Panel data-set of the paper Disentangling Covid-19, Economic Mobility, and Containment Policy Shocks

Data-set of the paper Disentangling Covid-19, Economic Mobility, and Containment Policy Shocks for replication purpose of the Data Editor of AEJMacro. 
Detailed information on the data-set is in the readme file in the public repository  openicpsr-175241 (under review).

We study the dynamic interaction between Covid-19, economic mobility, and containment policy. We use Bayesian panel structural vector autoregressions with daily data for 44 countries, identified through traditional and narrative sign restrictions. We find that incidence shocks and containment shocks have large and persistent effects on mobility, morbidity, and mortality that last for 1-2 months. These shocks are the main drivers of the pandemic, explaining between 20-60% of the average and historical variability in mobility, cases, and deaths worldwide. The policy tradeoff associated to non-pharmaceutical interventions is 1pp less economic mobility per day for 8% fewer deaths after three months.

The panel data-set contains the main data to perform the analysis in the paper. It contains dailiy data for (in sheets) Argentina, Australia, Austria, Belgium, Brazil, Canada, Chile, Colombia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hong Kong, Hungary, India, Indonesia, Ireland, Israel, Italy, Japan, Lithuania, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Russia, Saudi Arabia, Slovenia, South Korea, Spain, Sweden, Switzerland, Taiwan, Thailand, Turkey, United Arab Emirates, United Kingdom and United States. Included variables are: Confirmed Cases, Total Deaths, Days Last Reported Case, Total Tests, School Closing, Workplace Closing, Cancel Public Events, Restrictions Gatherings, Close Public Transport, Stay at Home Requirements, Restrictions Internal Movement, International Travel Controls, Income Support, Debt/Contract Relief, Fiscal Measures, International Support, Public Information Campaigns, Testing Policy, Contact Tracing, Healthcare Emergency Investment, Investment Vaccines, Stringency Index, Small Cap, Large Cap, Government Benchmarks 3 Month, Government Benchmarks 1 Year, Government Benchmarks 2 Year, Government Benchmarks 5 Year, Government Benchmarks 10 Year, FX Indices Broad, FX Indices Narrow, Mobility Retail Mobility Grocery,  Mobility Parks, Mobility Transit Stations Mobility Workplaces, Mobility Residential. Period: 30.12.2016 to 31.08.2020. All data are downloaded from Macrobond.

为《AEJMacro》数据编辑部的复制目的，本研究论文《解构新冠疫情、经济流动性及防控政策冲击》的数据集现已公布。该数据集的详细信息可在公开仓库openicpsr-175241（审稿中）的readme文件中找到。本研究所探讨的主题为新冠疫情、经济流动性与防控政策之间的动态相互作用。研究采用贝叶斯面板结构向量自回归模型，以44个国家的每日数据为基础，通过传统及叙事性约束方法进行识别。研究发现，疫情爆发和防控措施对流动性、发病率和死亡率产生了巨大且持久的冲击，这些冲击持续时间长达1-2个月。这些冲击是全球大流行的主导因素，解释了全球流动性、病例和死亡的平均及历史变异性中的20%-60%。非药物干预政策相关的政策权衡为：每天减少1个百分点经济流动性，在三个月后可减少8%的死亡人数。该面板数据集包含了进行论文分析所需的主要数据。数据集包括以下国家的每日数据：阿根廷、澳大利亚、奥地利、比利时、巴西、加拿大、智利、哥伦比亚、捷克共和国、丹麦、爱沙尼亚、芬兰、法国、德国、希腊、香港、匈牙利、印度、印度尼西亚、爱尔兰、以色列、意大利、日本、立陶宛、卢森堡、墨西哥、荷兰、新西兰、挪威、波兰、葡萄牙、俄罗斯、沙特阿拉伯、斯洛文尼亚、韩国、西班牙、瑞典、瑞士、台湾、泰国、土耳其、阿拉伯联合酋长国、英国和美国。数据集包含的变量包括：确诊病例、总死亡人数、最后报告病例的天数、总检测次数、学校关闭、工作场所关闭、取消公共活动、集会限制、关闭公共交通、居家隔离要求、内部移动限制、国际旅行控制、收入支持、债务/合同救济、财政措施、国际支持、公共信息宣传活动、检测政策、接触者追踪、医疗紧急投资、疫苗投资、严格度指数、小盘股、大盘股、政府基准3个月、政府基准1年、政府基准2年、政府基准5年、政府基准10年、外汇指数广泛、外汇指数狭窄、零售流动性、杂货店流动性、公园流动性、公共交通站流动性、工作场所流动性、住宅流动性。数据时间范围为2016年12月30日至2020年8月31日。所有数据均从Macrobond下载。