scholarly journals Consistency of bootstrap approximation to the null distributions of local spatial statistics with application to house price analysis

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Chang-Lin Mei ◽  
Shou-Fang Xu ◽  
Feng Chen
Keyword(s):  
Spatial Statistics ◽  
Bootstrap Method ◽  
Spatial Association ◽  
House Price ◽  
Housing Price ◽  
Bootstrap Approximation ◽  
Local Statistics ◽  
Null Distributions ◽  
Local Spatial Statistics ◽  
Distribution Of A Statistic

Abstract With the increasing availability of spatially extensive geo-referenced data, much attention has been paid to the use of local statistics to identify local patterns of spatial association, in which the null distributions of local statistics play an essential role in the related statistical inference. As a powerful tool to approximate the distribution of a statistic, the bootstrap method is used in this paper to derive null distributions of the commonly used local spatial statistics including local Getis and Ord’s $G_{i}$ G i , Moran’s $I_{i}$ I i and Geary’s $c_{i}$ c i . Strong consistency of the bootstrap approximation to the null distributions of the statistics is proved under some mild conditions, and the Boston housing price data are analyzed to demonstrate the application of the theoretical results.

Three essays on China's housing market, monetary policy and macroeconomy

2019 ◽  
Author(s):  
◽  
Yifeng Jia
Keyword(s):  
Monetary Policy ◽  
Housing Market ◽  
Negative Impact ◽  
House Price ◽  
Housing Price ◽  
Policy Instruments ◽  
Heterogeneous Effects ◽  
Price Appreciation ◽  
Economic Stimulus ◽  
Monetary Policy Shock

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] This dissertation studies China's housing market and macroeconomic activity with a strong focus on the role of monetary policy behind the markets. The first two chapters concentrate on the house price dynamics in China. Chapter 1 examines the in influence of monetary policy on China's housing price fluctuation by estimating a VAR model with China's aggregated house price data from 1998Q1 to 2015Q4. The monetary policy shock is identify ed by the sign restriction approach following Uhlig (2005), with the identification assumptions extended to three common policy instruments utilized by the central bank of China: interest rate, required reserve ratio and M2. The results suggest a negative impact of a contractionary monetary policy shock on the house price, and M2 tends to be the most effective monetary instruments in terms of policy transmission. The framework is also extended to examine the link between China's 2008 government economic stimulus plan and the subsequent house price appreciation. The obtained evidence suggests that the economic stimulus props up the house price, but its contribution to the post-2008 house price appreciation is not as prominent as indicated by other relevant studies. However, this discrepancy may be explained by the heterogeneous effects of the stimulus policy on local housing markets across China

International Real Estate Review

2009 ◽  
Vol 12 (3) ◽  
pp. 193-220
Author(s):  
Karol Jan Borowiecki ◽  
Keyword(s):  
Real Estate ◽  
Positive Impact ◽  
House Prices ◽  
House Price ◽  
Housing Price ◽  
Quality Improvements ◽  
Vector Autoregressive ◽  
Price Growth ◽  
Price Determinants ◽  
A Minor

This paper studies the Swiss housing price determinants. The Swiss housing economy is reproduced by employing a macro- series from the last seventeen years and constructing a vector-autoregressive model. Conditional on a comparatively broad set of fundamental determinants considered, i.e. wealth, banking, demographic and real estate specific variables, the following findings are made: 1) real house price growth and construction activity dynamics are most sensitive to changes in population and construction prices, whereas real GDP, in contrary to common empirical findings in other countries, turns out to have only a minor impact in the short-term, 2) exogenous house price shocks have no long-term impacts on housing supply and vice versa, and 3) despite the recent substantial price increases, worries of overvaluation are unfounded. Furthermore, based on a self-constructed quality index, evidence is provided for a positive impact of quality improvements in supplied dwellings on house prices.

scholarly journals Housing Prices in Unregulated Markets: Study on Verticalised Dwellings in Santiago de Chile

Buildings ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 6 ◽  
Author(s):  
José Francisco Vergara-Perucich ◽  
Carlos Aguirre-Nuñez
Keyword(s):  
Housing Market ◽  
Affordable Housing ◽  
Housing Prices ◽  
House Price ◽  
Housing Price ◽  
Housing Affordability ◽  
Price Formation ◽  
Land Values ◽  
Santiago De Chile ◽  
Data Transparency

Chile faces a housing affordability crisis, given that most of the population is unable to secure a house. While housing prices between 2008 and 2019 increased by 63.96%, wages only increased by 21.85%. This article presented an analysis of the housing price configuration for the main borough in the country—Santiago. The assessment focused on verticalised housing constructed between 2015 and 2019. The article developed an exploratory study on the price of housing in Santiago to generate a diagnosis to identify the role played by expectations of profitability when configuring price. Based on the information generated, we sought to contribute to the discussion on public policies that advance the development of affordable housing in central boroughs with high urban value, as is the case for Santiago’s borough of Greater Santiago. We hypothesised that profit expectation of real estate developers plays a key role in the housing prices, and an adjustment in the profit ratios might increase the affordability while keeping the housing market above profitable rates. This research addressed the lack of data transparency in the Chilean housing market with archival research, reconstructing costs and earnings from projects based on official registrations of transactions at the borough level. In Chile, the access to investment costs, land values, yields, and house price formation are not publicly available, even though these factors imply that many households are facing severe difficulties in paying for and accessing decent housing.

Estimating the price of apartments in Tehran using extracted compound variables

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Javad Koohpayma ◽  
Meysam Argany
Keyword(s):  
Design Methodology ◽  
House Price ◽  
Housing Price ◽  
Least Square ◽  
Hedonic Method ◽  
Content Type ◽  
Ordinary Least Square ◽  
Different Types ◽  
High Inflation ◽  
Practical Implications

Purpose Housing price is a barometer of a national economy. In recent years, Iran experienced high inflation in its economy, which affects everything, including housing. The purpose of this study is the estimation of the value of residential apartments of Tehran using ordinary least square (OLS) and geographically weighted regression (GWR) methods. Design/methodology/approach This paper proposed a method for determining the compound variables and used them to estimate and evaluate the prices in the district six of Tehran city. Also, this paper compared the GWR and OLS methods with different types of factors and their influences in house price estimations. Findings During the high inflation period of the study period, the age of buildings, inflation, parking, storage room and their locations are the most critical factors that affect the price of apartments in district six of Tehran. Besides, compound variables have the most influence on the prediction of the prices. Research limitations/implications The exact location of the apartments in the study area were unknown. Therefore, the positions are extracted from their addresses. The uncertainty of location forced us to ignore the neighborhood terms in the hedonic method. Practical implications The exact locations of the apartments in the study area were unknown. Therefore, the positions are extracted from their addresses. The uncertainty of location forced us to ignore the neighborhood terms in the hedonic method. Originality/value The originality of the proposed method is that it used a different approach to determine the valid variables of the apartment prices. Also, the evaluation of the method showed that the proposed variables are significantly useful.

Regional housing price dependency in the UK: A dynamic network approach

Urban Studies ◽  
2020 ◽  
pp. 004209802094348
Author(s):  
Dayong Zhang ◽  
Qiang Ji ◽  
Wan-Li Zhao ◽  
Nicholas J Horsewood
Keyword(s):  
Housing Market ◽  
House Prices ◽  
House Price ◽  
Housing Price ◽  
Dynamic Network ◽  
Network Approach ◽  
Market Interactions ◽  
Partial Correlations ◽  
Regional Housing Market ◽  
The Uk

The cross-regional dependency in the UK housing market is analysed using regional house price indices. In this article, a network approach based on partial correlations is proposed, along with rolling-window analysis to consider potential time-varying dependency. The results show that house prices in the outer South East region have the strongest influence on regional housing market interactions in the UK. This influence is stronger when the markets are highly interconnected, whereas the house prices in London have the strongest influence when the UK regional housing markets are relatively less connected.

Study on the Prediction Control Model Based on GM(1, 1)

2014 ◽  
Vol 631-632 ◽  
pp. 728-731
Author(s):  
Zhong Cheng Zhang
Keyword(s):  
House Price ◽  
Housing Price ◽  
Development Trend ◽  
Control Model ◽  
Grey Prediction ◽  
Grey System ◽  
Prediction Theory ◽  
Prediction Control ◽  
And Control ◽  
The Development Trend

With the development and application of prediction theory in the fields of engineering and control, the grey prediction model is introduced. Real estate can be regarded as a grey system in the engineering circle, and housing price is an uncertain indicator which is affected by multiple factors such as policy, market, and economy. In this paper, we study the prediction control problem of housing price, and present a prediction control model of housing price based on GM(1, 1). From the house price data of Huanggang city in recent five years, we use this prediction control model to predict the development trend of housing price in the next five years. We try to provide an effective reference for housing price control.

A housing price index with the improvement-value adjusted repeated sales (IVARS) method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chung Yim Edward Yiu ◽  
Ka Shing Cheung
Keyword(s):  
Price Index ◽  
Simulation Analysis ◽  
House Price ◽  
Housing Price ◽  
Housing Quality ◽  
Repeat Sales ◽  
Open Market ◽  
Hedonic Price ◽  
Content Type ◽  
Price Movements

Purpose The repeat sales house price index (HPI) has been widely used to measure house price movements on the assumption that the quality of properties does not change over time. This study aims to develop a novel improvement-value adjusted repeat sales (IVARS) HPI to remedy the bias owing to the constant-quality assumption. Design/methodology/approach This study compares the performance of the IVARS model with the traditional hedonic price model and the repeat sales model by using half a million repeated sales pairs of housing transactions in the Auckland Region of New Zealand, and by a simulation approach. Findings The results demonstrate that using the information on improvement values from mass appraisal can significantly mitigate the time-varying attribute bias. Simulation analysis further reveals that if the improvement work done is not considered, the repeat sales HPI may be overestimated by 2.7% per annum. The more quality enhancement a property has, the more likely it is that the property will be resold. Practical implications This novel index may have the potential to enable the inclusion of home condition reporting in property value assessments prior to listing open market sales. Originality/value The novel IVARS index can help gauge house price movements with housing quality changes.

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