Extreme value statistics for censored data with heavy tails under competing risks

This paper addresses the problem of estimating, from randomly censored data subject to competing risks, the extreme value index of the (sub)-distribution function associated to one particular cause, in a heavy-tail framework. Asymptotic normality of the proposed estimator is established. This estimator has the form of an Aalen-Johansen integral and is the first estimator proposed in this context. Estimation of extreme quantiles of the cumulative incidence function is then addressed as a consequence. A small simulation study exhibits the performances for finite samples.     

Family businesses and non-family equity: literature review and avenues for future research

Family firms commonly prefer internal funding and retention of control. Under certain circumstances, however, equity investments from outside the family can be a relevant alternative source of capital. To facilitate further knowledge about the interaction of family-owned businesses and external equity investors, the present work reviews 42 studies and suggests possible directions for future research. Results reveal that extant studies focus mainly on five key areas—corporate finance, contract design and collaboration, succession and exit route, strategy and performance, and corporate governance. Moreover, the paper discusses various gaps in the extant work and presents three opportunities for future research in a detailed manner. These include a comparison of different types of investors in the context of family-owned businesses, an investigation of minority investor exits from family firms, and an analysis of the impact of investors on family firm boards. All in all, the findings can guide the future development of this emerging field of research and have implications for theory and practice.     

On Bayesian estimation of seemingly unrelated regressions when some observations are missing

In this paper we have considered the problem of estimating the parameters of two seemingly unrelated regression equations when the number of available observations on all the variables in the first equation exceeds the number of available observations on all the variables in the second equation. We have shown how, within the Bayesian framework, extra observations on all the variables in the first equation can be readily and formally utilized in obtaining the exact or an approximate posterior distributions of all the coefficients including those in the second equation.     

The “Good Cause Norm” in Employment Relations: Empirical Evidence and Policy Implications

Critics of the American employment at-will doctrine have argued that it should be abandoned because it is at odds with a societal level norm that employees should only be discharged for good reasons (the good cause norm). This paper examines the extent to which there is conceptual and empirical support for the existence of such a norm. Theoretical perspectives supporting the norms existence are discussed and integrated, and an interdisciplinary review of relevant research is provided. In light of the support that is found for the existence of a good cause norm in the American workplace, it is proposed that the current employment at-will default rule be changed to a waivable employee right to be discharged for good cause only.     

Social capital effects on the discovery and exploitation of entrepreneurial opportunities

Social capital refers to social networks and the norms of reciprocity, cooperation and trust associated with them. It can be studied at different levels of analysis. As previous literature suggests, social capital has aspects at both the individual and collective levels. However, theory development and empirical research have focused on separate, sometimes diverging levels. In an attempt to address this, this research examines the simultaneous influence of individual and regional social capital on the discovery and exploitation of entrepreneurial opportunities using individual-level data from the Global Entrepreneurship Monitor linked with regional-level data on social capital. The results show that individuals from regions with higher social capital are more likely to discover and to exploit entrepreneurial opportunities. Moreover, individuals having networks with other entrepreneurs are also more likely to identify a business opportunity and to become an entrepreneur. Also, we found that social capital at individual level had a greater effect than social capital at regional level in the two stages of the entrepreneurial process.