A Bootstrap Likelihood Approach to Bayesian Computation

There is an increasing amount of literature focused on Bayesian computational methods to address problems with intractable likelihood. One approach is a set of algorithms known as Approximate Bayesian Computational (ABC) methods. One of the problems with these algorithms is that their performance depends on the appropriate choice of summary statistics, distance measure and tolerance level. To circumvent this problem, an alternative method based on the empirical likelihood has been introduced. This method can be easily implemented when a set of constraints, related to the moments of the distribution, is specified. However, the choice of the constraints is sometimes challenging. To overcome this difficulty, we propose an alternative method based on a bootstrap likelihood approach. The method is easy to implement and in some cases is actually faster than the other approaches considered. We illustrate the performance of our algorithm with examples from population genetics, time series and stochastic differential equations. We also test the method on a real dataset.     

Women's employment patterns during early parenthood: A group‐based trajectory analysis

Research on women's employment and parenthood frequently focuses on the correlates and consequences of decisions at a particular time, such as a birth. This article applies a group‐based trajectory method to examine women's employment trajectories across the period of early parenthood using the National Longitudinal Survey of Youth 1979 (N= 2,093). We find that throughout early parenthood, women exhibit significant movement into and out of the labor force. Factors that typically predict women's employment status, such as age at first birth and education, are also good predictors of women's employment patterns. We discuss the implications of these findings for future research, particularly on the use of a static measure of women's or couples’ employment status.     

FDI and Technology as Levering Factors of Competitiveness in Developing Countries

Technology creation and absorption are two relevant processes that affect the role that multinational enterprises (MNE) may play in the competitiveness improvement of the developing economies. The importance of internal factors in local contexts, the increasing integration in the industrial international value chain and the access of firms from these countries to diverse external learning sources, constitute a suitable framework for the analysis of competitiveness shift. In this paper, we study how the integration of firms from developing countries in sophisticated high-tech markets can be defined by the combined action of MNE and the ability for technology absorption and creation. Our empirical analysis with panel data shows how the different dimensions of internal and external factors affect international competitiveness in high-tech industries.     

Don’t mention it: Why people don’t share job information,when they do,and why it matters

Network-based job search is especially likely to foster workplace segregation and limit status attainment when information flows through homophilous ties. This paper takes the perspective of information holders and examines how the use of strong versus weak ties – which tend to be homophilous and heterophilous, respectively – differs with characteristics of labour markets in which jobs are located. Using in-depth interviews with entry-level white collar workers I show that information holders with opportunities to mention specific jobs to specific people do so only 27% of the time. Because they hesitate to share information if they are uncertain the information is specifically sought, information flows more commonly to strong ties, whose career goals are more likely to be known. Information is more likely to be shared with weak ties if it concerns occupations for which one may be specifically credentialed, since receiving relevant training serves as signal of interest in such jobs. These finding suggest that the homophily of referrals and their inequality-generating effects may vary across occupations.     

Bank Monitoring and Role of Diversification

I present a framework of banking in which banks’ main role is to monitor their borrowers. Within this framework I analyze the benefits of diversification and the threats of systemic risk and inter-bank competition. Diversification improves banks’ monitoring incentives. High systemic risk not only hampers banks’ monitoring incentives, but also makes diversification less effective. I also show that competition lowers monitoring incentives. I match the insights of the analysis with the abundant literature on the role of banks on the asset-side and provide some implications for recent developments in banking.

Positive Effects of Talking About the Negative: Family Narratives of Negative Experiences and Preadolescents' Perceived Competence

Family narratives about the past are an important context for the socialization of emotion, but relations between expression of negative emotion and children's emerging competence are conflicting. In this study, 24 middle‐class two‐parent families narrated a shared negative experience together and we examined the process (initiations and collaborations) and function (the expression and explanation of emotions) of co‐constructed narratives in relation to preadolescents' perceived competencies and self‐esteem. Family narratives in which specific emotions were expressed and explained in a collaborative fashion, especially negative emotion, were positively related to preadolescents' reported competencies and self‐esteem, whereas family narratives that expressed general positive emotion were negatively related to preadolescents' perceived competencies. Implications of family narratives about emotional events, specifically the ways in which families discuss emotion, in relation to preadolescents' self‐development are discussed.     

Stability of Estimates of the Compensation for Danger

Estimates of the extra earnings for jobs with higher risks of death are used in cost-benefit studies involving risk changes. Because of this use, the magnitude and stability of the estimated coefficient are important. Part of the current study closely reproduces the 1982 study by Marin and Psacharopoulos to check on the stability. We also examine the robustness of the estimate to the inclusion/exclusion of non-fatal risks and other relevant characteristics. While the magnitude of the coefficient has increased from the earlier study, the coefficient is robust to other changes in the specification. This yields a value of life figure of £9.7 million.     

Women's Education,Marital Violence,and Divorce: A Social Exchange Perspective

Drawing on social exchange theories, the authors hypothesized that educated women are more likely than uneducated women to leave violent marriages and suggested that this pattern offsets the negative education–divorce association commonly found in the United States. They tested these hypotheses using 2 waves of young adult data on 914 married women from the National Longitudinal Study of Adolescent Health. The evidence suggests that the negative relationship between women's education and divorce is weaker when marriages involve abuse than when they do not. The authors observed a similar pattern when they examined the association of women's proportional earnings and divorce, controlling for education. Supplementary analyses suggested that marital satisfaction explains some of the association among women's resources, victimization, and divorce but that marital violence continues to be a significant moderator of the education–divorce association. In sum, education appears to benefit women by both maintaining stable marriages and dissolving violent ones.     

Estimation of Variance Components for a Linear Toeplitz Model

The linear Toeplitz covariance structure model of order one is considered. We give some elegant explicit expressions of the Locally Minimum Variance Quadratic Unbiased Estimators of its covariance parameters. We deduce from a Monte Carlo method some properties of their Gaussian maximum likelihood estimators. Finally, for small sample sizes, these two types of estimators are compared with the intuitive empirical estimators and it is shown that the empirical biased estimators should be used.