Mixing process-generated data in market sociology

Mixed methods researchers often neglect the methodological discussion on data in general and process-generated data specifically. Assuming that the advantages and disadvantages of surveys, interviews and observations are well-known, the author discusses when and why researchers should prefer process-generated data to research-elicited data in market sociology. The author then compares four different types of process-generated data (aggregated statistical data, business directories, newspaper articles, engineering literature). For each data type, the author (a) describes the data type, (b) illustrates what kind of information researchers can gain from this data type and (c) discusses the draw-backs and limits of the data. The article concludes with a discussion of what one can learn for mixing methods and market sociology from this example and why primary data might be useful as an alternative data source after all.     

The optimal trade-off between interest rate risk and annual return of bond ladders

Bond laddering is a popular fixed-income investment strategy. The main purpose of this paper is to develop a methodology for determining private investors’ most interest rate risk (IRR)-return-efficient investment horizon for bond ladders (BLs), which are virtually free of credit risk. Two IRR measures of a continuously rolling and homogenous BL (CRHBL) are analytically derived under the assumption that interest rates are martingales. The first measure is the modified duration, which assumes a flat term structure of interest rates. However, this assumption is not fully supported by the empirical data and, thus, an additional IRR measure is proposed. Under each of these two measures, the ratios between the annual return in excess of the demand deposit rate and IRR of CRHBLs with different investment horizons are calculated. As expected, CRHBLs with rather low IRR are most risk-return-efficient. The results for the theoretical CRHBLs also apply to “real-world” discrete BLs. Thus, the proposed methodology can help private investors construct IRR-return-efficient discrete BLs.     

How far does evolution take us? Comment on Elinor Ostrom’s: do institutions for collective action evolve?

Elinor Ostrom’s article in this issue suggests that institutions for collective action evolve, highlights parallels between biological and institutional evolution, and describes an hypothetical example of institutional evolution related to an irrigation system. The article is provocative but not definitive in that it does not demonstrate that evolution is more than a metaphor for institutional change and that institutions actually evolve. This commentary unpacks the concept of evolutionary change and evaluates how well various aspects of institutional change fit within this model of change. The analysis supports Ostrom’s contention that evolution is not just a metaphor for institutional change, but also suggests that not all institutional change can be classified as evolutionary. The commentary highlights the need for further conceptual and theoretical development to delineate various forms and processes of institutional change, distinguish between evolutionary and non-evolutionary change, and draw out the consequences of various forms of change.     

Are directors’ dealings informative? Evidence from European stock markets

Are directors’ dealings reports informative for outside investors? We analyze short-term announcement effects for 2782 companies from eight European countries between January 2003 and December 2009. We find significant announcement effects in four out of eight countries after directors’ dealings reports have been disclosed. For most countries, the magnitude of the announcement effect depends on transaction size, firm size, book-to-market ratio, and multiple trades by different insiders on the same trading day. The results are stronger for purchases than for sales. For France, Ireland, and Sweden, we find tentative evidence that the corporate position of an insider is connected to the size of the announcement effect.     

How do different background variables predict learning outcomes?

This article is a part of a research project aimed to find out how different background variables are related to learning outcomes in school subject Sloyd as found in the national evaluation of the Finnish National Board of Education. Results from this larger research project were previously published in this journal, where pupils’ readiness for Self-Regulated Learning were reported. Since then, pupils’ experiences of classroom techniques, attitudes towards the subject, leisure time interests and learning within the two domains of the subject (Technical Domain and Textile Domain, as the subject is usually divided in Finland) have been studied and results have been published in different journals. In this article, a new Structural Equation Model concludes the previous results. The new model highlights two paths of how the use of different learning orientations can predict successful learning outcomes. These paths can be followed using two pedagogical models: the Exploratory Production Approach and the Domain Specific Approach. Experiencing Learner-Centred Learning predicts positive attitudes and success in Exploratory Production activities. Experiencing Collaborative Learning predicts success in domain specific learning outcomes. Success in Exploratory Production predicts successful learning outcomes in both domains. The conclusion is that regulatory knowledge, “why”, is related to production activities and it is processed prior to domain specific knowledge, “what” and “how”. To develop the subject and pedagogy for schools and teacher training, it is not important to follow an approach defined by the domains (technical or textile). It is more important to teach pupils how to manage in the modern technological world and to understand why they need to be able to improve their life-world through Exploratory Production activities.