 99%

Determinants of foreign and domestic non-listed real estate fund flows in India

Gupta

Newell

Bajaj³

et al. 2020

JPIF

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PurposeReal estate forms an important part of any economy and the investment in real estate, in turn, is impacted by the macroeconomic environment of that country. The purpose of the present research is to examine macroeconomic determinants of foreign and domestic non-listed real estate fund (NREF) flows and to examine whether they are similar or different for an emerging economy like India.Design/methodology/approachThe long and short-run cointegration between the time-series variables is estimated using the autoregressive distributed lag (ARDL) bounds test and error correction model (ECM) using quarterly data across the 2005–2017 period. ARDL is a suitable method for short time-series data.FindingsThe empirical results indicate that domestic NREF flows are positively and significantly impacted by real GDP and performance of listed real estate stocks (i.e. BSE realty index). Whereas, foreign NREF flows are positively and significantly impacted by the exchange rate, performance of listed real estate stocks and domestic NREF flows.Practical implicationsThe empirical results have significant implications for academicians, policy makers and real estate market practitioners. In the context of these results, some interesting insights are gained that would help in the implementation of the policies aimed toward increasing the fund flows in the real estate sector, which in turn would have a significant trickle-down effect on the Indian economy.Originality/valueThe existing literature looks at macroeconomic and other drivers of foreign investment in international real estate investments. However, there are very few studies on the determinants of domestic real estate investment flows and on determinants of NREFs' investment flows; particularly in emerging markets. The present study, in contrast, evaluates simultaneously the macroeconomic determinants of the domestic and foreign NREFs' investment flows in India. The ARDL and ECM method used has been applied for the first time to the study of NREFs.

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“…Building permits can influence spatial property development, as they prevent undesirable developments which are not in compliance with the city planning (Samsura et al, 2015;Eika, 2019). The building permitting process is also an important component of the institutional factors that significantly influence the success of construction projects (Gudienė et al, 2013(Gudienė et al, , 2014 and the number of building permits issued is a key indicator in microeconomic fundamentals (Meulen et al, 2014) and of construction sector performance (Kildienė et al, 2011). In a typical building permitting process, if a property owner or developer decides to apply for a building permit, it requires filling in various forms and providing different supporting documents.…”

Section: Introductionmentioning

confidence: 99%

Bim Adoption in the Aec/Fm Industry – The Case for Issuing Building Permits

Ullah

Raitviir

Lill

et al. 2020

International Journal of Strategic Property Management

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BIM adoption is a complex process and relatively little information exists on the BIM adoption processes of public authorities. This research aims to address this gap by examining how a contemporary public authority is approaching BIM adoption for their building permitting process. Firstly, a systematic literature review was carried out to understand extant descriptions of BIM adoption processes and the factors affecting adoption success. This resulted in the derivation of a generic BIM adoption process and the classification of factors that affect BIM adoption with reference to the Technology Organization and Environment (TOE) framework. The case of the BIM adoption process and the factors affecting its implementation in a contemporary public authority were then analysed in terms of the generic adoption process and factor classification derived from the literature. The findings reveal the planning strategies and execution steps for BIM adoption and the factors affecting them. This study provides a systematic approach to investigating BIM adoption in a public authority. It contributes to the understanding of BIM adoption processes and factors affecting them and is anticipated to be useful for AEC/FM professionals in understanding and facilitating successful BIM adoption.

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Forecasting real estate prices in Germany: the role of consumer confidence

Cited by 10 publications

References 32 publications

House prices and interest rates: Bayesian evidence from Germany

House prices and interest rates: Bayesian evidence from Germany

Determinants of foreign and domestic non-listed real estate fund flows in India

Bim Adoption in the Aec/Fm Industry – The Case for Issuing Building Permits

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