Hebei’s Counties Edge Toward Urban-Rural Coordination, but the Same Four Bottlenecks Persist

A decade-long analysis of all 135 counties, county-level cities and urban districts in Hebei Province, China, finds that the coordination between urban–rural integration and county prosperity industries has improved, but only modestly, and that the same handful of constraints has held back progress for eleven consecutive years. The study, published in Frontiers in Sustainable Food Systems, tracked the two systems from 2014 to 2024 using a coupling coordination degree model, a Dagum Gini decomposition of regional disparities, an obstacle factor diagnosis, and a two-way fixed-effects panel regression. It is an observational, county-level panel study of one Chinese province, and its authors are careful to describe the relationships they uncover as statistical associations rather than causal effects.

The headline number is the coupling coordination degree, a composite measure of how well the two systems move together. Across Hebei’s counties it rose from 0.439 in 2014 to 0.510 in 2024, an increase of 16.17 percent. On the study’s ten-tier classification scale, that shift carries the province as a whole from the verge of imbalance, where the two systems interact only weakly, into the barely coordinated band, where they interact positively. The distribution’s center moved from the 0.4–0.5 band to the 0.5–0.6 band, and by 2024 every mildly imbalanced county had disappeared, with 78 counties, or 57.8 percent of the total, classified as barely coordinated.

The improvement was anything but linear. From 2014 to 2019 the degree rose slowly, at roughly 1.24 percent per year, driven largely by catch-up among low-scoring counties under the poverty alleviation campaign, which tilted fiscal transfers and infrastructure investment toward underdeveloped areas. The number of counties in the 0.3–0.4 band fell from 34 to 10 over that stretch, and the standard deviation dropped from 0.058 to 0.048. Then came a sharp break in 2020, when the degree jumped 3.21 percent in a single year, 2.58 times the average annual growth of the previous six years. The authors attribute the jump to a convergence of forces: the final year of the poverty alleviation campaign brought concentrated policy support for agriculture, while the COVID-19 pandemic, despite disrupting farm input distribution and rural sales channels, accelerated the adoption of rural e-commerce and livestream selling and raised the strategic weight of food security.

Regional gaps narrowed steadily over the decade, but the mechanism matters. The overall Gini coefficient fell from 0.074 in 2014 to 0.049 in 2024, and a trend test on the Gini series yields a significantly negative year coefficient, indicating the decline is statistically solid. Decomposition shows that between-group differences across the province’s four functional zones were the largest source of disparity, averaging 40.08 percent annually, followed by the intensity of transvariation at 34.05 percent and within-group differences at 25.87 percent. Crucially, the narrowing came from latecomer catch-up rather than any slowdown in the leading zones. The northwestern ecological conservation zone, which started lowest at 0.396 in 2014, posted the largest gain of all four zones, rising to 0.482, a 21.72 percent increase, helped by ecological compensation funding and poverty-targeted transfers. The coastal zone remained on top throughout, ending at 0.539.

Perhaps the most striking finding is how stable the obstacle structure proved to be. Using an obstacle degree diagnosis that quantifies each indicator’s inhibiting effect on coordination, the researchers found that four indicators held the top four positions from 2014 through 2024: vegetable output, the level of agricultural industry chain extension, per capita general public budget revenue, and road density. Vegetable output led the ranking in every year, with its obstacle degree rising from 6.80 percent to 7.85 percent, and agricultural chain extension followed closely, climbing from 6.60 to 7.14 percent. The top five obstacles together accounted for a growing share of total obstacle degree, up from 30.33 percent in 2014 to 32.51 percent in 2024, meaning the core constraints gained in relative importance even as overall coordination improved.

The persistence of vegetable output at the top of the obstacle list reflects a structural paradox in Hebei’s agricultural economy. The province is a major vegetable producer, and the greenhouse vegetable belt around Beijing and Tianjin is a backbone of county agriculture, but the sector has long shipped out raw produce with a short processing chain and thin value added. Output growth has not translated into value-added growth along the chain. Similarly, the high obstacle degree of agricultural chain extension points to shallow processing of farm products and weak support services across farming sectors. The authors read this as a structural contradiction in county prosperity industries: fast scale expansion, slow chain extension, and weak enrichment effects for farmers.

To probe whether these obstacle rankings reflect genuine drivers, the study turned to a two-way fixed-effects panel regression with 1,485 county-year observations and city-level clustered standard errors. In the preferred specification, vegetable output showed the strongest positive association with the coupling coordination degree, with a coefficient of 0.105, followed by the number of industrial enterprises above designated size at 0.059, road density at 0.041, and agricultural chain extension at 0.031, all significant at the 1 percent level. Notably, general public budget revenue, despite ranking third among obstacles, lost significance entirely once county and year fixed effects were absorbed and standard errors corrected, with a coefficient of just 0.010. The authors suggest fiscal revenue may work indirectly, through the factories, roads, and vegetable infrastructure it funds, channels that are themselves captured in the model.

The findings carry explicit caveats. The obstacle degree model ranks weak links by statistical association and does not identify causal parameters; the fixed-effects regression controls for time-invariant county characteristics and common year shocks but cannot rule out time-varying confounders. County-level statistics in Hebei carry known quality issues, including proxied indicators, interpolated missing values, and self-reported fiscal and industrial figures, which the authors note likely attenuates coefficients, particularly on the fiscal side. The analysis also treats counties as independent units despite documented spatial spillovers in agricultural integration, and it does not split the sample by terrain. The authors suggest future work could exploit policy rollouts, such as the 2017 Beijing–Tianjin industrial transfer or ecological compensation expansions, as quasi-experimental variation to sharpen causal inference.

The policy implications the authors draw are zone-specific rather than uniform. For the coastal leading development zone, where agricultural chain extension led obstacles before 2017 and transport connectivity has since climbed, the priority is processing and cold-chain logistics that capture value locally, plus rural–urban transport links connecting wholesale markets to processing parks and ports. For the core functional zone around Beijing and Tianjin, the lever is deeper supply-chain integration with the two megacities and eased factor flows. For the central-southern expansion zone, where the vegetable output obstacle peaked at 8.12 percent in 2023, the highest of any zone, the emphasis falls on vegetable processing clusters and cold-chain capacity. For the northwestern ecological zone, where weak fiscal self-sufficiency and narrow industrial options dominate under a water-source conservation mandate, the recommendation is expanded and predictable ecological compensation alongside ecotourism and specialty agriculture.

More broadly, the study’s central lesson is that in a large agricultural province the persistent obstacle to coupling urban and rural systems is not output scale but chain depth and factor connectivity. The authors frame the stable eleven-year obstacle structure as evidence that the gap is structural and will not close on its own, and they propose monitoring the zone-specific package over the next planning cycle to test whether the diagnosis holds. They also caution that Hebei is a particular case, a northern coastal province next to two megacities, carrying a national food-basket mandate and hosting a critical water-source conservation zone, so the magnitudes are Hebei’s, even if the analytical framework of coupling two interacting rural systems may travel to neighboring provinces in the North China Plain and beyond.

Subject of Research: Coupling coordination between urban–rural integration and county prosperity industries across 135 counties in Hebei Province, China, from 2014 to 2024

Article Title: Coupling coordination of urban–rural integration and county prosperity industries: identifying obstacle factors using empirical data from 135 counties in Hebei Province, China

Article References: Huang, S., Wang, Y., Jia, L., Cai, N., Wang, W., & Shang, D. (2026). Coupling coordination of urban–rural integration and county prosperity industries: identifying obstacle factors using empirical data from 135 counties in Hebei Province, China. Frontiers in Sustainable Food Systems, 10, Article 1962078. https://doi.org/10.3389/fsufs.2026.1962078

Image Credits: AI Generated

DOI: 10.3389/fsufs.2026.1962078

Keywords: urban–rural integration, county prosperity industries, coupling coordination degree, Hebei Province, Dagum Gini coefficient, obstacle factor diagnosis, vegetable output, agricultural chain extension, panel regression, regional convergence, rural revitalization, China