Increase In House Prices Research Articles

The Incidence of Land Use Regulations

I study the welfare consequences of land use regulations for low- and high-skilled workers within a city. I use detailed geographic data for Cook County and Chicago in 2015-2016, together with a spatial quantitative model with two types of workers and real estate developers who face regulations. For identification, I use the 1923 Zoning Ordinance, which was the first comprehensive ordinance in Chicago. I find that an increase of 10 percentage points in the share of residential zoning in a block group, relative to block groups with more commercial zoning, leads to a 1.7% increase in housing prices, a 2.6% decrease in wages and a higher concentration of high-skilled residents. Welfare changes can be decomposed into changes in housing prices, sorting, wages and land rents. Results suggest that more mixed-use zoning and looser floor-to- area limits lead to welfare improvements, especially for low-skilled residents, and to a reduction in welfare inequality.

Real Estate and Rental Markets During COVID Times

In this work we introduce a general equilibrium model with landlords, indebted owner-occupiers and renters to study housing markets' dynamics. We estimate it by using standard Bayesian methods and match the US data of the last decades. This framework is particularly suited to explain current trends on housing markets. We highlight the crucial relationship between interest rates, house prices and rents, and argue that it helps understanding the main driving forces. Our analysis suggests that current developments on housing markets can play a role for a recovery from the Covid pandemic as they have an expansionary effect on aggregate output. Moreover, we account for the heterogeneous impact of crisis-induced policies depending on agents' status on the housing market. We show how, despite an increase in housing prices, the welfare of landlords has been negatively hit. This is associated to the joint decrease in returns on housing and financial assets that reduces their financial incomes.

Rich Buyers and Rental Spillovers: Evidence from Chinese Buyers in US Housing Markets

The influx of rich real-estate buyers into local housing markets would increase house prices, but the spillover effect onto rental prices is theoretically ambiguous. I estimate rich buyers’ impact during the Chinese buying boom in US residential housing markets, with $200 billion of purchases made between 2010 and 2019. I identify Chinese holdings using housing deed records and names, and estimate their causal impact by instrumenting for Chinese buyers’ demand using flight time from China due to flight route changes. I find a large positive house price impact. Consistent with investment q-theory, rents fall as constructions rise, especially in areas with elastic housing supply.

Varieties of Social Democracy and Cooperativism: Explaining the Historical Divergence between Housing Regimes in Nordic and German-Speaking Countries

AbstractThe historical-comparative study of social democracy and cooperative organization are the foster children of historical sociology. This article offers a first account of systematic ideological differences in social-democratic ideology regarding private ownership and different cooperative traditions in the housing sphere of Northern European and continental German-speaking countries. The long-run trajectory of housing welfare regimes in these two country groups has been one of divergence: Nordic countries have moved to Anglo-Saxon levels of high homeownership, high levels of mortgage indebtedness, and house price increases, whereas private tenancy, lower indebtedness, and lower price increases still characterize their German counterparts. Based on historical case studies of Germany and Norway, we argue that the divergence in these two countries can be understood by the different social-democratic and cooperative solutions to the urban housing question from the 1920s onward. Supported by a pro-ownership social democracy, Norway started to develop housing cooperatives of the owner cooperative type, whereas German social democracy was in favor of associations of the tenant cooperative type. The differential growth of these two types of cooperatives and disparities in social democratic party ideology contributed to the urban housing divergence between the two country groups that has been observed ever since. We argue, more generally, that varieties of social democracy and welfare-anticipating cooperative organizations are important in helping us understand the welfare differences between countries.

Land Price Dynamics and Macroeconomic Fluctuations with Imperfect Substitution in Real Estate Markets

The collateral channel, whereby an increase in residential house prices leads to an increase in commercial property prices, loosening firm borrowing constraints and increasing firm investment, is weaker when residential and commercial real estate are imperfect substitutes. We enrich the DSGE model of the collateral channel in Liu, Wang, and Zha (2013) by adding a land development sector to allow residential and commercial land to be imperfect substitutes. Bayesian estimation of our structural model based on aggregate U.S. data indicates imperfect substitution between the two types of land. With variance decompositions and impulse responses, we show that the strength of the collateral channel linking residential house prices and firm investment is weaker when the two types of land are imperfect substitutes. When residential and commercial land are assumed to be perfect substitutes, shocks to residential real estate demand explain 20-30% of the variance of total output and 30-40% of the total investment, but with the imperfect degree of substitution that we estimate, the same shocks explain less than 10% of the variance of output and 12-15% of investment.

Land Price Dynamics and Macroeconomic Fluctuations with Imperfect Substitution in Real Estate Markets

The collateral channel, whereby an increase in residential house prices leads to an increase in commercial property prices, loosening firm borrowing constraints and leading to higher firm investment, is weaker when residential and commercial real estate are imperfect substitutes. We first show in a reduced form regression with firm level data that the strength of local zoning regulations has a negative effect on the estimated increase in firm investment following an increase in local residential real estate prices. We then modify the DSGE model of the collateral channel in Liu, Wang, and Zha (2013) to allow imperfect substitutability between residential and commercial land. With Bayesian estimation and U.S. data, we estimate that the elasticity of substitution between the two types of land is 0.88. Variance decompositions and impulse responses show that the strength of the collateral channel linking house prices and investment is weaker when the two types of land are imperfect substitutes

Does Airbnb Reduce Matching Frictions in the Housing Market?

There is growing concern about the impact of the home-sharing markets on housing affordability, yet the underlying mechanisms are not well-studied. We use a theoretical model to provide key results on the mechanisms through which home-sharing can improve the quality of matches between buyers and sellers in the housing market. We then test these predictions empirically using daily Airbnb data for the entire U.S. and a novel shift-share approach. We find that an increase in Airbnb increases house prices, reduces total sales, increases for-sales inventory, increases sellers' time on the market, and reduces the probability of selling a house. The empirical evidence supports the hypothesis that Airbnb has reduced matching frictions in the housing market. We then examine heterogeneous responses to Airbnb using Generalized Random Forest (GRF). Consistent with our theoretical model, results from the GRF model indicate that locations with a less elastic housing supply respond more to the Airbnb growth.

Is Sharing Really Caring? The Effect of Airbnb on the Affordability of Housing

We examine the impact of peer-to-peer (P2P) short-term rentals on housing affordability. Using a simple model we illustrate that, although growth in the short-term rental market leads to higher housing prices, home-sharing profits can offset increased housing costs. That is, we show the net effect of the rise of platforms like Airbnb on housing affordability is theoretically ambiguous. To address this ambiguity empirically, we leverage city-level registration requirements that substantially increase the cost of hosting on Airbnb to estimate the effect of policy enforcement on the Airbnb market and the corresponding effects on home prices and foreclosures. Using data on Airbnb listings and transactions from the San Francisco and Chicago metro areas, we find that enforcing registration requirements on Airbnb listings within the city limits of Chicago and San Francisco reduces Airbnb supply and bookings by 40% relative to untreated areas within the two metros. We also find substantial heterogeneity in these effects, with the largest shocks experienced by zip codes with the highest per-capita density of Airbnb listings. Using the same identification strategy with transaction-level data from Zillow on home sales and foreclosures, we find that home prices decline by roughly 10% in the most Airbnb-dense zip codes while foreclosures in these same zip codes increase by almost 20%. These findings suggest that, while growth in P2P short-term rental markets increases housing prices, it may also improve individuals' ability to avoid negative financial outcomes like foreclosure.

Can Web Search Queries Predict Prices Change on the Real Estate Market?

This study aims to explore whether the intensity of internet searches, according to the Google Trends search volume index (SVI), is a predictor of changes in real estate prices. The motivation of this study is the possibility to extend the understanding of the extra predictive power of Google search engine query volume of future housing price change (shift direction) by (i) the introduction of a research approach that combines the advantages of the complementary use of cross-correlation analysis and machine learning classification algorithms; (ii) applying the multi-class HPI values classifier which allows predicting the housing price increase, decrease or relative stability; (iii) exploiting the SVI that relates to interests in both ‘real estate’ and ‘credit to buy real estate’; (iv) evaluation of the introduced approach in the context of the Polish real estate market. The main theoretical contribution of our work is a confirmation that the freely available information regarding Google user searches can provide an in-depth insight into enriching the generally accepted statistics on supply and demand in the real estate market. From the practical perspective, this research confirms that SVI can be associated as a sole determinant to anticipate the housing price change with time-lag sufficient for making decisions regarding the purchase (sale) of individual property or the real estate market control. Such findings can be also helpful for researchers who intend to use Google Trends data as an extra variable from demand side to improve the prediction accuracy if it is included in the model which is based on the existing housing prices determinants.

INTERNAL AND EXTERNAL DETERMINANTS OF HOUSING PRICE BOOM IN HONG KONG

Hong Kong’s housing market witnessed a dramatic housing price appreciation in recent years, with the price index for private domestic housing units being three times higher than ten years ago. This trend is supported by both internal and external factors, as illustrated in this paper. By developing a theoretical model and an empirical analysis on the key variables influencing housing prices using monthly data from 1999 to 2018, we find that the main drivers of housing price appreciation are from the demand side and include income level, money supply and inflation. The main contribution of this study is the quantification of the role of Mainland China’s macroeconomic factors in housing price booms in Hong Kong. Our study shows that capital inflow from and inflation and recessions in Mainland China contribute to increasing housing prices in Hong Kong because the city’s real estate is seen as a way to preserve asset value. These findings call for the need for control of capital inflow between the two economies as well as for stricter regulations against empty houses in Hong Kong.

What Airbnb does to the housing market

• Our model predicts that house prices rise more than rents with Airbnb presence. • Airbnb presence in a borough increases house prices and, to a lesser extent, rents. • Results suggest that tourist renting may offset increased housing costs for owners.

THE IMPACT OF LUXURY HOUSING ON NEIGHBORHOOD HOUSING PRICES: AN APPLICATION OF THE SPATIAL DIFFERENCE-IN-DIFFERENCES METHOD

This study investigated the spatial spillover effects of luxury housing during and after construction, in regards to increases in housing prices in neighboring areas as well as the spatial dependence of neighboring housing. This study focused on already completed luxury housing in Taipei, Taiwan. First, the nearest-neighbor matching approach of propensity score matching was used to overcome the problem of data heterogeneity. The difference-in-differences (DD) method and spatial econometrics were used for analysis. The empirical results indicated that the spatial error model had the best goodness of fit. This indicated that housing prices increased by 13.0% during construction of luxury housing nearby. This indicated that housing prices increased by 5.8% after the construction of luxury housing nearby. The empirical results showed that the ongoing and completed construction of luxury housing had spillover effects on housing prices. The effect of ongoing construction of luxury housing was particularly large in scope, indicating its role as a predictor of psychological reaction in the market.

The Rationality of Chinas Real Estate Tax Levy: An Analysis from the Perspective of Monogamy

According to the data from China Statistical Yearbooks, we can calculate the average annual house price increase rate, and get such results: in the 21st century the average annual house price increase rate of China, Beijing City, Shanghai City, and Shenzhen City are 7.89%, 11.7%,11.23%, and 13.96% respectively. A small part of people is happy this situation, but most people are not. This situation has led to a substantial increase in housing prices, which has severely eroded the housing demand and well-being of the middle and low classes, then interest conflicts emerge. This paper analyzes the similarities between marriage needs and housing needs, they both belong to the physiological needs and existence needs, then marriage needs and housing needs are both needed to be adjusted by the moral system, rather than to allow power and wealth to be unscrupulous and unconstrained in these fields of housing demand and marriage demand.

Internal migration and housing costs—A panel analysis for Germany

AbstractThe emergent crisis of affordable urban housing coupled with a sustained decline in internal migration rates in many Western countries warrants a thorough exploration of the relation between housing costs and internal migration. Although it is well established that housing is an important contextual determinant of migration flows, little attention has thus far been paid to the ways in which rising housing costs shape internal migration. In this paper, we use a time‐series of annual intercounty migration in Germany for the period 2004–2017 to examine the association between increasing housing prices and changes in internal migration flows. For this, we apply fixed effects Poisson panel regression models to migration flow tables. Our results show that regions with rising housing costs experience declining inflows. In larger cities, rising housing costs are also associated with increasing outflows. Our study provides new insights into the relationship between house price dynamics and internal migration.

The impact of land use regulation across the conditional distribution of home prices: an application of quantile regression for group-level treatments

By increasing housing prices, land use regulations can have positive impacts among homeowners, but they can also have negative impacts on the availability of affordable housing. We examined heterogeneity in the price impacts of land use regulation across the conditional house price distribution; this heterogeneity may ameliorate or exacerbate the impacts of land use regulation on affordable housing. Our results suggest that the distribution of price impacts across the conditional house price distribution is relatively uniform. Results suggest that land use regulations both constrain housing supply and induce within housing market migration that spreads price impacts throughout the region.

Impact of house price growth on mental health: Evidence from China.

BackgroundHousing boom has raised global attention in the past two decades. A number of studies attempted to analyse the effect of house price increase. However, little is known about the health consequence as a result of housing boom, likely due to the scarcity of the data. The objective of this paper is to investigate the relationship between housing affordability and mental health as a result of house price increase.MethodsBased on a panel dataset of 32 Chinese cities from January 2013 to December 2017, we used a fixed effect model adjusting for per capita disposable income to estimate the impact of house price growth rate on mental health, and applied the Instrumental Variable (IV) method to address the endogeneity problem.ResultsFrom both Ordinary Least Squares (OLS) and IV estimations, the results suggested that a one standard deviation increase in house price increase rate in the past three months is associated with a 0.443 standard deviation increase in people consulting with doctors about their mental disorders in the city. This effect does not vary by gender, but was more pronounced in residents older than 40 years.ConclusionThese results revealed the potential negative consequences in people's mental health due to house price increase, necessitate appropriate policy responses.

Learning from House Prices: Amplification and Business Fluctuations

AbstractWe formalize the idea that house price changes may drive rational waves of optimism and pessimism in the economy. In our model, a house price increase caused by aggregate disturbances may be misinterpreted as a sign of higher local permanent income, leading households to demand more consumption and housing. Higher demand reinforces the initial price increase in an amplification loop that drives comovement in output, labour, residential investment, land prices, and house prices even in response to aggregate supply shocks. The qualitative implications of our otherwise frictionless model are consistent with observed business cycles and it can explain the economic impact of apparently autonomous changes in sentiment without resorting to non-fundamental shocks or nominal rigidity.

Tweeting the High Line Life: A Social Media Lens on Urban Green Spaces

The objective of this study is to investigate elevated parks as urban green spaces using social media data analytics. Two popular elevated parks, the High Line Park in New York and the 606 in Chicago, were selected as the study sites. Tweets mentioning the two parks were collected from 2015 to 2019. By using text mining, social media users’ sentiments and conveyed perceptions about the elevated parks were studied. In addition, users’ activities and their satisfaction were analyzed. For the 606, users mainly enjoyed the free events at the park and worried about possible increases in housing prices and taxes because of the 606. They tended to participate in physical activities such as biking and walking. Although the 606 provides scenic observation points, users did not seem to enjoy these. Regarding the High Line, users frequently mentioned New York City, which is an important aspect of the identity of the park. The High Line users also frequently mentioned arts and relaxation. Overall, this study supports the idea that social media analytics can be used to gain an understanding of the public’s use of urban green spaces and their attitudes and concerns.

Affordable Housing in the Wake of Global Pandemics: A Reality or a Mirage the Kenyan Perspective?

Aim: This was an investigative study on affordable housing in the wake of global pandemics: A reality or a mirage the Kenyan perspective? 22 % of Kenyans stay in towns and the inhabitants in these cities continue to grow at the rate of 4.2 % annually. This growth rate has outstripped the supply of housing units built. For instance, Nairobi needs a minimum of 120,000 new houses per annually to satisfy the demand but a paltry 35,000 units are constructed annually. The excess demand is likely to continue pushing the housing prices beyond the reach of many Kenyans. Studies conducted in Kenya on housing prices focused on non-macroeconomic determinants and more importantly none of the studies globally envisaged how global pandemics can influence housing prices. Therefore, the influence of global pandemics like Corona Virus Disease (COVID-19) and macroeconomic factors on housing prices in Kenya remains unknown.
 Study Design: Correlational research design.
 Methodology: The study employed unrestricted Vector Autoregressive analysis involving quarterly time series from quarter 1 of 2014 to quarter 1 of 2020 with a dummy variable measuring the influence of COVID-19.
 Results: Results indicated that the total money supply had a positive influence on inflation that was highly influenced by extended broad money.
 Conclusion: From the results, it was concluded that some macroeconomic factors, time trends and global pandemics like COVID-19 influence housing prices in Kenya. Professional, administrative and support services, time trend, transport and storage, information and communication, real estate and housing prices at lag 1 increased housing prices in Kenya by 0.41%, 0.41%, 0.94%, 0.37% and 0.59% respectively given unrestricted VAR coefficients and t-statistics of 0.41(4.184), 1.27 (9.862), 0.19 (2.740), 0.94 (10.178) and 0.59 (6.055) for the variables. Housing prices at lag 1 and 4, COVID-19, other services and tax on products reduced housing prices in Kenya by 0.26%, 0.99%, 3.29%, 1.01% and 0.05% respectively given unrestricted VAR coefficients and t-statistics of -0.26(-2.366), -0.99 (-8.770), -3.29 (-4.550), -1.01 (-6.568) and -0.05 (-2.807) for the variables respectively. Economic growth, financial and insurance activities and previous housing prices at lag 5 had no influence on housing prices in Kenya.

Estimation of change in house sales prices in the United States after heat pump adoption

Electrifying most fossil-fuel-burning applications provides a pathway to achieving cost-effective deep decarbonization of the economy. Heat pumps offer a feasible and energy-efficient way to electrify space heating. Here, we show a positive house price premium associated with air source heat pump installations across 23 states in the United States. Residences with an air source heat pump enjoy a 4.3–7.1% (or US$10,400–17,000) price premium on average. Residents who are environmentally conscious, middle class and live in regions with mild climate are more likely to pay a larger price premium. We find that estimated price premiums are larger than the calculated total social benefits of switching to heat pumps. Policymakers could provide information about the estimated price premium to influence the adoption of heat pumps. Estimating the costs of green home improvements is not possible without accurate estimates of their impact on house prices. Now, Shen et al. use the sales data of more than 400,000 properties in the United States to determine how heat pump installations increase house prices.