Consider the following hypothetical pooled cross-sectional data of daily COVID-19 cases per 1,000 people during the early two months of the pandemic, from March to April 2020 in Ohio and 5 other neighboring states. The variable April takes value 1 if the recorded cases are from April 2020, and takes value 0 if the recorded cases are from March 2020. The variable lockdown takes value 1 if the state put in place a Stay-at-home order beginning from March 2020, and takes value 0 otherwise. Using the difference-in-differences estimator, assess the impact of the lockdown policy on daily COVID-19 cases. Table 1. Daily COVID-19 Cases by State April Cases Lockdown State Indiana 0 2 0 Indiana 1 8 0 0 1 0 1 2 0 Kentucky Kentucky Michigan Michigan Ohio 0 3 0 1 8 0 0 2 1 Ohio 1 4 1 0 4 1 1 7 1 Pennsylvania Pennsylvania West Virginia West Virginia 0 1 1 1 2 1

ENGR.ECONOMIC ANALYSIS
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Consider the following hypothetical pooled cross-sectional data of daily COVID-19 cases per 1,000 people during the early two months of the pandemic, from March to April 2020 in Ohio and 5 other neighboring states. The variable April takes value 1 if the recorded cases are from April 2020, and takes value 0 if the recorded cases are from March 2020. The variable lockdown takes value 1 if the state put in place a Stay-at-home order beginning from March 2020, and takes value 0 otherwise. Using the difference-in-differences estimator, assess the impact of the lockdown policy on daily COVID-19 cases. Table 1. Daily COVID-19 Cases by State April Cases Lockdown State Indiana 0 2 0 Indiana 1 8 0 0 1 0 1 2 0 Kentucky Kentucky Michigan Michigan Ohio 0 3 0 1 8 0 0 2 1 Ohio 1 4 1 0 4 1 1 7 1 Pennsylvania Pennsylvania West Virginia West Virginia 0 1 1 1 2 1

Problem 1. Consider the following hypothetical pooled cross-sectional data of daily
COVID-19 cases per 1,000 people during the early two months of the pandemic, from
March to April 2020 in Ohio and 5 other neighboring states. The variable April takes
value 1 if the recorded cases are from April 2020, and takes value 0 if the recorded cases
are from March 2020. The variable lockdown takes value 1 if the state put in place a
Stay-at-home order beginning from March 2020, and takes value 0 otherwise. Using the
difference-in-differences estimator, assess the impact of the lockdown policy on daily
COVID-19 cases.
Table 1. Daily COVID-19 Cases by State
State
April
Cases
Lockdown
Indiana
2
Indiana
1
8
Kentucky
1
Kentucky
1
2
Michigan
3
Michigan
1
8
Ohio
2
1
Ohio
1
4
1
Pennsylvania
4
1
Pennsylvania
1
7
1
West Virginia
1
1
West Virginia
1
1
Transcribed Image Text:Problem 1. Consider the following hypothetical pooled cross-sectional data of daily COVID-19 cases per 1,000 people during the early two months of the pandemic, from March to April 2020 in Ohio and 5 other neighboring states. The variable April takes value 1 if the recorded cases are from April 2020, and takes value 0 if the recorded cases are from March 2020. The variable lockdown takes value 1 if the state put in place a Stay-at-home order beginning from March 2020, and takes value 0 otherwise. Using the difference-in-differences estimator, assess the impact of the lockdown policy on daily COVID-19 cases. Table 1. Daily COVID-19 Cases by State State April Cases Lockdown Indiana 2 Indiana 1 8 Kentucky 1 Kentucky 1 2 Michigan 3 Michigan 1 8 Ohio 2 1 Ohio 1 4 1 Pennsylvania 4 1 Pennsylvania 1 7 1 West Virginia 1 1 West Virginia 1 1
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