Estimation of cost inefficiency in panel data models with firm specific and sub-company specific effects

This paper proposes a dual-level inefficiency model for analysing datasets with a sub-company structure, which permits firm inefficiency to be decomposed into two parts: a component that varies across different sub-companies within a firm (internal inefficiency); and a persistent component that applies across all sub-companies in the same firm (external inefficiency). We adapt the models developed by Kumbhakar and Hjalmarsson (J Appl Econom 10:33–47, 1995) and Kumbhakar and Heshmati (Am J Agric Econ 77:660–674, 1995), making the same distinction between persistent and residual inefficiency, but in our case across sub-companies comprising a firm, rather than over time. The proposed model is important in a regulatory context, where datasets with a sub-company structure are commonplace, and regulators are interested in identifying and eliminating both persistent and sub-company varying inefficiency. Further, as regulators often have to work with small cross-sections, the utilisation of sub-company data can be seen as an additional means of expanding cross-sectional datasets for efficiency estimation. Using an international dataset of rail infrastructure managers we demonstrate the possibility of separating firm inefficiency into its persistent and sub-company varying components. The empirical illustration highlights the danger that failure to allow for the dual-level nature of inefficiency may cause overall firm inefficiency to be underestimated

Satellite-Derived Bathymetry Using Multiple Images: The Alaska North Slope Case Study

Currently, charting data in much of the U.S. Arctic North Slope is inadequate or nonexistent and most of its areas have not been updated since the early-1950s. Although the charting infrastructure is out of date, ship transportation (such as, fishing and transit between the towns) has increased. NOAA conducted a preliminary multibeam survey in 2013 that reached Point Barrow, AK. However, all the Arctic North Slope remained untouched. Previous studies have shown that satellite-derived bathymetry (SDB) is a useful reconnaissance tool in tropical and sub-tropical waters in clear water conditions, especially over sandy seafloor. However, it is very difficult to extract good information over the Arctic using a single satellite image, especially over the U.S. North Slope. The glacial powder from land reduces the water clarity that limits the light penetration depth. Also, this turbidity is not uniform along the coast line and may affect the calculations. In this paper, a new SDB approach was developed that compiles multiple satellite images to extract only areas that were identified clear by comparison (i.e., minimum water clarity change between two satellite images). Preliminary results using Landsat 7 imagery from 1999-2002 and Landsat 8 imagery from 2013 are presented

Open University Learning Analytics dataset

Learning Analytics focuses on the collection and analysis of learners’ data to improve their learning experience by providing informed guidance and to optimise learning materials. To support the research in this area we have developed a dataset, containing data from courses presented at the Open University (OU). What makes the dataset unique is the fact that it contains demographic data together with aggregated clickstream data of students’ interactions in the Virtual Learning Environment (VLE). This enables the analysis of student behaviour, represented by their actions. The dataset contains the information about 22 courses, 32,593 students, their assessment results, and logs of their interactions with the VLE represented by daily summaries of student clicks (10,655,280 entries). The dataset is freely available at https://analyse.kmi.open.ac.uk/open_dataset under a CC-BY 4.0 license

Predicting yields of high priced trimmed beef cuts by means of carcass weight and visual assessments of fat cover and conformation

The total and individual trimmed meat yield of six hind quarter cuts and one fore quarter cut were estimated for 200 carcasses from animals of mixed origin with regard to breed, sex and feeding regimen. The linear models included carcass weight and visual assessment of fatness and conformation by means of seven fat and five conformation classes. Amount of variation accounted for (R2) was the most favourable for total yield (87.3%) and the least favourable for the rib-eye cut (43.5%). Carcass weight contributed to most of the variation accounted for and had a positive effect on the yield for all the cuts. Fat score and conformation score were significant in the models of all cuts and total yield except for the rump, and contributed at least 10 percentage points to the R2-value for the topside, thick flank, loin, rib-eye and fillet. Fat score had a negative effect on trimmed yield of all cuts except for the loin, which could be attributed to less trimming compared to other cuts. Conformation score had positive effects on the yield of all cuts except for the rump (non significant), fillet and thick flank. Fat score had the largest proportional effect (to size of the cut) on topside and thick flank, which both contain significant fat deposits. Conformation score had the largest proportional effect on the loin and rib-eye, which is probably due to the synergistic effect of fatness and conformation on the conformation score in this region. The accuracy of estimation of total yield for the purpose of awarding premiums to yield categories was considered to be good when the residual standard deviation of the estimated yield was compared with the standard deviation of the trial sample. However, separating cuts into different weight categories was less accurate and varied among cuts, which suggests that more information is needed for more reliable models before accurate individual yields of cuts can be predicted in practice. Keywords: Conformation score; fat score; premiums; saleable meat South African Journal of Animal Sciences Vol. 35 (3) 2005: pp.195-20

Nautical Chart Adequacy Evaluation Using Publicly-Available Data

The International Hydrographic Office (IHO) C-55 publication communicates the need to improve the collection, quality and availability of hydrographic data world-wide, while also monitoring and rectifying possible deficiencies and shortcomings that are presented on the chart. This task of evaluating the adequacy of nautical chart products poses a challenge to many national hydrographic offices. This stems from the dearth of readily available spatial information: namely, the lack of reliable and accessible vessel traffic data, and little means to assess the changing nature of both near-shore bathymetry and shoreline in a simple and reliable manner. In this paper, we present the potential use of automatic-identification system (AIS) data, satellite-derived bathymetry (SDB), and airborne-lidar bathymetry (ALB) to provide an operational procedure for evaluating the adequacy and completeness of information of NOAA charts. Preliminary results from three U.S. study sites are presented in this paper: Nantucket Sound, MA; Barnegat Bay Inlet, NJ; and Barataria Bay, LA. Based on the publically-available datasets it was possible to identify changes in the charts and develop a reconnaissance procedure to monitor these changes on a yearly basis

Large-Scale Modelling of the Environmentally-Driven Population Dynamics of Temperate Aedes albopictus (Skuse)

The Asian tiger mosquito, Aedes albopictus, is a highly invasive vector species. It is a proven vector of dengue and chikungunya viruses, with the potential to host a further 24 arboviruses. It has recently expanded its geographical range, threatening many countries in the Middle East, Mediterranean, Europe and North America. Here, we investigate the theoretical limitations of its range expansion by developing an environmentally-driven mathematical model of its population dynamics. We focus on the temperate strain of Ae. albopictus and compile a comprehensive literature-based database of physiological parameters. As a novel approach, we link its population dynamics to globally-available environmental datasets by performing inference on all parameters. We adopt a Bayesian approach using experimental data as prior knowledge and the surveillance dataset of Emilia-Romagna, Italy, as evidence. The model accounts for temperature, precipitation, human population density and photoperiod as the main environmental drivers, and, in addition, incorporates the mechanism of diapause and a simple breeding site model. The model demonstrates high predictive skill over the reference region and beyond, confirming most of the current reports of vector presence in Europe. One of the main hypotheses derived from the model is the survival of Ae. albopictus populations through harsh winter conditions. The model, constrained by the environmental datasets, requires that either diapausing eggs or adult vectors have increased cold resistance. The model also suggests that temperature and photoperiod control diapause initiation and termination differentially. We demonstrate that it is possible to account for unobserved properties and constraints, such as differences between laboratory and field conditions, to derive reliable inferences on the environmental dependence of Ae. albopictus populations

D5.3: Access Charge Final Report. The sustainable freight railway: Designing the freight vehicle – track system for higher delivered tonnage with improved availability at reduced cost (SUSTRAIL)

Document type: Boo