Job Turnover in Irish Manufacturing 1976 -2006

While growth in output and employment remains relatively strong in the Irish economy, there has been considerable focus recently on some high-profile job losses, particularly in the manufacturing sector. This paper places these developments within a broader context and shows that aggregate changes in the net number of jobs arise from large numbers of firms both increasing and decreasing employment simultaneously at all points in time. Even at the height of the Celtic Tiger boom when employment grew by 8 percent, this was the result of 15 percent growth in jobs by expanding firms offset by 7 percent of positions being eliminated in firms that were contracting their workforces. One important feature of job flows is that they may contribute to productivity growth by allowing movements from low to high productivity firms. To a degree, this reflects the re-allocation of jobs from declining sectors to expanding sectors, but this is not a comprehensive explanation. A significant factor underlying job flows is the reallocation within sectors from under-performing firms to expanding firms. This study also shows that productivity growth is, on balance, positive for employment growth, as it results, more often than not, in increased employment and higher earnings rather than job losses. On the other hand, these calculations also show how hard it is for policy-makers to identify firms that will be employment and productivity growth winners.

Job Turnover in Irish Manufacturing 1972–2006

With the recent slowdown in global economic growth, there has been considerable focus in Ireland on some high-profile job losses, particularly in the manufacturing sector. This paper places such developments into a broader context and shows that aggregate changes in the net number of jobs arise from large numbers of firms both increasing and decreasing employment simultaneously at all points in time. Even at the height of the Celtic Tiger boom when employment grew by 8 per cent, this was the result of 15 per cent growth in jobs by expanding firms offset by 7 per cent of positions being eliminated in contracting firms. One important feature of job flows is that they may contribute to productivity growth by allowing movements from low to high productivity firms. To a degree, this reflects the re-allocation of jobs from declining sectors to expanding sectors, but this is not a comprehensive explanation. A significant factor underlying job flows is the reallocation within sectors from under-performing firms to expanding firms. This study also shows that productivity growth is, on balance, positive for employment growth. On the other hand, these calculations also show how hard it is for policymakers to identify firms that will be employment and productivity growth winners.

Professional Fees and Other Direct Costs in Chapter 7 Business Liquidations

Here we provide a comprehensive look at direct costs associated with chapter 7 business bankruptcy liquidations by examining cases from five geographically dispersed judicial districts. This Article measures chapter 7 direct costs, which are essentially out-of-pocket administrative costs associated with chapter 7 proceedings. Examples of direct costs include attorneys\u27 fees, filing fees, and other professional fees. Part II describes the procedures we followed in gathering data. Part II also sets forth several assumptions we made when describing direct costs. Each time an assumption needed to be made, we took the assumption that produced the lowest bankruptcy costs. Accordingly, the data in this Article is a conservative estimate of chapter 7 costs. Part III describes the characteristics of the debtors and cases in our sample. Part IV discusses the actual cost measurements and quantifies the costs of chapter 7 business bankruptcy. Part V uses statistical analysis to identify determinants of chapter 7 costs. Part VI summarizes our major conclusions

An idealized study of coupled atmosphere-ocean 4D-Var in the presence of model error

Atmosphere only and ocean only variational data assimilation (DA) schemes are able to use window lengths that are optimal for the error growth rate, non-linearity and observation density of the respective systems. Typical window lengths are 6-12 hours for the atmosphere and 2-10 days for the ocean. However, in the implementation of coupled DA schemes it has been necessary to match the window length of the ocean to that of the atmosphere, which may potentially sacrifice the accuracy of the ocean analysis in order to provide a more balanced coupled state. This paper investigates how extending the window length in the presence of model error affects both the analysis of the coupled state and the initialized forecast when using coupled DA with differing degrees of coupling. Results are illustrated using an idealized single column model of the coupled atmosphere-ocean system. It is found that the analysis error from an uncoupled DA scheme can be smaller than that from a coupled analysis at the initial time, due to faster error growth in the coupled system. However, this does not necessarily lead to a more accurate forecast due to imbalances in the coupled state. Instead coupled DA is more able to update the initial state to reduce the impact of the model error on the accuracy of the forecast. The effect of model error is potentially most detrimental in the weakly coupled formulation due to the inconsistency between the coupled model used in the outer loop and uncoupled models used in the inner loop

Bayes linear kinematics in the analysis of failure rates and failure time distributions

Collections of related Poisson or binomial counts arise, for example, from a number of different failures in similar machines or neighbouring time periods. A conventional Bayesian analysis requires a rather indirect prior specification and intensive numerical methods for posterior evaluations. An alternative approach using Bayes linear kinematics in which simple conjugate specifications for individual counts are linked through a Bayes linear belief structure is presented. Intensive numerical methods are not required. The use of transformations of the binomial and Poisson parameters is proposed. The approach is illustrated in two examples, one involving a Poisson count of failures, the other involving a binomial count in an analysis of failure times

Progressing gender equality in fisheries by building strategic partnerships with development organisations

Gender equality, a universal agreed principle and value, has been adopted widely but implemented to varying levels in different sectors. Our study was designed to contrast how development and fisheries sectors view and invest in gender, and then explore opportunities to strengthen collaborative relationships and networks between the two, with the aim of improving capacity for gender inclusion in practice in fisheries. We conducted key informant interviews with fisheries (n=68) and development (n=32) practitioners (including managers) in Fiji, Solomon Islands and Vanuatu between 2018 and 2019. We found three points of divergence between fisheries and development practitioners and/or their organisations when it comes to the inclusion of gender into their work: (1) fundamental differences in organisational motivations for working on gender ‒ (i.e., fisheries organisations viewed gender equality as a means to achieve fisheries objectives (instrumental), while development organisations viewed it as a core value or principle (inherent); (2) fisheries practitioners had comparatively little to no access to qualified gender focal points and training, and limited networks with gender experts; and (3) differences in what each considered successful versus failed approaches to gender integration. Our findings illustrate opportunities, as well as limitations or challenges (e.g. resistance and indifference), to transfer knowledge and capacity to integrate gender into fisheries policies and practice. We suggest using these divergences to ‘pivot change’ in the fisheries sector by building on decades of knowledge, learning and experience from the development sector focusing on four areas for strategic partnership: (1) shifting values; (2) gender mainstreaming; (3) adopting gender best practice; and (4) investing in gender networks and coalitions. We argue that fundamental to the success of such a partnership will be the ability and willingness of fisheries and development practitioners and their organisations to break down silos and work collaboratively towards gender equality in the fisheries sector

Solomon Islands: Western Province situation analysis

Aquatic agricultural systems (AAS) are places where farming and fishing in freshwater and/orscoastal ecosystems contribute significantly to household income and food security. Globally, theslivelihoods of many poor and vulnerable people are dependent on these systems. In recognitionsof the importance of AAS, the CGIAR Research Program (CRP) is undertaking a new generationsof global agricultural research programs on key issues affecting global food security and ruralsdevelopment. The overall goal of the research program is to improve the well-being of peoplesdependent on these systems. Solomon Islands is one of five priority countries in the AAS program,sled by WorldFish. In Solomon Islands, the AAS program operates in the Malaita Hub (MalaitasProvince) and the Western Hub (Western Province). This program and its scoping activities aressummarized in this report

Analysis of hydration and subchondral bone density on the viscoelastic properties of bovine articular cartilage.

Funding JC is currently funded by an Engineering and Physical Sciences Research Council scholarship (EP/N509590/1). We are also grateful to Arthritis Research UK for the award of a PhD studentship to Anna A. Cederlund (Grant number 19971). The materials and testing equipment used in this study was funded by an Arthritis Research UK grant (H0671). The Engineering and Physical Sciences Research Council and Arthritis Research UK (now part of Versus Arthritis) had no role in the design of the study and collection, analysis and interpretation of data and in writing the manuscript.Peer reviewedPublisher PD