scholarly journals Residential Mortgage Loans Delinquencies Analysis and Risk Drivers Assessment

2020 ◽  
Vol 4 (2) ◽  
pp. 104-112
Author(s):  
Aivars Spilbergs
Keyword(s):  
Price Index ◽  
House Price ◽  
Housing Price ◽  
Developed Countries ◽  
Mortgage Loans ◽  
The Sustainable Development ◽  
Residential Mortgage ◽  
Housing Price Index ◽  
Financial Difficulties ◽  
Credit Losses

Residential mortgage loans play an important role in improving living conditions in developed countries. In Latvia, however, residential mortgage volumes have declined throughout the post-crisis year’s and were at the end of 2018 12% below the end 2008 level, while the house price index ca. 25% below pre-crisis level. The main reasons for this are banks credit losses, which resulted in a revision of credit granting standards and a deteriorating in their availability. On the other hand, households have experienced increased uncertainty, both as a result of financial difficulties, experienced during the crisis years and political instability in the post-crisis years. It is therefore essential to identify the true risk drivers and to analyse them. Based on existing researches in other countries, the author has identified several dozen macro-economic indicators, such as the unemployment rate, wage growth, housing price index, etc. and micro factors such as the age of the borrower, total debt to income, loan-to-value, etc., have developed univariate and multivariate econometric models and have examined their statistical stability. Consequently, through a consistent application, it is possible to take sound credit decisions, both in banks and by households, and to contribute to the sustainable development of the housing market.

scholarly journals REGIONAL HOUSE PRICE INDEX CONSTRUCTION – THE CASE OF SWEDEN

2013 ◽  
Vol 17 (3) ◽  
pp. 278-304 ◽  
Author(s):  
Lars-Erik Ericson ◽  
Han-Suck Song ◽  
Jakob Winstrand ◽  
Mats Wilhelmsson
Keyword(s):  
Labor Markets ◽  
Price Index ◽  
House Price ◽  
Housing Price ◽  
Standard Errors ◽  
Academic Literature ◽  
Housing Price Index ◽  
Thin Markets ◽  
Price Indexes ◽  
Open Question

The academic literature on the construction of regional house price indexes usually uses geographic areas whose boundaries are administratively drawn. However such administrative regions might not be optimal for the construction of regional price indexes. When producing housing price indexes, we often encounter problems with insufficient number of observations. One way to remedy this problem is to estimate a quarterly index instead of a monthly index. Another possible way to mitigate the thin markets problem is to construct indexes for geographically aggregated regions. However, the literature that discusses methods of dealing with the problem of thin markets and especially geographical aggregation is very rare. The goal of this paper is to construct a housing price index for a major part of Sweden, and to construct price index series for a number of regions. The number of regions, and how their boundaries should be created in order to construct reliable regional price indexes, is however an open question. We apply traditional hedonic methodology in order to estimate house price indexes for both predefined regions whose boundaries are based on a division of labor markets in Sweden, as well as a division of regions based on statistical cluster analysis. The results from this study suggest that regions should be clustered together based on regional price levels and/or price development as clustering variables. If only geographical proximity is used as clustering variable, our computations show that there is a high risk that we end up with some clusters having large standard errors, which in turn might result in inaccurate indexes.

scholarly journals Dynamics of the US Housing Market: A Quantal Response Statistical Equilibrium Approach

Entropy ◽  
2018 ◽  
Vol 20 (11) ◽  
pp. 831 ◽  
Author(s):  
Özlem Ömer
Keyword(s):  
Housing Market ◽  
Maximum Entropy ◽  
Price Index ◽  
Housing Price ◽  
Statistical Equilibrium ◽  
Market Dynamics ◽  
Quantal Response ◽  
Housing Price Index ◽  
The Us ◽  
Equilibrium Approach

In this article, we demonstrate that a quantal response statistical equilibrium approach to the US housing market with the help of the maximum entropy method of modeling is a powerful way of revealing different characteristics of the housing market behavior before, during and after the recent housing market crash in the US. In this line, a maximum entropy approach to quantal response statistical equilibrium model (QRSE) is employed in order to model housing market dynamics in different phases of the most recent housing market cycle using the S&P Case Shiller housing price index for 20 largest- Metropolitan Regions, and Freddie Mac housing price index (FMHPI) for 367 Metropolitan Cities for the US between 2000 and 2015. Estimated model parameters provide an alternative way to understand and explain the behaviors of economic agents, and market dynamics by questioning the traditional economic theory, which takes assumption for the behavior of rational utility maximizing representative agent with self-fulfilled expectations as given.

Testing the Predictability of U.S. Housing Price Index Returns Based on an IVX-AR Model

2020 ◽  
Vol 115 (532) ◽  
pp. 1598-1619 ◽  
Author(s):  
Bingduo Yang ◽  
Wei Long ◽  
Liang Peng ◽  
Zongwu Cai
Keyword(s):  
Price Index ◽  
Housing Price ◽  
Ar Model ◽  
Housing Price Index
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