The team is proposing to model how COVID-19 pandemics affect the economy and evaluate the effectiveness of the government's action. Later on, the team plans to apply the model in a different hypothetical scenario to draft potential improvements in government action. The economic data the team will use are stock prices, industry performance, bond yields, and credit default swap prices. The COVID data are the infection and deaths, vaccination rates, stringency index, and news and media coverage. Government action data will come from various news articles.
Seeing how much the pandemic greatly affects the economies around the world, I think the proposal is very relevant and important to understand in order to better handle future pandemics. The generalized model could be a vital data point to drive future policy changes. The datasets are reliable and are reasonable for the analysis. It is good to analyze different economic indicators to get a wider view of how COVID data affects different parts of the economy. I agree with the proposed plan to clean up the data, develop the model and analyze government action using the model. I am excited to see what the findings are.
However, there are a couple of points the team should also look out for. Other economic indicators such as GDP, CPI, inflation rates, interests rates, household income, and others could also be good indicators. With other indicators, more analysis could be made such as the policy impact different income levels differently. State-wide vs nationwide action could be different and produce completely different data. Looking at nationwide data might not give a clear picture. Adding a statewide model and comparing government action both state-wide and nationwide could also result in additional insights. Also comparing the government action on COVID and economic data separately might tell how the action effect one data set which in turn affects the other dataset.
The team is proposing to model how COVID-19 pandemics affect the economy and evaluate the effectiveness of the government's action. Later on, the team plans to apply the model in a different hypothetical scenario to draft potential improvements in government action. The economic data the team will use are stock prices, industry performance, bond yields, and credit default swap prices. The COVID data are the infection and deaths, vaccination rates, stringency index, and news and media coverage. Government action data will come from various news articles.
Seeing how much the pandemic greatly affects the economies around the world, I think the proposal is very relevant and important to understand in order to better handle future pandemics. The generalized model could be a vital data point to drive future policy changes. The datasets are reliable and are reasonable for the analysis. It is good to analyze different economic indicators to get a wider view of how COVID data affects different parts of the economy. I agree with the proposed plan to clean up the data, develop the model and analyze government action using the model. I am excited to see what the findings are.
However, there are a couple of points the team should also look out for. Other economic indicators such as GDP, CPI, inflation rates, interests rates, household income, and others could also be good indicators. With other indicators, more analysis could be made such as the policy impact different income levels differently. State-wide vs nationwide action could be different and produce completely different data. Looking at nationwide data might not give a clear picture. Adding a statewide model and comparing government action both state-wide and nationwide could also result in additional insights. Also comparing the government action on COVID and economic data separately might tell how the action effect one data set which in turn affects the other dataset.