Jobs requiring a capacity for engineering systems thinking (CEST): Selection using an interest inventory

Systems thinking is recognized as a critical ability for engineers who take a leading role in complex projects. Identifying those engineers with better systems‐thinking capabilities is critical in many projects and organizations and enables organizations and project managers to select and place the most suitable engineers for jobs requiring a Capacity for Engineering Systems Thinking (CEST). However, up until now, no tool aimed at assessing individuals' capacity for engineering systems thinking has ever been developed. This paper presents principles for developing an interest questionnaire aimed at selecting engineers for jobs requiring systems thinking as well as preliminary results regarding the tool's reliability and validity.     

Productivity Gains from Offshore Outsourcing: Evidence from the Chinese Manufacturing Industry

Using the Cobb–Douglas production function and vertical specialization share, the present paper measures the productivity spillover effects of offshore outsourcing in the Chinese manufacturing industry. We examine different production factors and the degree of openness by dividing the Chinese manufacturing industry into five major categories: capital‐intensive business, technological‐intensive business, labor‐intensive business, open business and non‐open business. The results show that offshore outsourcing is positively associated with productivity in the Chinese manufacturing industry as a whole, but less so in labor‐intensive industries and more in capital‐intensive industries. Moreover, the positive impact of outsourcing on productivity is slightly higher in open industries than in non‐open industries. These results shed light on the differential spillover effects of offshore outsourcing on productivity. Our findings suggest that outsourcing structure is important to China's long‐run competitive advantage. China's policy‐makers should encourage further offshore capital‐intensive and technology‐intensive activities and focus more on outward‐oriented offshore businesses.     

Volatility forecasting: combinations of realized volatility measures and forecasting models

This article examines financial time series volatility forecasting performance. Different from other studies which either focus on combining individual realized measures or combining forecasting models, we consider both. Specifically, we construct nine important individual realized measures and consider combinations including the mean, the median and the geometric means as well as an optimal combination. We also apply a simple AR(1) model, an SV model with contemporaneous dependence, an HAR model and three linear combinations of these models. Using the robust forecasting evaluation measures including RMSE and QLIKE, our empirical evidence from both equity market indices and exchange rates suggests that combinations of both volatility measures and forecasting models improve the forecast performance significantly.