Determinants of housing prices from an urban economic point of view: evidence from Hungary

2019 ◽  
Vol 12 (1) ◽  
pp. 2-31 ◽  
Author(s):  
Norbert Czinkan ◽  
Áron Horváth
Keyword(s):  
Population Growth ◽  
Housing Stock ◽  
Housing Prices ◽  
Housing Price ◽  
Ordinary Least Squares ◽  
Point Of View ◽  
City Size ◽  
Economic Point ◽  
Content Type ◽  
Urban Economic

Purpose The purpose of the paper is to investigate a cross section of Hungarian settlement-level unit housing prices with a special emphasis on measuring the effect of population and its growth, along with accessibility to the centre of an aggregated spatial unit such as a micro-region, county or region, for the period of 2001-2011. Design/methodology/approach The analysis uses cross-sectional ordinary least squares techniques with Moulton-corrected standard errors. The estimation is guided by the implications of a simplified monocentric urbanized area framework following the model of DiPasquale and Wheaton (1996), and the econometric model is augmented with population growth rate at the settlement level to bridge the theory explaining rents and data base containing prices instead. Findings The location is a key factor in determining housing prices: living 10 min further from the centre results in 11 per cent cheaper housing. When estimating bid-rent curves, results show that it is crucial to control for city size and the income effect. The elasticity of housing price with respect to city size is 0.09 according to our preferred model. Population growth has an asymmetric impact on housing prices: municipalities with positive expected population growth have higher prices today. Practical implications Estimating the quantitative relationship between commuting time and housing price is crucial for a cautious infrastructure development. The benefits of improved roads and faster access could be capitalized in appreciating the housing stock. Estimating the slope of the bid-rent curve is one possible ex ante quantification of the benefits of a public development. Originality/value One contribution of this research is providing empirical evidence to surprisingly limited applied work in the field of (monocentric) urban models using data from the CEE region. Second, to the best of the authors’ knowledge, this is the first study to investigate Hungarian settlement-level unit prices from an urban economic point of view.

Cops and COVID: an examination of California officers' perceptions and experiences while policing during a pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
John Shjarback ◽  
Obed Magny
Keyword(s):  
Police Officers ◽  
Online Survey ◽  
Ordinary Least Squares ◽  
Point Of View ◽  
Policy Implications ◽  
Organizational Level ◽  
Sensitive Information ◽  
Content Type ◽  
Police Agencies ◽  
Police Executives

PurposeUsing online survey data from a sample of 440 police officers in California throughout May 2020, the current study collected time-sensitive information on officers' perceptions and departmental experiences in the wake of the pandemic. It examined officers' perceptions of agency responsivity as well as their perceptions of morale, stress and risk following agency responses and changes in policy patterns, service delivery innovations and other administrative challenges.Design/methodology/approachCOVID-19 had a tremendous impact on the law enforcement community, who continued to work and adapt in order to provide public safety. During the first few months of the pandemic, a number of national data collection efforts set out to understand what police agencies, at the organizational-level, were doing to address the crisis. Largely missing from these initial discussions were the perspectives of individual officers, particularly how they felt about their respective departments ensuring safety and balancing risk.FindingsResults from ordinary least squares (OLS) regressions found that the number of departmental changes made in the wake of COVID-19 that reduced police–public contact was associated with (1) increased levels of perceived agency responsivity to officer needs (i.e. balancing officer safety, taking active steps to maintain officers' mental health) and (2) reduced levels of perceived negative outlook (e.g. stress, low morale, danger/risk). Policy implications and the importance of police executives' decisions during crisis are discussed.Originality/valueThis study is one of the first, to the authors’ knowledge, to examine perceptions of policing during the pandemic from an individual officer point of view rather than an organizational standpoint.

Restart tourism | build the future

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rita Marques
Keyword(s):  
Value Chain ◽  
Great Influence ◽  
Point Of View ◽  
Political Community ◽  
Data Systems ◽  
Scientific Publications ◽  
Economic Point ◽  
Content Type ◽  
The Future ◽  
The Impact

PurposeThis viewpoint aims to explore the question: How can we restart and monitor the path towards the tourism of the future?Design/methodology/approachThis paper identifies the progress made at scientific, institutional, political and technological levels, and how it is possible to foresee that we will enter in a new era of tourism indicators.FindingsA significant body of literature clearly demonstrates that tourism cannot be viewed simply from an economic point of view as it has a great influence on sociocultural and environmental dimensions. The impact of tourism and how to ensure its long-term success has been invoked for the last few decades, leading to the direct consideration of sustainability indicators in a wide array of scientific publications. However, despite significant advances, the lack of funding, lack of support or interest from the political community, bureaucracies or lack of methodological guidance and of technical skills along the entire value chain pose clear challenges to the development and adoption of wide data systems to support sustainable tourism policies.Originality/valueThe paper sheds light on the Portuguese position regarding the recovery of the tourism sector in the aftermath of the COVID-19 pandemic. It also highlights the commitment to knowledge and monitoring of sustainability in tourism, articulated at international level, and how this is essential in order to make progress and to overcome the challenges facing the sector. At the same time, it demonstrates how fundamental it is to identify solutions to boost the potential of tourism as an economic, social, environmental and cultural phenomenon.

Dynamic effects and spatial heterogeneity of land supply on housing price: evidence from Nanchang, China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhijiang Wu ◽  
Yongxiang Wang ◽  
Wei Liu
Keyword(s):  
Spatial Heterogeneity ◽  
House Prices ◽  
Housing Prices ◽  
Housing Price ◽  
Dynamic Effects ◽  
Negative Effects ◽  
Land Supply ◽  
Content Type ◽  
Major Factors ◽  
The City

Purpose Economic fundamentals are recognized as determining factors for housing on the city level, but the relationship between housing price and land supply has been disputed. This study aims to examine what kind of impact housing prices have on land supply and whether there is heterogeneity in different regional spaces. Design/methodology/approach This study collects the relevant data of land supply and housing prices in Nanchang from 2010 to 2018, constructs a vector autoregression (VAR) model, including one external factor and four internal factors of land supply to explore the dynamic effects and spatial heterogeneity of land supply on housing prices through regression analysis. Also, the authors use the geographic detector to analyze the spatial heterogeneity of housing prices in Nanchang. Findings This study found that the interaction between land supply and housing price is extremely complex because of the significant differences in the study area; the variables of land supply have both positive and negative effects on housing price, and the actual effect varies with the region; and residential land and GDP are the two major factors leading to the spatial heterogeneity in housing price. Research limitations/implications The dynamic effects of land supply on housing price are mainly reflected in the center and edge of the city, the new development area, and the old town, which is consistent with the spatial pattern of the double core, three circles and five groups in Nanchang. Originality/value This is a novel work to analyze the dynamic effects of land supply on house prices, instead of a single amount of land supply or land prices. Furthermore, the authors also explore the spatial heterogeneity according to the regional characteristics, which is conducive to targeted policymaking.

Property investor decisions using income and rental ratio signals

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Billie Ann Brotman
Keyword(s):  
Real Estate ◽  
Housing Market ◽  
Discount Rate ◽  
Price Index ◽  
Housing Prices ◽  
Housing Price ◽  
Consumer Sentiment ◽  
Content Type ◽  
Income Ratio ◽  
Real Estate Prices

PurposeThis paper, a case study, aims to consider whether the income ratio and rental ratio tracks the formation of residential housing price spikes and their collapse. The ratios are measuring the risk associated with house price stability. They may signal whether a real estate investor should consider purchasing real property, continue holding it or consider selling it. The Federal Reserve Bank of Dallas (Dallas Fed) calculates and publishes income ratios for Organization for Economic Cooperation and Development countries to measure “irrational exuberance,” which is a measure of housing price risk for a given country's housing market. The USA is a member of the organization. The income ratio idea is being repurposed to act as a buy/sell signal for real estate investors.Design/methodology/approachThe income ratio calculated by the Dallas Fed and this case study's ratio were date-stamped and graphed to determine whether the 2006–2008 housing “bubble and burst” could be visually detected. An ordinary least squares regression with the data transformed into logs and a regression with structural data breaks for the years 1990 through 2019 were modeled using the independent variables income ratio, rent ratio and the University of Michigan Consumer Sentiment Index. The descriptive statistics show a gradual increase in the ratios prior to exposure to an unexpected, exogenous financial shock, which took several months to grow and collapse. The regression analysis with breaks indicates that the income ratio can predict changes in housing prices using a lead of 2 months.FindingsThe gradual increases in the ratios with predetermine limits set by the real estate investor may trigger a sell decision when a specified rate is reached for the ratios even when housing prices are still rising. The independent variables were significant, but the rent ratio had the correct sign only with the regression with time breaks model was used. The housing spike using the Dallas Fed's income ratio and this study's income ratio indicated that the housing boom and collapse occurred rapidly. The boom does not appear to be a continuous housing price increase followed by a sudden price drop when ratio analysis is used. The income ratio is significant through time, but the rental ratio and Consumer Sentiment Index are insignificant for multiple-time breaks.Research limitations/implicationsInvestors should consider the relative prices of residential housing in a neighborhood when purchasing a property coupled with income and rental ratio trends that are taking place in the local market. High relative income ratios may signal that when an unexpected adverse event occurs the housing market may enter a state of crisis. The relative housing prices to income ratio indicates there is rising housing price stability risk. Aggregate data for the country are used, whereas real estate prices are also significantly impacted by local conditions.Practical implicationsRatio trends might enable real estate investors and homeowners to determine when to sell real estate investments prior to a price collapse and preserve wealth, which would otherwise result in the loss of equity. Higher exuberance ratios should result in an increase in the discount rate, which results in lower valuations as measured by the formula net operating income dividend by the discount rate. It can also signal when to start reinvesting in real estate, because real estate prices are rising, and the ratios are relative low compared to income.Social implicationsThe graphical descriptive depictions seem to suggest that government intervention into the housing market while a spike is forming may not be possible due to the speed with which a spike forms and collapses. Expected income declines would cause the income ratios to change and signal that housing prices will start declining. Both the income and rental ratios in the US housing market have continued to increase since 2008.Originality/valueA consumer sentiment variable was added to the analysis. Prior researchers have suggested adding a consumer sentiment explanatory variable to the model. The results generated for this variable were counterintuitive. The Federal Housing Finance Agency (FHFA) price index results signaled a change during a different year than when the S&P/Case–Shiller Home Price Index is used. Many prior studies used the FHFA price index. They emphasized regulatory issues associated with changing exuberance ratio levels. This case study applies these ideas to measure relative increases in risk, which should impact the discount rate used to estimate the intrinsic value of a residential property.

Housing supply and its relationships with land supply

2015 ◽  
Vol 8 (3) ◽  
pp. 375-395 ◽  
Author(s):  
Guowei Gu ◽  
Lynne Michael ◽  
Yapeng Cheng
Keyword(s):  
Least Squares Method ◽  
Linear Regression Analysis ◽  
Time Lag ◽  
Housing Price ◽  
Construction Cost ◽  
Ordinary Least Squares ◽  
Price Impact ◽  
Housing Supply ◽  
Land Supply ◽  
Content Type

Purpose – This paper aims to explore the determinants of housing supply and the relationships between land supply and housing supply in terms of quantity and time in Shanghai, China. Design/methodology/approach – Official statistical and property registration data[] from Shanghai are used to carry out multiple linear regression analysis. Findings – The authors find that land supply affects housing supply with a three-year time lag. Both construction cost and housing price impact supply with a one-year time delay. The construction cost elasticities range from 0.74 to 1.51, while housing price elasticity is 2. The authors also find that plot ratio may play more important role in the developer’s first housing sale than either plot area or sales price. An average time period from obtaining the land for residential development until marketing the product is established at 36.8 months. Research limitations/implications – Only ordinary least squares method is applied in this analysis and the property portal on which this research relies is still at an early stage. Originality/value – This research contributes to a wider understanding of issues surrounding housing supply in the local markets within China and provides the foundation for local government to better manage supply.

Housing price and enterprise financing: does mortgage effect exist?

2019 ◽  
Vol 9 (1) ◽  
pp. 137-152 ◽  
Author(s):  
Shujing Li ◽  
Nan Gao
Keyword(s):  
Financial Development ◽  
Design Methodology ◽  
Empirical Test ◽  
Housing Prices ◽  
Housing Price ◽  
Fixed Effect Model ◽  
Content Type ◽  
Empirical Results ◽  
Effect Model ◽  
High Level

Purpose The purpose of this paper is to explore the influence of the rise in housing prices on enterprise financing and also the sustainability and heterogeneity of this effect. Design/methodology/approach Empirical test, panel data, fixed-effect model, IV and 2SLS were used in this paper. Findings The empirical results indicate that the mortgage effect does exist, and the authors further analyze the heterogeneity of this effect by dividing the sample based on the degree of financial development and property rights; the empirical results reveal that the mortgage effect is significantly higher in places with the high level of financial development. Besides, compared to the SOE enterprise, the mortgage effect has more influence on non-SOE companies. Research limitations/implications The results indicate that the mortgage effect should be considered when regulating housing market, and in order to improve the financing capability of company, its profitability and financial market efficiency should be emphasized. Originality/value This paper not only confirms the existence of the mortgage effect, but also explores its sustainability and heterogeneity, which reveals the risk and bubble in the effect of house market on enterprise financing, and enlightens how to promote financing ability of company.

Modelling housing prices and market fundamentals: evidence from the Sydney housing market

2019 ◽  
Vol 12 (4) ◽  
pp. 746-762 ◽  
Author(s):  
Md Abdullah Al-Masum ◽  
Chyi Lin Lee
Keyword(s):  
Investment Decision ◽  
Housing Prices ◽  
National Level ◽  
Housing Price ◽  
Capital City ◽  
Content Type ◽  
Price Series ◽  
Long Run ◽  
Investment Decision Making ◽  
Market Fundamentals

PurposeHousing prices in Sydney have increased rapidly in the past three decades. This leads to a debate of whether Sydney housing prices have departed from macroeconomic fundamentals. However, little research has been devoted to this area. Therefore, this study aims to fill this gap by examining the long-run association between housing prices and market fundamentals. Further, it also examines the long-run determinants of housing prices in Greater Sydney.Design/methodology/approachThe analysis of this study involves two stages. The first stage is to estimate the presence of long-run relationship between housing prices and market fundamentals with the Johansen and Juselius Cointegration test. Thereafter, the determinants of housing prices in Greater Sydney is assessed by using a vector error correction model.FindingsThe empirical results show that Sydney housing prices are cointegrated with market fundamentals in the long run. In addition, there is evidence to suggest that market fundamentals such as gross disposable income, housing supply, unemployment rate and gross domestic product are the key long-run determinants of Sydney housing prices, reflecting that Sydney housing prices, in general, can be explained by market fundamentals in the long run.Research limitations/implicationsThe findings enable more informed and practical policy and investment decision-making regarding the relation between housing prices and market fundamentals.Originality/valueThis paper is the first study to offer empirical evidence of the degree to which the behaviour of housing prices can be explained by market fundamentals, from a capital city instead of at a national level, using a relatively disaggregated dataset of housing price series for Greater Sydney.

Green federal tax credits impact on US housing prices

2020 ◽  
Vol 13 (4) ◽  
pp. 553-564
Author(s):  
Billie Ann Brotman
Keyword(s):  
Regression Model ◽  
Energy Policy ◽  
Income Tax ◽  
Housing Prices ◽  
Housing Price ◽  
Tax Credits ◽  
Disposable Income ◽  
Content Type ◽  
Dummy Variable ◽  
Energy Policy Act

Purpose The purpose of this study is to investigate whether increases in homeowner green amenities occurred because of income tax credits to the degree that changes in housing prices are measurable. Are higher incomes, lower mortgage rates and green income-tax credits impacting housing price changes? Design/methodology/approach The paper uses the least-squares regression model with natural log specifications. The log of income and a dummy variable, which was assigned to the Energy Policy Act (2005) and the American Recovery and Reinvestment Act (2009) coverage dates are used as independent variables. Two regression models were examined using monthly housing price data from January 1990 through the year 2018. The first regression model used a single dummy variable for credits available under the Policy Act of 2005 and the Recovery Act of 2009. The second regression model considered the credits granted under these two laws separately. Disposable income per capita impacts demands for housing while green upgrade expenditures affect the cost of housing. Findings The laws set low credit limits of $500 followed by $1,500 but because of the multiplier effect, the spending appears to have magnified and been much higher. The credit availability variables have positive coefficients and were significant at 1 per cent. This implies that single-family housing prices were sensitive to the existence of residential energy property income-tax credits. The R2 results were 0.93 or above for both models. Research limitations/implications The data used was aggregated and publicly available online. Many studies use aggregated macroeconomic data when modeling housing prices using the exogenous variable of disposable income but there is no substitute for examining individual homes by location and their sales price to see under what conditions green income-tax credits have the most impact. There could be demographic issues that are missed when using aggregated information. Practical implications Spending on heating/cooling systems, dual pane windows and other green amenities keeps the housing stock modernized and housing prices steady or rising. An additional benefit is that spending motivated by self-interest can simulate household consumption spending. Houses deteriorate due to wear and tear. Physical-repairable depreciation represents a situation where maintenance funds are continuously needing to be spent. Repairs and upgrades to the structure of the property keep its price stable by stopping the physical depreciation that would otherwise occur with the passage of time. Social implications The paper provides support for the idea that residential green amenity upgrades positively impact the value of a house. These green-amenity upgrades, which other research studies have suggested should be included explicitly in the appraisal process, are a major characteristic of a property when a price estimate is being done. Housing being sold should have a section on the information sheet noting the property green upgrades that exist and an energy efficiency score should be assigned to each house listed for sale. Originality/value There are few (if any) academic research papers studying the impact of green tax credits available under the Energy Policy Act (2005) and under the American Recovery and Reinvestment Act (2009). The degree to which green income-tax credits stimulate spending on housing has not been addressed by researchers. This paper is an initial research attempt to quantify whether these legislative efforts measurably encouraged homeowners to adopt newer, greener technologies.

Residential properties, resources of basic education and willingness price of buyers

2014 ◽  
Vol 4 (3) ◽  
pp. 227-242 ◽  
Author(s):  
Hao Zhang ◽  
Zhong-fei Li
Keyword(s):  
Basic Education ◽  
Housing Prices ◽  
Housing Price ◽  
Educational Resources ◽  
Allocation Mechanism ◽  
Content Type ◽  
Education Resources ◽  
Standards Of Living ◽  
Residential Properties ◽  
The Individual

Purpose – China's resource allocation mechanism in education has become an important factor in determining residential access to educational resources. The purpose of this paper is to analyze the impacts made by the individual natures of buyers, the external environment, as well as the characteristics of residential properties on the willingness price of buyers. The study's aim is to lay theoretical foundations for the determination of problems related with the matters under consideration. Design/methodology/approach – Using the panel data of 54 districts and counties in Beijing, Shanghai, Guangzhou and Shenzhen, the study unifies macro factors and micro factors in a model for empirical analysis. Findings – Basic education resources can affect housing prices via the “capitalization of education.” The degree of those educational resources’ influence on willingness price changes according to personal income levels, standards of living, housing price fluctuations, the convenience of the residential area and the degrees of urbanization in a district. The greater the buyer's income and standard of living is, the higher is their willingness price. Buyers in urbanized areas prefer increases in educational resources. Increased educational resources increase the values of residential downtown areas. In developed areas with private educational facilities, the role of educational resources in influencing property prices is relatively small. Originality/value – This paper uses data concerning the consumption and investment of residential properties to build a theoretical model for the willingness price of buyers. It unifies macro factors and micro factors in a single model and presents new results about basic education resources and the willingness price of buyers under different conditions.

scholarly journals The effects of tourism on housing prices: applying a difference-in-differences methodology to the Portuguese market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
António Manuel Cunha ◽  
Júlio Lobão
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Housing Price ◽  
Generalized Least Squares ◽  
Equation Model ◽  
Seemingly Unrelated Regression ◽  
Housing Supply ◽  
Difference In Differences ◽  
Content Type ◽  
Price Increases

Purpose This paper aims to explore the effects of a surge in tourism short-term rentals (STR) on housing prices in municipalities within Portugal’s two largest Metropolitan Statistical Areas. Design/methodology/approach This study applies the difference-in-differences (DiD) methodology by using a feasible generalized least squares (FGLS) estimator in a seemingly unrelated regression (SUR) equation model. Findings The results show that the liberalization of STR had a significant impact on housing prices in municipalities where a higher percentage of housing was transferred to tourism. This transfer led to a leftward shift in the housing supply and a consequent increase in housing prices. These price increases are much higher than those found in previous studies on the same subject. The authors also found that municipalities with more STR had low housing elasticities, which indicates that adjustments to the transfer of real estate from housing to tourism were made by increasing house prices, and not by increasing supply quantities. Practical implications The study suggests that an unforeseen consequence of allowing property owners to transfer the use of real estate from housing to other services (namely, tourism) was extreme housing price increases due to inelastic housing supply. Originality/value This is the first time that the DiD methodology has been applied in real estate markets using FGLS in a SUR equation model and the authors show that it produces more precise estimates than the baseline OLS FE. The authors also find evidence of a supply shock provoked by STR.

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