Estimating Technical Efficiency and Production Risk under Contract Farming: A Bayesian Estimation and Stochastic Dominance Methodology

We investigate production risk, technical efficiency and risk attitudes amongst contract and independent farmers. We use a Bayesian parametric approach and stochastic dominance quantile regression methods to compare technical efficiency and risk attitude of smallholders in Nepal. Using farm‐level data, we find that contract farmers appear to show lower inefficiency and lower production risk. Additionally, contract and independent farmers can increase output by reducing the scale of operation. Regardless of the commodity produced and farming arrangement (contract or independent production), we find that labour, land and other inputs are risk‐augmenting, while the role of capital is mixed. We find a second order stochastic dominance (SSD) for lentils, and first order stochastic dominance (FSD) for tomatoes, ginger and HYV paddy seed commodities. Finally, contract farmers are more risk averse than independent farmers, regardless of the commodity produced.     

Off‐farm work and technical efficiency on U.S. dairies

In this study, we investigate the impact of an increase in farm households’ off‐farm work on technical efficiency (TE) of U.S. dairies. We present a theoretical framework that implies that an increase in farm household off‐farm work decreases TE. We use two nationally‐representative samples of U.S. dairies (2010 and 2005 Agricultural Resource Management Surveys) and a parametric approach (stochastic frontier analysis) to empirically test the hypothesis. Results are generally consistent with the hypothesis and show that an increase in off‐farm work by the farm household is associated with a significant decrease in TE. In addition, results show that there is a statistically significant difference in TE between small, medium, and large farms. Small farms are associated with significantly higher off‐farm work and have lower TE than large farms, which implies that less off‐farm work by households with larger farms is at least partially responsible for the evidence of economies of scale in the U.S. dairy industry.     

Technical,Allocative, Cost and Scale Efficiencies in Bangladesh Rice Cultivation: A Non‐parametric Approach

Applying programming techniques to detailed data for 406 rice farms in 21 villages, for 1997, produces inefficiency measures, which differ substantially from the results of simple yield and unit cost measures. For the Boro (dry) season, mean technical efficiency was 69.4 per cent, allocative efficiency was 81.3 per cent, cost efficiency was 56.2 per cent and scale efficiency 94.9 per cent. The Aman (wet) season results are similar, but a few points lower. Allocative inefficiency is due to overuse of labour, suggesting population pressure, and of fertiliser, where recommended rates may warrant revision. Second‐stage regressions show that large families are more inefficient, whereas farmers with better access to input markets, and those who do less off‐farm work, tend to be more efficient. The information on the sources of inter‐farm performance differentials could be used by the extension agents to help inefficient farmers. There is little excuse for such sub‐optimal use of survey data, which are often collected at substantial costs.     

Farm machinery use,off‐farm employment and farm performance in China

We analyse the joint impacts of farm machinery use and off‐farm employment on maize yields and agrochemical expenses from a household survey of 493 farmers in China. Our findings are obtained from an innovative two‐stage econometric procedure that combines a bivariate ordered probit model with an endogeneity‐corrected ordinary least square regression model. The results show that farmers are jointly making decisions to use farm machines and to work off the farm and that these two household activities affect maize yields and agrochemical expenses in different ways. We show that farm machinery use significantly increases both maize yields and agrochemical expenses, while off‐farm employment significantly decreases agrochemical expenses. Our findings highlight the importance of additional machinery use in increasing farm production; the need to account for possible endogeneity in estimation; and the statistical significance of key household characteristics (gender, education, and household size) on overall farm production.     

Efficiency Effects of Access to Information on Small‐scale Agriculture: Empirical Evidence from Uganda using Stochastic Frontier and IRT Models

Low power home electrical items such as radios, mobile phones and televisions are an important source of agricultural information for small‐scale farmers in developing countries. To empirically test the effects of access to information from these items on efficiency in agriculture, we formulate a stochastic frontier model augmented with a technical efficiency model that controls for an index capturing farmers' ‘ability to access information’. The index is constructed with a 2‐parameter item response theory (IRT) model based on farmers' access to the electrical items. Using six rounds of panel data on small‐scale farmers in Uganda, we find empirical evidence of a significant and positive relationship between farmer ability to access information and farm efficiency. There is also evidence that the size of these effects is larger for more literate hence better educated farmers. Greater access to information also appears to be associated with increased variance of (in)efficiency and output although the form of the increased variances is underpinned by low risk of lower efficiency and output realisations and high likelihood of higher efficiency and output realisations. Our findings imply that access to limited quantities of electricity needed to power these electrical items can have positive farm efficiency effects, and hence the importance of off‐grid electricity (e.g. standalone solar panels) for small‐scale farmers in typically isolated communities in developing countries.     

Production Risk and Technical Efficiency in Organic and Conventional Agriculture – The Case of Arable Farms in Germany

This paper quantifies the importance of production risk and technical efficiency as two possible sources of production variability in German organic and conventional farming. Determinants of production risk and inefficiency are investigated based on a combination of Just and Pope’s stochastic production framework and a Stochastic Frontier Analysis. The empirical analysis is conducted using a balanced panel of farm records from 1999/2000 to 2006/2007 on 37 organic and conventional arable farms, respectively. Euclidian‐Distance‐Matching is used to identify for each organic farm a conventional counterpart with similar structural features. Results indicate that output variability in both production technologies is mainly caused by production risk. Land and labour are identified as risk‐increasing inputs in both farm types whereas higher capital endowment, seed costs and soil quality have risk‐reducing effects.     

Determinants of off‐farm work and its effects on farm performance: the case of Norwegian grain farmers

Limited attention has been given in the literature to the impact of off‐farm work on farm performance. More knowledge about the determinants of part‐time farming and its effects on farm performance could help policymakers to introduce better targeted rural development policies. The aim in this article is to fill part of the above‐mentioned gaps by analyzing factors that influence the choices of off‐farm work by either the farmer alone or jointly by both the farmer and partner; and simultaneously examining how off‐farm work influences farm performance. These analyses were based on an unbalanced panel data set from Norwegian grain farms during 1991 to 2005. Among the determinants of off‐farm work hours, we found that, in addition to demographic, time trend, and some regional effects, there was a significant negative effect of farm output on farmers' off‐farm work hours. The production function results revealed that off‐farm work had a positive effect on farm output, at first increasing but then decreasing with increase in hours spent in off‐farm work. Furthermore, our analysis revealed no systematic effect of off‐farm work on farm technical efficiency.     

Spatial dependency and technical efficiency: an application of a Bayesian stochastic frontier model to irrigated and rainfed rice farmers in Bohol,Philippines

We investigated the role of spatial dependency in the technical efficiency estimates of rice farmers using panel data from the Central Visayan island of Bohol in the Philippines. Household‐level data were collected from irrigated and rainfed agro‐ecosystems. In each ecosystem, the geographical information on residential and farm‐plot neighborhood structures was recorded to compare household‐level spatial dependency among four types of neighborhoods. A Bayesian stochastic frontier approach that integrates spatial dependency was used to address the effects of neighborhood structures on farmers’ performance. Incorporating the spatial dimension into the neighborhood structures allowed for identification of the relationships between spatial dependency and technical efficiency through comparison with nonspatial models. The neighborhood structure at the residence and plot levels were defined with a spatial weight matrix where cut‐off distances ranged from 100 to 1,000 m. We found that spatial dependency exists at the residential and plot levels and is stronger for irrigated farms than rainfed farms. We also found that technical inefficiency levels decrease as spatial effects are more taken into account. Because the spatial effects increase with a shorter network distance, the decreasing technical inefficiency implies that the unobserved inefficiencies can be explained better by considering small networks of relatively close farmers over large networks of distant farmers.     

Farms’ technical inefficiencies in the presence of government programs*

We focus on determining the impacts of government programs on farms’ technical inefficiency levels. We use Kumbhakar's stochastic frontier model that accounts for both production risks and risk preferences. Our theoretical framework shows that decoupled government transfers are likely to increase (decrease) DARA (IARA) farmers’ production inefficiencies if variable inputs are risk decreasing. However, the impacts of decoupled payments cannot be anticipated if variable inputs are risk increasing. We use farm‐level data collected in Kansas to illustrate the model.     

Off‐farm employment and reasons for entering farming as determinants of production enterprise selection in US agriculture

In today’s agriculture, farmers consider off‐farm employment and lifestyle goals in complex ways to select production enterprises. Data from USDA’s Agricultural Resource Management Survey were used to examine how off‐farm employment and ‘reasons for entering farming’ influence production enterprise selection in US agriculture. A two‐stage analysis with a multivariate tobit model was used to examine the impact of off‐farm employment as influenced by government farm programme payments, reasons for entering farming, demographics and location on production enterprise selection. Results underscore the impacts of reasons for entering farming and off‐farm employment on production enterprise choice and provide implications for policy development. The study highlights the importance of government farm programme payments in production enterprise selection by US farmers.     

The influence of management characteristics on the technical efficiency of wheat farmers in eastern England

Technical efficiency of wheat farms in eastern England is measured through the estimation of a stochastic frontier production function using panel data for the 1993–1997 crop years. Variations in the technical efficiency index across production units are explained through a number of managerial and farm characteristic variables following Battese and Coelli (1995) [Empirical Econ. 20, 325–332] and incorporating the spirit of Rougoor et al. (1998) [Agric. Econ. 18, 261–272]. The technical efficiency index across production units ranges from 62 to 98%. The objectives of maximising annual profits and maintaining the environment are positively correlated with, and have the largest influence on, technical efficiency. Moreover, those farmers who seek information, have more years of managerial experience, and have a large farm are also associated with higher levels of technical efficiency. Future studies that seek to explain variation in technical efficiency should include further aspects of the managerial decision‐making process.     

The Effects of Direct Payments on Technical Efficiency of Irish Beef Farms: A Stochastic Frontier Analysis

The 2003 Mid‐Term Review of the CAP sought to refocus the EU's farm support policy to foster a more competitive and market‐orientated agricultural sector. The foundation of this reform comprised the introduction of decoupled payments to farmers, replacing the EU's previous system of supports that were directly linked to production of designated crops and livestock. This paper explores the effect of coupled payments and their subsequent replacement by decoupled support, on the technical efficiency of specialist beef farms in Ireland. Given the high reliance of beef farmers in Ireland on CAP payments, the decoupling of payments has been especially important for the sector. A stochastic production frontier is estimated using a panel dataset comprising detailed accountancy data for Irish beef farms between the years 2000 and 2013. Our results indicate that technical efficiency in the beef farming sector has been consistently poor, with an average efficiency score of only 0.53 during the period analysed. However, we found that direct income received in the form of coupled payments had a positive impact on farm efficiency, and that this positive effect was maintained after their replacement with decoupled income support.     

Farm and farmer characteristics and off‐farm work: evidence from Algeria

Off‐farm work is a widespread, two‐edged, phenomenon that can help both the survival and the demise of small‐ and medium‐sized agricultural exploitations. Given the prevalence of poverty in rural areas, nonfarm income has been credited with helping farmers to survive. But the observed shrinking of rural areas has also raised the question of whether off‐farm work is pulling farmers permanently away from farming. This paper explores the impact of farmer characteristics on the decision to work off‐farm in developing countries where this phenomenon has been largely neglected. A review of theory and prior empirical work suggests four main hypotheses which we test empirically. The results suggest that while some farmer characteristics appear to be universal, others appear to be country‐ or culture‐specific.     

A study of economic efficiency of Iranian farmers in Ramjerd district: an application of stochastic programming

An extension of utility-efficient programming to the non-linear discrete stochastic programming method was developed and used in the analysis of the economic efficiency of a sample of farmers in Iran. The results indicate that it would be feasible to increase substantially farmers' total net revenue by increasing their economic efficiency in terms of technical and allocative efficiencies. The study further suggested that risk aversion plays an important role in farmers' behaviour. The sample farmers are risk averse and hence are likely to trade higher expected profits for lower risk. Understanding this characteristic is important for interventions intended to raise farm productivity and efficiency.     

Effect of off‐farm income on smallholder commercialization: panel evidence from rural households in Ethiopia

This article investigates how off‐farm income affects crop output market participation decisions and marketed surplus of smallholder farmers in Ethiopia. A double‐hurdle model is estimated using three waves of panel data from the Ethiopian Rural Household Survey. Unobserved heterogeneity is controlled for using a correlated random effect procedure and potential endogeneity of explanatory variables using a control function approach. The results show that off‐farm income has no significant influence on household crop output market participation. However, conditional on market participation, additional off‐farm earnings negatively affect the marketed surplus. This indicates that farmers use off‐farm earnings for consumption rather than for investment in agricultural production. Policy measures that promote rural investment may help increase returns to labor for land‐poor households participating in off‐farm work in the process of agricultural commercialization.     

Modern Rice Technologies and Productivity in the Philippines: Disentangling Technology from Managerial Gaps

Using cross‐sectional farm‐level data from 3,164 rice‐farming households in the Philippines, we measure the impact of modern rice technologies on farm productivity while disentangling technology gaps (the distance between production frontiers) from managerial gaps (differences in technical efficiency). To do so, we combine a recently developed stochastic production frontier framework with impact evaluation techniques to control for biases stemming from observables and unobservables. First, we find an adequate control group using propensity score matching to mitigate the effect of biases from observable variables. Then, we test for biases that might arise from unobserved variables using a stochastic frontier framework corrected for self‐selection. Finally, we estimate meta‐frontiers to assess productivity differences between adopters and non‐adopters. The analysis shows that the adoption of certified seeds has a significant and positive impact on productivity, efficiency and net income in rice farming.     

Bt Cotton,Pesticide Use and Environmental Efficiency in Pakistan

There is a broad literature on the impact of Bt cotton adoption in different countries, but few studies have explicitly looked at environmental and health effects from an economic perspective. We analyse the impact of Bt cotton on environmental efficiency in Pakistan, using farm survey data and a doubly heteroskedastic stochastic production function framework. Negative environmental and health effects of chemical pesticide use are quantified with the environmental impact quotient. Bt‐adopting farms have higher cotton yields, while using lower pesticide quantities and causing less environmental damage. Bt farms are both technically and environmentally more efficient than non‐Bt farms. Bt adoption increases environmental efficiency by 37%. Achieving the same reduction in negative environmental and health impact without Bt would cost conventional cotton farmers US$ 54 per acre in terms of foregone yields and revenues (7% of total revenues). Extrapolating this shadow price of the technology's health and environmental benefits to the total Bt cotton area in Pakistan results in an aggregate value of US$ 370 million. These benefits are in addition to the profit gains for Bt‐adopting farmers. Our results suggest that Bt technology can contribute to sustainable agricultural development.     

Patterns in Technical Efficiency and Technical Change at the Farm‐level in England and Wales, 1982–2002

English and Welsh farm‐level survey data are employed to estimate stochastic frontier production functions for eight different farm types (cereal, dairy, sheep, beef, poultry, pigs, general cropping and mixed) for the period 1982 to 2002. Differences in the relative efficiency of farms are explored by the simultaneous estimation of a model of technical inefficiency effects. The analysis shows that, generally, farms of all types are relatively efficient with a large proportion of farms operating close to the production frontier. However, whilst the frontier farms of all types are becoming more efficient through time because of technical change, it is also the case that the efficiency of the average farm for most farm types is increasing at a slower rate. In addition, annual mean levels of efficiency for most farm types have declined between 1982 and 2002. The factors that consistently appear to have a statistically significant effect on differences in efficiency between farms are: farm or herd size, farm debt ratios, farmer age, levels of specialisation and ownership status.     

Institutional Environment and Technical Efficiency: A Stochastic Frontier Analysis of Cotton Producers in West Africa

This paper examines the effects of the institutional environment on West African cotton farmers’ technical efficiency (TE). First, key aspects of the cotton sector institutional environment are discussed, including input and credit access, and producers’ organisations. Then, a stochastic frontier production function, which incorporates technical inefficiency effects, is applied to farm level data collected in Benin, Burkina Faso and Mali. The survey includes farmers’ evaluations of the cotton sector institutional environment. Results suggest that institutional level features influence producers’ TE, besides farm‐level characteristics. Cotton growers who report a negative experience with the joint liability programme, who identify the cotton price mechanism or access to credit as the main constraints to performance, and who cultivate more hectares of cereals are technically more inefficient in producing cotton. Findings suggest that cotton farmers in Mali are less technically efficient in producing cotton than in Burkina Faso and Benin. Agricultural development policies focusing on reducing farmers’ financial stress, particularly through the establishment of adequate price mechanisms (i.e. higher farm‐gate prices and timely payments to farmers) and improvement in the input–credit markets should be encouraged to improve TE in West Africa.