House Price Growth, Collateral Constraints and the Accumulation of Homeowner Debt in the United States

2011 ◽  
Vol 11 (1) ◽  
Author(s):  
Richard Disney ◽  
John Gathergood
2012 ◽  
Vol 102 (3) ◽  
pp. 134-140 ◽  
Author(s):  
Fernando Ferreira ◽  
Joseph Gyourko

Examination of detailed geographical information on U.S. housing transactions from 1993 to 2009 find much heterogeneity at the neighborhood level in when the recent boom began, how big the initial jumps in price growth were, how long the booms lasted, and what types of neighborhoods boomed first. There is less neighborhood-level heterogeneity in when the bust began and in aggregate price appreciation during the boom. This heterogeneity suggests that there was no one dominant cause of the boom. We also comment on how very local data may help understand the role of contagion, among other housing market phenomena.


2011 ◽  
Vol 28 (6) ◽  
pp. 2369-2376 ◽  
Author(s):  
Mark J. Holmes ◽  
Jesús Otero ◽  
Theodore Panagiotidis

2019 ◽  
Vol 11 (15) ◽  
pp. 4151
Author(s):  
Xiaochun Jiang ◽  
Wei Sun ◽  
Peng Su ◽  
Ting Wang

Based on monthly data of six major financial variables from January 1996 to December 2018, this paper employs a structural vector autoregressive model to synthesize financial conditions indices in China and the United States, investigates fluctuation characteristics and the synergy of financial volatility using a Markov regime switching model, and further analyzes the transmission paths of the financial risk by using threshold regression. The results show that there is an approximately three-year cycle in the financial fluctuations of both China and the United States, and such fluctuations have a distinct asymmetry. Two thresholds were applied (i.e., 0.361 and 0.583), taking the synergy index (SI) as the threshold variable. The impact of the trade factor is significant across all thresholds and is the basis of financial linkages. When the SI is less than 0.361, the exchange rate factor is the main cause of the financial cycle comovement change. As the financial volatility synergy increases, the asset factor and interest rate factor start to become the primary causes. When the level of synergy breaks through 0.583, the capital factor based on stock prices and house price is still the main path of financial market linkage and risk transmission, but the linkage of monetary policy shows a restraining effect on synergy. Therefore, it is necessary to monitor the financial cycle and pay attention to the coordination between countries in terms of policy regulation.


2020 ◽  
Vol 72 (3) ◽  
pp. 780-803 ◽  
Author(s):  
By Kadir Atalay ◽  
Garry F Barrett ◽  
Rebecca Edwards ◽  
Chaoran Yu

Abstract We analyse the effect of housing wealth on household indebtedness in a life-cycle framework. Exploiting longitudinal household data and temporal and geographic variation in house prices, our empirical results indicate that households respond to increases in housing wealth by significantly increasing their debt. The effect is strongest for households that are moderately leveraged, highlighting the importance of collateral constraints. Furthermore, we uncover a weaker wealth effect from house price growth for households that have faced negative shocks to income or employment. Importantly, our findings are consistent with the theoretical predictions of the life-cycle model: households increase their mortgage debt, but not their unsecured credit card debt. A novel finding is that we uncover a moderate positive wealth effect on investment loans.


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