2019冠状病毒病大流行对墨西哥贫困和不平等的影响

Luis Huesca Reynoso, Linda Irene Llamas Rembao, Xavier Holguer Jara Tamayo, César Octavio Vargas Téllez, David Arturo Rodriguez Guerrrero
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引用次数: 5

摘要

目标是量化2019冠状病毒病大流行对墨西哥就业、贫困和不平等的影响。该方法基于probit模型,以识别面临失业风险的个人,根据ENOE和ETOE的调查,这些人的收入在ENIGH 2018中被设定为零,以匹配2019年12月至2020年5月期间观察到的就业和收入变化。墨西哥的微观模拟模型MEXMOD用于模拟基于covid - 19前和covid - 19情景的税收优惠政策。结果显示,失业人数为1210万。贫困人口占60.16%,极端贫困人口占29.73%;不平等增长了8.2%。建议通过追加资金(对富人征税)强化社会政策,实现更大程度的再分配。限制是收入分配保持不变,因为我们没有ENIGH 2020。其独创性在于利用微观模拟技术及时衡量贫困和不平等,以克服大流行期间缺乏数据的问题。研究得出的结论是,没有自动稳定器来应对COVID-19的负面影响,现金转移支付也不足以做到这一点。
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The impact of the COVID-19 pandemic on poverty and inequality in Mexico
The objective is to quantify the effect of the COVID-19 pandemic on employment, poverty and inequality in Mexico. The methodology is based on a probit model to identify individuals at risk of employment loss, whose earnings are set to zero in ENIGH 2018 to match changes in employment and earnings observed in between December 2019 and the May 2020 according to ENOE and ETOE surveys, respectively. MEXMOD, Mexico’s microsimulation model, is used to simulate tax-benefit policies based on the pre-COVID and COVID-scenarios. The results show that there was a loss of 12.1 million jobs. Poverty reached 60.16% and extreme poverty reached 29.73%; inequality grew 8.2%. It is recommended to strengthen social policy with extra funding (taxing the rich) to achieve greater redistribution. The limitation is that income distribution is held constant as we do not have ENIGH 2020. The originality is to offer timely measures of poverty and inequality using microsimulation techniques to overcome the lack of data during the pandemic. The research concludes that there are not automatic stabilizers to cope COVID-19 negative effects and cash-transfers are not sufficient to do so.
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