Estimation Of Cost Function Research Articles

Minimized sodium nitroprusside for mean arterial pressure regulation based on fuzzy rules emulated networks

An automatic regulation of mean arterial pressure (MAP) through the intravenous infusion of sodium nitroprusside (SNP) based on self adjustable networks called Multi-input Fuzzy Rules Emulated Networks (MIFREN) and its proposed learning algorithm is introduced in this article. To optimize the regulation performance and SNP dose, the estimated cost function is obtained by the first self adjustable network used to design the nearly optimum controller. The second network is designed as the direct controller via the human knowledge through the defined If-Then rules. The infusion rate of SNP is generated as the control effort to regulate MAP with the possible minimized drug level. All designed parameters such as the learning rates and some constant parameters have been selected to guarantee the system stability and bounded signals by the proof of the proposed theorem. The satisfied performance of the proposed controller is represented by computer simulations and comparison results with other control techniques are demonstrated the lower level of SNP at the steady state.

REINFORCEMENT FUZZY-RULE EMULATED NETWORKS AND ITS APPLICATION ON NONLINEAR DISCRETE-TIME SYSTEMS

The adaptive control algorithm based on Multi-Input Fuzzy Rules Emulated Networks (MIFRENs) with the reinforcement learning algorithm is introduced for a class of nonlinear discrete-time systems. Because of the unknown future values of systems, the long term cost function is estimated by the first MIFREN through the human knowledge with the defined IF-THEN rules and the proposed learning algorithm. The main controller is constructed by another MIFREN and the parameters in side this network have been tuned to minimize the estimated cost function and the control system error. All designed parameters are given with the Lyapunov method and the proposed theorem. The numerical simulation results are demonstrated the system performance with the selected nonlinear discrete-time systems

Global Approximations to Cost and Production Functions using Artificial Neural Networks

The estimation of cost and production functions in economics usually relies on standard specifications which are less that satisfactory in numerous situations. However, instead of fitting the data with a pre-specified model, Artificial Neural Networks (ANNs) let the data itself serve as evidence to support the model's estimation of the underlying process. In this context, the proposed approach combines the strengths of economics, statistics and machine learning research and the paper proposes a global approximation to arbitrary cost and production functions, respectively, given by ANNs. Suggestions on implementation are proposed. All relevant measures such as Returns to Scale (RTS) and Total Factor Productivity (TFP) may be computed routinely.

Productive innovations in hospitals: an empirical research on the relation between technology and productivity in the Dutch hospital industry

This paper studies the relationship between technology and productivity in Dutch hospitals. In most studies technical change is measured by a proxy, namely a time trend. In practice however, innovations slowly spread over all hospitals and so different hospitals are operating under different technologies at the same point in time. In this study we explicitly inventory specific and well-known innovations in the Dutch hospital industry in the past ten years. These innovations are aggregated into a limited number of homogenous innovation clusters, which are measured by a set of technology index numbers. The index numbers are included in the cost function specification and estimation. The results indicate that technical change is non-neutral and output- biased and that some technologies affect cost in beneficial ways.

Productivity growth and deregulation of Japanese electricity distribution

Deregulation of Japanese electric power industry began in 1995. After the amendment of Electricity Utility Industry Law in 1995, competition was partially introduced in a generation sector and retail competition started from 2000. Eligibility to choose suppliers was gradually extended from larger to smaller customers. As of 2008, almost all customers except households can choose their electricity suppliers. Based upon both previous implementation result of competition policy and review on their achievement, Japanese government will begin new policy debate in 2013 to assess further retail competition which includes household customers. To prepare for policy suggestion on the future electric power industry, this study examines the cost structure of Japanese electricity distribution. For the purpose, we estimate a multi-product translog cost function of Japanese electricity distribution from 1983 to 2003. Using the estimated cost function, we calculate several economic measures such as productivity growth, technical change and economies of scale and scope. The empirical results of this study indicate the improvement in productivity growth after deregulation.

A STUDY ON THE ESTIMATION OF COST FUNCTION FOR TRUCKING INDUSTRY IN KOREA

This research attempted an empirical analysis of the trucking industry in Korea through the estimation of cost functions; in the empirical analysis, the data were established based on a new method. Regarding the data, the availability of which has constrained research, it should be noted that this analysis was performed using estimated data instead of using existing survey data. The analysis results of this study were compared with other cost function analysis results with regard to economies of scale and the signs and sequence of elasticity. The results showed similarities, while also showing agreement with a considerable portion of the previous research.

Cost function estimates, scale economies and technological progress in the Turkish electricity generation sector

Turkish electricity sector has undergone significant institutional changes since 1984. The recent developments since 2001 including the setting up of a regulatory agency to undertake the regulation of the sector and increasing participation of private investors in the field of electricity generation are of special interest. This paper estimates cost functions and investigates the degree of scale economies, overinvestment, and technological progress in the Turkish electricity generation sector for the period 1984–2006 using long-run and short-run translog cost functions. Estimations were done for six groups of firms, public and private. The results indicate existence of scale economies throughout the period of analysis, hence declining long-run average costs. The paper finds empirical support for the Averch–Johnson effect until 2001, i.e., firms overinvested in an environment where there are excess returns to capital. But this effect was reduced largely after 2002. Technological progress deteriorated slightly from 1984–1993 to 1994–2001 but improved after 2002. Overall, the paper found that regulation of the market under the newly established regulating agency after 2002 was effective and there are potential gains from such regulation.

Perspectives on nonparametric and Semiparametric Modeling

Nonparametric regression techniques hold out the promise of more flexible modeling of data in many areas of physical, biological and social sciences. However, their use is hampered by the Ocurse of dimensionalityO which imposes enormous data requirements as the number of explanatory variables increases. After summarizing two of the most commonly used methods for mitigating the OcurseO, this paper outlines a new approach which exploits data on derivatives. In economics, such circumstances arise in the joint estimation of cost and factor demand functions, or when production function data are combined with data on factor prices. The ideas are illustrated using empirical examples from energy economics.

Capital Stock Approximation using Firm Level Panel Data

Summary Many recent studies exploring conditional factor demand or factor substitution issues use firm level panel data. A considerable number of establishment panels contains no direct information on the capital input, necessary for production or cost function estimation. Incorrect measurement of capital leads to biased estimates and casts doubt on any inference on output elasticities or input substitution properties. The perpetual inventory approach, commonly used for long panels, is a method that attenuates these problems. In this paper a modified perpetual inventory approach is proposed. This method provides more reliable measures for capital input when short firm panels are used and no direct information on capital input is available. The empirical results based on a replication study of Addison et al. (2006) support the conclusion that modified perpetual inventory is superior to previous attempts in particular when fixed effects estimation techniques are used. The method thus makes a considerable number of recently established firm panels accessible to more sophisticated production function or factor demand analyses.

Estimating cost functions for the four large carnivores in Sweden

The Swedish carnivore policy goal for the four large carnivores – wolverine ( Gulo gulo), wolf ( Canis lupus), brown bear ( Ursus arctos) and lynx ( Lynx lynx) – is to ensure a minimum viable population on a long-term basis. To reach this goal the policy restricts population regulation activities, like hunting (prohibited for wolverine and wolf and restricted for brown bear and lynx) in Sweden. For owners of semi-domesticated (i.e. reindeer), and domesticated (livestock) animals this policy and the existence of individuals of these four species results in externalities associated with predation. This paper presents econometric estimates of the predation and the social costs for these four species, based on ecological models of functional response. The data on costs is based on compensation provided to livestock owners by the Swedish government. The paper also applies these econometric estimates to predict the social cost per species when the population goals of the Swedish carnivore policy are reached. Based on out our model the wolverine and the lynx will impose the highest marginal, as well as total costs on society, given the current policy goals. The wolf is an efficient predator, but due to its geographical distribution in Sweden, its social costs are less than anticipated. The brown bear is largely omnivorous, thus resulting in relatively low social costs.

Regression approximation for a partially centralized inventory system considering transportation costs

Inventory centralization for multiple stores with stochastic demands reduces costs by establishing and maintaining a central ordering/distribution point. However the inventory centralization may increase the transportation costs since either the customer must travel more to reach the product, or the central warehouse must ship the product over longer distance to reach the customer. In this paper, we study a partially centralized inventory system where multiple central warehouses exist and a central warehouse fulfills the aggregated demand of stores. We want to determine the number, the location of central warehouses and an assignment of central warehouses and a set of stores. The objective is the minimization of the sum of warehouse costs and transportation cost. With the help of the regression approximation of cost function, we transform the original problem to more manageable facility location problems. Regression analysis shows that the approximated cost function is close to the original one for normally distributed demands.

A two-level distribution inventory system with stochastic lead time at the lower echelon

We consider a two-level distribution inventory system with a number of identical retailers at the lower echelon and a single supplier at the upper echelon. The replenishment policy is continuous review policy (R, Q) at all installations. We assume independent Poisson demands with stochastic lead time for the retailers and a constant transportation time for replenishing supplier orders from an external warehouse. Unsatisfied demands are assumed to be lost in the retailers and unsatisfied retailer orders are backordered in the supplier. We develop an approximate cost function to find optimal reorder points for given batch sizes in all installations, and the related accuracy is assessed through simulation. We present numerical examples for the gamma distributed lead time for the retailers orders at the supplier.

A two-level supply chain with partial backordering and approximated Poisson demand

We consider a two-level supply chain with a number of identical, independent ‘retailers’ at the lower echelon and a single supplier at the upper echelon controlled by continuous review inventory policy ( R, Q). Each retailer experiences Poisson demand with constant transportation times. We assume constant lead time for replenishing supplier orders from an external warehouse to the supplier and unsatisfied retailer orders are backordered in the supplier. We assume that the unsatisfied demand is partially backordered in the identical retailers. The partially backordering policy is implemented in the identical retailers using an explicit control parameter ‘ b’ which limits the maximum number of backorders allowed to be accumulated during the lead time. We develop an approximate cost function to find optimal reorder points for given batch sizes in all installations, the optimal value of b in the identical retailers and the related accuracy is assessed through simulation.

An Examination of Public Capital's Role in Production

This paper examines whether or not the long-term government bond rate could reasonably be employed as the rate of return on public capital when calculating public sector gross domestic product. It finds that the rate of return on public capital is lower than often reported and is roughly consistent with the rate of return on private capital. Given that there is a range of estimates that are plausible, the paper concludes that the long-run government bond rate could be used as a conservative estimate for the rate of return for public infrastructure. Previous studies have shown that production function estimates tend to find rates of return that are implausibly large, while cost function estimates appear more reasonable. This paper shows that public capital and multifactor productivity (MFP) growth behave similarly, and argues that production function estimates for the impact of public capital overstate its impact as a result, catching part of what belongs in estimates of MFP. It also shows that the similarity between the growth in public capital and MFP leads to a large confidence interval around public capital elasticity estimates derived from the production function framework. The paper then proceeds by generating a confidence interval from the production function estimated first with and then without MFP growth. It then uses a cost function to pinpoint more precisely estimates for the marginal cost savings from public capital. Importantly, the estimate derived from the cost function is found in the lower part of the confidence interval derived from the production function. The rate of return associated with the overlapping estimates is then shown to cover a range that extends from the average long-run government bond rate to the rate of return on private capital.

Moving-horizon state estimation for nonlinear discrete-time systems: New stability results and approximation schemes

A moving-horizon state estimation problem is addressed for a class of nonlinear discrete-time systems with bounded noises acting on the system and measurement equations. As the statistics of such disturbances and of the initial state are assumed to be unknown, we use a generalized least-squares approach that consists in minimizing a quadratic estimation cost function defined on a recent batch of inputs and outputs according to a sliding-window strategy. For the resulting estimator, the existence of bounding sequences on the estimation error is proved. In the absence of noises, exponential convergence to zero is obtained. Moreover, suboptimal solutions are sought for which a certain error is admitted with respect to the optimal cost value. The approximate solution can be determined either on-line by directly minimizing the cost function or off-line by using a nonlinear parameterized function. Simulation results are presented to show the effectiveness of the proposed approach in comparison with the extended Kalman filter.

Efficiency of commercial banks in Lebanon

The study evaluates the key performance indicators of the banking sector in post-war Lebanon, in an attempt to assess the efficiency of the sector in producing the conventional outputs. Using data from 1993 to 2002, we observe that the sector grew significantly in size as measured by assets, but the growth in assets was not accompanied by a similar growth in profits. Equity capital grew significantly over the period and the sector became safer. In fact, the prevalence of Lebanese treasury bills in the banks' asset portfolio indicates that commercial banks during this period did not play their traditional role of financing the private sector initiatives; instead, the bulk of their funds financed the public sector. The stochastic production and cost function estimates show that bank level inefficiency effects decreases with time and increases with number of branches, employees per branch, and ratio of staff to operating expenses.

Assessing the Costs of Adequacy in California Public Schools: A Cost Function Approach

In this study, a cost function is used to estimate the costs for California districts to meet the achievement goals set out for them by the state. I calculate estimates of base costs (i.e., per pupil costs in a district with relatively low levels of student need) and marginal costs (i.e., the additional costs associated with specific student characteristics) for poverty, English learners, and special education and then compare these estimates with the findings from cost studies in other states, which have used a variety of methods, and with other cost studies in California. Because of institutional constraints in California, the cost function estimate of total costs to achieve adequacy (which relies critically on the estimated relationship between spending and outcomes) may be quite imprecise. Nevertheless, the cost function estimates of base and marginal costs are not inconsistent with other studies, though they fall on the low end of the spectrum.

Economies of scale in the Swiss hydropower sector

The study considers the estimation of a translog cost function employing panel data for a sample of 43 Swiss hydropower companies, over the period of 1995 to 2002. The results of this analysis indicate the existence of economies of scale and density for most output levels. The basic novelty in this study is the estimation of a cost function for a sample of hydropower companies. In the economic literature, no study on the cost structure of the hydropower plants using an econometric approach has been published so far.

Quantifying the supply‐side benefits from forward contracting in wholesale electricity markets

AbstractThe assumption of expected profit‐maximizing bidding behavior in a multi‐unit, multi‐period auction with step‐function supply curves is used to estimate cost functions for electricity generation units and derive tests of expected profit‐maximizing behavior. Applying these techniques to data from the National Electricity Market in Australia reveals statistically significant evidence of output‐dependent marginal costs within and across half‐hours of the day, but no evidence against the hypothesis of expected profit‐maximizing behavior. These cost function estimates quantify the economic significance of output‐varying costs and how forward financial contract obligations impact the amount of these costs the generation unit owner incurs. This supplier's existing obligations imply average daily production costs that are 8% lower than the profit‐maximizing pattern of output with no forward contract obligations. Copyright © 2007 John Wiley & Sons, Ltd.

Estimation of cost functions in a data poor environment: the case of capacity estimation in fisheries

Fisheries economic analysis is often handicapped by the lack of adequate data to undertake robust econometric analyses. In this study, a translog cost function was required to estimate the potential direction of adjustment in a UK fleet segment if a new regulatory regime was introduced. However, the available data were not appropriate for such estimation. Data envelopment analysis (DEA) was used to modify the data subsequently used in the estimation of the long-run cost function. The resulting model appears robust and is consistent with economic theory and the supporting evidence produced using DEA.