School of Economics, Jiangxi University of Finance and Economics, Nanchang, Jiangxi Province, China.
School of Economics and Management, China University of Geosciences (Wuhan), Wuhan, Hubei Province, China.
PLoS One. 2023 Feb 13;18(2):e0273334. doi: 10.1371/journal.pone.0273334. eCollection 2023.
Based on the panel data of 280 prefecture-level cities in China from 2014 to 2018, we construct the digital divide index from three aspects including "access divide", "use divide" and "efficiency divide", using Thiel index to measure income inequality and study the impact of the digital divide on income inequality between different regions. We apply the two-stage spatial DID combined IV model. In the first stage, we introduce the "Internet + government affairs" policy to construct the spatial DID model, so as to obtain the estimated value of the digital divide index. When the estimated value is substituted into the two-stage regression as an instrumental variable, it is found that every 1unit increase in the digital divide will widen the income divide by 0.134 units. This conclusion is still robust under the replacement of Theil index and change of weights. The results of heterogeneity analysis show that digital divide has a more significant impact on the income divide in eastern China in terms of regions. It is found after distinguishing different types of digital divide that the other two types of digital divides have the most significant impact than income divide, 0.034 units higher than that of the traditional. Finally, we introduce the mechanism variables from three levels of "access divide", "use divide" and "efficiency divide", thus verifying the effect of information asymmetry, effect of human capital differentiation and effect of delaying industrial upgrade. Then we put forward the following policy recommendations: in order to reduce the deterioration effect of digital divide on income distribution, it is necessary to improve infrastructure, enhance the degree of digitalization of human capital and optimize the industrial structure.
基于 2014 年至 2018 年中国 280 个地级市的面板数据，我们从“接入鸿沟”“使用鸿沟”和“效率鸿沟”三个方面构建了数字鸿沟指数，采用泰尔指数衡量收入不平等，并研究数字鸿沟对不同地区收入不平等的影响。我们应用了两阶段空间双重差分法结合 IV 模型。在第一阶段，我们引入“互联网+政务”政策构建空间双重差分模型，以获得数字鸿沟指数的估计值。当将估计值代入两阶段回归作为工具变量时，发现数字鸿沟每增加 1 个单位，收入鸿沟就会扩大 0.134 个单位。这一结论在替换泰尔指数和改变权重后仍然稳健。异质性分析的结果表明，数字鸿沟对东部地区的收入鸿沟影响更为显著。在区分不同类型的数字鸿沟后发现，其他两种类型的数字鸿沟比传统数字鸿沟对收入鸿沟的影响更为显著，高出 0.034 个单位。最后，我们从“接入鸿沟”“使用鸿沟”和“效率鸿沟”三个层面引入机制变量，从而验证了信息不对称效应、人力资本差异化效应和延缓产业升级效应。然后我们提出了以下政策建议：为了减少数字鸿沟对收入分配的恶化效应，有必要改善基础设施，提高人力资本的数字化程度，优化产业结构。
