Spatial Variation in the Determinants of House Prices and Apartment Rents in China

This paper provides an examination of China??s residential real estate market at the county level using data from that country??s 2000 census. The market is a new one, having only been fully established in 1998. The analysis in the paper is in the form of an aggregate (county-level) hedonic model specified in two versions. Global parameters results are estimated using spatial error model specifications while more local effects are estimated by geographically weighted regression. Global results are typical in that structural characteristics such as floor space and contextual characteristics such as level of in-migration are important in residential prices. Local results, however, indicate significant spatial variation in the effect of both structural amenities and locational context on housing prices. In a simpler specification, rents are shown to respond positively to both median house prices levels and the supply of apartments available at market prices, but also with significant spatial variation across China.     

Speed of convergence to market efficiency: The role of ECNs

Chordia, Roll and Subrahmanyam (2005, CRS) estimate the speed of convergence to market efficiency based on short-horizon return predictability of the 150 largest NYSE firms. We extend CRS to a broad panel of NYSE stocks and are the first to examine the relation between electronic communication networks (ECNs) and the corresponding informational efficiency of prices. Overall, we confirm CRS's result that price adjustments to new information occur on average within 5–15 min for large NYSE stocks. We further show that it takes about 20 min longer for smaller firms to incorporate information into prices. Most importantly, we demonstrate that the speed of convergence to market efficiency is significantly related to the type of trading platform where orders are executed, even after controlling for relative order flows, trading costs, volatility, informational effects, trading conditions, market quality, institutional trading activity, and other firm-specific characteristics. Our findings provide direct answers and insights to issues raised in a recent SEC concept release document.     

Trading Volume-Induced Spatial Autocorrelation in Real Estate Prices

Spatial dependence is often seen as a problem in econometrics rather than in economics. This study seeks to find an economic explanation for spatially correlated real estate prices. We posit spatial dependence as a process to discover price information from neighboring property transactions. Weaker spatial dependence is expected when price information in the immediate vicinity of a subject property is abundant. In the context of apartment buildings, in addition to the more commonly known horizontal dependence, there is also spatial dependence in the vertical dimension within the same building. Based on more than 18,000 transactions of highly homogeneous apartment units in Hong Kong, we found that the trading volume of a building depresses horizontal spatial dependence, but raises vertical spatial dependence. This not only confirmed the role of trading volume in the real estate price discovery process, but also questioned the validity of constant spatial autocorrelation assumption adopted in many studies.     

Investor Attention and Earnings Management around the World

This study examines the determinants of earnings management in an international setting using the limited investor attention model of Hirshleifer and Teoh ( 2003 ). The model predicts that investor attention reduces earnings management. I use analyst following, institutional ownership, and Big N auditor choice to proxy for investor attention. I have four key findings. First, I document that financial analysts curb earnings management in U.S. firms but not in non‐U.S. firms. Second, I document that institutional block‐holdings curb earnings management across the world. Third, Big N auditors reduce earnings management in U.S. firms but not in non‐U.S. firms. Fourth, I document that corporate governance mechanisms reduce earnings management in U.S. firms but not in non‐U.S. firms.     

Dynamic Financial System: Complexity,Fragility and Regulatory Principles

A financial system improves the allocation of real resources and enhances the performance of the production economy, but these benefits are offset in part by the risk of financial distress and the associated deadweight loss resulting from bankruptcy costs. We argue that “tiers” of financial claims increase complexity and fragility of the financial network. In equilibrium, the financial system grows relative to the real economy as the allocation of funds and risks becomes more sophisticated and as more financial claims are tiered. Growth is limited by the risk of a tiered, complex financial network and by the need to set aside additional capital as the financial sector grows. We discuss several sources of fragility in the financial system. We propose that regulators should limit the breaks in the system and do more to improve the resiliency of the network and less on individual issues that are only symptoms of fundamental problems of a network. We advocate a market based system of regulation in which market participants regulate each other, to a degree. In order for this to be feasible, the financial network must be organized according to three principles: trading transparency, competitive markets and competitive regulators, and incentive alignment of participants. Insofar as these regulatory approaches are successful in limiting network fragility, capital requirements can be reduced. Regulators should keep in mind this tradeoff between capital and regulation. With regard to regulatory policy, regulators should let the three principles be their guide in adapting to the evolving financial system rather than implementing narrowly conceived regulations that are quickly outmoded.     

Government ownership,corporate governance and tax aggressiveness: evidence from China

This study investigates how government ownership and corporate governance influence a firm's tax aggressiveness. Using Chinese listed companies during 2003–2009, we find that compared with government‐controlled firms, non‐government‐controlled firms pursue a more aggressive tax strategy. In particular, non‐government‐controlled firms with a higher percentage of the board shareholdings and with a CEO who also serves as the board chairman are more aggressive. For government‐controlled firms, we find that board shareholding has an impact on tax aggressiveness and it does not differ between local and central government‐controlled firms. However, local government‐controlled firms in less developed regions where the implementation of corporate governance measures is generally less effective are more tax aggressive than those in other regions.     

Fourier-analytic measures for heavy-tailed insurance losses

We propose a family of three ‘Fourier-analytic’ measures to extend the conventional concepts of standard deviation, variance, and coefficient of variation to insurance losses with arbitrarily heavy tails. After motivating and computing their mathematical forms, we apply the proposed measures to the case of Lévy-stable loss portfolios. Finally, the new measures are used to study the diversification properties of heavy-tailed losses.     

Stability of international stock market relationships across month of the year and different holding intervals

Potential benefits from international diversification depend upon the stability in stock market relationships. Using monthly data of 11 international stock markets, this paper examines the stability in stock market relationships across month of the year and across different holding intervals. Empirical results show that the correlation structure is more stable than the covariance structure. While empirical evidence supports the hypothesis that the correlation structure is very stable across different holding intervals, the empirical support for the stability in correlation structure across month of the year is much weaker.     

Cosmopolitan risk community in a bowl: a case study of China’s good food movement

Abstract

Ulrich Beck fundamentally transformed our way of thinking about human interdependence through his three core theses on risk, individualisation and cosmopolitanisation. However, two commonly observed deficiencies in Beck’s grand theory were its Eurocentric orientation and a lack of empirical grounding. Based on 5 focus groups and 14 interviews with participants of the emerging Clean Food Movement in China, this paper extends the Beckian discussion outside Europe. Through examining how individuals understand both ‘traditional’ and ‘new’ risks associated with contemporary food consumption, this paper demonstrates that in the face of unpredictable and incalculable harms, risks are not seen as a ‘thing’, but are translated into ‘causal relations’. Subsequently, for Chinese stakeholders, the best way to safeguard food risks is to enact more visible and functioning interdependent relations in the food system. This in turn has given rise to new forms of communities which cut across conventional geographic, socio-economic and political boundaries. The paper deepens a Beckian theorisation in two ways. First, it demonstrates that the ‘enabling’ effect of risk towards a cosmopolitan society is not limited to obvious global crises, such as climate catastrophes and financial meltdown. In fact, the mundane yet intimate concern of putting ‘good’ food in one’s dinner bowl already presses actors to form new social solidarities that are cosmopolitan in nature. Second, it goes beyond Beck’s assertion that the risk society has culminated in a cosmopolitan moment, and explores how a performative cosmopolitan community reshapes the ‘relations of definition’ to mitigate risks on the ground.     

Nonparametric estimation for a stochastic volatility model

Consider discrete-time observations (X _{? δ} )_1≤?≤n+1 of the process X satisfying $dX_{t}=\sqrt{V_{t}}dB_{t}Consider discrete-time observations (X _{ℓ δ} )_{1≤ℓ≤n+1} of the process X satisfying dX_t=?{V_t}dB_tdX_{t}=\sqrt{V_{t}}dB_{t} , with V a one-dimensional positive diffusion process independent of the Brownian motion B. For both the drift and the diffusion coefficient of the unobserved diffusion V, we propose nonparametric least square estimators, and provide bounds for their risk. Estimators are chosen among a collection of functions belonging to a finite-dimensional space whose dimension is selected by a data driven procedure. Implementation on simulated data illustrates how the method works.