Microfinance, Efficiency and Agricultural Production in Bangladesh

The objectives of this study were to make a detailed and systematic empirical analysis of microfinance borrowers and non-borrowers in Bangladesh and also examine how efficiency measures are influenced by the access to agricultural microfinance. In the empirical analysis, this study used both parametric and non-parametric frontier approaches to investigate differences in efficiency estimates between microfinance borrowers and non-borrowers. This thesis, based on five articles, applied data obtained from a survey of 360 farm households from north-central and north-western regions in Bangladesh. The methods used in this investigation involve stochastic frontier (SFA) and data envelopment analysis (DEA) in addition to sample selectivity and limited dependent variable models. In article I, technical efficiency (TE) estimation and identification of its determinants were performed by applying an extended Cobb-Douglas stochastic frontier production function. The results show that farm households had a mean TE of 83% with lower TE scores for the non-borrowers of agricultural microfinance. Addressing institutional policies regarding the consolidation of individual plots into farm units, ensuring access to microfinance, extension education for the farmers with longer farming experience are suggested to improve the TE of the farmers. In article II, the objective was to assess the effects of access to microfinance on household production and cost efficiency (CE) and to determine the efficiency differences between the microfinance participating and non-participating farms. In addition, a non-discretionary DEA model was applied to capture directly the influence of microfinance on farm households production and CE. The results suggested that under both pooled DEA models and non-discretionary DEA models, farmers with access to microfinance were significantly more efficient than their non-borrowing counterparts. Results also revealed that land fragmentation, family size, household wealth, on farm-training and off farm income share are the main determinants of inefficiency after effectively correcting for sample selection bias. In article III, the TE of traditional variety (TV) and high-yielding-variety (HYV) rice producers were estimated in addition to investigating the determinants of adoption rate of HYV rice. Furthermore, the role of TE as a potential determinant to explain the differences of adoption rate of HYV rice among the farmers was assessed. The results indicated that in spite of its much higher yield potential, HYV rice production was associated with lower TE and had a greater variability in yield. It was also found that TE had a significant positive influence on the adoption rates of HYV rice. In article IV, we estimated profit efficiency (PE) and profit-loss between microfinance borrowers and non-borrowers by a sample selection framework, which provided a general framework for testing and taking into account the sample selection in the stochastic (profit) frontier function analysis. After effectively correcting for selectivity bias, the mean PE of the microfinance borrowers and non-borrowers were estimated at 68% and 52% respectively. This suggested that a considerable share of profits were lost due to profit inefficiencies in rice production. The results also demonstrated that access to microfinance contributes significantly to increasing PE and reducing profit-loss per hectare land. In article V, the effects of credit constraints on TE, allocative efficiency (AE) and CE were assessed while adequately controlling for sample selection bias. The confidence intervals were determined by the bootstrap method for both samples. The results indicated that differences in average efficiency scores of credit constrained and unconstrained farms were not statistically significant although the average efficiencies tended to be higher in the group of unconstrained farms. After effectively correcting for selectivity bias, household experience, number of dependents, off-farm income, farm size, access to on farm training and yearly savings were found to be the main determinants of inefficiencies. In general, the results of the study revealed the existence substantial technical, allocative, economic inefficiencies and also considerable profit inefficiencies. The results of the study suggested the need to streamline agricultural microfinance by the microfinance institutions (MFIs), donor agencies and government at all tiers. Moreover, formulating policies that ensure greater access to agricultural microfinance to the smallholder farmers on a sustainable basis in the study areas to enhance productivity and efficiency has been recommended. Key Words: Technical, allocative, economic efficiency, DEA, Non-discretionary DEA, selection bias, bootstrapping, microfinance, Bangladesh.

A parametric method 3 (PM3) study of trans‐stilbene

We report a comparative modified neglect of diatomic overlap (MNDO), Austin method one (AM1), and parametric method 3 (PM3) study of trans‐stilbene (tS) in its ground, excited (singlet and triplet), and ionic (positive and negative polarons and bipolarons) states. We have also calculated the barrier for ring rotation about the backbone single bond. Our results show that PM3 geometries are superior to MNDO and AM1, at least for tS. PM3 predicts, in contrast with MNDO, AM1 and even ab initio 3‐21G, a coplanar structure for tS, in accordance with recent experimental data. Singlet and triplet energies obtained from heats of formation are in surprisingly good agreement with experimental data.

Parametric instability of stochastic columns

Columns which have stochastically distributed Young's modulus and mass density and are subjected to deterministic periodic axial loadings are considered. The general case of a column supported on a Winkler elastic foundation of random stiffness and also on discrete elastic supports which are also random is considered. Material property fluctuations are modeled as independent one-dimensional univariate homogeneous real random fields in space. In addition to autocorrelation functions or their equivalent power spectral density functions, the input random fields are characterized by scale of fluctuations or variance functions for their second order properties. The foundation stiffness coefficient and the stiffnesses of discrete elastic supports are treated to constitute independent random variables. The system equations of boundary frequencies are obtained using Bolotin's method for deterministic systems. Stochastic FEM is used to obtain the discrete system with random as well as periodic coefficients. Statistical properties of boundary frequencies are derived in terms of input parameter statistics. A complete covariance structure is obtained. The equations developed are illustrated using a numerical example employing a practical correlation structure.

Acoustic performance of hoses - A parametric study

Modeling of wave propagation in hoses, unlike in rigid pipes or waveguides, introduces a coupling between the inside medium, the hose wall, and the outside medium, This alters the axial wave number and thence the corresponding effective speed of sound inside the hose resulting in sound radiation into the outside medium, also called the breakout or shell noise, The existing literature on the subject is such that a hose cannot be integrated into the,whole piping system made up of sections of hoses, pipes, and mufflers to predict the acoustical performance in terms of transmission loss (TL), The present paper seeks to fill this gap, Three one-dimensional coupled wave equations are written to account for the presence of a yielding wall with a finite lumped transverse impedance of the hose material, The resulting wave equation can readily be reduced to a transfer matrix form using an effective wave number for a moving medium in a hose section, Incorporating the effect of fluid loading due to the outside medium also allows prediction of the transverse TL and the breakout noise, Axial TL and transverse TL have been combined into net TL needed by designers, Predictions of the axial as well as transverse TL are shown to compare well with those of a rigorous 3-D analysis using only one-hundredth of the computation time, Finally, results of some parametric studies are reported for engineers involved in the acoustical design of hoses. (C) 1996 Institute of Noise Control Engineering.

A two timescale stochastic approximation scheme for simulation-based parametric optimization

A two timescale stochastic approximation scheme which uses coupled iterations is used for simulation-based parametric optimization as an alternative to traditional "infinitesimal perturbation analysis" schemes, It avoids the aggregation of data present in many other schemes. Its convergence is analyzed, and a queueing example is presented.

Parametric study of MSW landfill settlement model

A newly developed and validated constitutive model that accounts for primary compression and time-dependent mechanical creep and biodegradation is used for parametric study to investigate the effects of model parameters on the predicted settlement of municipal solid waste (MSW) with time. The model enables the prediction of stress strain response and yield surfaces for three components of settlement: primary compression, mechanical creep, and biodegradation. The MSW parameters investigated include compression index, coefficient of earth pressure at-rest, overconsolidation ratio, and biodegradation parameters of MSW. A comparison of the predicted settlements for typical MSW landfill conditions showed significant differences in time-settlement response depending on the selected model input parameters. The effect of lift thickness of MSW on predicted settlement is also investigated. Overall, the study shows that the variation in the model parameters can lead to significantly different results; therefore, the model parameter values should be carefully selected to predict landfill settlements accurately. It is shown that the proposed model captures the time settlement response which is in general agreement with the results obtained from the other two reported models having similar features. (C) 2011 Elsevier Ltd. All rights reserved.

Multiscale stochastic approximation for parametric optimization of hidden Markov models

A two-time scale stochastic approximation algorithm is proposed for simulation-based parametric optimization of hidden Markov models, as an alternative to the traditional approaches to ''infinitesimal perturbation analysis.'' Its convergence is analyzed, and a queueing example is presented.

Design enhancement of the underwater noise control linings through a parsimonious parametric study

Control of sound transmission through the structure and reflection from the structure immersed in fluid media impose highly conflicting requirements on the design of the carpeted noise control linings. These requirements become even more stringent if the structure is expected to be moving with considerable speed particularly under intense hydrostatic pressure. Numerous configurations are possible for designing these linings. Therefore, in this paper, a few lining configurations are identified from the literature for parametric study so that the designer is provided with an environment to analyze and design the lining. A scheme of finite element analysis is used to analyze these linings for their acoustic performance. Commercial finite element software, NISA®, is used as a platform to develop a customized environment wherein design parameters of different configurations can be varied with consistency checks and generate the finite element meshes using the 8-noded hexahedral element. Four types of designs proposed and analysed here address the parameters of interest such as the echo reduction and the transmission loss. Study of the effect of different surface distributions of the cavities is carried out. Effect of static pressure on different designs is reported.

Analysis and Synthesis of Reverberation for Parametric Stereo Audio

We propose a parametric stereo coding analysis and synthesis directly in the MDCT domain using an analysis by synthesis parameter estimation. The stereo signal is represented by an equalized sum signal and spatialization parameters. Equalized sum signal and the spatialization parameters are obtained by sub-band analysis in the MDCT domain. The de-correlated signal required for the stereo synthesis is also generated in the MDCT domain. Subjective evaluation test using MUSHRA shows that the synthesized stereo signal is perceptually satisfactory and comparable to the state of the art parametric coders.

Single-machine scheduling with past-sequence-dependent setup times and learning effects: a parametric analysis

In this article, we consider the single-machine scheduling problem with past-sequence-dependent (p-s-d) setup times and a learning effect. The setup times are proportional to the length of jobs that are already scheduled; i.e. p-s-d setup times. The learning effect reduces the actual processing time of a job because the workers are involved in doing the same job or activity repeatedly. Hence, the processing time of a job depends on its position in the sequence. In this study, we consider the total absolute difference in completion times (TADC) as the objective function. This problem is denoted as 1/LE, (Spsd)/TADC in Kuo and Yang (2007) ('Single Machine Scheduling with Past-sequence-dependent Setup Times and Learning Effects', Information Processing Letters, 102, 22-26). There are two parameters a and b denoting constant learning index and normalising index, respectively. A parametric analysis of b on the 1/LE, (Spsd)/TADC problem for a given value of a is applied in this study. In addition, a computational algorithm is also developed to obtain the number of optimal sequences and the range of b in which each of the sequences is optimal, for a given value of a. We derive two bounds b* for the normalising constant b and a* for the learning index a. We also show that, when a < a* or b > b*, the optimal sequence is obtained by arranging the longest job in the first position and the rest of the jobs in short processing time order.

Improved parametric models and DPCM techniques for EGG data compiression

This paper presents a novel algorithm for compression of single lead Electrocardiogram (ECG) signals. The method is based on Pole-Zero modelling of the Discrete Cosine Transformed (DCT) signal. An extension is proposed to the well known Steiglitz-Hcbride algorithm, to model the higher frequency components of the input signal more accurately. This is achieved by weighting the error function minimized by the algorithm to estimate the model parameters. The data compression achieved by the parametric model is further enhanced by Differential Pulse Code Modulation (DPCM) of the model parameters. The method accomplishes a compression ratio in the range of 1:20 to 1:40, which far exceeds those achieved by most of the current methods.