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Given some similarities in the banking industry and economic condition across Vietnam, China and India, the purpose of this paper is to estimate and compare the cost and revenue efficiency of banks across these three countries over the period 1995–2011.

This study employs the meta-frontier of Battese et al. (2004) and O’Donnell et al. (2008) which envelops the three country-frontiers to measure the cost and revenue efficiency of banks in these three countries.

This study finds that Chinese banks adopt the most advanced cost-reducing and revenue-increasing technology when providing banking products to their customers, followed by Indian banks. Indian banks are as cost-efficient as Chinese banks, but more cost-efficient than Vietnamese banks. Indian banks are as revenue-efficient as Vietnamese banks, but less revenue-efficient than Chinese banks. Over the analysis period, banks in the three countries have employed the more advanced technology in reducing costs, and they have become more cost-efficient. Nonetheless, for revenue side, the improvement in revenue efficiency and adopted technology are observed only in Chinese banks. The main source of meta-cost and meta-revenue inefficiency of these banking systems stems from undertaking inferior technology rather than managerial ability. Results from comparison across bank types show that state-owned banks (SOBs) are more cost and revenue-efficient than privately owned banks, with Indian and Chinese SOBs being the most cost- and revenue-efficient, respectively.

To improve meta-cost efficiency, Chinese and Indian banks would constitute a relevant benchmark for Vietnamese banks, while to improve meta-revenue efficiency, Chinese banks would be considered as a relevant benchmark for Vietnamese and Indian banks.

This is the first study which utilizes meta-frontier to compare cost and revenue efficiency and technology across banks in Vietnam, China and India.

The chapter examines the sources of total factor productivity growth (TFPG) of the 2-digit manufacturing industries as well as total manufacturing industry of Gujarat during the period from 1981–82 to 2010–11, using a stochastic frontier approach. The empirical finding clearly states that although factor accumulations as well as resource allocations in most of the 2-digit manufacturing industries of the state have been improved during the postreform period, technological progress (TP) and technical efficiency change (TEC) of the same have deteriorated in most industries of the state during that period. As a result TFPG in the major manufacturing industries as well as total manufacturing industry of the state have declined because the combined effect of their improvement in scale effect (SC) and allocation efficiency effect (AEC) could not offset the declining effect of both the TP and TEC of the same during that period. In this context, the government should take some policy initiatives to improve productive efficiency of the organized manufacturing industries in Gujarat. Once efficiency increases, it enhances competitiveness, thereby increasing productivity growth and its different sources of organized manufacturing industries of the state.

We consider a semiparametric panel stochastic frontier model where one-sided firm effects representing inefficiencies are correlated with the regressors. A form of the Chamberlain-Mundlak device is used to relate the logarithm of the effects to the regressors resulting in a lognormal distribution for the effects. The function describing the technology is modeled nonparametrically using penalized splines. Both Bayesian and non-Bayesian approaches to estimation are considered, with an emphasis on Bayesian estimation. A Monte Carlo experiment is used to investigate the consequences of ignoring correlation between the effects and the regressors, and choosing the wrong functional form for the technology.

Historically standard regression has been used to assess performance in marketing, especially of salespeople and retail outlets. A model of performance is estimated using ordinary least squares, the residuals are computed, and the decision-making units, say store managers, ranked in the order of the residuals. The problem is that the regression line approach characterizes average performance. The focus should be on best performance. Frontier analysis, especially stochastic frontier analysis (SEA), is a way to benchmark such best performance. Deterministic frontier analysis is also discussed in passing. The distinction between conventional ordinary least squares analysis and frontier analysis is especially marked when heteroscedasticity is present. Most of the focus of benchmarking has been on identifying the best performing units. The real insight, though, is from explaining the benchmark gap. Stochastic frontier analysis can, and should, model both phenomena simultaneously.

The purpose of this paper is to examine the impact of agricultural cooperative membership on potato production and technical efficiency.

A combination of propensity score matching technique and sample selection stochastic frontier framework that addresses potential selection bias due to observable and unobservable attributes is used to estimate the effect of participation between cooperative members and non-members. Using a stochastic meta-frontier approach, the technical efficiency of farmers was estimated and compared.

The empirical results show that the effect of participation in agricultural cooperatives is associated with increased yield and technical efficiency. A comparison of group-specific frontiers indicates that cooperative members perform better than non-members. Cooperative membership decisions is significantly associated with household and farm characteristics (e.g. education, participation in off-farm work, total farmland, distance to market and geographic location).

The findings of this study demonstrate that cooperative organisations can be an important tool to enhance the productivity and efficiency of smallholder farmers. Successful cooperative models together with training programs designed to enlighten farmers on the importance and tangible benefits of collective action should be used to enlarge participation in cooperative organisations. In addition, governments and development agencies should implement targeted investment and capacity building programs related to irrigation management, gender-sensitive awareness and development of the internal institutional mechanisms in cooperatives for the transfer of knowledge and mutual learning so that all members benefit from cooperatives.

Despite the pervasive evidence of the impact of cooperatives on productivity and technical efficiency in the Asian region, this study is probably the first attempt in the crop sector in Mongolia. It provides a rigorous empirical analysis of the impact of agricultural cooperative membership on potato production and technical efficiency through a counterfactual design.

The processes of liberalisation, globalisation and integration have brought new dynamics into banking markets. In an increasingly competitive environment, banks have been forced to refocus their strategies and examine their performance, because their survival in the 21st century will depend on efficiency (Denizer & Tarimcilar, 2001). In recent years, therefore, bank efficiency has received wide attention, and researchers have developed an extensive array of sophisticated methods and tools to estimate efficiency.

This study aims to discuss climate change, by modifying the timing of several agricultural operations, reduce the efficiency and yield of inputs leading to a lower production level. The reduction of the effects of climate change on production yields and on farmers' technical efficiency (TE) requires the adoption of adaptation strategies. This paper analyses the impact of climate change adaptation strategies adopted on maize farmers' TE in Benin.

This paper uses an endogeneity-corrected stochastic production frontier approach based on data randomly collected from 354 farmers located in three different agro-ecological zones of Benin.

Estimation results revealed that the adoption of adaptation strategies improve maize farmers' TE by 1.28%. Therefore, polices to improve farmers' access to climate change adaptation strategies are necessarily for the improvement of farmers' TE and yield.

The results of this study contribute to the policy debate on the enhancement of food security by increasing farmers' TE through easy access to climate change adaptation strategies. The improvement of farmers' TE will in turn improve the livelihoods of the communities and therefore contribute to the achievement of Sustainable Development Goals 1, 2 and 13.

This study contributes to theoretical and empirical debate on the relationship between adaptation to climate change and farmers' TE. It also adapts a new methodology (endogeneity-corrected stochastic production frontier approach) to correct the endogeneity problem due to the farmers' adaptation decision.

The purpose of this paper is to estimate technical efficiency obtained from both data envelopment analysis (DEA) and stochastic frontier approaches using household survey data for rice farming households in Vietnam.

A bootstrap method is used to provide statistical precision of the DEA estimator. Technical efficiency is modeled as a function of household and production factors.

The results from the deterministic, semi‐parametric and parametric approaches indicate that among other things, technical efficiency is significantly influenced by primary education and regional factors. In addition, scale efficiency analysis shows that many farms in Vietnam are operating with less than optimal scale of operation.

The study is among the first that employ a bootstrap method and compare estimates from both Data Envelopment Analysis (DEA) and stochastic frontier approaches.

The objective of the present study is to evaluate and analyse the performance of Indian electricity distribution utilities post the implementation of landmark Electricity Act 2003.

Stochastic frontier analysis (SFA) that incorporates exogenous influences on operational efficiency is adopted in the present study. Specifically, a stochastic frontier production function model with a technical inefficiency effects model (Battese and Coelli, 1995) is chosen as a preferred model. In this model, the function that explains the inefficiency scores is estimated in a single stage with the production technology. This avoids the problem of inconsistency which is possible in the two-stage approach.

The sample involved 52 Indian electricity distribution utilities for seven-year period from 2006 to 2013. Major findings of SFA show that Indian electricity distribution utilities post the implementation of Electricity Act (2003) had, on average, experienced efficiency improvement during the observed period. The overall mean technical effciency score is estimated as 78.5% which indicates that there exist wide scope for effciency improvement in the sector. Further, the empirical findings also indicate that publicly owned distribution utilities obtain average technical efficiencies of 71.3%, which is lower than privately owned distribution utilities, which achieve average technical efficiencies of 85.7%.

Power supply quality indicators such as SAIFI, SAIDI, CAIFI, etc. and unobserved heterogeneity also influence the efficiency analysis of electricity distribution utilities. Hence, these parameters as explanatory variables can be incorporated in the future work.

The results obtained from this empirical study would likely be helpful for utility managers and policymakers to know how well they are performing, and how a better corporate strategy a particular utility can formulate to improve its operational efficiency and also its position in the marketplace.

This paper is amongst the first significant attempts that implement SFA approach to the panel dataset over a longer period of time – 2006 to 2013, so, as to evaluate and analyse the operational efficiency of Indian electricity distribution utilities in a single framework after the enactment of Electricity Act (2003). Unlike previous studies, this study investigates the degree to which various exogenous (or environmental) factors influence efficiency levels in these utilities.