Stay Home Save Lives: A Machine Learning Approach to Causal Inference to Evaluate Impact of Social Distancing in the US
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Although there are few studies done to provide estimations of the impact of COVID-19 pandemic, however, there is a need for an actual policy evaluation of the already implemented social distancing measures. In the US context in specific, this is especially instrumental because nearly a dozen US states are considering the reopening of the economy following anti social distancing protests. Using a machine learning based Generalized Synthetic Control Method, considering the US states that adopted early social distancing approaches as the treatment group and the states that adopted social distancing much later as the control group and controlling for state and time fixed effects (to cancel out the selection bias and endogeneity),  this paper finds that social distancing is associated with lower COVID-19 infection growth rate (by 192%) when ' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Covid-19, Social Distancing, Machine Learning, Policy Evaluation, Pandemic"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Although there are few studies done to provide estimations of the impact of COVID-19 pandemic, however, there is a need for an actual policy evaluation of the already implemented social distancing measures. In the US context in specific, this is especially instrumental because nearly a dozen US states are considering the reopening of the economy following anti social distancing protests. Using a machine learning based Generalized Synthetic Control Method, considering the US states that adopted early social distancing approaches as the treatment group and the states that adopted social distancing much later as the control group and controlling for state and time fixed effects (to cancel out the selection bias and endogeneity),  this paper finds that social distancing is associated with lower COVID-19 infection growth rate (by 192%) when ' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Although there are few studies done to provide estimations of the impact of COVID-19 pandemic, however, there is a need for an actual policy evaluation of the already implemented social distancing measures. In the US context in specific, this is especially instrumental because nearly a dozen US states are considering the reopening of the economy following anti social distancing protests. Using a machine learning based Generalized Synthetic Control Method, considering the US states that adopted early social distancing approaches as the treatment group and the states that adopted social distancing much later as the control group and controlling for state and time fixed effects (to cancel out the selection bias and endogeneity),  this paper finds that social distancing is associated with lower COVID-19 infection growth rate (by 192%) when 
Covid-19, Social Distancing, Machine Learning, Policy Evaluation, Pandemic