Technical efficiency is the ability of a producer to obtain the maximum possible output from a given bundle of inputs, given the current state of technology.
The practical question it answers: with the land, labour, capital and seed a farm already has, is it actually producing as much as those resources allow?
Technical efficiency measures the gap between a producer’s actual performance and the Production Function‘s frontier — the maximum output theoretically obtainable from that input bundle. A technically efficient farm sits exactly on that frontier; a technically inefficient one lies below it, producing less than its own resources would allow under best practice.
What Is Technical Efficiency?
The modern definition of technical efficiency was formalised by the economist Michael Farrell in a landmark 1957 paper that established the framework still used today. Farrell proposed measuring a producer’s efficiency relative to a “best-practice” frontier constructed from the observed performance of the most productive firms or farms in a comparable sample, rather than against a purely theoretical ideal. A firm operating on that frontier is 100 percent technically efficient; a firm producing, say, 70 percent of the output the frontier predicts from its input bundle has a technical efficiency score of 0.70, or 70 percent.
Two statistical approaches dominate how technical efficiency is estimated in agricultural economics research:
- Stochastic Frontier Analysis (SFA), introduced independently by Aigner, Lovell and Schmidt, and by Meeusen and van den Broeck, in 1977, estimates a production frontier econometrically and splits the gap between a farm’s actual and frontier output into two parts: genuine inefficiency, and random noise from weather, measurement error or luck. This separation is SFA’s key advantage — it does not blame a farmer for a bad-weather year the way a purely deterministic method would.
- Data Envelopment Analysis (DEA) is a non-parametric, linear-programming method that builds the efficiency frontier directly from the best-performing observations in the sample, without assuming a specific functional form for the production relationship. DEA is more flexible but, unlike SFA, attributes the entire gap from the frontier to inefficiency, with no separate allowance for noise.
A technically inefficient farm falls short of the frontier because of sub-optimal management or resource allocation — not because its underlying technology or resource endowment is worse than its neighbours’. This distinction matters: raising technical efficiency does not require new land, more capital or better seed. It requires using the resources already at hand more effectively.
Why Does Technical Efficiency Matter?
It reveals how much output is available without any new investment. Because a technically inefficient farm is, by definition, producing less than its existing inputs allow, closing the efficiency gap is a pure productivity gain achievable through better practice, extension advice and management, rather than through the far costlier route of expanding land, labour or capital.
Measured efficiency gaps in smallholder agriculture are often large. A stochastic frontier study of maize production in Zimbabwe’s smallholder sector found an average technical efficiency of 65 percent, with about 90 percent of sampled farmers scoring between 60 and 75 percent — implying that average efficiency, and hence output, could be raised by roughly a third through better use of existing resources alone, primarily by improving access to extension services and farm-size-related constraints. A separate stochastic frontier study of crop production among 384 households in eastern Amhara, Ethiopia, found mean technical efficiency of 62.5 percent.
Efficiency is not simply a function of farm size or scale. A study of large-scale agricultural investment in northwest Ethiopia found average technical efficiency of only 71.7 percent among large commercial operations — meaning these producers were losing roughly 28 percent of potential grain output to inefficiency despite operating at considerable scale, a reminder that Economies of Scale and technical efficiency are distinct questions: an operation can be large and still manage its resources poorly.
It is one of two components economists separate out when explaining why a farm’s costs or output fall short of the theoretical optimum. Technical efficiency asks only whether the maximum physical output is being achieved from the input quantities used; it says nothing about whether those input quantities were the cheapest combination available at current prices, which is the separate question addressed by Allocative Efficiency. The two combine to form overall economic efficiency.
Key Takeaways
- Technical efficiency measures how close a producer’s actual output comes to the maximum obtainable from its existing bundle of inputs, given current technology.
- It was formally defined by Michael Farrell in 1957 and is estimated today mainly through Stochastic Frontier Analysis, which separates inefficiency from random noise, or Data Envelopment Analysis, which builds the frontier from the sample’s best performers.
- A technically inefficient farm is not using worse resources than an efficient one — it is using the same kind of resources less effectively.
- Measured efficiency gaps in smallholder agriculture are often substantial: studies have found average technical efficiency around 62 to 65 percent among smallholder maize and crop farmers in Ethiopia and Zimbabwe.
- Farm scale does not guarantee technical efficiency: a study of large-scale agricultural investment in Ethiopia found average technical efficiency of just 71.7 percent.
- Technical efficiency is one of two components of overall economic efficiency, alongside allocative efficiency, which asks whether the cheapest input combination was chosen at current prices.
Frequently Asked Questions
What is technical efficiency in simple terms?
Technical efficiency measures whether a farm is getting the maximum possible output from the inputs it already has. A farm producing less than its land, labour and capital would allow under best practice is technically inefficient, even if none of its individual resources are lacking.
How is technical efficiency measured?
The two main methods are Stochastic Frontier Analysis, which statistically estimates a production frontier and separates genuine inefficiency from random factors like weather, and Data Envelopment Analysis, a linear-programming method that builds the frontier from the best-performing farms in a sample. Both express a farm’s technical efficiency as a percentage of the frontier output.
What is a good technical efficiency score?
A score of 100 percent means a farm sits exactly on the best-practice frontier. Published studies of smallholder agriculture commonly find average scores in the 60 to 75 percent range, meaning most farms have meaningful room to raise output using only the resources they already have, without any new investment.
What is the difference between technical efficiency and productivity?
Productivity is the ratio of output to inputs for a single farm at a point in time. Technical efficiency compares that ratio to the best a farm with the same input bundle could achieve under current technology. Two farms can have different productivity levels because they use different technology, while having the same technical efficiency relative to their own respective frontiers.
Continue Exploring
- Allocative Efficiency
- Production Function
- Agricultural Productivity
- Total Factor Productivity
- Farm Management
References and Further Reading
- Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253–290.
- Aigner, D., Lovell, C. A. K. & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6(1), 21–37.
- Battese, G. E. & Coelli, T. J. (1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics, 20(2), 325–332.
- A stochastic frontier analysis of technical efficiency in smallholder maize production in Zimbabwe: the post-fast-track land reform outlook. Cogent Economics & Finance. https://www.tandfonline.com/doi/full/10.1080/23322039.2015.1117189
- The technical efficiency of large-scale agricultural investment in Northwest Ethiopia: a stochastic frontier approach. PLOS ONE / PMC. https://pmc.ncbi.nlm.nih.gov/articles/PMC10558816/
- Crop production efficiency in Eastern Amhara, Ethiopia. Discover Food, Springer Nature (2025). https://link.springer.com/article/10.1007/s44187-025-00529-w