Accuracy of Households’ Dwelling Valuations, Housing Demand and Mortgage Decisions: Israeli Case

Abstract

Housing policy, as well as academic research, are increasingly concerned with the role of bias in subjective dwelling valuations as a proximate measure of households’ house price expectations and their relationship with housing demand. This paper contributes to this area of study by exploring the possibility of simultaneous relationships between households’ price expectations and incentive to maximise the size of housing services demanded also accounting for the supply side factors and regional perspective. The empirical estimation takes the form of a system of a two simultaneous equations model applying two stage least squares estimation technique. Cross sectional estimations utilise data extracted from the Israeli Longitudinal Panel Survey (LPS) data. Applying the best available proxy for households’ price expectations, calculated as the ratio between subjective dwelling valuations (LPS) and the estimated market value of the same properties, research has identified the interrelated factors that simultaneously influence householders’ price expectations and housing demand. Results offer conceptual and empirical advantages, highlighting the imperfect nature of the housing market, as reflected by the inseparability of bias in subjective valuations and housing decisions.

Short-run dynamics and long-run effects of monetary policy on residential property prices in South Africa

“…Mortgage finance is one of the primary sources of financing the acquisition of residential properties in South Africa. An increase in access to credit increases the demand for properties, and when demand increases, so do the prices holding the supply of residential properties constant (Favara and Imbs, 2015; Koblyakova et al , 2021). The study has further shown that an appreciation in the rand’s value negatively impacts residential property prices.…”

“…Despite long and vast literature on monetary policy on house prices, there is a growing consensus that central banks’ influence on monetary policy has contributed significantly to the residential property prices fluctuations. The boom and bust of house prices were attributed to changes in several monetary policy proxies such as interest rates (Baily et al , 2008; Dullien et al , 2008; Dieckelmann et al , 2023; Jordà et al , 2015; Shi et al , 2014), conditions of obtaining mortgage finance, (Karley, 2006; Koblyakova et al , 2021) and other factors such as economic growth (Agnello and Sousa, 2009; Khan et al , 2014; Yildirim and Yağcibaşi, 2019). The study discussed literature with regard to the impact on interest rates on house prices, the impact of mortgage finance on residential property prices and finally, the impact of other monetary policy factors such as economic growth, inflation, inflation and exchange rate.…”

“…The Bank for International Settlement (2022) further noted that in the third quarter of 2021, global residential property prices accelerated to 5.5% yearly in real terms, the greatest since the eve of the 2007/2008 global financial crisis. The boom and bust of house prices were attributed to changes several monetary policy proxies such as interest rates (Baily et al , 2008; Dieckelmann et al , 2023; Jordà et al , 2015; Dullien et al , 2008; Shi et al , 2014), conditions of obtaining mortgage finance (Karley, 2006; Koblyakova et al , 2021) and other factors such as economic growth (Agnello and Sousa, 2009; Khan et al , 2014; Yildirim and Yağcibaşi, 2019). Given the potential impact monetary policy variables have on residential property prices, the paper addresses the question of how the current monetary policy regime in South Africa has managed to influence residential property prices in the short and long run.…”

Análisis de los determinantes socioeconómicos y su incidencia en la tenencia de viviendas propias en la ciudad de Machala, Ecuador

“…Una de las variables que aporta de manera positiva al modelo es la edad, debido a que es importante destacar la capacidad de experiencia y de negociación en la adquisición de viviendas, con un incremento de 1.33%, por eso Koblyakova et al (2021) indican que en su estudio la edad afecta de manera positiva y bajo esto los hogares tienden a controlar la demanda de viviendas. Por eso los jefes de hogar en cuanto a edad bordean por los 46 años quienes tienden a destacar más en la tenencia de viviendas.…”

Real Estate Market Perceptions, Housing and Investment Plans of Students and Graduates

“…The scientific literature on the real estate market focuses mainly on the analysis of housing demand and supply (Elder & Zumpano, 1991;Kenny, 1999;Börsch-Supan et al, 2001;Fingleton, 2008;Davidoff, 2013;Glaeser & Gyourko, 2018;Koblyakova et al, 2022). Researchers using econometric models try to forecast the forces of supply and demand to illustrate the directions of the real estate market.…”