C
CPPPS 中国综合评价指数
China Panoramic Public Performance Score
中国榜 · 县域 China · Counties

县域经济百强County Economy

全国百强县 / 经济强县 · 六维加权模型 · 排名更新日期：2026-10-20Top 100 counties / strong economic counties · Six-dimensional weighted model · Last updated: 2026-10-20

综述Overview

County-level economies are the bedrock of China's economy. More than 2,800 county-level administrative divisions carry over half of the population and contribute about 40% of GDP and nearly half of fiscal revenue; among them, the top 100 counties—fewer than 4% of all county-level divisions—create about one-tenth of county-level economic output, making them the most vivid samples of China's industrialization, urbanization, and industrial clustering. Leading counties and cities represented by Kunshan, Jiangyin, Zhangjiagang, Jinjiang, and Cixi each have an economic scale exceeding that of most prefecture-level cities and even some provincial capitals.
县域是中国经济的基本盘。全国 2800 余个县级行政区承载着过半人口，贡献着约四成的 GDP 与近半的财政收入；其中百强县以不足全国县域 4% 的数量，创造了约十分之一的县域经济总量，是中国工业化、城镇化与产业集群最鲜活的样本。以昆山、江阴、张家港、晋江、慈溪为代表的头部县市，单个经济体量已超过多数地级市甚至部分省会。
The evaluation of county-level economies must look at both total scale and quality and structure. This index selects six indicators—GDP, fiscal revenue, per-capita GDP, industrial value added, resident population, and industrial structure—to conduct a weighted comprehensive evaluation of the country's economically strong counties (based on the CCID Top 100 Counties and the Zhongjun County Economy Top 100, totaling 100 counties and county-level cities): GDP and fiscal revenue carry the highest weights (25% each), reflecting "size" and "family wealth"; per-capita GDP and industrial value added each account for 15%, measuring output efficiency and real manufacturing capability; industrial structure and resident population each account for 10%, characterizing the degree of industrialization and county scale.
县域经济的评价，既要看总量规模，也要看质量与结构。本指数选取 GDP、财政收入、人均 GDP、工业增加值、常住人口、产业结构 六项指标，对全国经济强县（以赛迪百强县、中郡县域经济百强为蓝本，共 100 个县及县级市）进行加权综合评价：GDP 与财政收入权重最高（各 25%），体现"块头"与"家底"；人均 GDP 与工业增加值各占 15%，衡量产出效率与实体制造能力；产业结构与常住人口各占 10%，刻画工业化程度与县域体量。
Results: Kunshan, Jiangyin, Zhangjiagang, Jinjiang, and Shenmu rank in the top five. Jiangsu and Zhejiang counties in the Yangtze River Delta hold absolute dominance, with the "Four Great Kings" of southern Jiangsu (Kunshan, Jiangyin, Zhangjiagang, Changshu) and Jinjiang in southern Fujian firmly in the first tier; energy counties such as Shenmu, Jungar Banner, and Ejin Horo Banner enter the front ranks through extremely high per-capita output and secondary-industry share; and Renhuai (Moutai) stands out uniquely through its baijiu industry. This ranking is based on public-list common knowledge and 2023 official approximations, marked "subject to official figures", permanently free and public, for research and reference only.
评价结果：昆山市、江阴市、张家港市、晋江市、神木市 位列前五。长三角的江苏、浙江县域占据绝对优势，苏南"四大天王"（昆山、江阴、张家港、常熟）与闽南晋江稳居第一梯队；神木、准格尔旗、伊金霍洛旗等能源县市凭借极高的人均产出与二产占比跻身前列；仁怀（茅台）以白酒产业一枝独秀。本排名数据以公开榜单常识与 2023 年官方近似值为依据，标注"以官方为准"，永久免费公开，仅供研究与参考。

分层梯队Tiers

A++ 前三Top 3 A+ 四至十4th–10th A 十一至三十 B 三十一至六十 C 其余Rest

县域经济百强排名Top 100 County Economies Ranking

排名县市综合得分GDP(亿)财政(亿)人均GDP(万)工业(亿)人口(万)二产占比梯队
1昆山市Kunshan, Jiangsu · Suzhou
江苏·苏州
88.43514046024.5260021051%A++
2江阴市Jiangyin, Jiangsu · Wuxi
江苏·无锡
74.38496025027.5250018052%A++
3张家港市Zhangjiagang, Jiangsu · Suzhou
江苏·苏州
55.61336022024.0175014052%A++
4晋江市Jinjiang, Fujian · Quanzhou
福建·泉州
53.79336315017.0190019856%A+
5神木市Shenmu, Shaanxi · Yulin
陕西·榆林
51.14230013040.017005774%A+
6慈溪市Cixi, Zhejiang · Ningbo
浙江·宁波
48.42263923014.0135018852%A+
7常熟市Changshu, Jiangsu · Suzhou
江苏·苏州
48.26280022018.5140015050%A+
8宜兴市Yixing, Jiangsu · Wuxi
江苏·无锡
37.92233813018.5120012650%A+
9长沙县Changsha County, Hunan · Changsha
湖南·长沙
37.24212915015.0110014252%A+
10仁怀市Renhuai, Guizhou · Zunyi
贵州·遵义
35.0616008524.012006672%A+
11准格尔旗Jungar Banner, Inner Mongolia · Ordos
内蒙古·鄂尔多斯
33.2914009033.09004365%A
12太仓市Taicang, Jiangsu · Suzhou
江苏·苏州
32.99173517020.08508749%A
13龙口市Longkou, Shandong · Yantai
山东·烟台
30.30160011518.59008756%A
14浏阳市Liuyang, Hunan · Changsha
湖南·长沙
30.01180010012.590014550%A
15诸暨市Zhuji, Zhejiang · Shaoxing
浙江·绍兴
29.17180010015.090012048%A
16余姚市Yuyao, Zhejiang · Ningbo
浙江·宁波
29.09170011013.085013050%A
17义乌市Yiwu, Zhejiang · Jinhua
浙江·金华
29.03205614011.060018829%A
18伊金霍洛旗Ejin Horo Banner, Inner Mongolia · Ordos
内蒙古·鄂尔多斯
27.9512008028.07504362%A
19胶州市Jiaozhou, Shandong · Qingdao
山东·青岛
27.77160011016.080010050%A
20乐清市Yueqing, Zhejiang · Wenzhou
浙江·温州
27.75170010012.080014546%A
21南安市Nan'an, Fujian · Quanzhou
福建·泉州
27.731600709.585017053%A
22福清市Fuqing, Fujian · Fuzhou
福建·福州
27.0316009011.580014050%A
23府谷县Fugu County, Shaanxi · Yulin
陕西·榆林
25.129006025.06503672%A
24海宁市Haining, Zhejiang · Jiaxing
浙江·嘉兴
24.70140010013.070010850%A
25如皋市Rugao, Jiangsu · Nantong
江苏·南通
24.5916007512.075013046%A
26溧阳市Liyang, Jiangsu · Changzhou
江苏·常州
24.1615008015.57209748%A
27丹阳市Danyang, Jiangsu · Zhenjiang
江苏·镇江
23.5415007015.072010048%A
28桐乡市Tongxiang, Zhejiang · Jiaxing
浙江·嘉兴
23.3813009513.065010550%A
29泰兴市Taixing, Jiangsu · Taizhou
江苏·泰州
22.6614007512.068011548%A
30温岭市Wenling, Zhejiang · Taizhou
浙江·台州
22.1614008510.560013543%A
31宁乡市Ningxiang, Hunan · Changsha
湖南·长沙
22.081300659.565013850%B
32靖江市Jingjiang, Jiangsu · Taizhou
江苏·泰州
22.0213007515.06508750%B
33启东市Qidong, Jiangsu · Nantong
江苏·南通
21.9214507013.065011045%B
34南昌县Nanchang County, Jiangxi · Nanchang
江西·南昌
21.441300559.565013750%B
35瑞安市Rui'an, Zhejiang · Wenzhou
浙江·温州
21.331300909.055014542%B
36迁安市Qian'an, Hebei · Tangshan
河北·唐山
21.1012006015.06508054%B
37海安市Hai'an, Jiangsu · Nantong
江苏·南通
20.7913007013.062010047%B
38惠安县Hui'an County, Fujian · Quanzhou
福建·泉州
20.6812005514.06508554%B
39沭阳县Shuyang County, Jiangsu · Suqian
江苏·宿迁
20.621400608.555016540%B
40新郑市Xinzheng, Henan · Zhengzhou
河南·郑州
18.9112006010.055012046%B
41平湖市Pinghu, Zhejiang · Jiaxing
浙江·嘉兴
18.8410007514.05507052%B
42邳州市Pizhou, Jiangsu · Xuzhou
江苏·徐州
18.031200558.050014542%B
43嘉善县Jiashan County, Zhejiang · Jiaxing
浙江·嘉兴
17.589007514.04806552%B
44荣成市Rongcheng, Shandong · Weihai
山东·威海
17.5211006515.05007345%B
45邹城市Zoucheng, Shandong · Jining
山东·济宁
17.521000708.548011548%B
46肥西县Feixi County, Anhui · Hefei
安徽·合肥
17.3911005511.052010047%B
47石狮市Shishi, Fujian · Quanzhou
福建·泉州
17.1911005515.55007046%B
48长兴县Changxing County, Zhejiang · Huzhou
浙江·湖州
16.279006513.54506750%B
49滕州市Tengzhou, Shandong · Zaozhuang
山东·枣庄
16.07900605.538016542%B
50寿光市Shouguang, Shandong · Weifang
山东·潍坊
16.021000759.042011042%B
51宁海县Ninghai County, Zhejiang · Ningbo
浙江·宁波
16.019006013.04607050%B
52巩义市Gongyi, Henan · Zhengzhou
河南·郑州
15.499005511.54507850%B
53仙桃市Xiantao, Hubei
湖北·省直辖
15.421000509.045011045%B
54招远市Zhaoyuan, Shandong · Yantai
山东·烟台
15.338506014.04206050%B
55兴化市Xinghua, Jiangsu · Taizhou
江苏·泰州
15.321100508.542012540%B
56东台市Dongtai, Jiangsu · Yancheng
江苏·盐城
14.7010005510.042010042%B
57醴陵市Liling, Hunan · Zhuzhou
湖南·株洲
14.689004010.04509050%B
58高邮市Gaoyou, Jiangsu · Yangzhou
江苏·扬州
14.3810005012.04208542%B
59海盐县Haiyan County, Zhejiang · Jiaxing
浙江·嘉兴
14.327005515.03804753%B
60武安市Wu'an, Hebei · Handan
河北·邯郸
13.94700458.54008057%B
61永康市Yongkang, Zhejiang · Jinhua
浙江·金华
13.908006011.53807048%C
62广饶县Guangrao County, Shandong · Dongying
山东·东营
13.737005012.53805654%C
63禹州市Yuzhou, Henan · Xuchang
河南·许昌
13.64900458.040011044%C
64沛县Pei County, Jiangsu · Xuzhou
江苏·徐州
13.52900457.038012542%C
65诸城市Zhucheng, Shandong · Weifang
山东·潍坊
13.38800608.036010045%C
66潜江市Qianjiang, Hubei
湖北·省直辖
13.339004510.04009044%C
67临海市Linhai, Zhejiang · Taizhou
浙江·台州
13.25800557.035011544%C
68博罗县Boluo County, Guangdong · Huizhou
广东·惠州
13.21800506.535012344%C
69德清县Deqing County, Zhejiang · Huzhou
浙江·湖州
13.187006012.53505550%C
70新沂市Xinyi, Jiangsu · Xuzhou
江苏·徐州
12.87900457.536012040%C
71盘州市Panzhou, Guizhou · Liupanshui
贵州·六盘水
12.75700406.035011550%C
72闽侯县Minhou County, Fujian · Fuzhou
福建·福州
12.417005010.03507050%C
73永城市Yongcheng, Henan · Shangqiu
河南·商丘
12.34700455.532012546%C
74大冶市Daye, Hubei · Huangshi
湖北·黄石
12.33700458.03508850%C
75丰城市Fengcheng, Jiangxi · Yichun
江西·宜春
12.33700405.532013046%C
76肥东县Feidong County, Anhui · Hefei
安徽·合肥
12.30800457.535010544%C
77枣阳市Zaoyang, Hubei · Xiangyang
湖北·襄阳
12.17800406.534012043%C
78莱州市Laizhou, Shandong · Yantai
山东·烟台
12.137505510.53407245%C
79汉川市Hanchuan, Hubei · Xiaogan
湖北·孝感
12.12800357.536010745%C
80玉环市Yuhuan, Zhejiang · Taizhou
浙江·台州
11.957005510.53306747%C
81长丰县Changfeng County, Anhui · Hefei
安徽·合肥
11.72800407.534010543%C
82天长市Tianchang, Anhui · Chuzhou
安徽·滁州
11.377004510.53306747%C
83邹平市Zouping, Shandong · Binzhou
山东·滨州
11.23600558.53007050%C
84四会市Sihui, Guangdong · Zhaoqing
广东·肇庆
11.127004511.03206446%C
85安宁市Anning, Yunnan · Kunming
云南·昆明
11.056004512.53004850%C
86瓦房店市Wafangdian, Liaoning · Dalian
辽宁·大连
11.04700407.53209346%C
87东阳市Dongyang, Zhejiang · Jinhua
浙江·金华
10.90700558.53008243%C
88任丘市Renqiu, Hebei · Cangzhou
河北·沧州
10.60600407.03008550%C
89库尔勒市Korla, Xinjiang · Bayingolin
新疆·巴州
10.44700407.030010043%C
90高州市Gaozhou, Guangdong · Maoming
广东·茂名
10.35750355.528013537%C
91惠东县Huidong County, Guangdong · Huizhou
广东·惠州
10.33750407.030010540%C
92肥城市Feicheng, Shandong · Tai'an
山东·泰安
10.13650456.528010043%C
93长葛市Changge, Henan · Xuchang
河南·许昌
10.06650409.03007246%C
94西昌市Xichang, Sichuan · Liangshan
四川·凉山
10.05650457.02809543%C
95简阳市Jianyang, Sichuan · Chengdu
四川·成都
10.05600354.525013542%C
96海城市Haicheng, Liaoning · Anshan
辽宁·鞍山
8.95600356.026010043%C
97三河市Sanhe, Hebei · Langfang
河北·廊坊
8.72600457.52508042%C
98庄河市Zhuanghe, Liaoning · Dalian
辽宁·大连
8.58600356.52609043%C
99宣威市Xuanwei, Yunnan · Qujing
云南·曲靖
7.40500304.020012040%C
100仁寿县Renshou County, Sichuan · Meishan
四川·眉山
6.67500304.018012536%C

算法详细论述Methodology

一、县域经济的评价维度与理论依据

County-level economy is a classic research subject in regional economics. This algorithm uses six quantifiable indicators to characterize the four facets of a county economy—"scale, efficiency, structure, and real economy":
县域经济是区域经济学的经典研究对象。本算法以六个可量化指标刻画县域经济的"规模—效率—结构—实体"四个侧面：
  1. GDP（地区生产总值）：衡量经济总量规模，是县域经济实力的第一标尺——依据国家统计局国民经济核算体系（SNA）口径。
  2. 财政收入（一般公共预算收入）：衡量地方政府可用财力与真实"造血"能力，反映经济增长质量与产业税源基础。
  3. 人均 GDP：衡量产出效率与发展阶段，消除县域间人口基数差异，体现"发展质量"——依据世界银行人均 GDP 发展阶段划分惯例。
  4. 工业增加值（含二产增加值）：衡量实体经济与制造能力——制造业是县域现代化的根基，呼应"脱虚向实"导向。
  5. 常住人口：衡量县域体量与集聚规模——人口是要素集聚的结果，也是市场规模与劳动供给的基础。
  6. 产业结构（二产占比）：衡量工业化程度——依据钱纳里（Chenery）工业化阶段理论，二产占比是县域工业化水平的直接表征。

二、模型的数学结构

This model uses linear weighted summation. Each indicator is first mapped to the [0,1] interval through min-max normalization, then weighted:
本模型采用线性加权求和。各指标先经最小—最大归一化映射到 [0,1] 区间，再按权重加权：
x′ = (x − xmin) / (xmax − xmin) 综合得分 = 100 × ( 0.25·GDP′ + 0.25·财政′ + 0.15·人均GDP′ + 0.15·工业′ + 0.10·结构′ + 0.10·人口′ )
The logic of the weight design: GDP and fiscal revenue are tied at the highest weight (25% each), because they are the core of a county economy's "total scale" and "fiscal strength", and are also the foremost indicators recognized in government assessment and public rankings; per-capita GDP and industrial value added (15% each) reflect efficiency and the real economy respectively; industrial structure and resident population (10% each) serve as structural and scale correction terms.
权重设计逻辑：GDP 与财政收入并列最高权重（各 25%），因二者是县域经济"总量"与"财力"的核心，也是政府考核与榜单公认的首要指标；人均 GDP 与工业增加值（各 15%）分别体现效率与实体；产业结构与常住人口（各 10%）作为结构与规模修正项。

三、指标与权重依据

指标方向权重衡量依据
GDP 总量正向0.25规模国民经济核算 SNA；百强县首要标尺
一般公共预算收入正向0.25财力财政造血与税源质量
人均 GDP正向0.15效率世界银行发展阶段划分
工业增加值正向0.15实体制造业根基；脱虚向实
产业结构（二产占比）正向0.10结构钱纳里工业化阶段理论
常住人口正向0.10体量要素集聚与市场规模

四、榜单参照与可比性

The CCID Consulting study "China's Top 100 County Economies" evaluates by dimensions such as economic strength, growth potential, prosperity, and green level; the Zhongjun County Economy Institute's "County Economy and County Development Monitoring and Evaluation" focuses on economic aggregate, per-capita level, quality, vitality, and sustainability. On the basis of these two, this index simplifies into a six-variable weighted model, highlighting the two hard indicators of GDP and fiscal revenue while balancing efficiency and structure, striving to be concise, transparent, and reproducible.
赛迪顾问《中国县域经济百强研究》以经济实力、增长潜力、富裕程度、绿色水平等维度评价；中郡县域经济研究所《县域经济与县域发展监测评价》以经济总量、均量、质量、活力与可持续性为主线。本指数在二者基础上简化为六维加权模型，突出 GDP 与财政两大硬指标，兼顾效率与结构，力求简洁、透明、可复现。
It should be noted that the "Four Counties of Southern Jiangsu"—Kunshan (Suzhou), Jiangyin, Zhangjiagang, and Changshu—have long been firmly in the first echelon of the nation's counties, forming the head tier together with Jinjiang in Fujian, Cixi in Zhejiang, and Changsha County in Hunan; energy counties and cities (Shenmu, Jungar Banner, Ejin Horo Banner) and the baijiu capital Renhuai rank ahead because of their extremely high per-capita output and secondary-industry share. This is a reasonable result of the model's weighting of "efficiency" and "structure", and is consistent with their true fiscal strength.
需说明：苏州昆山、江阴、张家港、常熟等"苏南四县"长期稳居全国县域第一方阵，与福建晋江、浙江慈溪、湖南长沙县共同构成头部梯队；能源型县市（神木、准格尔旗、伊金霍洛旗）与白酒之都仁怀因人均产出与二产占比极高而排名靠前，这是模型对"效率"与"结构"赋权的合理结果，亦符合其真实财力水平。

五、数据来源与局限性

Data are based on public data from the National Bureau of Statistics and the statistical bulletins and government work reports of counties and cities, combined with common knowledge from public lists such as the CCID Top 100 Counties and the Zhongjun County Economy Top 100, using 2023 approximations; for some counties, industrial value added is approximately replaced by the value added of the secondary industry; industrial structure is expressed as the share of secondary-industry value added in GDP. All values are marked "subject to official figures"; there are differences in statistical scope (such as fiscal scope between county-level cities and counties, and counties directly administered by provinces) and approximation errors, and the ranking is for research and reference only.
数据以国家统计局及各县市统计公报、政府工作报告的公开数据为基准，结合赛迪百强县、中郡县域经济百强等公开榜单常识，取 2023 年近似值；工业增加值部分县市以第二产业增加值近似替代；产业结构以二产增加值占 GDP 比重表示。所有数值标注"以官方为准"，存在口径差异（如县级市与县、省直辖县级市的财政口径）与近似误差，排名仅供研究与参考。

六、参考文献

  1. 赛迪顾问（CCID）：《中国县域经济百强研究》（历年）。
  2. 中郡县域经济研究所：《县域经济与县域发展监测评价报告》（历年）。
  3. 国家统计局：国民经济与社会发展统计公报、分县主要经济指标。
  4. 各县市人民政府：《统计年鉴》《政府工作报告》（GDP、一般公共预算收入、常住人口等）。
  5. 钱纳里（Chenery, H.）：《工业化与经济增长的比较研究》——工业化阶段理论。
  6. 世界银行：《世界发展指标》——人均 GDP 与发展阶段划分。
  7. 张五常：《中国的经济制度》——县域竞争与地方政府行为。
  8. Krugman, P.：新经济地理与集聚理论（空间经济学）。
  9. 国家统计局农村社会经济调查司：《中国县域统计年鉴》。

说明Notes

本版采用六维加权求和模型（线性加权）：综合得分 = 100 × (0.25·GDP + 0.25·财政收入 + 0.15·人均GDP + 0.15·工业增加值 + 0.10·产业结构 + 0.10·常住人口)，各指标经最小—最大归一化后加权。GDP、财政收入权重最高，体现"总量 + 财力"双核。数据以国家统计局及各县市统计公报公开数据为基准、赛迪百强县与中郡县域经济榜单常识为辅，取 2023 年近似值，标注"以官方为准"，存在口径差异与近似误差。评价对象为全国 100 个县及县级市。排名永久免费公开、永不卖榜，仅供研究与参考。
This edition adopts a six-dimension weighted-sum model (linear weighting): composite score = 100 × (0.25·GDP + 0.25·fiscal revenue + 0.15·GDP per capita + 0.15·industrial value added + 0.10·industrial structure + 0.10·permanent population), with each indicator min-max normalized before weighting. GDP and fiscal revenue have the highest weights, reflecting the "aggregate + fiscal strength" dual core. Data are based on public data from the National Bureau of Statistics and county/city statistical bulletins, supplemented by common knowledge from the CCID Top-100 Counties and Zhongjun county economic lists, using 2023 approximate values, marked "subject to official figures", with basis differences and approximate errors. Coverage includes 100 counties and county-level cities nationwide. The ranking is permanently free and public, rankings are never sold, and it is for research and reference only.