Cultural Context of Career Choice: Meta‐Analysis of Race/Ethnicity Differences

The authors focus on career counseling from a cultural perspective, using the proxy construct of race/ethnicity. They briefly describe traditional career counseling and critique the degree to which the myriad cultural contexts that shape clients' career development are incorporated into vocational theories and practice. They conducted a meta‐analysis of research that has investigated the relationship between culture and vocational choice variables and concluded (a) that race/ethnicity differences do not greatly affect career aspirations but (b) that there are differences among racial/ethnic groups in perceptions of career‐related opportunities and barriers.     

Community Economic Development Strategies in Rural Washington: Toward a Synthesis of Natural and Social Capital*

Abstract Routes to economic development attract considerable attention in community and rural sociology. Social scientists draw increasingly on studies of social capital and environmental surroundings as they examine the factors that facilitate and inhibit economic development. However, few empirical analyses exist that analyze the impact of the combination of social infrastructure and natural capital on different forms of economic development such as on industrial recruitment and self‐development. Using data collected from six communities in Washington State, the interaction of a community's social infrastructure and natural capital on industrial recruitment and self‐development efforts is examined. Results suggest that while natural capital positively impacts a community's successful recruitment of outside industries, it is not significant for a community's level of self‐development. However, a community's social infrastructure, measured by the existence of active civic organizations, local businesses that support local community projects, community‐wide fund‐raising capacity, and extra‐local linkages to nearby communities, state, and national agencies, positively affects both industrial recruitment and self‐development. These findings illustrate the need for communities and local activists to carefully weigh their advantages and potential shortcomings when deciding on an economic development strategy.     

Positioning terrorism in management and marketing: Research propositions

Terrorism poses both direct and indirect threats to the operations of the firm. It represents a market imperfection that increases transaction costs and creates barriers to the free flow of goods, affecting potential gains that would occur in the presence of unhindered exchange. Terrorism reflects the risk or actual encounter of violent acts, whose goal is to engender fear, coercion, or intimidation. We investigate terrorism and its association with marketing strategy and operations. Key concepts on terrorism are reviewed and a collection of propositions is offered. We highlight the pivotal roles of sourcing, production, distribution, pricing, communications, and general business strategy as functions influenced by, or capable of influencing, terrorism. Lastly, we offer managerial implications, as well as directions and guidelines for future research.     

Optimal sampling for repeated binary measurements

The authors consider the optimal design of sampling schedules for binary sequence data. They propose an approach which allows a variety of goals to be reflected in the utility function by including deterministic sampling cost, a term related to prediction, and if relevant, a term related to learning about a treatment effect To this end, they use a nonparametric probability model relying on a minimal number of assumptions. They show how their assumption of partial exchangeability for the binary sequence of data allows the sampling distribution to be written as a mixture of homogeneous Markov chains of order k. The implementation follows the approach of Quintana & Müller (2004), which uses a Dirichlet process prior for the mixture.     

Testing the Martingale Difference Hypothesis

In this paper we consider testing that an economic time series follows a martingale difference process. The martingale difference hypothesis has typically been tested using information contained in the second moments of a process, that is, using test statistics based on the sample autocovariances or periodograms. Tests based on these statistics are inconsistent since they cannot detect nonlinear alternatives. In this paper we consider tests that detect linear and nonlinear alternatives. Given that the asymptotic distributions of the considered tests statistics depend on the data generating process, we propose to implement the tests using a modified wild bootstrap procedure. The paper theoretically justifies the proposed tests and examines their finite sample behavior by means of Monte Carlo experiments.