本文旨在分析中国城乡之间劳动力资源错配的现状、原因及其对经济发展的影响，并探讨新型城镇化在纠正这一问题中的作用。本文首先基于刘易斯理论，提出城乡劳动力流动模型，之后基于多部门均衡模型，计算劳动力错配指数，对中国城乡劳动力市场的错配程度进行了全面的定量分析。通过时间序列和空间分布的视角，评估了劳动力错配的严重性，从全国视角来看，发现2022年农村劳动力错配指数的绝对值高达0.750，显著高于城镇的0.444，表明农村地区劳动力配置效率较低，错配问题更为突出。理论支撑方面，本文采用了广义价值论模型，深入探讨了劳动力错配的本质原因，即城乡劳动力之比与城乡比较生产力之比的不匹配。该理论模型为理解劳动力在不同产业间的流动提供了新的视角，并为政策制定提供了理论依据。本文的主要结论指出，单位劳动力在非农业部门的边际产出高于农业部门，而当前的劳动力配置并未充分体现这一效率差异。此外，中国的劳动力错配问题呈现出明显的经济相关性和地区差异性，提示了不同地区在经济发展水平、产业结构和政策环境方面的差异对劳动力错配的影响：一般来说，在经济较发达的地区，城市劳动力错配指数通常较高；在经济欠发达的地区，农村劳动力错配指数相对较高。此外，本文阐述了新型城镇化是改善劳动力错配的有效途径，通过促进农业转移人口市民化、优化户籍制度、加强基础设施建设以及提升公共服务水平等措施，可以有效提高劳动力配置效率，促进城乡经济的均衡发展。论文的创新之处在于：首先，通过构建和应用多部门均衡模型及劳动力错配指数，提供了一种新的量化工具来评估和分析劳动力市场的错配状况；其次，运用广义价值论模型，从理论上阐释了劳动力错配的经济根源，为相关经济理论提供了新的解释；最后，结合中国的具体国情，提出了一系列切实可行的政策建议，旨在通过新型城镇化进程，促进劳动力的有效配置和经济的高质量发展。这些创新点不仅丰富了劳动力市场和城乡发展的研究，也为政策制定者提供了有价值的参考和指导。

This paper aims to analyze the current state, causes, and impacts on economic development of labor resource misallocation between urban and rural areas in China, and to explore the potential role of new urbanization in addressing this issue. Initially, based on Lewis‘s theory, the paper proposes an urban-rural labor mobility model and then uses a multi-sector equilibrium model to calculate the labor mismatch index, providing a comprehensive quantitative analysis of the mismatch in China‘s urban and rural labor markets. From the perspectives of time series and spatial distribution, the severity of labor mismatch is assessed. Nationally, it was found that in 2022, the rural labor mismatch index reached a high absolute value of 0.750, significantly higher than the urban index of 0.444, indicating lower efficiency in labor allocation in rural areas and more pronounced mismatch issues.In terms of theoretical support, the paper utilizes the generalized theory of value model to delve into the fundamental causes of labor mismatch, specifically the mismatch between the ratio of urban to rural labor and the ratio of comparative productivity between urban and rural areas. This theoretical model provides a new perspective on the movement of labor between different industries and offers a theoretical basis for policy formulation.The main conclusions of the study indicate that the marginal output of labor in non-agricultural sectors is higher than that in the agricultural sector, yet the current allocation of labor does not fully reflect this efficiency difference. Moreover, the issue of labor mismatch in China exhibits significant economic correlation and regional disparities, suggesting that differences in economic development levels, industrial structures, and policy environments across regions affect labor mismatch: generally, in economically developed areas, the urban labor mismatch index tends to be higher; in less developed areas, the rural labor mismatch index is relatively higher. Furthermore, the paper outlines how new urbanization is an effective approach to improving labor mismatch, through measures such as promoting the urbanization of agricultural migrants, optimizing the household registration system, enhancing infrastructure construction, and improving the level of public services. These measures can effectively enhance labor allocation efficiency and promote balanced economic development between urban and rural areas.The innovation of this thesis lies in: firstly, the construction and application of a multi-sector equilibrium model and labor mismatch index, providing a new quantitative tool to assess and analyze the state of labor market mismatches; secondly, the use of the generalized theory of value model to theoretically elucidate the economic roots of labor mismatch, offering new interpretations for related economic theories; and lastly, proposing a series of practical policy recommendations tailored to China‘s specific national conditions, aimed at promoting efficient labor allocation and high-quality economic development through the process of new urbanization. These innovative points not only enrich research on labor markets and urban-rural development but also provide valuable references and guidance for policy-makers.