The CoronaNet Research Project compiles a database on government responses to COVID-19. Our primary focus is to collect as much information as possible about the various fine-grained actions governments take to address the pandemic. The data collection process includes gathering information about which governments respond to COVID-19, their policy targets (e.g., other countries), type of policies (e.g., travel restrictions), and the timeline of the policies.
Our data collection efforts have now been completed with a dataset consists of more than 180,000 separate policy announcements of governments from all over the world since 31 December 2019. Policymakers, academics, and journalists have already made use of this dataset to understand how governments have responded to the pandemic.
Our principal investigators for this project are:
I am a comparative political economist whose research examines the long-term drivers of wealth creation and democratization in developing countries. My book, Making Democracy Safe for Business: Corporate Politics During the Arab Uprisings (Cambridge University Press), examines the profound influence of prominent businesspeople on the political outcomes of the Arab Uprisings. I am also actively engaged in research into data-scientific methods, including causal inference, Bayesian statistics, and measurement, and is the author of the R packages idealstan and ordbetareg. I have published journal articles in Nature Human Behavior, The Journal of Politics, PLOS One, The Journal of the Royal Statistical Society: Series A, The Journal of Peace Research, Scientific Data, World Politics, Social Science Quarterly, Comparative Political Studies, and Political Analysis.
As a political scientist, my work has primarily engaged in examining the politics of crisis, including how both governments and people react to crisis and uncertainty as well as how their actions can contribute to it. I have explored these topics across a wide variety of issue areas common to the field of international political economy, including the COVID-19 pandemic, food safety, foreign aid and trade.
As a data scientist, I have deep expertise in applying a wide variety of methodological approaches ( e.g. causal inference, predictive modeling) and tools (e.g. (non)linear modeling, machine learning, Bayesian statistics) to forward new insights and research.
Previous Principal investigators for this project were:
Our core paper, which presents our initial findings, has been published by Nature: Human Behaviour.
The first prize with 15,000 euros goes to the project "CoronaNet Government Response Event Dataset" conducted by Cindy Cheng and Luca Messerschmidt, Hochschule für Politik at the Technical University of Munich, Chair for International Relations (Prof. Dr. Tim Büthe). The research project systematically documents the measures taken by governments worldwide in response to COVID-19 to enable academic and applied researchers, journalists and decision-makers to better understand the causes and consequences of these policy responses. To know more about Open Data Impact Award, see here.
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Please cite the project and dataset as:
Cheng, Cindy, Joan Barceló, Allison Spencer Hartnett, Robert Kubinec, and Luca Messerschmidt. "COVID-19 Government Response Event Dataset (CoronaNet v. 1.0)." Nature human behaviour 4, no. 7 (2020): 756-768. https://www.coronanet-project.org.
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