scholarly journals House Prices, Home Equity and Entrepreneurship: Evidence from U.S. Census Micro Data

2015 ◽  
Author(s):  
Sari Kerr ◽  
William Kerr ◽  
Ramana Nanda
Keyword(s):  
House Prices ◽  
Micro Data ◽  
Home Equity

scholarly journals The Housing Market (s) of San Diego

2015 ◽  
Vol 105 (4) ◽  
pp. 1371-1407 ◽  
Author(s):  
Tim Landvoigt ◽  
Monika Piazzesi ◽  
Martin Schneider
Keyword(s):  
Cross Section ◽  
San Diego ◽  
House Prices ◽  
Credit Market ◽  
San Diego County ◽  
Micro Data ◽  
Assignment Model ◽  
Metro Area ◽  
Poor Households ◽  
Credit Market Frictions

This paper uses an assignment model to understand the cross section of house prices within a metro area. Movers’ demand for housing is derived from a life-cycle problem with credit market frictions. Equilibrium house prices adjust to assign houses that differ by quality to movers who differ by age, income, and wealth. To quantify the model, we measure distributions of house prices, house qualities, and mover characteristics from micro-data on San Diego County during the 2000s boom. The main result is that cheaper credit for poor households was a major driver of prices, especially at the low end of the market. (JEL D14, D91, R21, R31)

scholarly journals House Prices, Home Equity and Health

2013 ◽  
Author(s):  
Eleonora Fichera ◽  
John Gathergood
Keyword(s):  
House Prices ◽  
Home Equity

scholarly journals House Prices, Home Equity–Based Borrowing, and the US Household Leverage Crisis

2011 ◽  
Vol 101 (5) ◽  
pp. 2132-2156 ◽  
Author(s):  
Atif Mian ◽  
Amir Sufi
Keyword(s):  
Instrumental Variables ◽  
House Prices ◽  
Significant Fraction ◽  
Household Debt ◽  
Home Equity ◽  
Instrumental Variables Estimation ◽  
The Us ◽  
Credit Scores

Borrowing against the increase in home equity by existing homeowners was responsible for a significant fraction of the rise in US household leverage from 2002 to 2006 and the increase in defaults from 2006 to 2008. Instrumental variables estimation shows that homeowners extracted 25 cents for every dollar increase in home equity. Home equity–based borrowing was stronger for younger households and households with low credit scores. The evidence suggests that borrowed funds were used for real outlays. Home equity–based borrowing added $1.25 trillion in household debt from 2002 to 2008, and accounts for at least 39 percent of new defaults from 2006 to 2008. JEL: D14, R31

scholarly journals House Prices, Home Equity Borrowing, and Entrepreneurship

2015 ◽  
Vol 28 (8) ◽  
pp. 2399-2428 ◽  
Author(s):  
Stefano Corradin ◽  
Alexander Popov
Keyword(s):  
House Prices ◽  
Home Equity

scholarly journals How do house prices affect consumption? Evidence from micro data

2007 ◽  
Vol 54 (3) ◽  
pp. 591-621 ◽  
Author(s):  
John Y. Campbell ◽  
João F. Cocco
Keyword(s):  
House Prices ◽  
Micro Data

scholarly journals The Covid-19 Effect on Security Mortgage Valuation

2021 ◽  
Vol 25 (1) ◽  
pp. 13-26
Author(s):  
Giovanna Di Lorenzo ◽  
◽  
Massimiliano Politano ◽  
Keyword(s):  
Interest Rates ◽  
House Prices ◽  
Gompertz Model ◽  
Mortgage Market ◽  
Elderly Persons ◽  
Home Equity ◽  
Reverse Mortgage ◽  
Mortgage Loans ◽  
Alternative Source ◽  
Cir Process

The reverse mortgage market has been expanding rapidly in developed economies in recent years. Reverse mortgages provide an alternative source of funding for retirement income and health care costs. We often hear the phrase “house rich and cash poor” to refer the increasing number of elderly persons who hold a substantial proportion of their assets in home equity. Reverse mortgage contracts involve a range of risks from the insurer’s perspective. When the outstanding balance exceeds the housing value before the loan is settled, the insurer suffers an exposure to crossover risk induced by three risk factors: interest rates, house prices, and mortality rates. In this context, Covid-19 has occurred and the insurer is faced with this additional source of risk. We analyse the combined impact of these risks on the pricing and the risk profile of reverse mortgage loans. We consider a CIR process for the evolution of the interest rate, a Black & Scholes model for the dynamics of house prices and the Gompertz model for the trend in mortality Our results show that the decrease in the mortality curve due to Covid exposes the insurer to higher risks once the shock is reabsorbed. The risk is higher the higher the age of entry. Only a significant reduction of the shock adjustment coefficient will return the situation to normality.

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