BEIJING, Feb. 4 (Xinhua) – China has recorded a reduction in the urban-rural income disparity in recent years amid efforts to increase farmers’ income, official data showed.
The urban-rural income ratio narrowed to 2.31:1 in 2025, down from 2.56:1 in 2020, Han Wenxiu, head of the Office of the Central Rural Work Leading Group, told a press conference on Wednesday.
In 2025, the per capita disposable income of farmers reached 24,456 yuan (about 3,517 U.S. dollars), marking a year-on-year growth of 6 percent, he noted, adding that farmers’ basic living conditions have seen consistent improvements.
The remarks came after China released its annual “No. 1 central document” on Tuesday, which outlined key tasks for advancing agricultural and rural modernization and promoting all-around rural revitalization in 2026.
Zhu Weidong, deputy head of the office, emphasized that steady income growth for farmers remains a top priority. The country will promote county-level industries, stabilize migrant workers’ employment, and revitalize rural resources to diversify farmers’ income sources, he noted.
Excellent progress on one of the larger contradictions the CPC must tackle as time goes on in constructing a prosperous socialist society for all.
Ah that’s nice, good for them.
Is there a graph that could estimate the rate at which the gap decreases? I’d like to see if the decrease follows a linear, exponential, or polynomial trend from when the PRC’s primary contradiction shifted to minimizing the gap between rural and urban.
It’s a pretty simple set of data points so I’d imagine it would be easy enough to make.
There has to be data points but sadly, due to the language barrier, I am unable to find the data source that might help us with this. 🫠
Hopefully, a comrade from Lemmygrad that knows mandarin might help us search for it.
Inshahallah.
Also I just realized that a polynomial trend wouldn’t really be that helpful because you can just increase the degree until R2 is nearly identical, however that wouldn’t actually tell you anything about the behavior of data.
But at what cost?





