EDITORIAL: TAX REFORM AND SIMPLIFICATION

Major tax reform to simplify the UK tax system is possible. Merging income taxes, social security taxes and corporation tax into only a single flat-rate of tax on all incomes would be a radical start. Avoiding taxes on income and expenditure which are 'too high' requires major reductions in government spending, mainly on the welfare state. Given the political will, over a period of years we really can hugely improve the UK tax system.     

Thought leadership in investment banking: The beginning of a new era

The paper argues that although considerations such as industry consolidation, the role of lending and the effects of technology are still important in shaping the future of investment banking, sustainable competitive advantage necessitates that emphasis is also placed on thought leadership. This entails quite a radical change in terms of the way in which the industry approaches the problem of competition and requires emphasis on value creation for all the constituent parts of the industry: corporations, investors, the banks themselves and research departments. Accordingly, the paper provides a rationale for this change and provides inter alia a range of examples to illustrate how thought leadership could lead to a fundamental change in the future of the investment banking industry.     

A play-the-winner-type urn design with reduced variability

We propose a new adaptive allocation rule, the drop-the-loser, that randomizes subjects in the course of a trial comparing treatments with dichotomous outcomes. The rule tends to assign more patients to better treatments with the same limiting proportion as the randomized play-the-winner rule. The new design has significantly less variable allocation proportion than the randomized play-the-winner rule. Decrease in variability translates into a gain in statistical power. For some values of success probabilities the drop-the-loser rule has a double advantage over conventional equal allocation in that it has better power and assigns more subjects to the better treatment. Acknowledgments. I thank Stephen Durham, the associate editor, and the referees for their helpful suggestions.     

Self‐help in housing and chengzhongcun in China's urbanization

This article focuses on the housing issues of rural migrants arising from urbanization, with particular reference to chengzhongcun, a topic with considerable impact on policymaking. An attempt is made to understand the underlying rationale of self‐help in housing and the important role of chengzhongcun in sheltering rural migrants in the context of China's rural‐urban dichotomy. As demonstrated in this study, chengzhongcun accommodate, with little in the way of government resources and assistance, millions of rural migrants because of their social accessibility and affordability. While not denying their social problems, we argue that chengzhongcun in fact act as an innovative and positive agent to promote urbanization in present day China by housing massive numbers of rural migrants and assimilating them into cities. Current government policies towards chengzhongcun have generated a wide range of interest conflicts and confrontations. The consequences of such conflicts show that the government policies were problematic and unworkable, as they violated basic market principles as well as citizen rights. Policy strategy towards the redevelopment of chengzhongcun must acknowledge their credibility in the Chinese road to urbanization and requires more thoughtful and prudent consideration of migrants' demands for affordable housing.     

Density estimation in the uniform deconvolution model

We consider the problem of estimating a probability density function based on data that are corrupted by noise from a uniform distribution. The (nonparametric) maximum likelihood estimator for the corresponding distribution function is well defined. For the density function this is not the case. We study two nonparametric estimators for this density. The first is a type of kernel density estimate based on the empirical distribution function of the observable data. The second is a kernel density estimate based on the MLE of the distribution function of the unobservable (uncorrupted) data.