The Industrial Context of Occupational Mobility: Change in Structure

The neglect of a consideration of history has been a feature of mobility research. ‘History’ affects the results of analyses of social mobility by altering the occupational/industrial structure and by encouraging exchange mobility. Changes in industrial structure are rooted more directly in historical causes and can be seen as more fundamental than changes in occupational structure. Following a substantial review of the secondary literature on changes in industrial and occupational structure in Northern Ireland, loglinear analyses of intra- and intergenerational mobility tables for sociologically-derived cohort generations that incorporate occupational and industrial categories are presented. Structural and inheritance effects for industry are as significant as those for occupation. Given the well-established finding of ‘constant social fludity’ in mobility tables once structural effects are controlled, the inclusion of categorization by industry is necessary in order to reach an accurate understanding of occupational mobility and the role of historical change in mobility.

Northern Ireland:The Development Context

This article provides a contextual framework for the new agenda for development, represented in the economic strategy known as Strategy 2010, and the regional spatial plan known as Shaping Our Future. These are considered in the following two articles. This article begins by setting a perspective on the political economy of Northern Ireland and follows with an outline of the spatial planning process. In conclusion, it raises the key challenges facing attempts to renew the region.

Power-law behaviour, heterogeneity, and trend chasing

Long-range dependence in volatility is one of the most prominent examples in financial market research involving universal power laws. Its characterization has recently spurred attempts to provide some explanations of the underlying mechanism. This paper contributes to this recent line of research by analyzing a simple market fraction asset pricing model with two types of traders---fundamentalists who trade on the price deviation from estimated fundamental value and trend followers whose conditional mean and variance of the trend are updated through a geometric learning process. Our analysis shows that agent heterogeneity, risk-adjusted trend chasing through the geometric learning process, and the interplay of noisy fundamental and demand processes and the underlying deterministic dynamics can be the source of power-law distributed fluctuations. In particular, the noisy demand plays an important role in the generation of insignificant autocorrelations (ACs) on returns, while the significant decaying AC patterns of the absolute returns and squared returns are more influenced by the noisy fundamental process. A statistical analysis based on Monte Carlo simulations is conducted to characterize the decay rate. Realistic estimates of the power-law decay indices and the (FI)GARCH parameters are presented.