A dataset of governments' economic responses to COVID-19.

We introduce a new dataset of ten economic measures in percentage of gross domestic product implemented by governments worldwide between January 2020 and June 2021 to fight COVID-19. The measures coded include fiscal measures (wage support, cash transfers, in-kind transfers, tax cuts, sectorial support and credit schemes), tax deferrals, off-budget measures, and main policy rate cuts. The data can be used to study the impact of economic measures on different outcomes, and to understand the diffusion of economic policies during crises.

Policy Design for COVID-19: Worldwide Evidence on the Efficacies of Early Mask Mandates and Other Policy Interventions.

To understand the extent to which a policy instrument's early adoption is crucial in crisis management, we leverage unique worldwide data that record the daily evolution of policy mandate adoptions and COVID-19 infection and mortality rates. The analysis shows that the mask mandate is consistently associated with lower infection rates in the short term, and its early adoption boosts the long-term efficacy. By contrast, the other five policy instruments-domestic lockdowns, international travel bans, mass gathering bans, and restaurant and school closures-show weaker efficacy. Governments prepared for a public health crisis with stronger resilience or capacity and those with stronger collectivist cultures were quicker to adopt nationwide mask mandates. From a policy design perspective, policymakers must avoid overreacting with less effective instruments and underreacting with more effective ones during uncertain times, especially when interventions differ in efficacy and cost.

Social distancing beliefs and human mobility: Evidence from Twitter.

We construct a novel database containing hundreds of thousands geotagged messages related to the COVID-19 pandemic sent on Twitter. We create a daily index of social distancing-at the state level-to capture social distancing beliefs by analyzing the number of tweets containing keywords such as "stay home", "stay safe", "wear mask", "wash hands" and "social distancing". We find that an increase in the Twitter index of social distancing on day t-1 is associated with a decrease in mobility on day t. We also find that state orders, an increase in the number of COVID-19 cases, precipitation and temperature contribute to reducing human mobility. Republican states are also less likely to enforce social distancing. Beliefs shared on social networks could both reveal the behavior of individuals and influence the behavior of others. Our findings suggest that policy makers can use geotagged Twitter data-in conjunction with mobility data-to better understand individual voluntary social distancing actions.

Response2covid19, a dataset of governments' responses to COVID-19 all around the world.

Following the COVID-19 outbreak, governments all around the world have implemented public health and economic measures to contain the spread of the virus and to support the economy. Public health measures include domestic lockdown, school closures and bans on mass gatherings among others. Economic measures cover wage support, cash transfers, interest rates cuts, tax cuts and delays, and support to exporters or importers. This paper introduces 'Response2covid19', a living dataset of governments' responses to COVID-19. The dataset codes the various policy interventions with their dates at the country-level for more than 200 countries from January 1 to October 1, 2020 and is updated every month. The production of detailed data on the measures taken by governments can help generate robust evidence to support public health and economic decision making.

Impact of regulation on English and Welsh water-only companies: an input-distance function approach.

The assessment of productivity change over time and its drivers is of great significance for water companies and regulators when setting urban water tariffs. This issue is even more relevant in privatized water industries, such as those in England and Wales, where the price-cap regulation is adopted. In this paper, an input-distance function is used to estimate productivity change and its determinants for the English and Welsh water-only companies (WoCs) over the period of 1993-2009. The impacts of several exogenous variables on companies' efficiencies are also explored. From a policy perspective, this study describes how regulators can use this type of modeling and results to calculate illustrative X factors for the WoCs. The results indicate that the 1994 and 1999 price reviews stimulated technical change, and there were small efficiency gains. However, the 2004 price review did not accelerate efficiency change or improve technical change. The results also indicated that during the whole period of study, the excessive scale of the WoCs contributed negatively to productivity growth. On average, WoCs reported relatively high efficiency levels, which suggests that they had already been investing in technologies that reduce long-term input requirements with respect to exogenous and service-quality variables. Finally, an average WoC needs to improve its productivity toward that of the best company by 1.58%. The methodology and results of this study are of great interest to both regulators and water-company managers for evaluating the effectiveness of regulation and making informed decisions.