Housing Economy
Ali Hasanvand
Abstract
Housing is a critical economic sector, with its growth benefiting households. However, rising prices in recent years have diminished household welfare. Using provincial-level data (2011–2021) and a spatial econometric approach, this study analyzed the factors driving housing price increases. The ...
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Housing is a critical economic sector, with its growth benefiting households. However, rising prices in recent years have diminished household welfare. Using provincial-level data (2011–2021) and a spatial econometric approach, this study analyzed the factors driving housing price increases. The findings revealed that urbanization and economic growth positively influenced housing prices, while financial development had negative spillover effects, underscoring the role of traders in price determination. Although industrialization had no direct effect, its spillover effects were found to be positive, highlighting the service sector’s influence. The study confirmed the housing price divergence and recommended enforcing tax laws on vacant properties and increasing financing in the housing sector to improve Iran’s housing market.IntroductionHousing is considered a unique commodity due to its dual nature as both a consumption good and a capital asset, along with its inelastic supply, essential role as shelter for primary households, and lack of substitutes. In the short term, housing supply remains inelastic to price changes due to the structural characteristics of durable goods. Given the significant capital aspect of housing, it is consistently subject to price fluctuations, much like other capital goods markets. Urbanization plays a dual role in housing demand: it increases consumption demand while simultaneously creating investment opportunities, driving up demand for housing as an asset. Another key factor influencing housing prices is the credit ratio. A higher credit-to-GDP ratio suggests the expansion of rentier markets—such as speculative housing transactions—that lack real added value, ultimately leading to price increases. Therefore, analyzing the factors influencing housing prices is both important and valuable.Materials and MethodsThe present research relied on theoretical and empirical literature (i.e., Cook et al., 2018; Kavlihua and Kameti, 2019; Su et al., 2021) to identify the factors influencing housing prices. Accordingly, Equation (1) was used to analyze these factors.(1)In Equation (1), pric represents the price per square meter of housing, gdp denotes real gross domestic product, indus refers to industrialization (measured as the ratio of industry value added to total value added), and cred is the ratio of bank credit to GDP, serving as an indicator of financial development. Additionally, urban represents the urbanization rate, calculated as the ratio of the urban population to the total population. Research data was collected from the Central Bank of Iran and the Statistical Center of Iran. To apply the spatial econometric approach, the study used the Moran test to examine spatial effects of the research variables.Results and DiscussionWhen spillover effects were not considered, financial development in each province had a positive and significant effect on the housing price. This is primarily because the production sector lacks more profitable investment opportunities than housing, leading to a substantial portion of credit flowing into the housing market and driving up prices. A high credit-to-GDP ratio indicates a surplus of financial resources, which, in turn, accelerates the growth of rentier activities. As a result, part of the credit expansion’s effect on housing demand stems from speculative investment, while another part is driven by increased access to credit for lower-decile households and consumer demand.The second factor influencing the housing price is GDP, which has a positive and significant effect. The rise in GDP can be analyzed from two perspectives: the macroeconomic level and the household (microeconomic) level. At the household level, an increase in GDP leads to higher per capita income, boosting purchasing power. Consequently, demand for housing—considered a normal good—rises, which drives up prices. This hypothesis is supported by two key observations: first, a relatively high proportion of households do not own homes, and second, there is a significant diversity in housing options. At the macro level, part of the increased economic growth can be attributed to the expansion of the housing sector, which led to a greater supply of housing. However, since micro-level effects outweigh macro-level effects in this case, housing prices still rose. Given that economic growth in the 1990s was below one percent, the impact of this factor was not particularly significant.The spatial camera approach was employed to examine the spatial effects of factors on the housing price. The results indicated that increased urbanization in neighboring provinces does not significantly impact the housing price in a specific province. This suggests that the opportunities and benefits of urbanization are not transferred between provinces. However, other research variables showed a significant spatial effect on the housing price. According to the estimates, a rise in the credit ratio in neighboring provinces reduces speculative demand for housing in a specific province, leading to a decline in the housing price. An increase in the credit ratio indicates greater prosperity in non-value-added speculative activities. The movement of these sources to certain provinces results in declining housing prices in others. Moreover, as GDP rises in neighboring provinces, employment opportunities become more attractive, making those provinces more desirable places to live. This then leads to a drop in the housing price.ConclusionThe rise in the housing price has long been one of the biggest challenges in ensuring affordable housing for households. As housing prices increase and a larger portion of household income is spent on essential goods, overall household welfare declines significantly. In contemporary Iran, the existing legal texts emphasize financing housing for households and enforcing the Production Leap Law. Therefore, analyzing the factors influencing housing prices is crucial for shaping an effective policy roadmap. The results indicated that rising urbanization, the credit-to-GDP ration, and GDP itself have a positive and significant effect on the housing price. Furthermore, convergence analysis suggests that housing prices in Iranian cities are diverging. The negative spatial correlation of housing prices between cities reflects the dominance of housing as a capital asset rather than a consumer good. A key factor behind traders’ strong influence in the housing market is their greater access to financial credits compared to consumer buyers. However, the positive effects of urbanization have not been widely transferable across many cities due to its benefits. Furthermore, the high share of the service sector in GDP and the positive spillover effects of industrialization across provinces have led to an inverse relationship in housing prices—rising prices in neighboring provinces have contributed to price declines in specific provinces. To improve housing conditions, the most critical policy measures include enhancing financial access for low-income households and diversifying housing options to increase their chances of securing affordable housing.AcknowledgmentsThe author sincerely thanks all colleagues and individuals who contributed to the completion of this article.
Housing Economy
Mohammad Hossein Amjadi; Ali Reza Shakibaei; Sayyed Abdolmajid Jalaee
Abstract
The purpose of the study is to portray the effect of exchange rates, its uncertainty and covid-19 pandemic on house prices in Tehran using the monthly data from Mar, 2016 to Mar, 2021. In order to calculate the uncertainty, IGARCH model and to estimate the mean equation, the ARDL method have been used. ...
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The purpose of the study is to portray the effect of exchange rates, its uncertainty and covid-19 pandemic on house prices in Tehran using the monthly data from Mar, 2016 to Mar, 2021. In order to calculate the uncertainty, IGARCH model and to estimate the mean equation, the ARDL method have been used. According to research results, the effect of exchange rate and exchange rate uncertainty index on housing prices as the objectives of this study, are positive and significant. Accordingly, a 100% increase in the exchange rate and the exchange rate uncertainty index will cause a 14% and 6% increase in housing prices in Tehran, respectively. Therefore, any action that reduces uncertainty in the future situation of the foreign exchange market can be effective in reducing the negative effects on housing supply and demand. Also, the results of model estimation show that the outbreak of Corona virus has acted as a shock and increased housing prices in Tehran.
