Mortgage market and housing prices. Evidence from financial risk

Author(s):  
O. I. Ivanov ◽  
M. M.S. Naimi

The article considers the problem of choosing between the ownership of residential real estate and its rental as a solution to the investment problem. The purpose of the article is to formalize this task using only financial variables (without explicitly including non-monetary preferences) and testing it on real Russian data on real estate and mortgage lending markets. The results can be used: a) at the house-hold level, which usually poorly take into account the financial side of the decision; b) at the level of macroeconomic policy to predict the dynamics of the mortgage market. We identified the following key model parameters: the expected rate of growth in housing and rental prices, mortgage interest, and the planned period of real estate ownership. The model demonstrates that for an average of Moscow or Russian housing with enough period of ownership, the purchase is generally more profitable in the cur-rent macroeconomic conditions. However, if the forecast for the dynamics of changes in housing prices worsens, when the nominal price increase is 5-8% lower than the discount rate, the answer may change in favor of renting. This is especially true in connection with the negative dynamics of real prices in the Russian housing market.  


2020 ◽  
Author(s):  
Nikodem Szumilo

Abstract This article examines the effect of a new lender’s entry into a local mortgage market on the supply of new loans, housing prices and repossessions in areas around its branches. I use the decision of the European Commission to force the UK’s largest retail bank to divest a part of its business as a shock to the entry of a new lender, and show that incumbent banks increase mortgage lending in areas where the new bank has its branches. Furthermore, house prices increase by around 5% in the real estate market impacted by the shock. Average transaction numbers and mortgage repossession rates also increase in places where the new bank enters. Overall, my results show that increased competition in the banking market can have adverse consequences for risk-taking and financial stability.


Urban Studies ◽  
2018 ◽  
Vol 56 (13) ◽  
pp. 2688-2708 ◽  
Author(s):  
Kyungsoon Wang

The advent of the millennium witnessed unparalleled volatility in the housing market, a cycle of bust and recovery to which some US neighbourhoods were resilient and others not. Most planning scholars interested in resilience have paid little attention to examining the resilience of the housing market to economic shocks at the neighbourhood level across the USA. Using cluster analysis and hierarchical linear models, together with changes in housing prices, this study examines patterns and drivers explaining neighbourhood resilience within the context of metropolitan housing markets over periods of housing boom, bust, and recovery. Findings suggest that neighbourhood and metropolitan factors associated with housing market resilience varied across space and time: housing and mortgage market conditions affected neighbourhood recovery in the relatively short term while most urban form variables affected recovery over the long term. In addition, the associations and recovery patterns varied among the types of metropolitan areas, showing that neighbourhoods in strong markets had more drivers of resilience and reverted to their original status more quickly than those in weak markets, highlighting the growth of regional housing disparity during the housing recovery. Across the nation, however, home values in neighbourhoods that experienced more extreme periods of boom and bust underwent short-lived depreciation during the recession but long-term appreciation. This study should help policy makers establish sound policies that stabilise neighbourhoods and prevent future downturns.


Author(s):  
R. Kelley Pace ◽  
Raffaella Calabrese

AbstractAutomated valuation models (AVMs) are widely used by financial institutions to estimate the property value for a residential mortgage. The distribution of pricing errors obtained from AVMs generally show fat tails (Pender 2016; Demiroglu and James Management Science, 64(4), 1747–1760 2018). The extreme events on the tails are usually known as “black swans” (Taleb 2010) in finance and their existence complicates financial risk management, assessment, and regulation. We show via theory, Monte Carlo experiments, and an empirical example that a direct relation exists between non-normality of the pricing errors and goodness-of-fit of the house pricing models. Specifically, we provide an empirical example using US housing prices where we demonstrate an almost perfect linear relation between the estimated degrees-of-freedom for a Student’s t distribution and the goodness-of-fit of sophisticated evaluation models with spatial and spatialtemporal dependence.


2018 ◽  
Vol 10 (10) ◽  
pp. 3452
Author(s):  
Fengyun Liu ◽  
Chuanzhe Liu ◽  
Honghao Ren

The regional systemic financial risks driven by escalating urban housing prices have been of great concern recently. Based on the theoretical analyses on the mechanism of formation of regional systemic financial risk driven by urban housing price fluctuations, this paper builds panel spatial economic models to empirically analyze the relationship between urban housing price fluctuations and regional systemic financial risks, in addition to their spatial linkages, in 13 cities in Jiangsu, a representative province of China. The empirical results show the following. (1) The excessive investment or speculation of local governments, banks, real estate developers, individuals, and families on the housing market stimulate the escalation in urban housing prices, leading to the systemic financial risks; (2) Urban housing prices and the land supply price of local governments have strong spatial contagion effects among cities, which will diffuse risks to adjacent cities, causing regional systemic financial risk; (3) Compared with North Jiangsu, South Jiangsu has more serious investment expansion from real estate developers and stronger spatial contagion effects, suggesting the existence of heavier regional systemic financial risks derived from housing price fluctuations; (4) North Jiangsu has slightly stronger “imitative behavior” among local governments, and fewer “substitution effects” of central cities’ demand to adjacent cities’ demand than does South Jiangsu.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Antonios Marios Koumpias ◽  
Jorge Martínez-Vázquez ◽  
Eduardo Sanz-Arcega

Purpose The purpose of this paper is to quantify to what extent the housing bubble in the early-to-mid 2000s in Spain exacerbated land planning corruption among Spain’s largest municipalities. Design/methodology/approach The authors exploit plausibly exogenous variation in housing prices induced by changes in local mortgage market conditions; namely, the rapid expansion of savings banks (Cajas de Ahorros). Accounting for electoral competition in the 2003–2007 and 2007–2009 electoral cycles among Spanish municipalities larger than 25,000 inhabitants, the authors estimate a positive relationship between housing prices and land planning corruption in municipalities with variation in savings bank establishments using instrumental variables techniques. Findings A 1% increase in housing prices leads to a 3.9% points increase in the probability of land planning corruption. Moreover, absolute majority governments (not needing other parties’ support) are more susceptible to the incidence of corruption than non-majority ones. Two policy implications to address corruption emerge: enhance electoral competition and increase scrutiny over land planning decisions in sparsely populated. Originality/value First empirical evidence of a formal link between the 2000s housing bubble in Spain and land planning corruption.


2013 ◽  
Author(s):  
Rod Duclos ◽  
Echo Wen Wan ◽  
Yuwei Jiang

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