Housing Boom Research Articles

China's GDP at risk: The role of housing prices

This paper studies the impact of house prices on the distribution of GDP growth in China (the 5th, median, and 95th percentiles). We show that house price appre-ciation positively affects future GDP growth, with a more significant impact on the tail outcomes - GDP at risk. Moreover, we find that housing bust is associated with GDP growth vulnerability; a sharp decline in house prices generates severe economic downturns. Our finding is supported by the investment channel, a housing boom stim-ulates investment, which boosts GDP growth. However, the subsequent housing bust suppresses investment, leading to increased downside risks to GDP growth.

The effect of soaring housing prices on the quality of export products: Evidence from China

AbstractThis paper examines the impact of rising housing prices on the quality of export products. When housing prices increase, the collateral value of firms can rise, easing financial constraints and potentially boosting investment in innovation and product quality. However, higher housing prices can also lead firms to divert investments from their core business operations to the housing sector, where returns are relatively higher. This diversion can negatively affect product quality. We empirically investigate this relationship using Chinese firm‐level data, matched with customs and city‐level data from 2000 to 2013. Our results show that during China's housing boom, rising housing prices significantly reduced the quality of export products. The negative impact of speculative investment in the housing sector outweighed the positive effects of eased credit constraints. Firms with real estate investments and industries with low external financial dependence were more affected by rising housing prices. Additionally, government restrictions on home purchases helped mitigate the negative impact of rising housing prices on export product quality.

House Prices and Misallocation: The Impact of the Collateral Channel on Productivity

Abstract This paper investigates the impact of local house price booms on capital misallocation within industries. Using the geographical variation provided by the Spanish housing boom (2003–7), we show that firms exposed to positive local house price shocks received more bank credit and their investment grew more when they had a higher proportion of real estate assets. This collateral channel results in an increasing dispersion of the capital-labour ratio within industries. A counterfactual calculation suggests that the capital misallocation generated by this channel can account for around 40% of the total factor productivity decline experienced by the Spanish economy during the housing boom.

How the War between Russia and Ukraine Caused a Multi-Cycle in the Polish Housing Market

We examine the effects of the war between Russia and Ukraine on the housing market in the six largest cities in Poland and explain how these effects emerged. Since Poland’s transition to a market economy and its accession to the EU, Poland has experienced normal cycles in house prices, i.e. relatively long periods of increases in house prices followed by similarly long periods of decreases in house prices. However, the combination of the COVID-19 pandemic and the war between Russia and Ukraine created a situation that can be described as a multi-cycle. The pandemic initially halted nearly all transactions on the market, but after a few quarters of fiscal and monetary intervention aimed at saving the economy we observed a housing boom. Just a few quarters later, the Russian aggression in Ukraine caused significant inflation, which required a sharp increase in interest rates, and once again demand slowed down. This was followed just a few quarters later by a resurgence in house purchases in order to escape inflation, with many people using cash for these purchases. This situation has shaken the housing market, while the war has also generated a demographic shock. Construction and transportation workers began returning to Ukraine to help in its reconstruction, while women with children came to Poland from Ukraine seeking safety and creating a demand for rental housing.

Studentification, youthification, and gentrification, all at once? New-builds, newcomers, and near-campus change in a post-industrial city

Higher education growth changes the neighbourhoods of university cities in multiple ways. The most evidenced way is studentification, although researchers also report youthification and gentrification. However, empirical studies on near-campus change through the tri-conceptual prism of studentification, youthification, and gentrification are recent and limited to North America. Therefore, we apply it to another context. In this paper, we look at Lodz, Poland, and its campus-adjacent, post-industrial area that is facing a housing boom. We describe the new-builds (their scale, types, and morphologies) and the newcomers (their demographics, residential choices, satisfaction and plans). As a result, we claim the change here is a gentrification-like hybrid of new-build youthification and studentification. Consequently, we suggest that boundaries between studentification, youthification, and gentrification can be fuzzy in particular locales. We also nuance previous findings about the near-campus change, especially the features of studentification and studentifiers, and the role of the campus itself in this process.

Household debt and economic growth in Europe

Abstract We investigate the role and impact of household debt on the economic performance of European economies during the double-dip recession of 2008–2013. We use a loan-level data set of millions of residential mortgages originated between 2000 and 2013 to calculate regional indicators of household debt. The granular information allows us to construct a measure of interest rate mispricing during the housing boom that we use to identify the effect of a credit shock (CS) on household debt. Our analysis provides three main conclusions. First, in the period 2004–2006, the measure of CS was negative in most European regions which indicates that credit conditions were significantly relaxed relative to earlier years. Second, we find that regions in which household leverage increased more rapidly during the 2002–2007 period experienced a more severe decline in output and employment after 2008. Third, we find that the CS had the largest effect on increasing leverage for the low-income and the middle-income households, although the leverage of the high-income households represents a more powerful predictor of the decline in economic activity.

Housing cycle and firm investment: International firm-level evidence

The macro-finance literature provides conflicting views on how movements in housing price affect firms’ capital spending or R&D. We further explore this issue by analyzing a comprehensive international firm-level data set. We use the housing price component independent of firms’ investment opportunities and credit supply shocks. The results support the collateral channel as housing price and firm investment exhibit a positive relationship. This collateral channel is more distinct for capital expenditure than R&D, and in housing downturns when firms’ credit constraints bind. Nevertheless, housing appreciations are negatively associated with R&D and large housing booms are also detrimental to capital investment, which suggests a possible resource reallocation from the production sector to the housing sector during those phases. Small firms and firms with stronger investment opportunities respond more sensitively to housing price. Countries that rely more on bank financing and collateralized lending display a larger collateral effect in capital expenditure.

Borrower-based measures, house prices and household debt

This paper quantifies the credit-driven housing demand and the role of macro-prudential Loan-to-Income (LTI) and Loan-to-Value (LTV) limits. Using granular and time-varying changes in borrowing capacity, I estimate how shocks in credit availability feed into credit demand and affect household debt. The findings indicate a robust relationship between debt and borrowing capacity that amplifies throughout a housing boom. The relationship is heterogeneous, as changes in borrowing capacity have larger effects among low-income and first-time buyers and in expensive property markets. If no downpayment is required, tightening the LTV limit may not contain borrowing capacity but still curbs leverage among highly-indebted borrowers.

All That Glitters is Not Gold: Examining the Negative Impact of Real Estate Value on Companies' Market Competitiveness

AbstractThis paper introduces and investigates the hypothesis that the crowding-out effect surpasses the collateral effect, suggesting that an increase in the value of real estate holdings by companies hinders their competitiveness in the product market within emerging economies. Through our analysis, we elucidate the underlying mechanism, demonstrating that although Chinese listed companies benefit from their real estate holdings in terms of debt financing, these financial resources are predominantly reinvested in real estate projects rather than other productive endeavors. This effect is particularly pronounced when companies face significant financial constraints, operate in highly monopolistic industries, and are situated in regions where local governments heavily rely on land finance and face substantial pressure for GDP growth. By shedding light on the adverse implications of companies' real estate holdings and uncovering the factors contributing to the crowding-out effect, our research underscores the importance of enhanced regulations in the real estate markets of developing nations during the periods of irrational housing booms.

THE EFFECTS OF TRANSACTION HOTSPOTS AND FLIPPING HOTSPOTS ON HOUSING PRICES

In contrast to much of the literature that focuses on the issue of spatial dependence in housing price research, this study addresses the spatial aggregation of housing transactions and analyzes the effects of transaction hotspots and short-term flipping hotspots on housing prices by using real housing transaction data in Taipei City, Taiwan. The empirical results show that after controlling for the effects of spatial dependence and individual housing attributes, the impact of transaction hotspot areas on housing prices is significantly negative, while the impact of flipping hotspot areas on housing prices is significantly positive. The results verify that the key to driving up housing prices lies in flipping activities. Furthermore, the results of the spatial quantile regression model show that low-priced residential properties are more sensitive to the spatial concentration of housing transactions and flipping transactions in the housing market. Our results have implications for the government’s policy intending to control hot trade volumes to cool skyrocketing housing prices in a booming housing market. It is suggested that the government should pay attention to restraining short-term flipping activities in the housing market rather than setting constrains on housing transactions.

Bubbly booms and welfare

We show the competing effects of a housing bubble on the real economy by developing a multi-sector dynamic model with housing production. On the one hand, firms can sell or collateralize their housing, so a housing bubble helps firms obtain credit to finance their investment and expand production. On the other hand, a boom in the housing sector crowds out labor in the non-housing sector. We show that housing booms can reduce social welfare both in the steady state and in the transitional dynamics only when the production externalities in the non-housing sector are sufficiently large. We quantitatively evaluate our model and demonstrate its robustness with model extensions. Policies that target labor, housing transactions and output generate different welfare implications.

Reexamining the 'Role of the Community Reinvestment Act in Mortgage Supply and the U.S. Housing Boom'

Concerns have lingered since the 2007 subprime crisis that government housing policies promote risky mortgage lending. The first peer-reviewed evidence of a causal effect was published by the Review of Financial Studies in a paper (Saadi, 2020) linking the crisis to changes in the Community Reinvestment Act (CRA) in 1995. A review of that paper, however, shows that it misrepresents the policy changes as having taken effect in mid-1998, 2.5 years after they were implemented. When the correct timing is used, a similar analysis yields no evidence of a relationship between CRA and riskier mortgage lending. Instead, the results are shown to reflect an unrelated confounding event, the first collapse of the U.S. subprime mortgage market following Russia’s debt default in August 1998.

Monetary policy and housing market cycles

Abstract Using monthly data from 1978:M1 to 2019:M9, this paper provides empirical evidence concerning the role that monetary policy plays in the US housing market. We first show that shocks to short-run interest rates have significant impacts on house prices and that these effects are persistent. Our findings also provide evidence supporting the claim that too-low-for-too-long interest rates are responsible for the 2002–2006 US housing boom. We further investigate the different channels through which an easing monetary policy fuels the house price boom and find that faster sales and lower inventory levels in the housing market most amplify the policy effects. Lastly, we provide compelling evidence of the asymmetric effects of contractionary and expansionary monetary policies on house prices.

Are younger buyers driving the housing boom? A geographic perspective on US home purchases, 2018-2021

ABSTRACT Rapid growth in US housing prices has coincided with the large Millennial demographic group reaching peak homebuying age, leading some to speculate that new demand from younger buyers is putting upward pressure on home prices. This Research Note uses data from the Home Mortgage Disclosure Act mortgage data to examine where younger buyers are purchasing homes. Data show that the share of buyers under age 35 fell in more than half of US counties, including 45% of metropolitan counties. A county- and MSA-level regression analysis finds a null or slightly negative correlation between changes in the share of buyers under age 35 and changes in home prices, and a small positive effect on debt-to-income ratios from 2018 to 2021, providing little to no evidence that young buyers are pushing up home prices.

Did marginal propensities to consume change with the housing boom and bust?

SummaryWe extend a widely used semi‐structural model to identify and estimate dynamic consumption elasticities with respect to transitory income shocks. Applying our model to household survey data, we find a structural break in marginal propensities to consume following the end of the housing market boom, with the average across households increasing significantly. There is important heterogeneity by different household balance sheet characteristics, and the increase in the average appears to be driven by higher short‐run consumption elasticities for homeowners with low liquid wealth. The change in consumption behavior is consistent with tighter borrowing constraints more than a shift in wealth distributions.

Understanding Spatial House Price Dynamics in a Housing Boom

Understanding Spatial House Price Dynamics in a Housing Boom

Is religion an inferior good? Evidence from fluctuations in housing wealth

An increase in local house prices in the US is associated with a decrease in the time homeowners spend on religious activities compared to renters. Notably, this effect is not observed in volunteering and civic activities. The decline in religious activities is more pronounced for credit-constrained households. The main result is attributed to a wealth effect, whereby activities that have an inferior-good component decline with housing wealth, and to a substitution effect whereby the attractiveness of activities linked to the residential asset increases during housing booms.

Can housing booms elevate financing costs of financial institutions?

We show that house price appreciation elevates financial institutions' financing costs because it can make households invest more in houses and invest less in or require higher returns on other assets. For identification, we employ the unique feature of wealth management products (WMPs, the largest component of China's shadow-banking sector) that the issuing markets are local whereas the markets of some products' underlying assets are national. Stocks, bonds, and deposits do not possess this feature. We find that house price growth raises WMPs' expected returns offered by banks. Household-level analyses further confirm that house price growth reduces households' WMP-investment demands.

Anatomy of the Beginning of the Housing Boom across U.S. Metropolitan Areas

Abstract We provide novel estimates of the location, timing, magnitude, and determinants of the start of the previous U.S. housing boom. The housing cycle cannot be interpreted as a single, national event, as different markets began to boom across a decade-long period, some of them multiple times. A fundamental factor, income of prospective buyers, can account for half of the initial jump in price growth, while expansion of purchases by underrepresented minorities cannot. The start of the boom also was financed conventionally, not by subprime mortgages. The latter's share did rise sharply over time, but only after a multiyear lag.

The housing boom and selection into entrepreneurship

Existing evidence shows that increases in property prices produce immediate positive effects on economic activity and, particularly, on business creation. In this paper, we ask the following question: how does a housing boom alter the selection of individuals that open a firm? The answer to this question is important to understand how robust and long-lasting is the positive effect of a housing shock. We find that the early 2000 US housing boom increased entry into entrepreneurship mostly for lower ability house-owners. We derive our results using IQ scores and an indirect measure of ability constructed from individuals’ wage history.