Abstract
This paper examines the effect of dialect distance on firm performance in underdeveloped counties within urban agglomerations, using dialect similarity as a conceptual entry point and firms as the primary unit of analysis. Drawing on a panel of 33,228 firm-year observations from underdeveloped counties from 2012 to 2015, we employ a fixed-effects model to identify the causal influence of dialect similarity on firm performance and explore the underlying mechanisms. We document several key findings: (a) greater dialect similarity significantly improves firm performance in these regions; (b) this effect is stronger among older firms and more pronounced in non-state-owned enterprises; (c) the positive impact is amplified in urban agglomerations with higher internet development, greater urban primacy, and higher per capita GDP; (d) dialect similarity enhances performance through increased sales, lower sales and financing costs, higher capital investment, and improved human capital; (e) further analysis suggests that cultural effects, rather than communication effects, drive the results. The study offers theoretical insights and policy implications for promoting common prosperity at the urban agglomeration level.
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Data availability
To balance the transparency of academic research, data property rights protection, and the coherence of subsequent studies, we have divided data availability into two parts for detailed explanation: (A) Publicly available data: (a1) Manual compilation of dialect databases: We invested substantial manpower and time in manually identifying the paper maps of the “China Language Atlas (2nd Edition)” and performing precise matching against administrative divisions, resulting in foundational databases such as the “Statistics of Chinese Dialects in Impoverished Counties.” This data represents original human labor and holds significant academic value. To advance subsequent research in dialects and regional economics, we sincerely make these manually compiled original dialect data and related code publicly available, enabling researchers to reproduce or expand their studies. (a2) Original indicator data of urban agglomerations: We also disclose the original data of urban agglomeration-related indicators to provide data support for academic discussions on spatial evolution of urban agglomerations and related fields. (B) Non-publicly available data: (b1) China industrial enterprise database: The micro-level enterprise data we use comes from the “China Industrial Enterprise Database.” According to data purchase agreements and relevant confidentiality regulations, this database contains a large amount of sensitive production and operational information at the enterprise level, making it legally impermissible to disclose directly to third parties. (b2) Dialect diversity: As other papers using this core indicator are currently under review, to protect research originality and prevent premature leakage or improper plagiarism of the metrics, the data of this derived indicator are temporarily not disclosed. The online link to the publicly available data is provided below: https://pan.baidu.com/s/1TtDBL1ZfHCEwQKRjp7xxWQ?pwd=u8tb. Researchers may access the relevant data by visiting this open-source URL. Additionally, despite certain restrictions, we still support reasonable academic exchanges. If researchers require access to non-public data or computational results for academic purposes, they may directly contact the corresponding author of our paper to submit an application. Provided that the necessary data usage commitment letter is signed and the data confidentiality agreement is not violated, we will endeavor to provide assistance.
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Shaopeng Zhang and Qiang Li wrote the main manuscript text, Shubin Wang prepared Tables 1–4, and Jing Yang prepared Fig. 1 and Tables 5–10. All authors revised the manuscript.
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Zhang, S., Li, Q., Wang, S. et al. The impact of dialect distance on firm performance in underdeveloped counties: evidence from urban agglomerations. Humanit Soc Sci Commun (2026). https://doi.org/10.1057/s41599-026-07022-4
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DOI: https://doi.org/10.1057/s41599-026-07022-4
