The impact of labelled seeds on the technical efficiency of rice farming in Indonesia

One of the governmental strategies to enhance the national rice production involves improving farmers’ access to high-quality seeds through subsidies and the distribution of labelled rice seeds. This research aims to assess rice cultivation’s technical efficiency using labelled seeds compared to those without. Earlier investigations into the impact of labelled seeds on rice farming performance did not account for potential biases carried on by variables that are both observed and unobserved variables. This study utilized household-level data from 14 districts situated in the rice production centre of Indonesia. Propensity score matching was employed to mitigate observed variable biases, while selectivity-corrected stochastic production frontier models were applied to address biases associated with unobserved variables. The findings revealed that rice farming with labelled seeds demonstrated greater technical efficiency than farming with unlabelled seeds. Meanwhile, if no correction was made to the observed and unobserved variables, the TE of the rice farming with labelled seeds was not statistically different from the unlabelled seeds. The policy implication underscores the necessity for public policies to ensure the quality of labelled seeds used by farmers and to encourage adherence to the prescribed cultivation practices for labelled seeds.

Authors

Institutions

Publication Details

Journal
Cogent Food & Agriculture
Published
2025-09-12
DOI
https://doi.org/10.1080/23311932.2025.2558944
Primary Topic
Efficiency Analysis Using DEA
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The impact of labelled seeds on the technical efficiency of rice farming in Indonesia

Tursina Andita Putri, Harmini Harmini, Dwi Rachmina, Harianto Harianto
Cogent Food & Agriculture
Efficiency Analysis Using DEA
article

The impact of labelled seeds on the technical efficiency of rice farming in Indonesia

Tursina Andita Putri, Harmini Harmini, Dwi Rachmina, Harianto Harianto
article en

Abstract

One of the governmental strategies to enhance the national rice production involves improving farmers’ access to high-quality seeds through subsidies and the distribution of labelled rice seeds. This research aims to assess rice cultivation’s technical efficiency using labelled seeds compared to those without. Earlier investigations into the impact of labelled seeds on rice farming performance did not account for potential biases carried on by variables that are both observed and unobserved variables. This study utilized household-level data from 14 districts situated in the rice production centre of Indonesia. Propensity score matching was employed to mitigate observed variable biases, while selectivity-corrected stochastic production frontier models were applied to address biases associated with unobserved variables. The findings revealed that rice farming with labelled seeds demonstrated greater technical efficiency than farming with unlabelled seeds. Meanwhile, if no correction was made to the observed and unobserved variables, the TE of the rice farming with labelled seeds was not statistically different from the unlabelled seeds. The policy implication underscores the necessity for public policies to ensure the quality of labelled seeds used by farmers and to encourage adherence to the prescribed cultivation practices for labelled seeds.

Cogent Food & AgricultureVol. 11(1)
IPB University (ID)
Openalex Percentile: Top 69%
Efficiency Analysis Using DEA
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.