Nonlinear Influence of Chinese Real Estate Development on Environmental Pollution: New Evidence from Spatial Econometric Model

Environmental pollution is a problem of universal concern throughout the globe. The development of real estate industry not only consumes huge resources, but also has close ties with high-consumption industries such as the construction industry. However, previous studies have rarely explored the impact of real estate development on environmental pollution. Therefore, this paper employs the entropy method to construct a comprehensive index of environmental pollution based on panel data of 31 provinces in China from 2000 to 2017, and empirically examines the impact of real estate development on environmental pollution. This article uses real estate investment to measure the development of the real estate industry. In view of the high spatial autocorrelation of environmental pollution, this paper selects a spatial econometric model. The empirical study found that: (1) By using the Spatial Durbin Model, real estate development has an inverted U-shaped impact on environmental pollution. Meanwhile, most cities have not yet reached the turning point; that is, with the continuous development of the real estate industry, environmental pollution will continue to increase. (2) Further regional heterogeneity found that the inverted U-shaped relationship still exists in coastal and inland areas. (3) Finally, this article used the Spatial Mediation Model to explain the nonlinear impact of real estate development on environmental pollution, with two important mediating variables: population density and industrial structure. Through the above analysis, it can be observed that real estate development has a significant impact on environmental pollution. Thus, the country and the government can reduce environmental pollution by improving the investment structure, using environmentally friendly building materials, guiding population flow and promoting industrial upgrading.

Sustainable Gig Economy Finance Towards GDP Growth of India Through “Aatmanirbhar Bharat”

In recent years, India has become the world's fastest-growing major economy. Its development has been fuelled mostly by the services sector, which accounts for over 55% of GDP, as contrasting to the industrial sector, which has remained stable at roughly 16%. To facilitate ‘Aatmanirbhar Bharat', the government has brought in the product-linked incentive (PLI) scheme to encourage several sectors to increase their local manufacturing and supply chain base, among other things, to help India become self-reliant for high end products. These efforts will aid in the creation of jobs, the alleviation of stressed sectors, the assurance of liquidity, the boost of manufacturing, the energization of the real estate industry, and the assistance of farmers. The chapter aims to evaluate the Balance of Payment of India as structural growth country wise and sector wise growth of FDI in India as well as the ‘Aaatmanirbhar Bharat' status and stimulus packages, which have been announced for sustainable growth of GDP during this pandemic situation.

Productivity assessment of the real estate industry in China: a DEA-Malmquist index

PurposeThe high-quality development of the real estate industry is crucial to the transformation of China's economy. However, few studies apply the productivity to explore the development path of the real estate industry in China. To fill this gap, this study mainly investigates the total factor productivity (TFP) of the real estate industry of 30 sample provinces in mainland China from 2007 to 2016.Design/methodology/approachThe Malmquist index is applied to estimate the productivity (i.e. TFP) of the real estate industry, based on the data envelopment analysis (DEA). Then, the truncated tobit regression analysis explores the external influencing factors on the TFP of the real estate industry.FindingsThrough empirical analysis, it is found that the high-quality development of the real estate industry depends on the technological innovation by the real estate enterprises and the targeted policies by the provincial government. Moreover, the development of the real estate industry has a positive correlation with the growth of China's economy but a negative correlation with the development of other industries.Practical implicationsTFP mainly reveals the development status of the provincial real estate industry and identifies the driving force for exploring the high-quality development mode of the real estate sector. Furthermore, the fluctuation rule of TFP can be applied to predict the development trend of the real estate industry in the future.Originality/valueAs an application, this study measures the TFP of the Chinese real estate industry in different provinces and periods. The results have meaningful policy implications for policymakers regulating the real estate industry.

Value-relevance of reported changes in fair values and measurement-related fair value disclosures: evidence from the Australian real estate industry

PurposeThe paper aims to investigate the value-relevance of changes in fair values of investment property reported under International Accounting Standards (IAS) 40 and International Financial Reporting Standards (IFRS) 13.Design/methodology/approachMultivariate regression models are used to regress cumulative market-adjusted stock returns of real estate firms on changes in fair values, along with control variables and corporate governance variables, in order to examine the research question.FindingsUsing hand-collected data from the Australian Real Estate Industry (AREI), the authors find that changes in fair values of investment property are value-relevant for equity investors. The authors further find that using unobservable inputs in an active market (Level 3 inputs) does not diminish the information content of fair values. The authors document that properties valued exclusively by directors have a significantly reduced value-relevance, whereas property valuations made collectively by both directors and independent valuers have superior value-relevance, possibly owing to the combination of inside knowledge and externally imposed monitoring. Collectively, the findings suggest that in the real estate industry, where unobservable inputs are commonly used to determine fair values of properties, the fair values determined subjectively are perceived to be sufficiently informative and relevant.Research limitations/implicationsThe authors' findings have important implications for accounting standard-setters in considering whether an external valuation should be required and whether the extensive measurement-related fair value disclosure requirements are useful.Originality/valueThe study extends previous archival evidence and complements prior commentaries on experimental and analytical work in the Australian regulatory environment.

Analysis of Urban Residents' Sports Consumption Demand Based on Intercepted Regression Model

At this stage, broadening the consumer market, upgrading the consumption system and gradually establishing a consumption-led development concept are key factors in promoting high-quality economic development. At the same time, China's macro economy is also experiencing another test. The rapid development of China's real estate market in recent years has attracted a large number of investors, and real estate prices have produced irrational and substantial increases. Behind the boom of the real estate market is a social system crisis driven by profiteering and the growing seriousness of real estate financial bubble. So exploring the mechanism of the influence of real estate prices on the upgrading of residents' consumption is important for the current stage of China. Therefore, it is important to investigate the mechanism of real estate price impact on consumer upgrading for the coordinated development of real estate industry and national economy. In this paper, we analyze and examine the theory on the consumption improvement by the literature survey method. We also summarize the present research on the correlation and the influence mechanism of the real estate price and the consumption improvement and choose the index which reflects the present state of the real estate industry and the consumption of the inhabitant. Besides the input indicators that qualitatively manage the impact of housing prices on the improvement of residents' consumption, we first use the descriptive statistics method to understand the level of the Chinese real estate market and improve consumer spending. Based on this, the descriptive statistical method is applied to define the current state of China's real estate market and the level of improvement in consumption, and to define the standard for improving consumption in China. On the other hand, based on the spatial and spatial spillover points of view, we use spatial analysis framework combined with exploratory spatial data analysis and GIS to investigate spatial correlation between consumption structure and housing price, and accurately reflect the spatial clustering status of the index by drawing. Moran dispersion plot and Lisa cluster plot, then the spatial Darwinian model, are used to investigate the impact of real estate prices on the increase in occupant consumption from a macro perspective.