THE ROLE OF NON-PARAMETRIC APPROACH IN ADJUSTING PRODUCTIVITY MEASURES FOR ENVIRONMENTAL IMPACTS

This paper addresses the role of non-parametric analysis in adjusting agricultural productivity measures for environmental impacts. The modified Tornquist-Theil index computed using shadow prices derived from the programming procedures is compared and contrasted with a non-parametric hyperbolic graph productivity index for the case of Nebraska agriculture.Nonparametric, Shadow price, Productivity, Environmental Economics and Policy, Productivity Analysis,

NON-PARAMETRIC ENVIRONMENTAL ADJUSTED PRODUCTIVITY (EAP) MEASURES: NEBRASKA AGRICULTURE SECTOR

Traditional Total factor productivity [TFP] misrepresents the true change in agricultural productivity because environmental bads jointly produced with desirable outputs are unaccounted. Nonparametric measures incorporating environmental bads support the hypothesis that prior [after] to 1980's the traditional TFP overstate [understate] production growths, reflecting peak use of chemicals.Environmental Economics and Policy, Productivity Analysis,

Returns to Scale of Production Function: Pooled, Within and Between Quantile Regression Approach

Production function, Pooled, Between and Within Quantile Regression, Panel data, Production Economics, Research Methods/ Statistical Methods,

Do Farm Programs Explain Mean and Variance of Technical Efficiency? Stochastic Frontier Analysis

Past literature has examined the importance of farm programs on the volatility and returns on general and agriculture economic growth. The objective of this study was to assess the impact of farm program payments on technical efficiency. The study used aggregate state level panel data from the U.S agricultural sector. Results indicate production increasing with increasing units of inputs. Results from this study indicate that farm program payments play an important role in technical efficiency. For example, farm program payments indicate a negative and positive effect on mean and variance of technical efficiency in the long-run and short-run, respectivelyProduction Economics, Productivity Analysis, Risk and Uncertainty,

A single-phase synchronization technique for grid-connected energy storage system under faulty grid conditions

The control of a single-phase grid-connected energy storage system (ESS) requires a very fast and accurate estimation of grid voltage frequency and phase angle. A phase-locked loop (PLL) based synchronization algorithm usually extracts this information. The operation and control of the entire system are directly affected by the performance of PLL. In this article, a novel advanced single-phase PLL (ASϕPLL) technique with reduced complexity is proposed for the fast and accurate extraction of grid information in an ESS under distorted and abnormal grid conditions, including harmonics, interharmonics, dc offset, and grid faults. The proposed method provides a faster dynamic response, lower frequency overshoot, and accurate estimation under off-nominal grid frequencies with reduced computational complexity in comparison with the existing method. The advanced performance of the proposed ASϕPLL is verified through the simulation and experimental results

An improved pre-filtering moving average filter based synchronization algorithm for single-phase V2G application

The performance and overall operation of grid- connected electric vehicle is directly affected by abnormal grid conditions. In this regard, Moving Average Filter (MAF) provide high noise cancellation capability and require less computational resources. However, the conventional in-loop MAF based synchronization suffers from slower dynamic response. In this paper, an improved pre-filtering MAF based PLL (IPMAFPLL) is proposed where MAF is removed from the control-loop and placed in the pre-filtering stage to improve the dynamic response of system. The phase drift provided by MAF under off-nominal frequency is further mitigated by introducing a compensation factor in the pre-filtering stage. The proposed technique is compared with conventional MAF-PLL and non-adaptive MAF- PLL. The simulation and experimental results show that our proposed approach have lower frequency overshoot and improved performance towards compensating grid harmonics under nominal and off-nominal grid frequencies

Aggregation Issues in the Estimation of Linear Programming Productivity Measures

This paper demonstrates the sensitivity of the linear programming approach in the estimation of productivity measures in the primal framework using Malmquist productivity index and Malmquist total factor productivity index models. Specifically, the sensitivity of productivity measure to the number of constraints (level of dis-aggregation) and imposition of returns to scale constraints of linear programing is evaluated. Further, the shadow or dual values are recovered from the linear program and compared to the market prices used in the ideal Fisher index approach to illustrate sensitivity. Empirical application to U.S. state-level time series data from 1960-2004 reveal productivity change decreases with increases in the number of constraints. Further, the input and output shadow or dual values are skewed, leading to the difference in the productivity measures due to aggregation.Aggregation, Share-weights, single and multiple output and input, Malmquist productivity index, Malmquist total factor productivity index, Agribusiness, Production Economics,

Online reduced complexity parameter estimation technique for equivalent circuit model of lithium-ion battery

For control-oriented battery management applications in electric vehicles, Equivalent Circuit Model (ECM) of battery packs offer acceptable modelling accuracy and simple mathematical equations for including the cell parameters. However, in real-time applications, circuit parameters continuously changes by varying operating conditions and state of the battery and thus, require an online parameter estimator. The estimator must update the battery parameters with less computational complexity suitable for real-time processing. This paper presents a novel Online Reduced Complexity (ORC) technique for the online parameter estimation of the ECM. The proposed technique provides significantly less complexity (hence estimation time) compared to the existing technique, but without compromising the accuracy. We use Trust Region Optimization (TRO) based Least Square (LS) method as an updating algorithm in the proposed technique and validate our results experimentally using Nissan Leaf (pouch) cells and with the help of standard vehicular testing cycles, i.e. the Dynamic Driving Cycle (DDC), and the New European Driving Cycle (NEDC)

An Assessment of the Efficiency of Agribusiness Trucking Companies: A Data Envelopment Analysis Approach

The purpose of this study is to investigate the issue of efficiency in the U.S. motor carrier industry using DEA and SFA. While both methods used the same variables, the resulting efficiency scores were significantly different. This leads to the question of which method is a better measure of efficiency.Public Economics,