The impact of government land supply on housing starts

This paper investigates the impact of government land supply on new residential construction. By estimating a housing supply equation using a panel data set covering 35 major Chinese cities for the period of 1999 to 2010, it is found that the quantity of the land sold by the government is tightly associated with the number of housing starts. Two -or three - year lag of land sales has a larger impact on new construction than one- year lag , which is consistent with the fact that there is normally a two- to three-year interval between the date of land transaction and the date when construction is initiated. It is also found that the decrease in land sales accounts for a large proportion of the decrease in new construction in Beijing, Shanghai and Shenzhen. The estimates of city -specific supply elasticities are provided based on the housing supply model, it is found that housing price appreciation tends to be more considerable in cities with inelastic supply

Direct Government Control Over Residential Land Supply And Its Impact On Real Estate Market: Evidence From Major Chinese Market

In the early and mid - 2000s, the development of land reserve system promoted a structural change in residential land market in urban China, and the municipal government has become the sole supplier of urban residential land after the structural change. This paper examines the impact that direct government control over residential land supply has on real estate markets in major Chinese cities. It is found that there is a significant decrease in land supply after the establishment of direct government control over residential land supply, and the decrease in land supply has put downward pressure on new housing supply. It is also found that there is a decline in the price elasticity of new housing supply in the period characterized by more restrictive land supply

Backward-bending new housing supply curve: evidence from China

This paper tests the existence of a backward-bending housing supply relationship in China, and estimates price elasticity of new housing supply for 35 major Chinese cities. Based on the panel data model of 35 cities, it is found that the response of housing supply to price change is relatively insensitive in China, and the supply elasticity has decreased with the rise in housing price. As a result, the remarkable increase in housing prices in China can be at least partly attributed to the inelastic housing supply. The results from this paper may inform Chinese government to take effective measures to reduce the large amount of idle land so as to increase the supply for the housing market

3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes

While deep convolutional neural networks (CNN) have been successfully applied for 2D image analysis, it is still challenging to apply them to 3D anisotropic volumes, especially when the within-slice resolution is much higher than the between-slice resolution and when the amount of 3D volumes is relatively small. On one hand, direct learning of CNN with 3D convolution kernels suffers from the lack of data and likely ends up with poor generalization; insufficient GPU memory limits the model size or representational power. On the other hand, applying 2D CNN with generalizable features to 2D slices ignores between-slice information. Coupling 2D network with LSTM to further handle the between-slice information is not optimal due to the difficulty in LSTM learning. To overcome the above challenges, we propose a 3D Anisotropic Hybrid Network (AH-Net) that transfers convolutional features learned from 2D images to 3D anisotropic volumes. Such a transfer inherits the desired strong generalization capability for within-slice information while naturally exploiting between-slice information for more effective modelling. The focal loss is further utilized for more effective end-to-end learning. We experiment with the proposed 3D AH-Net on two different medical image analysis tasks, namely lesion detection from a Digital Breast Tomosynthesis volume, and liver and liver tumor segmentation from a Computed Tomography volume and obtain the state-of-the-art results

On the Relation between Discrete and Continuous-time Refined Instrumental Variable Methods

The Refined Instrumental Variable method for discrete-time systems (RIV) and its variant for continuous-time systems (RIVC) are popular methods for the identification of linear systems in open-loop. The continuous-time equivalent of the transfer function estimate given by the RIV method is commonly used as an initialization point for the RIVC estimator. In this letter, we prove that these estimators share the same converging points for finite sample size when the continuous-time model has relative degree zero or one. This relation does not hold for higher relative degrees. Then, we propose a modification of the RIV method whose continuous-time equivalent is equal to the RIVC estimator for any non-negative relative degree. The implications of the theoretical results are illustrated via a simulation example.</p

A Dielectric Affinity Microbiosensor

We present an affinity biosensing approach that exploits changes in dielectric properties of a polymer due to its specific, reversible binding with an analyte. The approach is demonstrated using a microsensor comprising a pair of thin-film capacitive electrodes sandwiching a solution of poly(acrylamide-ran-3-acrylamidophenylboronic acid), a synthetic polymer with specific affinity to glucose. Binding with glucose induces changes in the permittivity of the polymer, which can be measured capacitively for specific glucose detection, as confirmed by experimental results at physiologically relevant concentrations. The dielectric affinity biosensing approach holds the potential for practical applications such as long-term continuous glucose monitoring