Nonparametric Efficiency Estimation in Stochastic Environments (II)

We consider the issues of noise-to-signal estimation, finite sample performance andhypothesis testing for the nonparametric efficiency estimation technique proposed inCherchye, L., T. Kuosmanen and G. T. Post (2001) 'Nonparametric efficiencyestimation in stochastic environments', forthcoming in Operations Research. Inaddition, we apply the technique for analyzing European banks.hypothesis testing;European banks;noise-to-signal estimation;nonparametric efficiency estimation;finite sample performance

Applying regression quantiles to farm efficiency estimation

This article is concerned with the methodological question of frontier production functions estimation for agriculture, and the appropriateness of regression quantiles, as a useful semi-parametric approach. Better insights are reached using the proposed methodology that provides robust farm efficiency scores estimates. Using the 2007 Farm Accountancy Data Network (FADN) data for Greece, analysis shows that the distribution of efficiency scores is closer to normality when employing regression quantiles, while underestimation of efficiency obtained by other parametric or deterministic methods based on the conditional mean can be avoided. The results further suggest that government support aimed at enhancing farms viability should be directed towards payments decoupled from output or prices, as well as rural development payments that affect productivity in a uniform way.Efficiency, Quantile Regression, Agriculture, Agricultural and Food Policy, Productivity Analysis, Research Methods/ Statistical Methods, C14, D24, Q18,

When, where and how to perform efficiency estimation

In this paper we compare two flexible estimators of technical efficiency in a cross-sectional setting: the nonparametric kernel SFA estimator of Fan, Li and Weersink (1996) to the nonparametric bias corrected DEA estimator of Kneip, Simar andWilson (2008). We assess the finite sample performance of each estimator via Monte Carlo simulations and empirical examples. We find that the reliability of efficiency scores critically hinges upon the ratio of the variation in efficiency to the variation in noise. These results should be a valuable resource to both academic researchers and practitioners.Bootstrap; Nonparametric kernel; Technical efficiency

When, Where and How to Perform Efficiency Estimation

In this paper we compare two flexible estimators of technical efficiency in a cross-sectional setting: the nonparametric kernel SFA estimator of Fan, Li and Weersink (1996) to the nonparametric bias corrected DEA estimator of Kneip, Simar and Wilson (2008). We assess the finite sample performance of each estimator via Monte Carlo simulations and empirical examples. We find that the reliability of efficiency scores critically hinges upon the ratio of the variation in efficiency to the variation in noise. These results should be a valuable resource to both academic researchers and practitioners.nonparametric kernel, technical efficiency, bootstrap

When, where and how to perform efficiency estimation

In this paper we compare two flexible estimators of technical efficiency in a cross-sectional setting: the nonparametric kernel SFA estimator of Fan, Li and Weersink (1996) to the nonparametric bias corrected DEA estimator of Kneip, Simar and Wilson (2008). We assess the finite sample performance of each estimator via Monte Carlo simulations and empirical examples. We find that the reliability of efficiency scores critically hinges upon the ratio of the variation in efficiency to the variation in noise. These results should be a valuable resource to both academic researchers and practitioners.Bootstrap, Nonparametric Kernel, Technical Efficiency

Dynamic Efficiency Estimation: An Application to US Electric Utilities

The static production efficiency model and the dynamic duality model of intertemporal decision making using a parametric approach have been continuously developed but in separate direction. In this study the static shadow cost approach and the dynamic duality model of intertemporal decision making are integrated to formulate theoretical and econometric models of dynamic efficiency with intertemporal cost minimizing firm behavior. The dynamic efficiency model is empirically implemented using a panel data set of 72 U.S. major investor-owned electric utilities using fossil-fuel fired steam electric power generation during the time period of 1986 to 1999. The major results of this study are that most electric utilities in this study underutilized fuel relative to the aggregated labor and maintenance input and they overutilized capital in production. Electric utilities with relatively high technical inefficiency of variable inputs demand in production in states adopting a deregulation plan improve the performance of the utilities. The estimates of the input price elasticities present the substitution possibilities among the inputs. Finally, the results suggest evidence of increasing returns to scale in the production of the electricity industry.

Comparison of Frontier Efficiency Methods: An Application to the U.S. Life Insurance Industry

The objective of this paper is to provide new information on the performance of efficiency estimation methods by applying a wide range of econometric and mathematical programming techniques to a sample of U.S. life insurers. Average efficiencies differ significantly across methods. The efficiency rankings are well-preserved among the econometric methods; but the rankings are less consistent between the econometric and mathematical programming methods and between the data envelopment analysis and free disposal hull techniques. Thus, the choice of estimation method can have a significant effect on the conclusions of an efficiency study. Most of the insurers in the sample display either increasing or decreasing returns to scale, and stock and mutual insurers are found to be equally efficient after controlling for firm size. Key words: Efficiency estimation, stochastic frontiers, data envelopment analysis, free disposal hull, life insurance industry, organizational form.

Hardware Impairments in Large-scale MISO Systems: Energy Efficiency, Estimation, and Capacity Limits

The use of large-scale antenna arrays has the potential to bring substantial improvements in energy efficiency and/or spectral efficiency to future wireless systems, due to the greatly improved spatial beamforming resolution. Recent asymptotic results show that by increasing the number of antennas one can achieve a large array gain and at the same time naturally decorrelate the user channels; thus, the available energy can be focused very accurately at the intended destinations without causing much inter-user interference. Since these results rely on asymptotics, it is important to investigate whether the conventional system models are still reasonable in the asymptotic regimes. This paper analyzes the fundamental limits of large-scale multiple-input single-output (MISO) communication systems using a generalized system model that accounts for transceiver hardware impairments. As opposed to the case of ideal hardware, we show that these practical impairments create finite ceilings on the estimation accuracy and capacity of large-scale MISO systems. Surprisingly, the performance is only limited by the hardware at the single-antenna user terminal, while the impact of impairments at the large-scale array vanishes asymptotically. Furthermore, we show that an arbitrarily high energy efficiency can be achieved by reducing the power while increasing the number of antennas.Comment: Published at International Conference on Digital Signal Processing (DSP 2013), 6 pages, 5 figure

Two-dimensional GaAs/AlGaAs superlattice structures for solar cell applications: ultimate efficiency estimation

We calculate the band structure of a two-dimensional GaAs/AlGaAs superlattice and estimate the ultimate efficiency of solar cells using this type of structure for solar energy conversion. The superlattice under consideration consists of gallium arsenide rods forming a square lattice and embedded in aluminium gallium arsenide. The ultimate efficiency is determined versus structural parameters including the filling fraction, the superlattice constant, the rod geometry and the concentration of Al in the matrix material. The calculated efficiency of the superlattice proves to exceed the efficiency of each component material in the monolithic state in a wide range of parameter values.Comment: 11 pages, 7 figure

Massive MIMO Systems with Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits

The use of large-scale antenna arrays can bring substantial improvements in energy and/or spectral efficiency to wireless systems due to the greatly improved spatial resolution and array gain. Recent works in the field of massive multiple-input multiple-output (MIMO) show that the user channels decorrelate when the number of antennas at the base stations (BSs) increases, thus strong signal gains are achievable with little inter-user interference. Since these results rely on asymptotics, it is important to investigate whether the conventional system models are reasonable in this asymptotic regime. This paper considers a new system model that incorporates general transceiver hardware impairments at both the BSs (equipped with large antenna arrays) and the single-antenna user equipments (UEs). As opposed to the conventional case of ideal hardware, we show that hardware impairments create finite ceilings on the channel estimation accuracy and on the downlink/uplink capacity of each UE. Surprisingly, the capacity is mainly limited by the hardware at the UE, while the impact of impairments in the large-scale arrays vanishes asymptotically and inter-user interference (in particular, pilot contamination) becomes negligible. Furthermore, we prove that the huge degrees of freedom offered by massive MIMO can be used to reduce the transmit power and/or to tolerate larger hardware impairments, which allows for the use of inexpensive and energy-efficient antenna elements.Comment: To appear in IEEE Transactions on Information Theory, 28 pages, 15 figures. The results can be reproduced using the following Matlab code: https://github.com/emilbjornson/massive-MIMO-hardware-impairment