Lost in translation: Dialect distance, social assimilation and immigrant crimes in China

IF 5.5 1区 经济学 Q1 ECONOMICS 中国经济评论 Pub Date : 2025-06-01 Epub Date: 2025-04-09 DOI:10.1016/j.chieco.2025.102410
Wen Liu , Zhicheng Xu
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Abstract

This study offers a novel perspective on migrant crime by focusing on internal migration within China, distinguishing it from the predominant literature that examines international migration. Using a large dataset of over 6 million criminal convictions during 2000–2020, we document the significantly positive link between the cultural barrier proxied by dialectal distances and the criminal behaviors among immigrants under the dyadic specification. This effect is particularly pronounced among migrants with lower educational attainment and male migrants. We employ a series of robustness checks and instrumental variable estimations, confirming the causality. Furthermore, we identify the underlying mechanism, showing that the impact of dialectal distance on crime is driven primarily by challenges in social assimilation and a weak sense of local identity, rather than factors such as immigrant population size or dialect communication barriers. These findings highlight the crucial role of fostering an inclusive pro-immigrant culture and supportive policies to reduce crime. Our study emphasizes the need to address cultural barriers and enhance social integration to mitigate criminal behavior among immigrant workers in China.
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迷失在翻译中:中国的方言距离、社会同化与移民犯罪
本研究通过关注中国国内的移民,为移民犯罪提供了一个新的视角,将其与研究国际移民的主流文献区分开来。利用2000-2020年间超过600万起刑事定罪的大型数据集,我们证明了方言距离代表的文化障碍与二元规范下移民犯罪行为之间的显著正相关。这种影响在受教育程度较低的移民和男性移民中尤为明显。我们采用一系列稳健性检查和工具变量估计,确认因果关系。此外,我们确定了潜在的机制,表明方言距离对犯罪的影响主要是由社会同化的挑战和地方认同感的薄弱驱动的,而不是移民人口规模或方言交流障碍等因素。这些发现强调了培养包容的亲移民文化和支持性政策在减少犯罪方面的关键作用。本研究强调了解决文化障碍和加强社会融合的必要性,以减少中国外来务工人员的犯罪行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
中国经济评论
中国经济评论 ECONOMICS-
CiteScore
10.60
自引率
4.40%
发文量
380
期刊介绍: The China Economic Review publishes original works of scholarship which add to the knowledge of the economy of China and to economies as a discipline. We seek, in particular, papers dealing with policy, performance and institutional change. Empirical papers normally use a formal model, a data set, and standard statistical techniques. Submissions are subjected to double-blind peer review.
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