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This paper aims to analyze the median price for existing single-family housing units in Las Cruces, New Mexico. The proposed theoretical model accounts for the interplay between supply and demand sides of a metropolitan housing market.

This study analyzes the median price for existing single-family housing units in Las Cruces, New Mexico. The proposed theoretical model accounts for the interplay between supply and demand sides of a metropolitan housing market. Explanatory variables used in the analysis are real per capita income, the housing stock, real mortgage rates, real apartment rents and the median real price of single-family units in the USA. Annual frequency data are collected for a 1971–2017 sample period. Parameter estimation is completed using two-stage generalized least squares. Empirical results confirm several, but not all, of the hypotheses associated with the underlying analytical model. In particular, Las Cruces housing prices are found to be reliably correlated with local income and national housing prices.

Empirical results confirm several of the hypotheses associated with the underlying analytical model. In particular, Las Cruces housing prices are found to be reliably correlated with local income and national housing prices.

Results obtained support only a subset of the hypothetical relationships associated with the theoretical model. Additional testing for other small and/or medium sized is required to clarify whether these outcomes are unique to Las Cruces.

Local income fluctuations and national housing price fluctuations appear to be reliably related to housing price fluctuations for this metropolitan economy.

Comparatively little housing market research has been conducted for small and medium size urban economies. There is no guarantee that results obtained for large metropolitan housing markets are representative of smaller regional housing markets. The model developed has fairly moderate data requirements and may be applicable to other small and medium size economies such as Las Cruces.

Introduction: Financial development has a direct impact on the housing market by facilitating access to credit. The increase in housing loans resulting from the relaxation of the credit constraint causes an increase in housing demand and house prices. Purpose: This study aims to examine the relationship between financial development and house prices in Turkey, using the variables: the domestic credit to the private sector and total housing and consumer credits. Methodology: To determine any long-run relationship between financial development and house prices, the autoregressive distributed lag methods are used, covering the selected variables such as real GDP, inflation, mortgage interest rate, and stock price from 2010Q1 to 2020Q2. Findings: The study’s findings show that both variables representing financial development have a statistically significant and substantial positive effect on house prices. Besides, the selected macroeconomic variables have the theoretically expected impact on house prices.

The purpose of this paper is to provide an estimate of the demand and supply in the housing market in Colombia in a period of high real estate valuation (2005-2016). On the demand side, it evaluates the impact of new housing prices, unemployment, stock market returns, real wages in the retail sector, remittances and mortgage rates. On the supply side, it estimates the influence of the price of new housing, construction costs, time deposit (TD) and mortgage rates. Real estate valuation was analyzed considering foreigners migration and land prices evolution.

Ordinary least squares (OLS) was used to estimate housing area with the semilog regression model and also to construct price models. OLS was also used in price models. Since quantities depend on prices and vice versa, a two-stage least squares (2SLS) was implemented.

Rising prices in new homes have an “elastic” effect on both demand and even higher effect on supply. Likewise, the real wage index for the retail sector has an elastic effect. On the other hand, the response to interest rates is negative, but statistically significant only on the supply side. Furthermore, the inflow of remittances is “inelastic” and statistically insignificant.

Housing can sometimes be a Giffen good, this result challenges the traditional neoclassical model, but it can be explained by investment reasons and “bubble” behavior in the housing market. One last influence is the difference between “temporary” and “permanent” migrations. The latter has a statistically significant and perfectly inelastic effect on the price of new homes.

The purpose of this study is to investigate the relationship between tourism development and urban housing prices in Chinese cities. Specifically, the study aimed to explore whether there is a relationship between the two variables in tourist and non-tourist cities and whether there is a non-linear relationship between them.

In this study, the entropy method was used to construct the China City Tourism Development Index, which provides a more comprehensive measure of the level of tourism development in different cities. In total, 45 major cities in China were studied using the panel data approach for the period of 2011 to 2019.

The empirical analysis conducted for this study found that tourism development affects urban house prices, and that there is an inverted U-shaped relationship. However, this varies across cities, with house prices in tourist cities tending to be more influenced by tourism development than non-tourist cities. Also, foreign direct investment, population size, fixed asset investment and disposable income per capita were found to have an impact on house prices in both tourism and non-tourism cities.

There are significant differences in tourism development and urban house prices in different cities in China. This study considers these differences when examining the impact of tourism on house prices in 45 major cities in China by dividing the sample cities into tourist and non-tourist cities.

The monetary policy is an important driver of the real estate sector’s performance. The recent wave of monetary tightening in 2022 in response to the cost-of-living crisis has been associated with the decline in housing prices across the globe. There are two main channels through which the US monetary policy may affect the real estate market in the dollar-pegged countries: the cost of serving mortgages (financing cost) and the exchange rate channel (for example, the appreciation of the US dollar and consequently the local currency). The exchange rate channel, which involves the appreciation of the US dollar and the subsequent effect on the local currency, is particularly significant in the case of Dubai, given how international the housing market in Dubai and might be viewed as a tradable good. Using recent data, the purpose of this study to evaluate the spillover impact of the US monetary policy on the housing market performance in the dollar-pegged countries using Dubai as a case study.

For this purpose, this study collected unique longitudinal data on the volume of the monthly transactions of residential properties and performs a panel-data analysis using within-variation models. The changes in the interest rate policy in the USA are determined by the domestic inflation in the USA, thereby, representing an exogenous shock in the UAE.

The results are robust to different specifications and suggest that a strong negative correlation between the interest rate in the USA and the housing sector demand in Dubai. Fiscal policy measures can be taken to mitigate tighter financial conditions in case of policy misalignment.

Few studies have looked at the spillover impact of the global monetary conditions on the real estate market in the GCC region. This study fills this gap by exploring the impact of the US financial conditions on Dubai’s real estate, using panel data analysis.

The purpose of this study is to examine the interaction between banks’ lending to public and private sectors and house prices using data from the Iranian banking system including, commercial government-owned banks (CGBs), specialized government-owned banks and private banks.

The authors use quarterly data from the second quarter of 2004 to the first quarter of 2016 and apply structural vector autoregression models.

The results show that: a positive shock to the loan supply to the private sector triggers a positive response from house prices; a positive shock to the loan supply to the public sector does not trigger a positive response from house prices; house price appreciations contribute significantly to banks’ lending to the public sector but not lending to the private sector; each loan supply by three different types of banks influences house prices positively; and CGBs’ lending to the private sector does not respond to house price shocks.

Although the relationship between banks’ lending and house prices is well-established in the literature, existing studies have not yet examined whether bank ownership matters for the link between banks’ lending and house prices.

This research aims to analyse the housing demand in northern France with respect to socio-demographic variables and the distance between the residence and the workplace.

Econometrics with discrete choice models are used to study the three main dimensional choices of housing demand: tenure, type and location. A contribution is to use a heteroscedastic logit model where the variance of the error term is allowed to differ over alternatives and to capture in particular the heterogeneity of tastes. As a matter of fact, household characteristics are very likely to influence the magnitude of the scale parameter in the choice of housing alternatives and then influencing the results if it is not taken into account. Applications for housing demand are nearly non-existent. This paper fills this gap.

Econometric estimation confirms that residential choices are influenced by age, income and size of the household, as well as by the rent-to-income ratio. An increase in any of these variables decreases the probability of choices of all the alternatives other than the most often chosen alternative (which is for this application house ownership in the suburb). Moreover, the distance to work systematically influences the housing choice for single-parent families and two-earner households. Additionally, preferences are found to significantly differ between local housing markets, specifically between Lille (a large agglomeration and capital city of the North area) and Dunkerque (an industrialised area). The geographical areas are defined based on INSEE employment zones (“zones d’emplois”).

This research has been performed for the north of France and may not hold for other areas even though the methodology can be replicated and the mechanisms at play are quite similar elsewhere.

An important conclusion for sustainable development is the importance to improve city centre amenities relative to those of the suburb or to increase the services associated with high-density dwelling because clearly the most desired alternative remains a house in the suburb. The housing market in the Dunkerque area has some special features characterised by a strong industrial landscape (with port and heavy-duty industrial activities). In this context, amenities provided by the city centre offset the strong attraction of a house in the suburb.

This research shows that households with similar characteristics tend to prefer the same type of real estate property. Therefore, to avoid social segregation, it is important that housing supply respond to different household preferences and needs in the different segments of the housing market. Moreover, the housing supply should take into account the specificities of the geographical areas (both in terms of population who may have a different profile) and in terms of amenities.

This research is one of the very few conducted ones on discrete housing choices in France (with the notable exception of De Palma et al., 2007 for the choice of location). Three simultaneous choices are considered: tenure (including social housing which is almost always ignored), type of building and location. The authors have shown that it is important to take into account the heterogeneity of the preferences in the econometric model with a heteroscedastic logit model.

This paper aims to investigate the characteristics of house price dynamics for a sample of 16 emerging economies from Asia and Central and Eastern Europe over the period of 1995-2011.

Linking housing valuations to a set of conventional fundamental determinants – relative to both the supply and the demand side of the market, institutional factors and other asset prices – and modelling short-term price dynamics – which reflect gradual adjustment to underlying fundamentals –conclusions about the existence and the basic nature of house price overvaluation (undervaluation) are drawn.

Overall, it was found that actual house prices in the sample of emerging economies are not overly disconnected from fundamentals. Rather, they tend to reflect a somewhat slow adjustment to shocks to the latter. Moreover, the evidence that housing valuations may be driven by overly optimistic (or pessimistic) expectations is, in general, weak.

Residential property prices used in the empirical analysis have many limitations: while some series are derived using a hedonic pricing method, others are based on floor area prices collected by national authorities; while some countries publish house prices in national currency per-square metre (or per apartment or per dwelling), others calculate an index number scaled to some base year; while some countries publish statistics for the whole national territory, others produce data only for the capital city or for the largest cities in the country; data from national sources refer to different types of residential property; finally, available time series are relatively short, which may adversely affect the robustness of estimation results.

The decomposition suggested in the paper has important implications: it would be paramount, in fact, for policymakers to implement market-specific diagnoses, and to find the right policy instruments that can ideally distinguish between the two underlying components driving house price short-run dynamics.

There is a very small body of empirical literature on housing market developments in emerging economies, especially if focussed on the comparisons between the actual dynamics of housing valuations and the equilibrium ones.

The study aims to analyze the effects of the Covid-19 pandemic on house prices.

The authors start by discussing the possibility that house price indexes may not fully incorporate the effects of the pandemic as of yet. Against the background of the pandemic, the authors then analyze economic and behavioral effects affecting house prices. The authors also discuss how the linkages between tourism and house prices have been affected. The authors further present evidence of an emerging shift in preferences from urban locations to more peripheral ones.

The authors report variance in the evolution of house prices across countries at the onset of the pandemic, with locations depending heavily on tourism showing slower price appreciation while appreciation has firmed in other places. The authors argue that the resilience of house prices is not only because of the low-interest rate environment and government efforts to support firms and households, but also behavioral factors. In some locations, the price of condominiums has declined relative to the price of detached houses. This could indicate that wealthier households are seeking more space and larger units as a result of the crisis. There is also evidence of a downward pressure on rents, leading to increased price–rent ratios in the USA.

By considering both economic and behavioral factors, this paper provides for a better understanding of the resilience and realignment of house prices at the onset of the Covid-19 pandemic.

The purpose of this study is to examine whether there is a causal relationship between mortgage credit and house prices in Turkey.

Granger causality test, Toda–Yamamoto causality test, Fourier Granger causality test and Fourier Toda–Yamamoto causality tests are applied.

The findings show that there is a strong one-way causality between mortgage credit and house prices and that the developments in credit markets are more decisive in the relationship between mortgage credit and house prices than the developments in the housing markets.

Considering a causal relationship between mortgage credit and house prices may contribute to more efficient use of the tools of both macroeconomic and microeconomic policies for the mortgage credit and housing markets in Turkey. Furthermore, by understanding the importance of the direction of causality between both dynamics, it may be possible to prevent and/or mitigate the negative effects of large house price movements on both Turkish housing and mortgage markets as well as on Turkish economy.

To the best of the authors’ knowledge, the contribution of this study is to examine for the first time whether the causal relationship between mortgage credit and house prices in Turkey is mutual as well as to apply four different causality tests and to compare their results for the first time.