The contingent value of marketing strategy innovativeness for product development performance in Chinese new technology ventures

This study extends research on entrepreneurial behavior by investigating the relationship between the marketing strategy innovativeness (MSI) and new product performance in technology-based new ventures in China. Specifically, premised on contingent resource-based view we argue that MSI is a firm capability that must be bundled with external managerial relationships and be deployed in the appropriate environment to ensure its success. We found that the team's extra industry relationships and market dynamism enhanced the impact of MSI on new product performance. In contrast, top management team's intraindustry relationships, financial relationships, and technology dynamism hindered the impact of MSI on new product performance.     

Regulating Banks through Market Discipline: A Survey of the Issues

Abstract.  The interest in the application of market discipline to regulate the financial industry has boomed recently due to the proposed New Capital Accord. This paper reviews the potential role market discipline can play in financial regulation. We start with a discussion of the rationale for financial regulation and with a brief history of the current regulatory mechanisms. Next, a definition of market discipline as a regulatory mechanism is advanced. We evaluate the disciplining power various market participants have. Finally, we argue that more external risk management disclosure is a condition sine qua non in order to enable market discipline as a regulatory mechanism. In this respect, the Basle Committee has taken the right approach.     

Fitting dynamic factor models to non-stationary time series

Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional dimensionality. This is done by explaining common co-movements in the panel through the existence of a small number of common components, up to some idiosyncratic behaviour of each individual series. To capture serial correlation in the common components, a dynamic structure is used as in traditional (uni- or multivariate) time series analysis of second order structure, i.e. allowing for infinite-length filtering of the factors via dynamic loadings. In this paper, motivated from economic data observed over long time periods which show smooth transitions over time in their covariance structure, we allow the dynamic structure of the factor model to be non-stationary over time by proposing a deterministic time variation of its loadings. In this respect we generalize the existing recent work on static factor models with time-varying loadings as well as the classical, i.e. stationary, dynamic approximate factor model. Motivated from the stationary case, we estimate the common components of our dynamic factor model by the eigenvectors of a consistent estimator of the now time-varying spectral density matrix of the underlying data-generating process. This can be seen as a time-varying principal components approach in the frequency domain. We derive consistency of this estimator in a “double-asymptotic” framework of both cross-section and time dimension tending to infinity. The performance of the estimators is illustrated by a simulation study and an application to a macroeconomic data set.