Reference no: EM133261139

Economists believe that containing the pandemic is essential to the expansion of the economy. However, they acknowledged that this condition alone would not be enough to ensure a robust economic recovery. They believed that reducing the number of people who died should be the primary focus of any effective response. The key to a successful response to the pandemic is to keep the death rate low and the infection rate low. People will be reluctant to leave their houses and engage in economic activity, according to what they wrote. "As a result of this, there will be a significant slowdown and increase in unemployment," they said.

The coronavirus pandemic has had a significant impact on the global economy, with growth forecasts for 2020 and 2021 being revised downwards. In the short term, businesses have closed and people have been asked to stay at home, leading to a decrease in demand for goods and services.

Explanation:

Question 1

Economists have long held the belief that containing the pandemic is essential to the expansion of the economy. In a paper that was published in June, three economists from the University of Chicago argued that "a successful response to the pandemic is a necessary but not sufficient condition for a strong economic recovery." However, they acknowledged that this condition alone would not be enough to ensure a robust economic recovery.

Lars Hansen, who was awarded the Nobel Peace Prize, Robert Lucas, and John Cochrane were the authors of the study that was published under the title "Pandemic, Policy, and the Stock Market." Economists believed that reducing the number of people who died as a result of the pandemic should be the primary focus of any effective response to the epidemic.

They claimed that if the death rate was high, people would be unwilling to leave their houses and participate in economic activity. "As a result of this, there will be a significant slowdown in economic activity as well as an increase in unemployment." The economists also suggested that the key to an effective response to the pandemic is to keep the infection rate low. "If the infection rate is high, people will be reluctant to leave their houses and engage in economic activity," they said. "If the infection rate is high, people will be reluctant to leave their homes." "This will lead to a dramatic decrease in economic activity and an increase in unemployment."

Economists stated that the key to a successful response to the epidemic is to reduce the death rate and infection rate as low as possible simultaneously. People will be reluctant to leave their houses and engage in economic activity, according to what they wrote. "If the death rate is high and the infection rate is low, people will be reluctant to leave their homes." "This will lead to a dramatic decrease in economic activity and an increase in unemployment." The economists stated that the key to a successful response to the pandemic is to keep the death rate low and the infection rate low.

"If the death rate is low and the infection rate is high, people will be reluctant to leave their houses and engage in economic activity," they wrote. "This will lead to a dramatic decrease in economic activity and an increase in unemployment." Economists stated that the key to a successful response to the epidemic is to reduce the death rate and infection rate as low as possible simultaneously.

"If the death rate is high and the infection rate is high, people will be unwilling to leave their houses and engage in economic activity," they wrote. "As a result of this, there will be a significant slowdown in economic activity as well as an increase in unemployment." The economists claimed that the key to a successful response to the pandemic is to keep the death rate low, the infection rate low, and to enact policies that will encourage people to leave their houses and engage in economic activity. "If the death rate is low, the infection rate is low, and policies are in place that encourage people to leave their homes and engage in economic activity, the economy will grow," they wrote. "This will lead to better salaries and lower unemployment."

Question 2

The coronavirus pandemic has had a significant impact on the global economy, with growth forecasts for 2020 and 2021 being revised downwards in the wake of the outbreak. In the short term, the pandemic has caused a significant decrease in economic activity as businesses have been forced to close and people have been asked to stay at home. This has led to a decrease in demand for goods and services, and a decrease in investment and consumption.

In the longer term, the pandemic is likely to have a more mixed impact on the economy. On the one hand, it is expected to lead to a decrease in productivity as businesses adapt to the new normal of social distancing and remote working. On the other hand, it is also expected to lead to an increase in spending on health care and other pandemic-related products and services.

The overall impact of the pandemic on the economy will depend on a number of factors, including the length of the outbreak, the effectiveness of government interventions, and the response of the private sector. In the short term, the coronavirus pandemic has caused a significant decrease in economic activity.

Businesses have been forced to close their doors and people have been asked to stay at home in order to slow the spread of the virus. This has led to a decrease in demand for goods and services, and a decrease in investment and consumption. The decrease in economic activity has had a knock-on effect on a number of industries, including retail, hospitality, tourism, and transportation. In the longer term, the pandemic is expected to have a more mixed impact on the economy.

On the one hand, it is expected to lead to a decrease in productivity as businesses adapt to the new normal of social distancing and remote working. On the other hand, it is also expected to lead to an increase in spending on health care and other pandemic-related products and services. The overall impact of the pandemic on the economy will depend on a number of factors, including the length of the outbreak, the effectiveness of government interventions, and the response of the private sector.
The two states you will consider are Pennsylvania and Ohio.

This involves two elements.

1. Discuss in general the things that might affect infection rates in addition to state restrictive/non-restrictive policies among states. Outside sources with citation needed.

2. Consider your Element 1 discussion. Describe the steps you might take to satisfy the "all else constant" requirements of your analysis for Pennsylvania and Ohio. These include things that might be similar in the two states and therefore are constant. These need to be listed with reference to the sources you use. In addition, list factors that you have to ASSUME are constant, that you will need caveats for in your analysis.

sections with subheadings. proper citation methodology is needed

Question 1

Infection rates among states may be influenced by a number of factors, including population density and weather. States that have been hit hard by the virus in the past are more likely to have higher infection rates. This is because the population may not yet have built up immunity to the virus. There are 11,799,448 people living in Ohio, giving the state a population density of 282 persons per square mile. 14.0% of the population in Ohio is considered to live below the poverty level. As of December 2020, the state had a total of 471,801 confirmed cases of the disease.

Question 2

Both states were hit particularly hard by the pandemic during the early stages. Pennsylvania recorded a total of 498,334 confirmed cases, including 12,872 fatalities. As of the end of the year 2020, the state of Ohio recorded 471,801 confirmed cases and 10,785 deaths.

Explanation:

Question 1

Infection rates among states may be influenced by a number of other factors in addition to the laws of individual governments, which may either be restrictive or non-restrictive. The first factor to consider is the population density. Because there are more people living in close proximity to one another, states that contain large cities and high population densities are more likely to have higher infection rates. This is because the virus is able to spread more easily in areas where there are more people living in close quarters. The weather is also a significant component. Because the virus is better able to live and propagate in warmer conditions, states with warmer climates are more likely to have higher infection rates than states with cooler climates. In addition to this, states that have lower incomes and less access to healthcare are also more likely to have higher infection rates. This is due to the fact that people living in these states are more likely to have preexisting health conditions that make them more susceptible to the virus, and they may not be able to afford the treatment they require if they become infected with the virus.
In conclusion, states that have been hit hard by the virus in the past are more likely to have higher infection rates because the population may not yet have built up immunity to the virus. This is the case because states that have been hit hard by the virus in the past tend to have higher infection rates. There are 12,801,989 people living in the state of Pennsylvania, giving it a population density of 284 people per square mile. The state of Pennsylvania is known for its pleasant weather, with an annual average temperature of 54 degrees Fahrenheit. 14.9% of the population of Pennsylvania is considered to live on less than the federal poverty line, despite the state's household income median being $61,842. In the early days of the pandemic, Pennsylvania was one of the states that was hit the hardest by the virus. As of December 2020, the state had a total of 498,334 confirmed cases of the illness, and 12,872 people had died as a result of it.
There are 11,799,448 people now living in Ohio, giving the state a population density of 282 persons per square mile. The state of Ohio enjoys a climate that is considered to be temperate, with an annual average temperature of 51 degrees Fahrenheit. 14.0% of the population in Ohio is considered to live below the poverty level despite the state's median household income being $57,951. In the early days of the pandemic, Ohio was one of the states that was hit the hardest by the virus. As of December 2020, the state had a total of 471,801 confirmed cases of the disease, and 10,785 people had died as a result of it.
Both Pennsylvania and Ohio have comparable population densities, as well as temperatures, both of which may be contributing factors in the high infection rates in those states. In addition, the median family income in both states is relatively low, and the poverty rate is relatively high, both of which could be contributing factors in the states' high infection rates. In conclusion, the fact that both states were hit particularly hard by the virus during the early stages of the pandemic may help to provide light on the continued high infection rates in those states.

Question 2

In order to make an accurate comparison of the infection rates in Pennsylvania and Ohio, there are a few factors that need to be taken into consideration. The first factor to consider is the population density. The population density of Pennsylvania is 284 people per square mile, while the population density of Ohio is 282 people per square mile. Both states have roughly the same number of people per square mile, which would explain why their infection rates are so high.
Climate is yet another aspect that should be taken into account. Whereas Ohio has a climate that is considered to be temperate, with an average temperature of 51 degrees Fahrenheit, Pennsylvania has a climate that is considered to be warm, with an average temperature of 54 degrees Fahrenheit. Both states have climates that are considered to be on the milder side, which would explain why their infection rates are so high.
In addition, both Pennsylvania and Ohio have significant poverty rates and median household incomes that are below the national average. This could be another factor that contributes to the states' high infection rates. 14.9% of the population of Pennsylvania is considered to live on less than the federal poverty line, despite the state's household income median being $61,842. 14.0% of the population in Ohio is considered to live below the poverty level despite the state's median household income being $57,951.
In conclusion, the fact that both states were hit particularly hard by the virus during the early stages of the pandemic may help to provide light on the continued high infection rates in those states. As of December 2020, the state of Pennsylvania recorded a total of 498,334 confirmed cases, including 12,872 fatalities. As of the end of the year 2020, the state of Ohio recorded a total of 471,801 confirmed cases and 10,785 deaths.
Based on the Question 1 and Question 2

Your states are Pennsylvania and Ohio. Please only analyze 2020

1. Using the Johns Hopkins University data investigate for possible correlations between state restrictive/non-restrictive policies and infection rates. Look at trends, not just individual data points. Consider that some periods might have different results than others. There may be a relationship or there may not be. Based on your analysis what is your research observation regarding policy and infection rates? This is strictly positive analysis and must be objective. Avoid overly stringent claims, like "a caused b." Instead, there "appears/doesn't appear" to be a correlation.

2. In Part 2 you listed factors that you held constant by assumption. In this element you will explain how those assumptions might bias your results. Might your outcome have been different if you didn' impose the all else constant requirement. This is essentially a caveat to your results.