Compensating Wage Differentials for Mandatory Overtime

Our paper estimates the extent to which employees are compensated for an unfavorable job characteristic, being required to accept mandatory assignment of overtime, by receiving higher straight-time wages. Our estimating equations are derived from a model in which wage rates and the existence of mandatory assignment of overtime are jointly determined in the market by the interaction of employee and employer preferences. While - on average, we do not observe the existence of a compensating wage differential for mandatory overtime, we do observe the existence of such differentials for unionized workers and workers with only a few years experience at a firm. Given any estimated compensating wage differential for an unfavorable working condition, one must decide whether its magnitude is sufficiently large to allow one to conclude that the differential fully compensates workers for the disutility of being subject to the unfavorable working condition. We develop and illustrate a methodology that can be used to answer this question, at least for the case of mandatory overtime provisions and other rules that restrict employees' choice of hours.

Compliance with the Overtime Pay Provisions of the Fair Labor Standards Act

Our paper presents a methodology that can be used to estimate the extent of noncompliance with the overtime pay provisions of the Fair Labor Standards Act (FLSA). The methodology is applied to data from the May 1978 Current Population Survey and the 1977 Michigan Quality of Employment Survey. These data suggest that the fraction of covered workers working overtime who fail to receive a premium of at least time and a half, as called for by the legislation, is in the range of 25 percent. They also suggest that the extent of noncompliance is greater in those industries in which size class exemptions to the legislation exist (retail trade and selected service industries). Finally, probit analyses of the determinants of noncompliance suggest that decisions about whether to comply with the overtime provisions of the FLSA are at least partially based on the associated benefits and costs.

A near real-time algorithm for flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management and flood forecasting. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, classifying 89% of flooded pixels correctly, with an associated false positive rate of 6%. Of the urban water pixels visible to TerraSAR-X, 75% were correctly detected, with a false positive rate of 24%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 57% and 18% respectively

DISTRIBUTION CHOICE UNDER NULL PRIORS AND SMALL SAMPLE SIZE

Defining appropriate probability distributions for the variables in an economic model is an important and often arduous task. This paper evaluates the performance of several common probability distributions under different distributional assumptions when sample sizes are small and there is limited information about the data.Research Methods/ Statistical Methods,

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy. The accuracy was reduced in urban areas partly because of TerraSAR-X’s restricted visibility of the ground surface due to radar shadow and layover

Stochastic Optimization: An Application to Sub-Arctic Dairy Farming

The paper demonstrates how a deterministic farm linear programming (LP) model can be made stochastic and simulated using Solver and Simetar© in Excel©. The demonstration is conducted with an LP-model for a dairy farm for a sub arctic region of Norway. The income risks arising from variation in milk and crop yields due to winter damage in leys and pastures have been quantified for farms demonstrating low, medium and high forage yield risk. The estimated distribution of farm profit will be skewed to the left, indicating a downside risk. In the presence of risks, farmers maximize income by producing the milk quota with using surplus forage for meat production. The analysis demonstrated here may assist farmers and farm managers in improving sensitivity analysis for risky variables in farm LP models.dairy production, Northern Norway, stochastic optimization, stochastic simulation, yield risks, Livestock Production/Industries,

Sequential epiretinal membrane removal with internal limiting membrane peeling in brilliant blue G-assisted macular surgery

Purpose To assess the selectivity of brilliant blue G (BBG) staining by analysing the morphological components of unstained and stained tissue obtained during epiretinal membrane (ERM) removal with internal limiting membrane (ILM) peeling in BBG-assisted macular surgery. Methods Twenty-six surgical specimens were removed from 13 eyes with epiretinal gliosis during vitrectomy using BBG for ERM and ILM peeling. We included eyes with idiopathic macular pucker, idiopathic macular hole and vitreomacular traction syndrome. The dye was injected into the fluid-filled globe. Unstained and stained epiretinal tissue was harvested consecutively and placed into separate containers. All specimens were processed for conventional transmission electron microscopy. Results The first surgical specimen of all eyes showed no intraoperative staining with BBG and corresponded to masses of cells and collagen. The second surgical specimen demonstrated good staining characteristics and corresponded to the ILM in all patients included. In seven eyes, the ILM specimens were seen with minor cell proliferations such as single cells or a monolayer of cells. Myofibroblasts, fibroblasts and astrocytes were present. In five cases, native vitreous collagen fibrils were found at the ILM. In six of the eyes, ILM specimens were blank. Conclusion Our clinicopathological correlation underlines the selective staining properties of BBG. The residual ILM is selectively stained by BBG even when a small amount of cells and collagen adheres to its vitreal side. To reduce the retinal exposure to the dye, the surgeon might choose to remove the ERM without using the dye, followed by a BBG injection to identify residual ILM