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This paper aims to explore the sources of China's property boom from 2000 to 2009. The basic research hypothesis is that the property boom is largely associated with Chinese local governments’ incentive structure which prioritizes GDP growth for evaluating their performance.

Based on the fixed effects panel data regression model of 35 major Chinese cities, the determinants of property investment, property price and land sale price are identified. In particular, the roles of local governments in boosting the property boom are discussed.

Property investment is driven by accelerating urbanization process, easier availability of bank loans and more housing sales. Meanwhile, higher disposable income, more housing sales and increasing property investment are identified to mainly account for the property price escalation. It is further demonstrated that increasing property price has positive effect on land sale price. Local governments have quickened the urbanization process, released more bank loans and sold more land through public auction to support property development, sustain property price and increase land sale revenue. Such behaviour is closely related to Chinese local governments’ incentive structure.

Previous studies have not empirically tested the relationships between local governments’ pursuits for higher revenue in the urban land market and China's magnified and sustained property boom over the past decade. A prosperous property market is conducive to economic development and hence local officials’ chances of political promotion.

The purpose of this study is to conduct a thorough empirical investigation of the intricate relationship between urban housing sales prices and land supply prices in China, with the aim of elucidating the underlying economic principles governing this dynamic interplay.

Using monthly data of China, the authors use the asymmetry nonlinear autoregressive distributed lag (NARDL) model to test for nonlinearity in the relationship between land supply price and urban housing prices.

The empirical results confirm the existence of an asymmetric relationship between land supply price and urban housing prices. The authors find that land supply price has a positive and statistically significant impact on urban housing prices when land supply is increasing. Policymakers should strive to strike a balance between safeguarding residents’ housing rights and maintaining market stability.

Although the asymmetric effect of land supply price has been identified as a significant contributor in this study, it is important to note that the research primarily relies on time series data and focuses on analysis at the national level. Although time series data offer a macroscopic perspective of overall trends within a country, they fail to adequately showcase the structural variations among different cities.

To ensure a stable housing market and meet residents’ housing needs, policymakers must reexamine current land policies. Solely relying on restricting land supply to control housing prices may yield counterproductive results. Instead, increasing land supply could be a more viable option. By rationally adjusting land supply prices, the government can not only mitigate excessive growth in housing prices but also foster the healthy development of the housing market.

First, the authors have comprehensively evaluated the impact of land supply prices in China on urban housing sales prices, examining whether they play a facilitating or mitigating role in the fluctuation of these prices. Second, departing from traditional linear analytical frameworks, the authors have explored the possibility of a nonlinear relationship existing between land supply prices and urban housing sales prices in China. Finally, using an advanced NARDL model, the authors have delved deeper into the asymmetric effects of land supply prices on urban housing sales prices in China.

In this research, the purpose of this paper is to assess the relative pricing behavior for land in Beijing, China. The paper sees this as important for three core reasons. First, China has a strong growth economy but is still in many ways an undeveloped country and thus the paper do not have significant data about asset pricing behavior there. Second, China has not traditionally had a market-based land and property transfer system – thus, it is interesting to assess how prices are determined relative to typical market expectations. Third, the authors have extensive evidence on pricing behavior in the USA and Europe but little such evidence on China – are the same variables important in land pricing in China and are there other unique local variables.

This paper analyzes prices of non-industrial and industrial land separately using a comprehensive data set and a semi-parametric framework. The data and flexible model specification allow the hedonic price coefficients to be estimated more accurately.

The key results are that pricing behavior in general follows the traditional expected variables as determined by size, planning use, location and other neighborhood characteristics. However, the authors also find that land prices are associated with buyer characteristics; for example, foreign investors pay less than local investors.

The study fills the gap in the literature in two ways. First, this paper analyzes prices of non-industrial and industrial land separately using a comprehensive data set and a semi-parametric framework. The data and flexible model specification allow the hedonic price coefficients to be estimated more accurately. Second, and more importantly, the authors find evidences that land prices in China are determined by both market force and “Chinese characteristics.” The land market, although established only recently, is at work. In line with the literature, determinants such as size and planning uses are found to be important in determining land prices.

Oklahoma has seen rapid growth in the development of wind energy over the past decade. Residents are concerned about the negative impacts of turbines such as noise or their appearance. This has raised concerns about property values. Thus, this paper aims to examine and quantify the overall impact of wind turbines upon real estate prices in Western Oklahoma.

Sales prices and the history of approximately 23,000 residential real estate records for both platted and unplatted properties in five counties were examined prior to the announcement of construction, after announcement and after construction. A hedonic analysis was undertaken to examine the real estate prices of the properties near wind farms.

While there may be isolated instances of lower property values for homes near wind turbines, results show no significant decreases in property values over homes near wind farms in the study area. Similar results are found for the unplatted properties.

This paper highlights that in spite of mixed attitudes toward wind farms and misconceptions regarding the link between turbines and property values, Oklahoma’s growing wind industry can continue to thrive without negatively impacting nearby home and land values and prices.

Although there have been numerous studies examining the relationship between wind turbine locations and real estate prices, no study has combined the large quantity of records (over 23,000) as well as both platted and unplatted locations.

Focusing on the externality effects of historic districts, this paper aims to assess and compare the impact of historic district designation on the value of residential vacant land property.

Hedonic regression is used to analyze data from 4,233 residential vacant site transactions to measure the influence of historic district designation on the price of residential vacant site properties.

Results support established theory and research on other residential property types, showing a significant and positive relationship between designation in a historic district and property prices. Residential vacant sites located in a designated historic district sold at a 10-11 per cent premium compared to similar vacant sites not located in a historic district.

This is the first empirical study of the influence of historic districts on residential vacant land property. The paper extends limited previous literature on the externality effects of historic districts through detailed analysis of a large Australian housing market (Brisbane).

China's real estate market is rampantly expanding. The purpose of this paper is to examine the factors underpinning China's real estate price escalation from 1998 to 2009.

Cointegration approach, vector error correction model and Granger causality test are adopted to analyze whether stable and long‐run equilibrium interactions exist between housing prices and key macroeconomic variables, such as CPI, land sale and GDP.

Cointegration analysis shows long‐term equilibrium between real estate price (HP) and CPI or GDP, but not land sale. A bilateral Granger causality is observed between CPI and HP. However, GDP does not Granger cause HP, indicating personal gain (disposable income) does not catch up with national gain (GDP) in China, or “Guojinmintui” (national gain outpaces personal gain). Neither is there a feedback effect from HP to GDP, indicating housing price appreciation does not result in immediate capital gain or speculations in housing purchase. Besides, lack of cointegration relationships between HP and land sale is probably caused by restrictive polices on land supply.

This paper represents the first attempt to adopt cointegration approach and Granger causality tests to examine the real estate price escalation in China using national monthly data. Econometric analysis and subsequent policy discussion suggest that real estate price is driven by both economic and institutional factors. In particular, “Guojinmintui” is a fiscal issue while capital gain is a monetary issue. Together with land market policies, these institutional factors significantly contribute to the price escalation.

The “stigma” associated with remediated contaminated land is the blighting effect on property value caused by perceived risk and uncertainty. Uncertainties relate to negative intangible factors such as the inability to effect a total “cure”, the risk of failure of the remediation method, the risk of changes in legislation or remediation standards, the difficulty in obtaining finance, or simply a fear of the unknown. Post‐remediation “stigma” is the residual loss in value after all costs of remediation, including insurance and monitoring, have been allowed for. It equates to the difference in value between a remediated contaminated site and a comparable “clean” site with no history of contamination. The initial results from a study of the market sales data of post‐remediated vacant residential land along the Swan River, in Perth, Western Australia, from 1992‐1998 are summarized. The aim of this ongoing research is to estimate the amount of “stigma” arising from a site’s contamination history and measure the effect of this on residential property values of remediated property. The results show that while a site’s contamination history impacts negatively on property prices, the price decreases are offset by the positive influence on price from additional amenities provided in the case study neighbourhood.

A tax based on land value is in many ways ideal, but many economists dismiss it by assuming it could not raise enough revenue. Standard sources of data omit much of the potential tax base, and undervalue what they do measure. The purpose of this paper is to present more comprehensive and accurate measures of land rents and values, and several modes of raising revenues from them besides the conventional property tax.

The paper identifies 16 elements of land's taxable capacity that received authorities either trivialize or omit. These 16 elements come in four groups.

In Group A, Elements 1‐4 correct for the downward bias in standard sources. In Group B, Elements 5‐10 broaden the concepts of land and rent beyond the conventional narrow perception, while Elements 11‐12 estimate rents to be gained by abating other kinds of taxes. In Group C, Elements 13‐14 explain how using the land tax, since it has no excess burden, uncaps feasible tax rates. In Group D, Elements 15‐16 define some moot possibilities that may warrant further exploration.

This paper shows how previous estimates of rent and land values have been narrowly limited to a fraction of the whole, thus giving a false impression that the tax capacity is low. The paper adds 14 elements to the traditional narrow “single tax” base, plus two moot elements advanced for future consideration. Any one of these 16 elements indicates a much higher land tax base than economists commonly recognize today. Taken together they are overwhelming, and cast an entirely new light on this subject.

This paper seeks to explore the dynamics of the spatial distribution of landed residential property values in Singapore in the 1990s. Topics covered include: spatial patterns that can be discerned in the distribution of landed property values; how property values change over time; and how government intervention influenced this dynamic property value surface. Data are collected from the Singapore Institute of Surveyors and Valuers property transaction database, and are analysed by using the geographic information system, parametric and non‐parametric statistics. Findings of this paper contribute to the understanding of the urban dynamics of an Asian metropolis, especially in terms of its residential property market and internal spatial structure.

This article aims at analysing the different institutional aspects of the rural land market that are manifest at the transactional level. Second, it answers the question whether including these aspects in a land price model increases the understanding of rural land market outcomes. Institutional economics scholars have challenged the limited institutional behaviour of conventional land market models. Despite their research methods remaining primarily qualitative, research findings suggest that we should look at institutional aspects to understand land and real estate market outcomes better.

This paper presents a hedonic price model explaining rural land prices by using individual institutional transaction aspects from the deeds of purchase of the land exchange.

The results indicate that incorporating institutional aspects, such as property rights, transactional arrangements and governance context, as explanatory variables significantly improves the power of the model.

The approach taken in this article is new in the sense that it tries to combine a quantitative research method with a rich data set of a more qualitative character. The use of deeds of purchase as a primary source of a hedonic price model is relatively new and provides a first step in bridging the gap between advanced hedonic land price models and rich institutional economic insights in market processes.