scholarly journals Capital Flows, Real Estate, and Local Cycles: Evidence from German Cities, Banks, and Firms

2021 ◽  
Author(s):  
Peter Bednarek ◽  
Daniel Marcel te Kaat ◽  
Chang Ma ◽  
Alessandro Rebucci
Keyword(s):  
Real Estate ◽  
Capital Flows ◽  
Real Estate Market ◽  
The State ◽  
Capital Inflows ◽  
Policy Framework ◽  
Gdp Growth ◽  
Real Estate Markets ◽  
Percentage Points ◽  
German Cities

Abstract We study how capital flows affects German cities’ GDP growth depending on the state of their real estate markets. Identification exploits a policy framework assigning refugees to cities on a quasi-random basis and variation in nondevelopable area for the construction of an exposure measure to real estate market tightness. We estimate that the most exposed cities to real estate market tightness grew at least 1.9 percentage points more than the least exposed ones, cumulatively, from 2009 to 2014. Capital inflows shift credit to firms with more collateral, which leads firms to hire and invest more in response to these shocks.

scholarly journals Analysis of the residential real estate market in St. Petersburg

2021 ◽  
Vol 18 (5) ◽  
pp. 167-172
Author(s):  
I. V. Drozdova ◽  
Keyword(s):  
Real Estate ◽  
Economic Sanctions ◽  
Real Estate Market ◽  
The State ◽  
Residential Real Estate ◽  
Real Estate Markets ◽  
The Cost

The article analyzes the state of the primary and secondary residential real estate markets in St. Petersburg for the period from 2016 to 2020. The rating of developers leading in St. Petersburg in terms of the housing commissioning volume has been compiled. There have been identified the factors (economic sanctions, quarantine restrictions, devaluation of the ruble, inflation, decrease in the level of income of the population) influencing a decrease in the volume of housing commissioning, an increase in the cost and decrease in the affordability of housing in the primary and secondary residential real estate markets in 2019-2020. The trends in the development of residential real estate markets in St. Petersburg in 2021-2022 have been revealed.

Der regionale Immobilienmarkt – Indikator für den Strukturwandel im Ruhrgebiet

2006 ◽  
Vol 50 (1) ◽  
Author(s):  
Andreas Schulten
Keyword(s):  
Real Estate ◽  
Service Sector ◽  
Real Estate Market ◽  
Structural Shift ◽  
Real Estate Markets ◽  
Ruhr Area ◽  
Significant Patterns ◽  
Residential Market ◽  
The One ◽  
German Cities

The regional real estate market as an indicator for structural change in the Ruhr area. The regional real estate markets are robust indicators for the structural shift within the Metropole Ruhr. Growth in service sector industry as well as demographic changes are accompanied or sometimes enhanced by real estate developments and investments. New stock either in the commercial or residential market reflects new demand - or the lack of it - in a very precise way. Especially in the local office markets the cyclical change of rent-, price- and yield levels offers a tool to measure the structural shift in detail. Most of the new and sustainable anchors in regional development of the Ruhr within the past two decades could not have been realized without private real estate investment on the one hand and improved skills of the local business development agencies on the other hand. The warehouse and the residential markets however show much less significant patterns in comparison among the Ruhr cities as well as compared to other German cities.

Digitalization Real Estate on American Real Estate Society 2018: A Dramatic and Irreversible Shift in Real Estate Systems

2019 ◽  
Vol 10 (5) ◽  
pp. 380-386
Author(s):  
Jan Veuger ◽  
Keyword(s):  
Real Estate ◽  
Capital Flows ◽  
Global Economy ◽  
Real Estate Market ◽  
Educational Models ◽  
Annual Congress ◽  
Real Estate Education ◽  
Demographic Effects

The 34th annual congress of April 10-14 this year took place in Bonita Springs (Florida) where the professionals in real-estate education and research discussed six themes: global economy and capital flows, real estate market cycles, demographic effects, future-proof real estate, disruption in technology and future educational models.

RUSSIAN REAL ESTATE MARKET STATE AND PROSPECTS

2021 ◽  
Vol 3 (5) ◽  
pp. 23-27
Author(s):  
V. A. ERONIN ◽  
◽  
O. E. EMELYANOV ◽  
Keyword(s):  
Real Estate ◽  
Real Estate Market ◽  
The State ◽  
The Real ◽  
The Real Estate ◽  
The Real Estate Market ◽  
Market State

The article considers the state, main problems and prospects of development of the real estate market in Russia in modern conditions.

scholarly journals Predicting real estate market trends and value using pre-processing and sentiment text mining analysis

2021 ◽  
pp. 35-43
Author(s):  
Nikolay Sinyak ◽  
Singh Tajinder ◽  
Jaglan Madhu Kumari ◽  
Vitaliy Kozlovskiy
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Real Estate ◽  
Real Estate Market ◽  
Media Analysis ◽  
Market Information ◽  
Real Estate Markets ◽  
The Real Estate ◽  
Crowd Wisdom ◽  
Market Trends

Ubiquitous growth in the text mining field is unprecedented, where social media mining is playing a significant role. Gigantic growth of text mining is becoming a potential source of crowd wisdom extraction and analysis especially in terms of text pre-processing and sentiment analysis. The analysis of a potential influence of sentiment on real estate markets controversially discussed by scholars of finance, valuation and market efficiency supporters. Therefore, it’s a significant task of current research purview which not only provide an appropriate platform for the contributors but also for active real estate market information seekers. Text mining has gained the widespread attention of real estate market information users which is almost on explosion level. Accessibility of data on such behemoth scale mandates regular and critical analysis of this information for various perspectives’ plausibility. Rich patterns of online social text can be exploited to extract the relevant real estate information effectively. As text mining plays a significant and crucial role in discovery of these insights therefore its challenges and contribution in social media analysis must be explored extensively. In this paper, we provide a brief about the current summary of the modern state of text mining in pre-processing and sentiment for the real estate market analysis. Empha-sis is placed on the resources and learning mechanism available to real estate researchers and practitioners, as well as the major text mining tasks of interest to the community. Thus, the main aim of this chapter is to expound and intellectualize the domains of social media which are accessible on an extraordinary range in the field of text mining real estate for predicting real estate market trends and value.

scholarly journals International Real Estate Review

2016 ◽  
Vol 19 (1) ◽  
pp. 27-49
Author(s):  
William Mingyan Cheung ◽  
◽  
James Chicheong Lei ◽  
Desmond Tsang ◽  
◽  
...  
Keyword(s):  
Real Estate ◽  
Price Discovery ◽  
Common Factor ◽  
Significant Proportion ◽  
Real Estate Market ◽  
Reverse Causality ◽  
Public And Private ◽  
Real Estate Markets ◽  
The Public ◽  
Private Real Estate

This study examines whether property transaction affects the price discovery process in real estate markets. Prior literature shows that price discovery generally first takes place in the securitized public real estate investment trust (REIT) market. We conjecture that property transaction provides novel information to the direct real estate market and can change the dynamics between public and private real estate returns. We employ a unique dataset of property transactions to construct "transaction windows¨ and specifically examine the causality between public and private real estate markets around these periods. We form firm-level pairs of public and private price series, and estimate the normalized common factor loadings per Gonzalo and Granger (1995) by using a vector error-correction model. Our findings show that a significant proportion of price discovery happens in the private market instead of the public REIT market. Our results are robust to investments of different property types and different lengths of transaction windows. Overall, the findings in this study imply that property acquisition and disposition provide crucial information to the private real estate market and induce a reverse causality between the public and private markets.

scholarly journals COVID-19 Infects Real Estate Markets: Short and Mid-Run Effects on Housing Prices in Campania Region (Italy)

2020 ◽  
Vol 9 (7) ◽  
pp. 114 ◽  
Author(s):  
Vincenzo Del Giudice ◽  
Pierfrancesco De Paola ◽  
Francesco Paolo Del Giudice
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Real Estate Market ◽  
Campania Region ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Short Run ◽  
Predator Model ◽  
Real Estate Prices

The COVID-19 (also called “SARS-CoV-2”) pandemic is causing a dramatic reduction in consumption, with a further drop in prices and a decrease in workers’ per capita income. To this will be added an increase in unemployment, which will further depress consumption. The real estate market, as for other productive and commercial sectors, in the short and mid-run, will not tend to move independently from the context of the aforementioned economic variables. The effect of pandemics or health emergencies on housing markets is an unexplored topic in international literature. For this reason, firstly, the few specific studies found are reported and, by analogy, studies on the effects of terrorism attacks and natural disasters on real estate prices are examined too. Subsequently, beginning from the real estate dynamics and economic indicators of the Campania region before the COVID-19 emergency, the current COVID-19 scenario is defined (focusing on unemployment, personal and household income, real estate judicial execution, real estate dynamics). Finally, a real estate pricing model is developed, evaluating the short and mid-run COVID-19 effects on housing prices. To predict possible changes in the mid-run of real estate judicial execution and real estate dynamics, the economic model of Lotka–Volterra (also known as the “prey–predator” model) was applied. Results of the model indicate a housing prices drop of 4.16% in the short-run and 6.49% in the mid-run (late 2020–early 2021).

The dynamics of return co-movements and volatility spillover effects in Greater China public property markets and international linkages

2014 ◽  
Vol 32 (6) ◽  
pp. 610-641 ◽  
Author(s):  
Kim Hiang Liow
Keyword(s):  
Real Estate ◽  
Spillover Effects ◽  
Real Estate Market ◽  
Market Volatility ◽  
Volatility Spillover ◽  
Content Type ◽  
Real Estate Markets ◽  
Volatility Spillovers ◽  
Public Property ◽  
Property Markets

Purpose – The purpose of this paper is to examine weekly dynamic conditional correlations (DCC) and vector autoregressive (VAR)-based volatility spillover effects within the three Greater China (GC) public property markets, as well as across the GC property markets, three Asian emerging markets and two developed markets of the USA and Japan over the period from January 1999 through December 2013. Design/methodology/approach – First, the author employ the DCC methodology proposed by Engle (2002) to examine the time-varying nature in return co-movements among the public property markets. Second, the author appeal to the generalized VAR methodology, variance decomposition and the generalized spillover index of Diebold and Yilmaz (2012) to investigate the volatility spillover effects across the real estate markets. Finally, the spillover framework is able to combine with recent developments in time series econometrics to provide a comprehensive analysis of the dynamic volatility co-movements regionally and globally. The author also examine whether there are volatility spillover regimes, as well as explore the relationship between the volatility spillover cycles and the correlation spillover cycles. Findings – Results indicate moderate return co-movements and volatility spillover effects within and across the GC region. Cross-market volatility spillovers are bidirectional with the highest spillovers occur during the global financial crisis (GFC) period. Comparatively, the Chinese public property market's volatility is more exogenous and less influenced by other markets. The volatility spillover effects are subject to regime switching with two structural breaks detected for the five sub-groups of markets examined. There is evidence of significant dependence between the volatility spillover cycles across stock and public real estate, due to the presence of unobserved common shocks. Research limitations/implications – Because international investors incorporate into their portfolio allocation not only the long-term price relationship but also the short-term market volatility interaction and return correlation structure, the results of this study can shed more light on the extent to which investors can benefit from regional and international diversification in the long run and short-term within and across the GC securitized property sector, with Asian emerging market and global developed markets of Japan and USA. Although it is beyond the scope of this paper, it would be interesting to examine how the two co-movement measures (volatility spillovers and correlation spillovers) can be combined in optimal covariance forecasting in global investing that includes stock and public real estate markets. Originality/value – This is one of very few papers that comprehensively analyze the dynamic return correlations and conditional volatility spillover effects among the three GC public property markets, as well as with their selected emerging and developed partners over the last decade and during the GFC period, which is the main contribution of the study. The specific contribution is to characterize and measure cross-public real estate market volatility transmission in asset pricing through estimates of several conditional “volatility spillover” indices. In this case, a volatility spillover index is defined as share of total return variability in one public real estate market attributable to volatility surprises in another public real estate market.

scholarly journals The changing real estate market transparency in the European real estate markets

2016 ◽  
Vol 34 (4) ◽  
pp. 407-420 ◽  
Author(s):  
Graeme Newell
Keyword(s):  
Decision Making ◽  
Real Estate ◽  
Real Estate Market ◽  
Real Estate Investment ◽  
Content Type ◽  
Real Estate Markets ◽  
Market Transparency ◽  
Global Context ◽  
Business Competitiveness ◽  
Risk Dimensions

Purpose – Real estate market transparency is an important factor in real estate investment and occupier decision making. The purpose of this paper is to assess real estate transparency over 2004-2014 to determine whether the European real estate markets have become more transparent in a regional and global context. Design/methodology/approach – Using the JLL real estate transparency index over 2004-2014, changes in real estate market transparency are assessed for 102 real estate markets. This JLL real estate market transparency index is also assessed against corruption levels and business competitiveness in these markets. Findings – Improvements in real estate transparency are clearly evident in many European real estate markets, with several of these European real estate markets seen to be the major improvers in transparency from a global real estate markets perspective. Practical implications – Institutional investors and occupiers see real estate market transparency as a key factor in their strategic real estate investment and occupancy decision making. By assessing changes in real estate transparency across 102 real estate markets, investors and occupiers are able to make more informed real estate investment decisions across the global real estate markets. In particular, this relates to both investors and occupiers being able to more fully understand the risk dimensions of their international real estate decisions. Originality/value – This paper is the first paper to assess the dynamics of real estate market transparency over 2004-2014, with a particular focus on the 33 European real estate markets in a global context to facilitate more informed real estate investment and occupancy decision making.

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