Multiscale Effects of Multimodal Public Facilities Accessibility on Housing Prices Based on MGWR: A Case Study of Wuhan, China

The layout of public service facilities and their accessibility are important factors affecting spatial justice. Previous studies have verified the positive influence of public facilities accessibility on house prices; however, the spatial scale of the impact of various public facilities accessibility on house prices is not yet clear. This study takes transportation analysis zone of Wuhan city as the spatial unit, measure the public facilities accessibility of schools, hospitals, green space, and public transit stations with four kinds of accessibility models such as the nearest distance, real time travel cost, kernel density, and two step floating catchment area (2SFCA), and explores the multiscale effect of public services accessibility on house prices with multiscale geographically weighted regression model. The results show that the differentiated scale effect not only exists among different public facility accessibilities, but also exists in different accessibility models of the same sort of facility. The article also suggests that different facilities should adopt its appropriate accessibility model. This study provides insights into spatial heterogeneity of urban public service facilities accessibility, which will benefit decision making in equal accessibility planning and policy formulation for the layout of urban service facilities.

The Age–Period–Cohort Problem in Hedonic House Prices Models

The age–period–cohort problem has been studied for decades but without resolution. There have been many suggested solutions to make the three effects estimable, but these solutions mostly exploit non-linear specifications. Yet, these approaches may suffer from misspecification or omitted variable bias. This paper is a practical-oriented study with an aim to empirically disentangle age–period–cohort effects by providing external information on the actual depreciation of housing structure rather than taking age as a proxy. It is based on appraisals of the improvement values of properties in New Zealand to estimate the age-depreciation effect. This research method provides a novel means of solving the identification problem of the age, period, and cohort trilemma. Based on about half a million housing transactions from 1990 to 2019 in the Auckland Region of New Zealand, the results show that traditional hedonic prices models using age and time dummy variables can result, ceteris paribus, in unreasonable positive depreciation rates. The use of the improvement values model can help improve the accuracy of home value assessment and reduce estimation biases. This method also has important practical implications for property valuations.

An Improved Model for House Price/Land Price Prediction using Deep Learning

House price predictions are a crucial reflection of the economy; sometimes house prices include the land prices and demand of the place and location. The house price and land price are two different things, but both are important for both buyers and sellers. This chapter introduced the combination of ML and DL approaches to predict the house price with the updated regression algorithm. The algorithm named as ‘Mopuri algorithm' reads the 14 attributes like crime rate, population density, rooms, etc. and produces the cost estimation result as a prediction. The proposed model accurately estimates the worth of the house as per the given features. The results of the model tested with the different datasets existing in the Kaggle data source using Python libraries with the Jupyter platform and continuation of the model using the Android OS to develop the smart home web-based application.

Developments and convergence of real housing prices in Poland during the COVID-19 pandemic: focus on voivodeship capitals

The paper aims to present and assess the changes in real housing prices in Poland during the COVID-19 pandemic. We analyse transaction prices of residential premises in a multi-family housing (apartments) in the primary and secondary markets within 16 administrative capitals of voivodeships. We use quarterly data on House Prices Database collected by the National Bank of Poland and data on quarterly price indices of consumer goods and services from Statistics Poland. The research period covers the period 2018-2021, with distinction into COVID-19- and pre-COVID-19 periods. We observe the highest housing prices in Warszawa, Gdańsk, Kraków, and Wrocław, while the lowest in Zielona Góra and Kielce. Surprisingly, the growth rate in real housing prices in the pandemic sub-period is lower than in corresponding pre-COVID-19 period. In the COVID-19 sub-period, we observe the most significant increases in real estate prices in Zielona Góra and Szczecin in the primary market, and Kraków, Lublin, and Łódź in the secondary market. Additionally, we reveal the existence of regional price convergence in the housing market in analysed cities, both in primary and secondary markets. However, we do not observe a common price convergence, but only convergence clubs (city-groups) where the housing prices tend to converge in the COVID-19 sub-period.

Mortgage volume and macroeconomic factors: Evidence from Turkey

This paper investigates the impacts of several macroeconomic variables on Turkey's volume of mortgage loans. Johansen cointegration test, vector error correction model, Granger causality tests, variance decomposition, and impulse-response analysis is employed for the econometric analysis to show short and long-run relationships between the variables using time series monthly data from January 2010 to March 2020. Paper results demonstrate that growth of housing credit size negatively correlates with mortgage interest rates, US Dollar/Turkish Lira exchange rate and level of real estate supply. At the same time, there is a positive correlation with house prices. Causal relationships between mortgage volume and macroeconomic indicators are bidirectional for all variables, except for mortgage interest rates. There is a one-way causality relationship from mortgage rates to mortgage loan volume. Econometric analyses show that the recent steep depreciation in the Turkish Lira hurts the Turkish mortgage market. In conclusion, a stable economic environment is essential to build a robust mortgage market.

Information Opportunities of Administrative Data on Residential Real Estate Transactions for Calculating the House Prices in Russia’s Housing Market

Purpose of the study. Development, justification and testing of a methodology for improving statistical monitoring of average prices in the Russian housing market, based on the use of registration information of the Unified State Register of Real Estate (USRN) on transactions for the purchase of residential real estate, in accordance with international statistical standards for Residential Property Price statistics.Materials and methods. The theoretical basis of the study was the United Nations system of national accounts (version of 2008), including the European system of accounts as amended in 2010. The research methodological base was made up of official statistical sources: metadata and international statistics guidelines in the field of national accounting, Handbook on Residential Property Price Indices and related housing indicators, as well as methodological provisions and an album of Rosstat forms, and methodological materials of the administrative statistics of the Federal Service for State Registration, Cadastre and Cartography of the Russian Federation (Rosreestr). The depersonalized registration data on households’ market transactions of the Unified State Register of Property Rights and Transactions maintaining by Rosreestr were used as an information database of the research.Results. The main result of the study is the design and substantiation of a system of indicators for the construction of an integrated information source for Residential Property Price statistics, on the base on interdepartmental information interaction.Conclusion. The proposed system of indicators will provide a highquality database that could be used in order to construct constant quality House Prices for various types of homogeneous residential property in the housing market, complying with the concepts of international statistical standards.