Regional innovation and small high technology firms in peripheral regions

This paper highlights the difficulty of developing HT firms in a peripheral region of Spain. Although the endogenous development of HT firms in these regions is possible, their evolution depends on more central regions. The firm's geographical location and the type of HT production are the most important endogenous factors governing the firm's success.     

Numerical issues in threshold autoregressive modeling of time series

This paper analyses the contribution of various numerical approaches to making the estimation of threshold autoregressive time series more efficient. It relies on the computational advantages of QR factorizations and proposes Givens transformations to update these factors for sequential LS problems. By showing that the residual sum of squares is a continuous rational function over threshold intervals it develops a new fitting method based on rational interpolation and the standard necessary optimality condition. Taking as benchmark a simple grid search, the paper illustrates via Monte Carlo simulations the efficiency gains of the proposed tools.     

Dividend reinvestment plans: An empirical analysis

This study examines the effect of initiating discount and no discount dividend reinvestment plans on shareholder wealth. The results show a negative response to DRP announcements, which is significantly smaller than that found in studies of new equity offerings. These results are consistent with the Scholes and Wolfson (1989) hypothesis that managers in need of equity capital use DRPs to mitigate the adverse stock price effects of new equity issue announcements. Furthermore, there is a significant difference in the price response of discount and no discount DRPs for industrial firms. This result is supportive of the signaling potential of discount DRPs. Supportive evidence is also found in the analysis of firm characteristics for industrial firms.     

应该将扩大消费需求提升到国家战略的高度

消费问题经过几十年的讨论,至今仍没有得到一些人的高度重视。重投资,重GDP的增长,不重视消费拉动的老毛病,一直制约着我国经济的可持续发展。事实上,如果我国消费水平再不上一个新台阶,还将制约我国经济的持续发展。应该将扩大消费需求提升到我国发展的战略高度来认识。一、应     

The endless need for regulation in telecommunication: An explanation

Telecommunication services have existed as a legal monopoly nearly throughout its entire history. In 1998, telecom market liberalisation was achieved across the European Union (EU) through the introduction of competition among telephone services. Asymmetrical obligations were deemed necessary in order to compensate the market power of the former monopolist.As the evolution of asymmetrical regulation in Spain illustrates, obligations and the telecommunications operators subject to them increased with the regulatory framework established in 2002 in the EU. This new regulatory framework may continue to expand through the inclusion of functional separation as another possible asymmetrical obligation. In short, it seems that the regulatory pressure on the telecommunications industry is increasing, despite the lapse in time since the liberalisation of the industry.In this paper, a methodology developed by the Austrian School of Economics is applied in order to explain why the telecommunication market is subject to increasing regulation in Europe, rather than deregulation, after more than 10 years of liberalisation. In particular, Mises's theory of price control is used to explain the evolution of the regulation of local loop unbundling.     

AN EVALUATION OF PROCESS‐ORIENTED SUPPLY CHAIN MANAGEMENT FRAMEWORKS

Supply chain management (SCM) is implemented by integrating corporate functions using business processes within and across companies. Several process‐oriented frameworks for SCM have been proposed but only two of these provide sufficient detail to enable implementation. We evaluate the Supply‐Chain Operations Reference (SCOR) framework and The Global Supply Chain Forum (GSCF) framework using four criteria and identify their relative strengths and weaknesses.     

Feature selection methods involving support vector machines for prediction of insolvency in non‐life insurance companies

We propose two novel approaches for feature selection and ranking tasks based on simulated annealing (SA) and Walsh analysis, which use a support vector machine as an underlying classifier. These approaches are inspired by one of the key problems in the insurance sector: predicting the insolvency of a non‐life insurance company. This prediction is based on accounting ratios, which measure the health of the companies. The approaches proposed provide a set of ratios (the SA approach) and a ranking of the ratios (the Walsh analysis ranking) that would allow a decision about the financial state of each company studied. The proposed feature selection methods are applied to the prediction the insolvency of several Spanish non‐life insurance companies, yielding state‐of‐the‐art results in the tests performed. Copyright © 2005 John Wiley & Sons, Ltd.     

Partial Horizontal Inequity Orderings: A Non‐parametric Approach*

We provide a partial ordering view of horizontal inequity (HI), based on the Lorenz criterion, associated with different post‐tax income distributions and a (bistochastic) non‐parametric estimated benchmark distribution. As a consequence, several measures consistent with the Lorenz criterion can be rationalized. In addition, we establish the so‐called HI transfer principle, which imposes a normative minimum requirement that any HI measure must satisfy. Our proposed HI ordering is consistent with this principle. Moreover, we adopt a cardinal view to decompose the total effect of a tax system into a welfare gain caused by HI‐free income redistribution and a welfare loss caused by HI, without any additive decomposable restriction on the indices. Hence, more robust tests can be applied. Other decompositions in the literature are seen as particular cases.     

Statistical Decision Problems and Bayesian Nonparametric Methods

This paper considers parametric statistical decision problems conducted within a Bayesian nonparametric context. Our work was motivated by the realisation that typical parametric model selection procedures are essentially incoherent. We argue that one solution to this problem is to use a flexible enough model in the first place, a model that will not be checked no matter what data arrive. Ideally, one would use a nonparametric model to describe all the uncertainty about the density function generating the data. However, parametric models are the preferred choice for many statisticians, despite the incoherence involved in model checking, incoherence that is quite often ignored for pragmatic reasons. In this paper we show how coherent parametric inference can be carried out via decision theory and Bayesian nonparametrics. None of the ingredients discussed here are new, but our main point only becomes evident when one sees all priors—even parametric ones—as measures on sets of densities as opposed to measures on finite-dimensional parameter spaces.