962 resultados para Lower cost
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This study of the wholesale electricity market compares the efficiency performance of the auction mechanism currently in place in U.S. markets with the performance of a proposed mechanism. The analysis highlights the importance of considering strategic behavior when comparing different institutional systems. We find that in concentrated markets, neither auction mechanism can guarantee an efficient allocation. The advantage of the current mechanism increases with increased price competition if market demand is perfectly inelastic. However, if market demand has some responsiveness to price, the superiority of the current auction with respect to efficiency is not that obvious. We present a case where the proposed auction outperforms the current mechanism on efficiency even if all offers reflect true production costs. We also find that a market designer might face a choice problem with a tradeoff between lower electricity cost and production efficiency. Some implications for social welfare are discussed as well.
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In this paper we use the 2004-05 Annual Survey of Industries data to estimate the levels of cost efficiency of Indian manufacturing firms in the various states and also get state level measures of industrial organization (IO) efficiency. The empirical results show the presence of considerable cost inefficiency in a majority of the states. Further, we also find that, on average, Indian firms are too small. Consolidating them to attain the optimal scale would further enhance efficiency and lower average cost.
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This study of the wholesale electricity market compares the cost-minimizing performance of the auction mechanism currently in place in U.S. markets with the performance of a proposed replacement. The current mechanism chooses an allocation of contracts that minimizes a fictional cost calculated using pay-as-offer pricing. Then suppliers are paid the market clearing price. The proposed mechanism uses the market clearing price in the allocation phase as well as in the payment phase. In concentrated markets, the proposed mechanism outperforms the current mechanism even when strategic behavior by suppliers is taken into account. The advantage of the proposed mechanism increases with increased price competition.
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The relative merits of PBSCT versus BMT for children with standard and high risk hematologic malignancies remain unclear. In a retrospective single center study, we compared allogeneic peripheral blood stem cell transplantation (PBSCT) (n=30) with bone marrow transplantation (BMT) (n=110) in children with acute leukemia. We studied recipients of HLA matched sibling stem cells, and of stem cells from alternative donors (HLA mismatched and/or unrelated) and determined whether sourcing the stem cells from PB or marrow affected engraftment, incidence of acute and chronic GvHD, and disease-free survival at 1 year. Our results show a modest reduction in time to engraftment from PB stem cells and no greater risk of GvHD, but illustrate that the severity of the underlying disease is by far the greatest determinant of 1 year survival. Patients in the BMT group had a higher treatment success rate and lower costs than the recipients of the PBSCT within the standard but not the high risk disease group, where the treatment success rate and the cumulative costs were lower in the PBSCT group compared to the BMT group. Our current incremental cost-effectiveness ratio and analysis of uncertainty suggest that allogeneic transplantation of bone marrow grafts was a more cost-effective treatment option compared to peripheral blood stem cells in patients with standard risk childhood acute leukemia disease. For high risk disease our data are less prescriptive, since the differences were more limited and the range of costs much larger. Neither option demonstrated a clear advantage from a cost-effectiveness standpoint.^
The determinants of improvements in health outcomes and of cost reduction in hospital inpatient care
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This study aims to address two research questions. First, ‘Can we identify factors that are determinants both of improved health outcomes and of reduced costs for hospitalized patients with one of six common diagnoses?’ Second, ‘Can we identify other factors that are determinants of improved health outcomes for such hospitalized patients but which are not associated with costs?’ The Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS) database from 2003 to 2006 was employed in this study. The total study sample consisted of hospitals which had at least 30 patients each year for the given diagnosis: 954 hospitals for acute myocardial infarction (AMI), 1552 hospitals for congestive heart failure (CHF), 1120 hospitals for stroke (STR), 1283 hospitals for gastrointestinal hemorrhage (GIH), 979 hospitals for hip fracture (HIP), and 1716 hospitals for pneumonia (PNE). This study used simultaneous equations models to investigate the determinants of improvement in health outcomes and of cost reduction in hospital inpatient care for these six common diagnoses. In addition, the study used instrumental variables and two-stage least squares random effect model for unbalanced panel data estimation. The study concluded that a few factors were determinants of high quality and low cost. Specifically, high specialty was the determinant of high quality and low costs for CHF patients; small hospital size was the determinant of high quality and low costs for AMI patients. Furthermore, CHF patients who were treated in Midwest, South, and West region hospitals had better health outcomes and lower hospital costs than patients who were treated in Northeast region hospitals. Gastrointestinal hemorrhage and pneumonia patients who were treated in South region hospitals also had better health outcomes and lower hospital costs than patients who were treated in Northeast region hospitals. This study found that six non-cost factors were related to health outcomes for a few diagnoses: hospital volume, percentage emergency room admissions for a given diagnosis, hospital competition, specialty, bed size, and hospital region.^
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Preventable Hospitalizations (PHs) are hospitalizations that can be avoided with appropriate and timely care in the ambulatory setting and hence are closely associated with primary care access in a community. Increased primary care availability and health insurance coverage may increase primary care access, and consequently may be significantly associated with risks and costs of PHs. Objective. To estimate the risk and cost of preventable hospitalizations (PHs); to determine the association of primary care availability and health insurance coverage with the risk and costs of PHs, first alone and then simultaneously; and finally, to estimate the impact of expansions in primary care availability and health insurance coverage on the burden of PHs among non-elderly adult residents of Harris County. Methods. The study population was residents of Harris County, age 18 to 64, who had at least one hospital discharge in a Texas hospital in 2008. The primary independent variables were availability of primary care physicians, availability of primary care safety net clinics and health insurance coverage. The primary dependent variables were PHs and associated hospitalization costs. The Texas Health Care Information Collection (THCIC) Inpatient Discharge data was used to obtain information on the number and costs of PHs in the study population. Risk of PHs in the study population, as well as average and total costs of PHs were calculated. Multivariable logistic regression models and two-step Heckman regression models with log-transformed costs were used to determine the association of primary care availability and health insurance coverage with the risk and costs of PHs respectively, while controlling for individual predisposing, enabling and need characteristics. Predicted PH risk and cost were used to calculate the predicted burden of PHs in the study population and the impact of expansions in primary care availability and health insurance coverage on the predicted burden. Results. In 2008, hospitalized non-elderly adults in Harris County had 11,313 PHs and a corresponding PH risk of 8.02%. Congestive heart failure was the most common PH. PHs imposed a total economic burden of $84 billion at an average of $7,449 per PH. Higher primary care safety net availability was significantly associated with the lower risk of PHs in the final risk model, but only in the uninsured. A unit increase in safety net availability led to a 23% decline in PH odds in the uninsured, compared to only a 4% decline in the insured. Higher primary care physician availability was associated with increased PH costs in the final cost model (β=0.0020; p<0.05). Lack of health insurance coverage increased the risk of PH, with the uninsured having 30% higher odds of PHs (OR=1.299; p<0.05), but reduced the cost of a PH by 7% (β=-0.0668; p<0.05). Expansions in primary care availability and health insurance coverage were associated with a reduction of about $1.6 million in PH burden at the highest level of expansion. Conclusions. Availability of primary care resources and health insurance coverage in hospitalized non-elderly adults in Harris County are significantly associated with the risk and costs of PHs. Expansions in these primary care access factors can be expected to produce significant reductions in the burden of PHs in Harris County.^
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Objectives: This study included two overarching objectives. Through a systematic review of the literature published between 1990 and 2012, the first objective aimed to assess whether insuring the uninsured would result in higher costs compared to insuring the currently insured. Studies that quantified the actual costs associated with insuring the uninsured in the U.S. were included. Based upon 2009 data from the Medical Expenditure Panel Survey (MEPS), the second objective aimed to assess and compare the self-reported health of populations with four different insurance statuses. The second part of this study involved a secondary data analysis of both currently insured and currently uninsured individuals who participated in the MEPS in 2009. The null hypothesis was that there were no differences across the four categories of health insurance status for self-reported health status and healthcare service use. The alternative hypothesis was that were differences across the four categories of health insurance status for self-reported health status and healthcare service use. Methods: For the systematic review, three databases were searched using search terms to identify studies that actually quantified the cost of insuring the uninsured. Thirteen studies were selected, discussed, and summarized in tables. For the secondary data analysis of MEPS data, this study compared four categories of health insurance status: (1) currently uninsured persons who will become eligible for Medicaid under the Patient Protection and Affordable Care Act (PPACA) healthcare reforms in 2014; (2) currently uninsured persons who will be required to buy private insurance through the PPACA health insurance exchanges in 2014; (3) persons currently insured under Medicaid or SCHIP; and (4) persons currently insured with private insurance. The four categories were compared on the basis of demographic information, health status information, and health conditions with relatively high prevalence. Chi-square tests were run to determine if there were differences between the four groups in regard to health insurance status and health status. With some exceptions, the two currently insured groups had worse self-reported health status compared to the two currently uninsured groups. Results: The thirteen studies that met the inclusion criteria for the systematic review included: (1) three cost studies from 1993, 1995, and 1997; (2) four cost studies from 2001, 2003, and 2004; (3) one study of disabilities and one study of immigrants; (4) two state specific studies of uninsured status; and (5) two current studies of healthcare reform. Of the thirteen studies reviewed, four directly addressed the study question about whether insuring the uninsured was more or less expensive than insuring the currently insured. All four of the studies provided support for the study finding that the cost of insuring the uninsured would generally not be higher than insuring those already insured. One study indicated that the cost of insuring the uninsured would be less expensive than insuring the population currently covered by Medicaid, but more expensive to insure than the populations of those covered by employer-sponsored insurance and non-group private insurance. While the nine other studies included in the systematic review discussed the costs associated with insuring the uninsured population, they did not directly compare the costs of insuring the uninsured population with the costs associated with insuring the currently insured population. For the MEPS secondary data analysis, the results of the chi-square tests indicated that there were differences in the distribution of disease status by health insurance status. As anticipated, with some exceptions, the uninsured reported lower rates of disease and healthcare service use. However, for the variable attention deficit disorder, the uninsured reported higher disease rates than the two insured groups. Additionally, for the variables high blood pressure, high cholesterol, and joint pain, the currently insured under Medicaid or SCHIP group reported a lower rate of disease than the two currently insured groups. This result may be due to the lower mean age of the currently insured under Medicaid or SCHIP group. Conclusion: Based on this study, with some exceptions, the costs for insuring the uninsured should not exceed healthcare-related costs for insuring the currently uninsured. The results of the systematic review indicated that the U.S. is already paying some of the costs associated with insuring the uninsured. PPACA will expand health insurance coverage to millions of Americans who are currently uninsured, as the individual mandate and insurance market reforms will require. Because many of the currently uninsured are relatively healthy young persons, the costs associated with expanding insurance coverage to the uninsured are anticipated to be relatively modest. However, for the purposes of construing these results, it is important to note that once individuals obtain insurance, it is anticipated that they will use more healthcare services, which will increase costs. (Abstract shortened by UMI.)^
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Information about the computational cost of programs is potentially useful for a variety of purposes, including selecting among different algorithms, guiding program transformations, in granularity control and mapping decisions in parallelizing compilers, and query optimization in deductive databases. Cost analysis of logic programs is complicated by nondeterminism: on the one hand, procedures can return múltiple Solutions, making it necessary to estímate the number of solutions in order to give nontrivial upper bound cost estimates; on the other hand, the possibility of failure has to be taken into account while estimating lower bounds. Here we discuss techniques to address these problems to some extent.
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The research in this thesis is related to static cost and termination analysis. Cost analysis aims at estimating the amount of resources that a given program consumes during the execution, and termination analysis aims at proving that the execution of a given program will eventually terminate. These analyses are strongly related, indeed cost analysis techniques heavily rely on techniques developed for termination analysis. Precision, scalability, and applicability are essential in static analysis in general. Precision is related to the quality of the inferred results, scalability to the size of programs that can be analyzed, and applicability to the class of programs that can be handled by the analysis (independently from precision and scalability issues). This thesis addresses these aspects in the context of cost and termination analysis, from both practical and theoretical perspectives. For cost analysis, we concentrate on the problem of solving cost relations (a form of recurrence relations) into closed-form upper and lower bounds, which is the heart of most modern cost analyzers, and also where most of the precision and applicability limitations can be found. We develop tools, and their underlying theoretical foundations, for solving cost relations that overcome the limitations of existing approaches, and demonstrate superiority in both precision and applicability. A unique feature of our techniques is the ability to smoothly handle both lower and upper bounds, by reversing the corresponding notions in the underlying theory. For termination analysis, we study the hardness of the problem of deciding termination for a speci�c form of simple loops that arise in the context of cost analysis. This study gives a better understanding of the (theoretical) limits of scalability and applicability for both termination and cost analysis.
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By analysing the dynamic principles of the human gait, an economic gait‐control analysis is performed, and passive elements are included to increase the energy efficiency in the motion control of active orthoses. Traditional orthoses use position patterns from the clinical gait analyses (CGAs) of healthy people, which are then de‐normalized and adjusted to each user. These orthoses maintain a very rigid gait, and their energy cosT is very high, reducing the autonomy of the user. First, to take advantage of the inherent dynamics of the legs, a state machine pattern with different gains in eachstate is applied to reduce the actuator energy consumption. Next, different passive elements, such as springs and brakes in the joints, are analysed to further reduce energy consumption. After an off‐line parameter optimization and a heuristic improvement with genetic algorithms, a reduction in energy consumption of 16.8% is obtained by applying a state machine control pattern, and a reduction of 18.9% is obtained by using passive elements. Finally, by combining both strategies, a more natural gait is obtained, and energy consumption is reduced by 24.6%compared with a pure CGA pattern.
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Young birds and mammals frequently solicit food by means of extravagant and apparently costly begging displays. Much attention has been devoted to the idea that these displays are honest signals of need, and that their apparent cost serves to maintain their honesty. Recent analyses, however, have shown that the cost needed to maintain a fully informative, honest signal may often be so great that both offspring (signaler) and parent (receiver) would do better to refrain from communication. This apparently calls into question the relevance of the costly signaling hypothesis. Here, I show that this argument overlooks the impact of sibling competition. When multiple signalers must compete for the attention of a receiver (as is commonly the case in parent–offspring interactions), I show that (all other things being equal) individual equilibrium signal costs will typically be lower. The greater the number of competitors, the smaller the mean cost, though the maximum level of signal intensity employed by very needy signalers may actually increase with the number of competitors. At the same time, costs become increasingly sensitive to relatedness among signalers as opposed to relatedness between signalers and receivers. As a result of these trends, signaling proves profitable for signalers under a much wider range of conditions when there is competition (though it is still likely to be unprofitable for receivers).
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The Iterative Closest Point algorithm (ICP) is commonly used in engineering applications to solve the rigid registration problem of partially overlapped point sets which are pre-aligned with a coarse estimate of their relative positions. This iterative algorithm is applied in many areas such as the medicine for volumetric reconstruction of tomography data, in robotics to reconstruct surfaces or scenes using range sensor information, in industrial systems for quality control of manufactured objects or even in biology to study the structure and folding of proteins. One of the algorithm’s main problems is its high computational complexity (quadratic in the number of points with the non-optimized original variant) in a context where high density point sets, acquired by high resolution scanners, are processed. Many variants have been proposed in the literature whose goal is the performance improvement either by reducing the number of points or the required iterations or even enhancing the complexity of the most expensive phase: the closest neighbor search. In spite of decreasing its complexity, some of the variants tend to have a negative impact on the final registration precision or the convergence domain thus limiting the possible application scenarios. The goal of this work is the improvement of the algorithm’s computational cost so that a wider range of computationally demanding problems from among the ones described before can be addressed. For that purpose, an experimental and mathematical convergence analysis and validation of point-to-point distance metrics has been performed taking into account those distances with lower computational cost than the Euclidean one, which is used as the de facto standard for the algorithm’s implementations in the literature. In that analysis, the functioning of the algorithm in diverse topological spaces, characterized by different metrics, has been studied to check the convergence, efficacy and cost of the method in order to determine the one which offers the best results. Given that the distance calculation represents a significant part of the whole set of computations performed by the algorithm, it is expected that any reduction of that operation affects significantly and positively the overall performance of the method. As a result, a performance improvement has been achieved by the application of those reduced cost metrics whose quality in terms of convergence and error has been analyzed and validated experimentally as comparable with respect to the Euclidean distance using a heterogeneous set of objects, scenarios and initial situations.
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Thesis (Ph.D.)--University of Washington, 2016-06
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This study employs stochastic frontier analysis to analyze Malaysian commercial banks during 1996-2002, and particularly focuses on determining the impact of Islamic banking on performance. We derive both net and gross efficiency estimates, thereby demonstrating that differences in operating characteristics explain much of the difference in costs between Malaysian banks. We also decompose productivity change into efficiency, technical, and scale change using a generalised Malmquist productivity index. On average, Malaysian banks experience moderate scale economies and annual productivity change of 2.68 percent, with the latter driven primarily by technical change, which has declined over time. Our gross efficiency estimates suggest that Islamic banking is associated with higher input requirements. However, our productivity estimates indicate that full-fledged Islamic banks have overcome some of these cost disadvantages with rapid technical change, although this is not the case for conventional banks operating Islamic windows. Merged banks are found to have higher input usage and lower productivity change, suggesting that bank mergers have not contributed positively to bank performance. Finally, our results suggest that while the East Asian financial crisis had a short-term cost-reducing effect in 1998, the crisis triggered a more lasting negative impact by increasing the volume of non-performing loans.
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This study employs Stochastic Frontier Analysis (SFA) to analyse Malaysian commercial banks during 1996–2002, and particularly focuses on determining the impact of Islamic banking on performance. We derive both net and gross efficiency estimates, thereby demonstrating that differences in operating characteristics explain much of the difference in costs between Malaysian banks. We also decompose productivity change into efficiency, technical, and scale change using a generalized Malmquist productivity index. On average, Malaysian banks experience moderate scale economies and annual productivity change of 2.68%, with the latter driven primarily by Technical Change (TC), which has declined over time. Our gross efficiency estimates suggest that Islamic banking is associated with higher input requirements. However, our productivity estimates indicate that full-fledged Islamic banks have overcome some of these cost disadvantages with rapid TC, although this is not the case for conventional banks operating Islamic windows. Merged banks are found to have higher input usage and lower productivity change, suggesting that bank mergers have not contributed positively to bank performance. Finally, our results suggest that while the East Asian financial crisis had a short-term costreducing effect in 1998, the crisis triggered a long-lasting negative impact by increasing the volume of nonperforming loans.