Estimation Of Technical Efficiency Research Articles

TECHNICAL EFFICIENCY OF VEGETABLE PRODUCTION AMONG WETLAND VEGETABLE FARMERS IN SOUTHWEST NIGERIA

This study employed Cobb-Douglas Stochastic Frontier Production function to measure technical efficiency and its determinants among dry season vegetable farmers in selected wetland catchments in Southwest Nigeria. A multistage random sampling procedure was adopted to select 450 wetlands vegetable farmers across Oyo, Ogun and Lagos States and data were collected with the aid of structured questionnaire in 2020. Technical efficiency (TE) estimates indicated that wetlands vegetable farmers operated below the production frontier with the mean technical efficiency value of 0.74. Increased farm size, family labour, quantity of seed planted, and quantity of agrochemical significantly (p<0.01) improved the farmers’ technical efficiency level. The study found that extension contact, access to credit, farming experience, and membership of an association negatively and significantly related to technical inefficiency at 1 and 5%. Weighted average price and household size were significantly and positively related to technical inefficiency. It was recommended that attention should be given to improvement in the visitation by extension agent, the provision of improved seeds and affordable financial support. Key words: Efficiency, Stochastic frontier, Vegetable, Wetland,

A firm-specific Malmquist productivity index model for stochastic data envelopment analysis: an application to commercial banks

In the data envelopment analysis (DEA) literature, productivity change captured by the Malmquist productivity index, especially in terms of a deterministic environment and stochastic variability in inputs and outputs, has been somewhat ignored. Therefore, this study developed a firm-specific, DEA-based Malmquist index model to examine the efficiency and productivity change of banks in a stochastic environment. First, in order to estimate bank-specific efficiency, we employed a two-stage double bootstrap DEA procedure. Specifically, in the first stage, the technical efficiency scores of banks were calculated by the classic DEA model, while in the second stage, the double bootstrap DEA model was applied to determine the effect of the contextual variables on bank efficiency. Second, we applied a two-stage procedure for measuring productivity change in which the first stage included the estimation of stochastic technical efficiency and the second stage included the regression of the estimated efficiency scores on a set of explanatory variables that influence relative performance. Finally, an empirical investigation of the Iranian banking sector, consisting of 120 bank-year observations of 15 banks from 2014 to 2021, was performed to measure their efficiency and productivity change. Based on the findings, the explanatory variables (i.e., the nonperforming loan ratio and the number of branches) indicated an inverse relationship with stochastic technical efficiency and productivity change. The implication of the findings is that, in order to improve the efficiency and productivity of banks, it is important to optimize these factors.

Technical efficiency and assessment of input excess in all European farms by a non-parametric methodology and the conditional inference tree

The technical efficiency is a fundamental tool in order to evaluate the performances of farms. The main purpose of this study was to investigate the technical efficiency in all European farms part of the FADN dataset using a non-parametric approach such as the DEA. The estimation of the technical efficiency has pointed out a dichotomy between new and older member states of the European Union. The further stage of this research has been addressed in evaluating the excess of input able to impact to technical inefficiency patterns using a new approach such as the Multi-directional Efficiency Analysis. The Multi-directional Efficiency Analysis is a novelty in the literature because it estimates the percentage of excess in input involved in the inefficiency overcoming the main bottleneck in the estimation on efficiency using the DEA. By the estimation of the technical efficiency, it has been possible also to assess the impact of financial subsides allocated by the CAP. Results have corroborated as CAP subsidies have reduced the technical efficiency in farms. In the third stage of this research, it has been possible to assess by the machine learning using the conditional inference tree the excess of input and how the excess impacts on the technical efficiency with an accuracy of more 90%. The conditional inference tree is also a novelty in the literature about the technical efficiency estimation in farms combining the estimation of the technical efficiency with the patterns and reasons of inefficiency.

Connecting catch profiles with efficiency: An application to the beam trawl fishery in the Northern Adriatic Sea

Estimation of technical efficiency in fisheries is most commonly finalized at comparing the conversion from inputs (e.g. time at sea, fuel consumption) to production (i.e. landed fish) among vessels or gears. In this paper we adopt a novel approach focusing on the efficiency of fishing trips characterized by different catch composition within the same fleet. In particular, the case study under analysis is represented by the beam trawl (“rapido”) fishery of Chioggia (Adriatic Sea, GSA 17), which has been subject to increasing technical and effort limitations in recent years due to its severe impacts on the marine ecosystem. The methodological strategy first involves a cluster analysis of catch profiles to identify homogeneous groups of fishing trips, which are subsequently compared in terms of economic performance based on the efficiency scores from stochastic frontier analysis. By including also an estimation of Greenhouse Gas emissions per trip, the results from our study can be used to inform future management interventions that aim at improving the overall efficiency of the fishery while reducing its carbon footprint and the pressure on the most relevant target species.

Estimation of Technical Efficiency of Sorghum Production in Dejen District, North-west Ethiopia

Ethiopian agriculture is characterized by low productivity due to natural, social, economic, and institutional factors. Farmers with homogeneous resources produce different outputs per hectare due to inefficient utilization of limited resources. There is no due attention given to crop production efficiency issues, particularly in sorghum production. The objective of this study was to assess the level of technical efficiency and its determinant factors on sorghum production in Dejen District, North-west Ethiopia. The two-stage sampling procedure was used to determine the sample size. Data were collected from 192 households using a systematic random sampling technique. A semi-structured questionnaire was used for the data collection. Focus group discussions and key informant interviews were also conducted. Both descriptive statistics and econometric analysis were used for data analysis. The average technical efficiency of Sorghum producers was 62.8%, with a min of 23.5% and a max of 96.7%. About 37.2% of output variation from optimal production was observed in the study area. The estimated Gamma (γ) value was 73.4% indicating the presence of inefficiency. Thus, farmers have a chance to maximize their output level by making efficient use of existing resources and technology

Productive Performance of Indian Food Manufacturing Industry: A Sub-Sectoral Analysis in a Stochastic Frontier Framework

This article examines the productive performance of the Indian food manufacturing industry measured in terms of technical efficiency (TE) of its 13 sub-sectors under the organised sector. For estimating their TE, it makes the use of the Cobb–Douglas production technology with the truncated normal distribution of stochastic inefficiency term ( Stevenson, 1980 ) via Jondrow et al. (1982) estimator of cross-sectional data. Data are sourced from the Annual Survey of Industries, 2017–2018. The results show that this industry, as a whole, observed 92% TE in 2017–2018, but among its sub-sectors, it varied between 100% and 74%, that is, they exhibited differential productive performance. Modern sub-sectors, such as fruits and vegetables, edible oils, bakery and beverage products, realised frontier-level efficiency, while sugar and starch products were identified as marginal performers in the industry. The robustness of the results is confirmed by the non-parametric estimates of TE from the data envelopment analysis. The results are expected to be useful in framing specific policies for these two different groups of food processors. In the case of sub-sectors performing below the frontier, policy actions aiming at pure technical and scale efficiencies, such as capacity building, research, skill programmes, and extension activities, need to be operationalised, while for sub-sectors performing at the frontier, only technological progress needs to be prioritised.

The Impact of Data Envelopment Analysis on Effective Management of Inputs: The Case of Farms Located in the Regional Unit of Pieria

Technical efficiency is considered a useful advisory tool for managers whose main goal is to maximize profit and minimize costs. Data envelopment analysis is a widely accepted methodology for technical efficiency estimation in the sector of agriculture. For that reason and with the view to extract useful conclusions regarding farmers’ effective management of inputs, this study aims to present the DEA method through its implementation in a set of farms located in the regional unit of Pieria. To conduct this analysis, relevant data were collected through a survey in which 40 farms participated. The output variable was chosen to be each farm’s total amount of sales, while the inputs were selected in a way to represent the main factors of production, such as (1) land in acres, (2) labor in hours, and (3) variable costs in EUR. The results showed that the examined farms need to reduce the inputs used by 34.6% to operate more efficiently from the point of view of the CRS model. Therefore, farmers should be motivated to reduce the inputs used, something that can be done through the provision of specialized advisory services. This will, of course, be helped by both the local authorities and the policies of the country in which the rational use of inputs seems to be necessary. This study may contribute to the relevant literature, agriculture, and the area since management suggestions are formulated for the farmers of Pieria’s regional unit.

Applicability of data envelopment analysis using vessel-level data to the estimation of technical efficiency and capacity utilization of the small-scale squid angling fishery in Aomori Prefecture, Japan

Applicability of data envelopment analysis using vessel-level data to the estimation of technical efficiency and capacity utilization of the small-scale squid angling fishery in Aomori Prefecture, Japan

Estimation of Technical Efficiency in Tea Farms at Plantation Level: A Review

The systematic literature review of 111 abstracts has been conducted to comprehensively compile the empirical studies of 21 complete text papers from all over the globe in context to estimation or determination of the technical efficiency (TE) at plantation level of tea production system (TPS), by adopting two methodologies viz., stochastic frontier analysis (SFA) and data envelopment analysis (DEA) during the period 2012-2022. Investigation from these empirical studies revealed that the average TE (TEmean) of tea growers (TG)s all around the globe computed by using both the approaches is around 67.98%, which showcased that the TGs have ability to increase the green tea leaf (GTL) production by 32.02% through better utilization of available resources and technology. The influence of various factors on TE of these TGs had contradictory outcomes, which broke new ground for future research. Computation of TE will enable an investigator to benchmark the best performing TGs in a particular area, which may be referred to by the inefficient TGs to enhance their performance.

Estimation of technical and capacity efficiency and surpluses in production factors In rabbit farms in Kafr El-Sheikh Govern orate.

Estimation of technical and capacity efficiency and surpluses in production factors In rabbit farms in Kafr El-Sheikh Govern orate.

Estimation of technical efficiency of chemical-free farming using data envelopment analysis and machine learning: evidence from India

PurposeThis study aims to examine the technical efficiency of the chemical-free farming system in India using a hybrid combination of data envelopment analysis (DEA) and machine learning (ML) approaches.Design/methodology/approachThe study used a two-stage approach. In the first stage, the efficiency scores of decision-making units’ efficiency (DMUs) are obtained using an input-oriented DEA model under the assumption of a variable return to scale. Based on these scores, the DMUs are classified into efficient and inefficient categories. The 2nd stage of analysis involves the identification of the most important predictors of efficiency using a random forest model and a generalized logistic regression model.FindingsThe results show that by using their resources efficiently, growers can reduce their inputs by 34 percent without affecting the output. Orchard's size, the proportion of land, grower's age, orchard's age and family labor are the most important determinants of efficiency. Besides, growers' main occupation and footfall of intermediaries at the farm gate also demonstrate significant influence on efficiency.Research limitations/implicationsThe study used only one output and a limited set of input variables. Incorporating additional variables or dimensions like fertility of the land, climatic conditions, altitude of the land, output quality (size/taste/appearance) and per acre profitability could yield more robust results. Although pineapple is cultivated in all eight northeastern states, the data for the study has been collected from only two states. The production and marketing practices followed by the growers in the remaining six northeastern states and other parts of the country might be different. As the growers do not maintain farm records, their data might suffer from selective retrieval bias.Practical implicationsGiven the rising demand for organic food, improving the efficiency of chemical-free growers will be a win-win situation for both growers and consumers. The results will aid policymakers in bringing necessary interventions to make chemical-free farming more remunerative for the growers. The business managers can act as a bridge to connect these remote growers with the market by sharing customer feedback and global best practices.Social implicationsAlthough many developments have happened to the DEA technique, the present study used a traditional form of DEA. Therefore, future research should combine ML techniques with more advanced versions like bootstrap and fuzzy DEA. Upcoming research should include more input and output variables to predict the efficiency of the chemical-free farming system. For instance, environmental variables, like climatic conditions, degree of competition, government support and consumers' attitude towards chemical-free food, can be examined along with farm and grower-specific variables. Future studies should also incorporate chemical-free growers from a wider geographic area. Lastly, future studies can also undertake a longitudinal estimation of efficiency and its determinants for the chemical-free farming system.Originality/valueNo prior study has used a hybrid framework to examine the performance of a chemical-free farming system.

Estimation of technical efficiency of Indian farms for major crops during 2013–2014 and 2017–2018: a stochastic Frontier production approach

Estimation of technical efficiency of Indian farms for major crops during 2013–2014 and 2017–2018: a stochastic Frontier production approach

Leverage and firm value

AbstractThree highly cited studies with over 6000 citations collectively report a negative relationship between the market value of the firm and leverage. Such empirical findings clearly contradict the hypothesis of leverage adding value to the firm and an optimal capital structure that maximizes firm value—these findings have yet to be resolved. Employing a sample of 3,768 firms consisting of 39,015 observations, a stochastic frontier analysis was used to assess the relationship of leverage among other capital structure factors with firm value. It was found that in general the use of leverage promotes firm value, consistent with the trade‐off theory and that the inverse relationship between leverage and firm value was a temporary occurrence and is likely attributable to firms employing tax loss carrybacks in response to the 1986 Tax Reform Act. The estimates of technical efficiency indicate that many firms can do more to increase their value, the sample as a whole improves efficiency (value) over the sample period. The findings reconcile the reports of leverage decreasing firm value as reported in Baker and Wurgler, Fama and French, and Habib and Ljungqvist. The empirical findings suggest prior observation was a due to a decline in the value of the tax shield generated by leverage after the Tax Reform Act of 1986. Specifically, tax carrybacks extended the pre‐Tax Reform Act of 1986 tax shield value to 1991 and after 1991 the tax shield value declined.

Estimation of technical efficiency and determinants of technical inefficiency of dairy farmers in Maharashtra

Estimation of technical efficiency and determinants of technical inefficiency of dairy farmers in Maharashtra

Technical and Scale Efficiency of farms producing grapes for wine

climatechange and the subsequent requirements to comply with environmental standards, continuoustechnological change, and the need to adapt it, adjust, and remain competitive. The COVID-19 pandemic and the economic hardship it brought about, followed by the current energy crisis,make it imperative to address issues of competitiveness and efficiency of farm units. Theseunfavorable developments particularly affect mountainous and disadvantaged rural areassuch as the Region of Western Macedonia in Greece. Furthermore, the decarbonizationprocess that this region is undergoing, leads to a period of uncertainty, especially in relationto employment. The cultivation of vineyards and wine production are dominant economicactivities with Xinomavro being the main grape for wine variety. The efficiency of grape-producing farms are considered important for the whole wine supply chain. The objective of this paper is to estimate the technical and scale efficiency of wine-related agricultural firms in the region of Western Macedonia, by applying the DEA methodology. An output-oriented empirical model was applied for the estimation of technical and scale efficiency of farms producing grapes for wine.
 Keywords: technical efficiency, scale efficiency, wine grape cultivation, Western Macedonia, wineries

Estimation and determinants of technical efficiency of smallholder cashew (anacardium) farmers in Dassa district, Benin: a bootstrap data envelopment approach

Cashew nut production is becoming more important in Benin’s economy, and it helps to improve the living conditions of rural populations. This paper examines cashew producers’ technical efficiency in Dassa District using survey data collected from 100 farms in 2020. The research relies on bootstrap modeling of Data Envelopment Analysis, and Fractional Regression Model is applied to assess the determinants of producers’ technical efficiency. The results show the technical efficiency of the farms to be 34.56%, and the same level of production is obtained when inputs are reduced by 65.44%. The research shows that, contrary to theory, farmers without access to credit are more efficient than those with access, with a difference of 12.64%. Finally, the results show that schooling expenses and the sale of cashew apples as a by-product of production are promising factors that may increase the efficiency of cashew nut production. Policies to promote cashew farm efficiency need to focus on promoting formal education in rural areas, establishing a financial literacy training program for farm managers, and promoting the expansion of agricultural extension for farmers. In addition, producers should also set up a system for productive, substainable, and profitable use of cashew apples to increase their income.

Technical Efficiency and Export Potential of the World Palm Oil Market

Palm oils have been proven to have the highest yield among vegetable oils, which is one of the critical factors in ensuring global food security. However, the world palm oil market has not been entirely utilised due to intervention policies that disrupt the global trade flow. Hence, this study aims to identify the technical efficiency of palm oil exports and then analyse the export potential of two leading producers and exporters of palm oil, Malaysia and Indonesia. A stochastic frontier model (SFM) has been used to estimate the level of technical efficiency across two countries for a sample of 59 major palm oil importing countries during 2009–2019. Palm oil export potential is then calculated using the value of technical export efficiency obtained from the SFM. The main findings revealed the technical inefficiency of world palm oil exports. Comparing the two countries, the Indonesian average technical efficiency value is higher than Malaysian throughout the year. Moreover, the technical efficiency estimates reveal that Malaysia and Indonesia dominate different markets, except in the Netherlands. In terms of export potential, the study found that both major exporting countries of palm oil have great potential to tap more into the same countries, namely China, India, Thailand and the United States. The policy implications of this study suggest that policymakers from both countries should set up a new combined strategy to maximise the palm oil export to their trading partners. Low technical efficiency values in several importing countries show great potential to explore further. Hence, there is a vast potential market for palm oil export to be tapped in those countries.

Contract Farming and Technical Efficiency: A Case of Export-Oriented Organic Rice Farmers in Pakistan

Although organic rice is a niche market in Pakistan, it has exhibited enormous potential for growth in export-oriented production. Since contract farming is the leading promoter of export-oriented organic rice production in Punjab, Pakistan, improving the technical efficiency of smallholder rice farmers through contract farming holds sufficient potential. This work examines the influence of contract farming participation on smallholder rice farmers’ technical efficiency using a cross-sectional data set of 650 respondents. We applied a stochastic frontier analysis (SFA) to examine the production frontier and inefficiency estimates. Further, propensity score matching (PSM) was used to control endogeneity and self-selection bias in technical efficiency estimates. The results reveal that the technical efficiency score of organic rice farmers in Punjab, Pakistan, is 89.7%, which can still be improved by 10.3% at the current sociodemographic characters and input levels. Likewise, land size, seed, and machine expenditures are the key inputs of the production frontier. Results show a positive and significant connection between contract farming participation and technical efficiency. The study extends the literature on technical efficiency, export-oriented production, contract farming, and the well-being of smallholder farmers. Moreover, the study’s findings provide cues for policies and practices.

Analysing the Technical Efficiency of Rural Cooperative Banks in India

Using data envelopment analysis, this paper investigates the technical efficiency of rural cooperative banks in India from 2013 to 2019. The results indicate a continuous deterioration in efficiency as well as a large asymmetry between states regarding the technical efficiency estimates. Our results highlight the need for improving risk management and lending operations of banks for sustainable increase in the performance of the cooperative banking sector in India.

Assessing efficiency of dairy goat farms by performance evaluation and benchmarking

The efficiency of goat farming sector in Greece is analyzed in this study. A survey was carried out in 96 goat farms, randomly selected in the area of Macedonia and Thrace, Greece. Accounting data were recorded through face-to-face interviews with farmers and Data Envelopment Analysis was applied to estimate technical efficiency (TE) of goat farms. The mean TE estimated at 0.791, indicating that input savings of 20.9% could be achieved. 75% of the goat farms are deemed as inefficient. The gross revenue varies considerably between efficient and inefficient farms, with the first achieving €210.09 and inefficient farms €143.41/doe. Farm size classification reveals significant difference of TE among groups of small and medium sized farms (P≤0.05). The analysis of the existing structure of the farms, compared to the optimal plan resulted from DEA, shows that farms could achieve higher economic results, through a rational use of the available inputs.