Mobility Shocks and Regional Wage Inequality: Evidence from Romania during the COVID-19 Lockdown

County-level data on net average monthly wages and the number of employees, obtained from the Monthly Statistical Bulletins published by the Romanian National Institute of Statistics (NIS), were used to compute Gini coefficients for each of Romania’s eight development regions (North-West, Centre, North-East, South-East, South-Muntenia, Bucharest-Ilfov, South-West Oltenia, and West) and for the main economic sectors: agriculture, forestry and fishing; industry and construction; and services. The study period extends from January 2019 to July 2021, covering both the pre-pandemic period and the first waves of the COVID-19 crisis. The dataset includes Gini coefficients, changes in human mobility across six categories, namely (i) retail and recreation, (ii) grocery and pharmacy, (iii) parks, (iv) transit stations, (v) workplaces, and (vi) residential areas, based on the Google COVID-19 Community Mobility Reports. Additional variables collected at a monthly frequency include exports per capita, unemployment rates, and natural population growth, sourced from the Romanian National Institute of Statistics. Research hypotheses: H1: Demographic factors exert a statistically significant and stronger influence on income inequality during the COVID 19 health crisis compared to the pre pandemic period. H2: The determinants of intra regional wage disparity differ significantly across economic sectors, indicating sector specific inequality dynamics. H3: Reductions in human mobility associated with the COVID 19 pandemic have a positive and statistically significant effect on intra regional between county wage inequality. Findings provide evidence in support of the three proposed hypotheses.本研究依托罗马尼亚国家统计局（National Institute of Statistics, NIS）发布的月度统计公报中的县级月均净工资与雇员人数数据，测算得到罗马尼亚8个发展大区（西北、中部、东北、东南、南蒙特尼亚、布加勒斯特-伊尔夫、西南奥尔特尼亚、西部）及三大主要经济部门（农林渔业、工业与建筑业、服务业）的基尼系数（Gini Coefficient）。研究时段为2019年1月至2021年7月，覆盖新冠疫情暴发前阶段与新冠疫情首轮流行浪潮。本数据集包含以下内容：其一为各区域与经济部门的基尼系数；其二为基于谷歌新冠社区流动报告（Google COVID-19 Community Mobility Reports）的六大类人类流动变化数据，具体类别包括：(i) 零售与休闲场所、(ii) 食品杂货店与药店、(iii) 公园、(iv) 交通枢纽、(v) 工作场所、(vi) 居住区；其三为月度频率的额外变量，涵盖人均出口额、失业率与自然人口增长率，上述数据均来源于罗马尼亚国家统计局。研究提出三项假设如下： H1：相较于疫情前时期，新冠疫情期间人口统计因素对收入不平等的影响在统计学上更为显著且强度更高； H2：区域内部工资差距的决定因素在不同经济部门间存在显著差异，体现出部门特异性的不平等动态特征； H3：与新冠疫情相关的人类流动减少对区域内部县级间工资不平等具有正向且统计学上显著的影响。本研究的实证结果为上述三项研究假设提供了支撑依据。