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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 Michigan 1 Ohio 2 1 Ohio 1 4 1 Pennsylvania 4 1 Pennsylvania 1 7 1 West Virginia 1 1 West Virginia 1 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 Michigan 1 Ohio 2 1 Ohio 1 4 1 Pennsylvania 4 1 Pennsylvania 1 7 1 West Virginia 1 1 West Virginia 1 1

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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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 Indiana 1 8 Kentucky 1 Kentucky 1 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 2.
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 Indiana 1 8 Kentucky 1 Kentucky 1 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 2.
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