The role of banks in financial integration: evidence from new EU members

EU enlargement involves the simultaneous liberalisation of goods and financial markets. While the issue of free trade in capital versus goods has frequently been the subject of study in international economics, the emphasis has typically been on physical capital (machines etc) rather than financial capital. This paper considers this distinction in a world with asymmetric information, moral hazard and hence credit rationing, and explores the resulting ambiguous theoretical predictions via an econometric analysis of the entry of the Central and Eastern European Countries to the EU.     

A survey of the Feldstein–Horioka puzzle: What has been done and where we stand

The objective of this paper is to present a survey of the research related to the Feldstein–Horioka puzzle and, in particular, to investigate what economists have learned, which parts of the puzzle have been resolved, which parts remain to be addressed, and where future research is heading. This paper is different from other attempts because it reviews the most recent literature and presents it according to the theoretical and/or empirical approach to the subject. Thus, it can be useful to academics and policy makers who are interested in understanding how and why savings and investment move the way they do.     

On non-revealing rational expectations equilibrium

It is shown that a non-revealing rational expectations equilibrium may not be coalitionally Bayesian incentive compatible, may not be implementable as a perfect Bayesian equilibrium and may not belong to the weak fine core and thus may not be fully Pareto optimal. These negative results lead us to conclude the non-revealing rational expectations equilibrium is not a sensible solution concept. We wish to thank Dr A. Hadjiprocopis for his invaluable help with the implementation of Latex in a Unix environment. We also thank a referee for several, constructive suggestions.     

An Examination of New Product Development Best Practice

Efforts continue to identify new product development (NPD) best practices. Examples of recognized studies include those by the Product Development and Management Association's Comparative Performance Assessment Study and the American Productivity Quality Center NPD best practices study. While these studies designate practices that distinguish top‐performing companies, it is unclear whether NPD practitioners as a group (not just researchers) are knowledgeable about what represents a NPD best practice. The importance of this is that it offers insight into how NPD practitioners are translating potential NPD knowledge into actual NPD practice. In other words, are practitioners aware of and able to implement NPD best practices designated by noteworthy studies? The answer to this question ascertains a current state of the field toward understanding NPD best practice and the maturity level of various practices. Answering this question further contributes to our understanding of the diffusion of NPD best practices knowledge by NPD professionals, possibly identifying gaps between prescribed and actual practice. Beginning the empirical examination by conducting a Delphi methodology with 20 leading innovation researchers, the study examined the likely dimensions of NPD and corresponding definitions to validate the NPD practices framework originally proposed by Kahn, Barczak, and Moss. A survey was then conducted with practitioners from the United States, United Kingdom, and Ireland to gauge opinions about perceptions of the importance of different NPD dimensions, specific characteristics reflected by each of these dimensions, and the level of NPD practice maturity that these characteristics would represent. The study is therefore unique in that it relies on the opinions of NPD practitioners to see what they perceive as best practice versus prior studies where the researcher has identified and prescribed best practices. Results of the present study find that seven NPD dimensions are recommended, whereas the 2006 Kahn, Barczak, and Moss framework had suggested six dimensions. Among practitioners across the three country contexts, there is consensus on which dimensions are more important, providing evidence that NPD dimensions may be generalizable across Western contexts. Strategy was rated higher than any of the other dimensions followed by research, commercialization, and process. Project climate and metrics were perceived as the lowest in importance. The high weighting on strategy and low weighting on metrics and project climate reinforce previous best practice findings. Regarding the characteristics of each best practice dimension, practitioners appear able to distinguish what constitutes poor versus best practice, but consensus on distinguishing middle range practices are not as clear. The suggested implications of these findings are that managers should emphasize strategy when undertaking NPD efforts and consider the fit of their projects with this strategy. The results further imply that there are clearly some poor practices that managers should avoid and best practices to which managers should ascribe. For academics, the results strongly suggest a need to do a better job of diffusing NPD knowledge and research on best practices. Particular attention by academics to the issues of metrics, project climate, and company culture appears warranted.     

Competition and the dispersion of labour productivity amongst UK companies

Based on a sample of 140,000 UK companies over the period 1989–93,this paper finds a wide dispersion of labour productivity acrossfirms. Some dispersion is transitory: amongst surviving companiesthere is regression towards the mean and dispersion faDs overtime. However, there are tignifimnt differences between sectorsin the extent of dispersion, eg. in manufacturing it is around40% lower. A possible explanation is greater competition inmanufacturing. A role for competition is also suggested by thefinding that surviving companies which were initially belowthe mean improve their performance more rapidly than those initiallyabove the mean.     

MCMC maximum likelihood for latent state models

This paper develops a pure simulation-based approach for computing maximum likelihood estimates in latent state variable models using Markov Chain Monte Carlo methods (MCMC). Our MCMC algorithm simultaneously evaluates and optimizes the likelihood function without resorting to gradient methods. The approach relies on data augmentation, with insights similar to simulated annealing and evolutionary Monte Carlo algorithms. We prove a limit theorem in the degree of data augmentation and use this to provide standard errors and convergence diagnostics. The resulting estimator inherits the sampling asymptotic properties of maximum likelihood. We demonstrate the approach on two latent state models central to financial econometrics: a stochastic volatility and a multivariate jump-diffusion models. We find that convergence to the MLE is fast, requiring only a small degree of augmentation.