scholarly journals Real Estate Markets and Lending: Does Local Growth Fuel Risk?

2021 ◽  
Author(s):  
Maximilian Zurek
Keyword(s):  
Real Estate ◽  
Local Level ◽  
Portfolio Risk ◽  
Real Estate Markets ◽  
Savings Banks ◽  
Price Growth ◽  
Real Estate Prices ◽  
Using Data ◽  
Credit Portfolio ◽  
Economic Forecasts

AbstractReal estate price growth affects credit risk for several reasons: it provides input for economic forecasts as it’s closely tied to economic growth; when used as collateral by banks, rising real estate prices may decrease both expected and actual losses; and banks may become less risk averse in lending practices in the presence of rising property prices. Therefore, we analyze these effects on loan portfolios’ estimated and realized risks on a local level. Using data of 390 German savings banks, however, we find that real estate prices have little or no impact on savings banks’ credit portfolio risk or risk precautions.

scholarly journals POWER LAWS IN REAL ESTATE PRICES DURING BUBBLE PERIODS

2012 ◽  
Vol 16 ◽  
pp. 61-81 ◽  
Author(s):  
TAKAAKI OHNISHI ◽  
TAKAYUKI MIZUNO ◽  
CHIHIRO SHIMIZU ◽  
TSUTOMU WATANABE
Keyword(s):  
Real Estate ◽  
Power Law ◽  
House Price ◽  
Power Laws ◽  
Cross Sectional ◽  
Price Distribution ◽  
Before And After ◽  
Real Estate Prices ◽  
Using Data ◽  
The U.S

How can we detect real estate bubbles? In this paper, we propose making use of information on the cross-sectional dispersion of real estate prices. During bubble periods, prices tend to go up considerably for some properties, but less so for others, so that price inequality across properties increases. In other words, a key characteristic of real estate bubbles is not the rapid price hike itself but a rise in price dispersion. Given this, the purpose of this paper is to examine whether developments in the dispersion in real estate prices can be used to detect bubbles in property markets as they arise, using data from Japan and the U.S. First, we show that the land price distribution in Tokyo had a power-law tail during the bubble period in the late 1980s, while it was very close to a lognormal before and after the bubble period. Second, in the U.S. data we find that the tail of the house price distribution tends to be heavier in those states which experienced a housing bubble. We also provide evidence suggesting that the power-law tail observed during bubble periods arises due to the lack of price arbitrage across regions.

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).

Housing Market Hedonic Price Study Based on Boosting Regression Tree

2017 ◽  
Vol 21 (6) ◽  
pp. 1040-1047 ◽  
Author(s):  
Guangtong Gu ◽  
Bing Xu ◽  
◽  
◽  
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Regression Tree ◽  
Gradient Boosting ◽  
Hedonic Price ◽  
Tree Model ◽  
Policy Makers ◽  
Real Estate Markets ◽  
Architectural Features ◽  
Real Estate Prices

Based on the purchase price data of new real estate markets three cities in China, Beijing, Shanghai, and Guangzhou, including architectural features, neighborhood property features, and location features, in this study a boosting regression tree model was built to study the factors and the influence path of housing prices from the microcosmic perspective. First, a classical hedonic price model was constructed to analyze and compare the significant effect factors on housing prices in the market segments of the three cities. Second, the gradient boosting regression tree method that is proposed in this paper was applied to the three markets in combination to analyze the influence paths and factors and the importance of the type of housing hedonic price. The influence paths of housing hedonic prices and decision tree rules are visualized. The significant housing features are effectively extracted. Finally, we present three main conclusions and several suggestions for policy makers to improve urban functions while stabilizing real estate prices.

scholarly journals International Real Estate Review

2003 ◽  
Vol 6 (1) ◽  
pp. 43-62
Author(s):  
Wen-Chieh Wu ◽  
◽  
Chin-Oh Chang ◽  
Zekiye Selvili ◽  
◽  
...  
Keyword(s):  
Real Estate ◽  
Banking System ◽  
Lower Percentage ◽  
Bank Profitability ◽  
Real Estate Markets ◽  
Nonperforming Loans ◽  
Price Performance ◽  
Lending Rate ◽  
Real Estate Prices

This paper examines the link between nonperforming loans, real estate prices, and the banking system. We found that the level of nonperforming loans affects bank profitability as well as the price performance of real estate markets. We also analyzed the factors that cause the ratio of nonperforming loans to total loans to fluctuate. We observed that a higher ratio of corporateloans to individual loans results in a lower percentage of nonperforming loans. In contrast, a lower real estate lending rate relative to the primary lending rate leads to a higher percentage of nonperforming loans. These results suggest that the percentage of nonperforming loans can be partially governed by the lending practices of banks.

scholarly journals Similarities in Time-Series of Housing Prices on Local Markets in Poland

2014 ◽  
Vol 22 (3) ◽  
pp. 45-53 ◽  
Author(s):  
Mirosław Belej ◽  
Sławomir Kulesza
Keyword(s):  
Real Estate ◽  
Structural Changes ◽  
Housing Prices ◽  
Local Markets ◽  
Real Estate Markets ◽  
The North ◽  
Real Estate Prices ◽  
Changes Over Time ◽  
External Stimuli ◽  
Over Time

Abstract This study examined similarities between local real estate markets in Poland from 2006 - 2013 by analyzing changes in housing prices. The analyses covered five cities - all of which are major centers of their regions: Warsaw (Mazovia - the center of Poland), Bialystok (Podlasie - the east of Poland), Cracow (Malopolska - the south of Poland), Poznan (Wielkopolska - the west of Poland) and Gdansk (Pomerania - the north of Poland). The time period was chosen so that it covered an interval of rapid changes in real estate prices (a housing bubble) and their subsequent relaxation to the equilibrium state. Firstly, a multi-dimensional analysis which took into account the Chebyshev distance was employed. This helped to conduct an analysis of the correlation of price changes over time, which revealed their concurrence and, moreover, showed specific propagation delays to external stimuli, and hence could be a measure of the market’s inertia. The degree of integration of the local markets under study changed only slightly over time; therefore, a thesis can be put forth in regard to the interrelation of local real estate markets, imagined as a system of communicating vessels. In the second stage, the damped harmonic oscillator model was employed to describe the observed evolution of real estate prices. This study exhibited high inertia in real estate markets, manifested during rapid structural changes in the system’s state occurring in conditions far from equilibrium. In long-term evolution, the pace of change is slow enough for the systems to remain close to equilibrium

scholarly journals Does Immigration Affect Residential Real Estate Prices? Evidence From Australia

2020 ◽  
Author(s):  
Narvada Gopy-Ramdhany ◽  
Boopen SEETANAH
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Housing Demand ◽  
Population Increase ◽  
Residential Real Estate ◽  
Vector Autoregressive ◽  
Long Run ◽  
Short Run ◽  
Real Estate Prices ◽  
Using Data

Abstract Worldwide migration flows have been gaining momentum over the past years, leading to population increases in some countries. Consequently, the population increase might have led to more housing demand in the host country. This study investigates the effect of immigration on housing prices in Australia by using data for eight states on a quarterly basis from 2004 – 2017. To study the possible dynamic and endogenous relationship between housing prices and immigration, a panel vector autoregressive error correction approach (PVECM) is adopted. Analysis of the results indicates that in the short run immigration positively and significantly affects housing prices, whereas in the long run no significant relationship was observed. From the regional breakdown and analysis, it is discerned that in some states there is significant and positive effect of immigration on residential real estate prices in the long run. Interestingly, analysis of reverse causation indicates that housing prices affect migration in a negative and significant way.

A Study on Operational Risk and Credit Portfolio Risk Estimation Using Data Analytics*

2020 ◽  
Author(s):  
Rongda Chen ◽  
Ze Wang ◽  
Liu Yang ◽  
Chi To Ng ◽  
T.C.E. Cheng
Keyword(s):  
Data Analytics ◽  
Risk Estimation ◽  
Operational Risk ◽  
Portfolio Risk ◽  
Using Data ◽  
Credit Portfolio

Gambling on Real Estate: Limited Rationality in the Global Economy

1991 ◽  
Vol 34 (4) ◽  
pp. 391-401 ◽  
Author(s):  
John R. Logan
Keyword(s):  
Real Estate ◽  
Global Economy ◽  
Causal Power ◽  
Local Level ◽  
Economic Restructuring ◽  
Interorganizational Network ◽  
Urban Theory ◽  
Real Estate Markets ◽  
Theoretical Approaches ◽  
Development Organizations

Urbanization is taking on a more global character, with increasing scale of development organizations and new linkages between developers and financial institutions. These changes bring into question the way sociologists think about urbanization processes. This paper argues that the reshaping of real estate markets under the influence of global restructuring is not a one-way process, nor is it necessarily rational or functional. One should be skeptical of theoretical approaches from either an ecological or Marxist perspective that attribute autonomous causal power to “globalization” or “economic restructuring.” Deal-making, politics, mistakes, and miscalculations are as essential to the interorganizational network at the global level as at the local level. The challenge for urban theory is not to shift from local to global explanations, but rather to examine how processes at both levels intersect and collide with one another.

Sign in / Sign up

Export Citation Format

Share Document