Firing Blanks?The following is analysis from my senior undergraduate thesis from 2015 (when I was an Anteater;Zot Zot) examining the effect of California's assault weapon's ban on crime rates. This paper uses amodified difference-in-difference estimator. The treatment group is Non-CA states, who let thefederal assault weapons ban in 2004 lapse while California maintained a state assault weapons ban,serving as our control. The data examines per capita crime, various controls, as well astreatment/control and pre/post treatment for counties that lie exactly on the border of CA withNevada, Oregon, and Arizona. I estimated the following regression:In(Murder) it = -8.36 0.02Povertyit -0.16Treatit - 0.40 Postit(5.57) (0.03)(0.5)(0.012)-0.06CountyUnemploymentit 0.14(POST X Treat)(0.35)(0.08)In(Murder) the logged murder rate per 10,000 people.Poverty is the percentage of the population within each county that is below the Federal povertyline.Treat is a binary variable = 1 for states that let the federal assault weapons ban expire (non-CAcounties), O for CA.Post is a binary variable = 1 for years after the federal assault weapons ban expire. (2004 onward), orfor pre-2004.County Unemployment is the unemployment rate.The interaction term, Post X Treat measures the interaction between counties within the treatmentstates. That is, the effect of being aRound to 2 decimal places and include a negative sign if necessary.A. Should I have run RTO instead? Assume at the 95% confidence level and a Z distribution. Answer"YES" or "NO".B. What is the T-statistic associated with the unemployment rate? Round to 2 decimal places andinclude a negative sign if necessary.C. What is the t-critical value associated with the 95% confidence level and a Z distribution? Roundto 2 decimal places.D. What is the effect of being a treated state, before the treatment year? That is, what is the effectof being a county that removed an assault weapons ban before the year the ban expired. Include anegative value if the answer is negative, round to 2 decimal places.E. Is unemployment rate a determinant of the murder rate in this data? Answer "YES" or "NO"F. Is the treatment effect statistically significant at the 95% confidence level? That is, did removingthe assault weapons ban have a statistically significant effect on the murder rate? Hint: Think aboutwhich coefficient we care about in a diff-in-diff set up. Answer "YES" or "NO".G. Does running this as a two-way fixed effects model make sense? Answer by inputting the numberthat is associated with the correct statement: Post is a binary variable = 1 for years after the federal assault weapons ban expire. (2004 onward), orfor pre-2004.County Unemployment is the unemployment rate.The interaction term, Post X Treat measures the interaction between counties within the treatmentstates. That is, the effect of being aRound to 2 decimal places and include a negative sign if necessary.A. Should I have run RTO instead? Assume at the 95% confidence level and a Z distribution. Answer"YES" or "NO".B. What is the T-statistic associated with the unemployment rate? Round to 2 decimal places andinclude a negative sign if necessary.C. What is the t-critical value associated with the 95% confidence level and a Z distribution? Roundto 2 decimal places.D. What is the effect of being a treated state, before the treatment year? That is, what is the effectof being a county that removed an assault weapons ban before the year the ban expired. Include anegative value if the answer is negative, round to 2 decimal places.E. Is unemployment rate a determinant of the murder rate in this data? Answer "YES" or "NO"F. Is the treatment effect statistically significant at the 95% confidence level? That is, did removingthe assault weapons ban have a statistically significant effect on the murder rate? Hint: Think aboutwhich coefficient we care about in a diff-in-diff set up. Answer "YES" or "NO".G. Does running this as a two-way fixed effects model make sense? Answer by inputting the numberthat is associated with the correct statement:1. No, because there really shouldn't be anything different between bordering counties in CAand counties in Nevada, Arizona, or Oregon2. No, because we only really need to account for county level differences in CA, Nevada,Arizona, and Oregon3. No, because we only really need to account for how murder changes over time4. Yes, because crime probably has a time trend component that is fixed across counties as wellas having some unobserved fixed characteristics between counties that we should accountfor.5. Yes, because we need to control for simultaneity --- did the state pass assault weapons ban inresponse to higher crime or did the crime rate respond to the passage of the assault weaponsban?H. Suppose that you believe that undergraduate Harrison was an idiot and omitted the variableeducation. You also know:Cov(Educ, Poverty)

Question

Firing Blanks?The following is analysis from my senior undergraduate thesis from 2015 (when I was an Anteater;Zot Zot) examining the effect of California's assault weapon's ban on crime rates. This paper uses amodified difference-in-difference estimator. The treatment group is Non-CA states, who let thefederal assault weapons ban in 2004 lapse while California maintained a state assault weapons ban,serving as our control. The data examines per capita crime, various controls, as well astreatment/control and pre/post treatment for counties that lie exactly on the border of CA withNevada, Oregon, and Arizona. I estimated the following regression:In(Murder) it = -8.36 0.02Povertyit -0.16Treatit - 0.40 Postit(5.57) (0.03)(0.5)(0.012)-0.06CountyUnemploymentit 0.14(POST X Treat)(0.35)(0.08)In(Murder) the logged murder rate per 10,000 people.Poverty is the percentage of the population within each county that is below the Federal povertyline.Treat is a binary variable = 1 for states that let the federal assault weapons ban expire (non-CAcounties), O for CA.Post is a binary variable = 1 for years after the federal assault weapons ban expire. (2004 onward), orfor pre-2004.County Unemployment is the unemployment rate.The interaction term, Post X Treat measures the interaction between counties within the treatmentstates. That is, the effect of being aRound to 2 decimal places and include a negative sign if necessary.A. Should I have run RTO instead? Assume at the 95% confidence level and a Z distribution. Answer&#34;YES&#34; or &#34;NO&#34;.B. What is the T-statistic associated with the unemployment rate? Round to 2 decimal places andinclude a negative sign if necessary.C. What is the t-critical value associated with the 95% confidence level and a Z distribution? Roundto 2 decimal places.D. What is the effect of being a treated state, before the treatment year? That is, what is the effectof being a county that removed an assault weapons ban before the year the ban expired. Include anegative value if the answer is negative, round to 2 decimal places.E. Is unemployment rate a determinant of the murder rate in this data? Answer &#34;YES&#34; or &#34;NO&#34;F. Is the treatment effect statistically significant at the 95% confidence level? That is, did removingthe assault weapons ban have a statistically significant effect on the murder rate? Hint: Think aboutwhich coefficient we care about in a diff-in-diff set up. Answer &#34;YES&#34; or &#34;NO&#34;.G. Does running this as a two-way fixed effects model make sense? Answer by inputting the numberthat is associated with the correct statement: Post is a binary variable = 1 for years after the federal assault weapons ban expire. (2004 onward), orfor pre-2004.County Unemployment is the unemployment rate.The interaction term, Post X Treat measures the interaction between counties within the treatmentstates. That is, the effect of being aRound to 2 decimal places and include a negative sign if necessary.A. Should I have run RTO instead? Assume at the 95% confidence level and a Z distribution. Answer&#34;YES&#34; or &#34;NO&#34;.B. What is the T-statistic associated with the unemployment rate? Round to 2 decimal places andinclude a negative sign if necessary.C. What is the t-critical value associated with the 95% confidence level and a Z distribution? Roundto 2 decimal places.D. What is the effect of being a treated state, before the treatment year? That is, what is the effectof being a county that removed an assault weapons ban before the year the ban expired. Include anegative value if the answer is negative, round to 2 decimal places.E. Is unemployment rate a determinant of the murder rate in this data? Answer &#34;YES&#34; or &#34;NO&#34;F. Is the treatment effect statistically significant at the 95% confidence level? That is, did removingthe assault weapons ban have a statistically significant effect on the murder rate? Hint: Think aboutwhich coefficient we care about in a diff-in-diff set up. Answer &#34;YES&#34; or &#34;NO&#34;.G. Does running this as a two-way fixed effects model make sense? Answer by inputting the numberthat is associated with the correct statement:1. No, because there really shouldn't be anything different between bordering counties in CAand counties in Nevada, Arizona, or Oregon2. No, because we only really need to account for county level differences in CA, Nevada,Arizona, and Oregon3. No, because we only really need to account for how murder changes over time4. Yes, because crime probably has a time trend component that is fixed across counties as wellas having some unobserved fixed characteristics between counties that we should accountfor.5. Yes, because we need to control for simultaneity --- did the state pass assault weapons ban inresponse to higher crime or did the crime rate respond to the passage of the assault weaponsban?H. Suppose that you believe that undergraduate Harrison was an idiot and omitted the variableeducation. You also know:Cov(Educ, Poverty) < 0Cov(Educ, Murder) < 0What is the direction of the bias on the coefficient for Poverty? Answer &#34;UPWARD&#34; or&#34;DOWNWARD&#34;

Accepted Answer

Since you have posted a question with multiple sub-parts, we will solve the first three sub-parts…