Enhancing Productivity and Resource Conservation by Eliminating Inefficiency of Thai Rice Farmers: A Zero Inefficiency Stochastic Frontier Approach

Abstract

The study first identified fully efficient farmers and then estimated technical efficiency of inefficient farmers, identifying their determinants by applying a Zero Inefficiency Stochastic Frontier Model (ZISFM) on a sample of 300 rice farmers from central-northern Thailand. Next, the study developed scenarios of potential production increase and resource conservation if technical inefficiency was eliminated. Results revealed that 13% of the sampled farmers were fully efficient, thereby justifying the use of our approach. The estimated mean technical efficiency was 91%, implying that rice production can be increased by 9%, by reallocating resources. Land and labor were the major productivity drivers. Education significantly improved technical efficiency. Farmers who transplanted seedlings were relatively technically efficient as compared to those who practised manual and/or mechanical direct seeding methods. Elimination of technical inefficiency could increase output by 8.64% per ha, or generate 5.7-6.4 million tons of additional rice output for Thailand each year. Similarly, elimination of technical inefficiency would potentially conserve 19.44% person-days of labor, 11.95% land area, 11.46% material inputs and 8.67% mechanical power services for every ton of rice produced. This translates into conservation of 2.9-3.0 million person-days of labor, 3.7-4.5 thousand km 2 of land, 10.0-14.5 billion baht of material input and 7.6-12.8 billion baht of mechanical power costs to produce current level of rice output in Thailand each year. Policy implications include investment into educating farmers, and improving technical knowledge of seeding technology, to boost rice production and conserve scarce resources in Thailand.

Assessment of Technical Efficiency and Its Potential Determinants among Small-Scale Coffee Farmers in Rwanda

“…TE of an individual farm producer (Equation (2)) is defined as the ratio of the observed output (Y) to the corresponding frontier output (Y * ) [16]. The model is expressed as follows [21][22][23]:…”

Analysis of technical efficiency in maize production in Guji Zone: stochastic frontier model

“…The farmers who achieved relatively higher education level are believed to have higher exposure to agricultural technology and agricultural technology adoption possibility. This could enhance the farm productivity per hectare, since better educated farmers are more likely to adopt modern equipment efficiently [11,25].…”

Assessing Production Efficiency by Farm Size in Rwanda: A Zero-inefficiency Stochastic Frontier Approach

“…2 Typically, in the literature, two empirical approaches have been broadly used to estimate TE. The first is DEA, which is a nonparametric approach involving the use of linear programming techniques (Khataza et al 2019;Liu et al 2017). Although efficiency estimation using DEA does not impose a functional form on the data, this approach fails to effectively address statistical noise that is likely to affect the accuracy of estimates (Khataza et al 2019;Liu et al 2017).…”

“…Gebremedhin et al (2009) also found that education has a significantly positive effect in improving the TE of smallholder farmers in Ethiopia. As a plausible explanation for this finding, better educated farmers are likely to have better access to necessary information on the state of agricultural technologies and on the optimal use of farming practices than their counterparts (Liu et al 2017).…”