Gender and Income Differences among Workers: Evidence from the Agricultural Sector in Vietnam

As economies grow, social and economic challenges also become more visible. Gender-based income inequality remains a key concern for both researchers and policymakers. In Vietnam, this issue is drawing attention from the government, civil society, and workers. There is a shared interest in promoting stable and balanced development. This study examines income differences between men and women in the agricultural sector. The data come from a 2025 survey of 498 agricultural workers in Vietnam. The analysis uses an Ordinary Least Squares (OLS) model and a t-test to evaluate the effect of gender on income. The findings revealed that, when comparing income differences by gender among workers in the same occupation, men typically earn more than women. Specifically, the standardized coefficient beta for the interaction between gender and job position is −0.059. Additionally, men also earn more than women when they have the same education level, with a standardized coefficient beta of −0.290 for the interaction between gender and education level. The income difference test further indicated that men's income is generally higher than women's by approximately VND 6,011,000 per month (equivalent to approximately USD 228 per month). Based on these findings, the study puts forward several recommendations to reduce gender-based income disparities among agricultural workers in Vietnam.

Authors

Institutions

Publication Details

Journal
Research on World Agricultural Economy
Published
2026-10-27
DOI
https://doi.org/10.36956/rwae.v7i4.105655
Primary Topic
Labour Market and Migration
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Gender and Income Differences among Workers: Evidence from the Agricultural Sector in Vietnam

Thi Yen Le, Van Hung Pham
Research on World Agricultural Economy
Labour Market and Migration
article

Gender and Income Differences among Workers: Evidence from the Agricultural Sector in Vietnam

Thi Yen Le, Van Hung Pham
article en

Abstract

As economies grow, social and economic challenges also become more visible. Gender-based income inequality remains a key concern for both researchers and policymakers. In Vietnam, this issue is drawing attention from the government, civil society, and workers. There is a shared interest in promoting stable and balanced development. This study examines income differences between men and women in the agricultural sector. The data come from a 2025 survey of 498 agricultural workers in Vietnam. The analysis uses an Ordinary Least Squares (OLS) model and a t-test to evaluate the effect of gender on income. The findings revealed that, when comparing income differences by gender among workers in the same occupation, men typically earn more than women. Specifically, the standardized coefficient beta for the interaction between gender and job position is −0.059. Additionally, men also earn more than women when they have the same education level, with a standardized coefficient beta of −0.290 for the interaction between gender and education level. The income difference test further indicated that men's income is generally higher than women's by approximately VND 6,011,000 per month (equivalent to approximately USD 228 per month). Based on these findings, the study puts forward several recommendations to reduce gender-based income disparities among agricultural workers in Vietnam.

Research on World Agricultural EconomyVol. 7(4)
National Economics University (VN), Hanoi Architectural University (VN)
Openalex Percentile: Top 6%
Labour Market and Migration
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.

Laika access coming soon