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There Has Been Much Debate About the Impact of Minimum

question 28

Essay

There has been much debate about the impact of minimum wages on employment and unemployment.While most of the focus has been on the employment-to-population ratio of teenagers,you decide to check if aggregate state unemployment rates have been affected.Your idea is to see if state unemployment rates for the 48 contiguous U.S.states in 1985 can predict the unemployment rate for the same states in 1995,and if this prediction can be improved upon by entering a binary variable for "high impact" minimum wage states.One labor economist labeled states as high impact if a large fraction of teenagers was affected by the 1990 and 1991 federal minimum wage increases.Your first regression results in the following output: $There has been much debate about the impact of minimum wages on employment and unemployment.While most of the focus has been on the employment-to-population ratio of teenagers,you decide to check if aggregate state unemployment rates have been affected.Your idea is to see if state unemployment rates for the 48 contiguous U.S.states in 1985 can predict the unemployment rate for the same states in 1995,and if this prediction can be improved upon by entering a binary variable for high impact minimum wage states.One labor economist labeled states as high impact if a large fraction of teenagers was affected by the 1990 and 1991 federal minimum wage increases.Your first regression results in the following output: = 3.19 + 0.27 × ,R2 = 0.21,SER = 1.031 (0.56)(0.07) (a)Sketch the regression line and add a 450 line to the graph.Interpret the regression results.What would the interpretation be if the fitted line coincided with the 450 line? (b)Adding the binary variable DhiImpact by allowing the slope and intercept to differ,results in the following fitted line: = 4.02 + 0.16 × - 3.25 × DhiImpact + 0.38 × (DhiImpact× ), (0.66)(0.09)(0.89)(0.11) R2 = 0.31,SER=0.987 The F-statistic for the null hypothesis that both parameters involving the high impact minimum wage variable are zero,is 42.16.Can you reject the null hypothesis that both coefficients are zero? Sketch the two regression lines together with the 450 line and interpret the results again. (c)To check the robustness of these results,you repeat the exercise using a new binary variable for the so-called mining state (Dmining),i.e. ,the eleven states that have at least three percent of their total state earnings derived from oil,gas extraction,and coal mining,in the 1980s.This results in the following output: = 4.04 + 0.15× - 2.92 × Dmining + 0.37 × (Dmining × ), (0.65)(0.09)(0.90)(0.10) R2 = 0.31,SER=0.997 How confident are you that the previously found effect is due to minimum wages?$ = 3.19 + 0.27 × $There has been much debate about the impact of minimum wages on employment and unemployment.While most of the focus has been on the employment-to-population ratio of teenagers,you decide to check if aggregate state unemployment rates have been affected.Your idea is to see if state unemployment rates for the 48 contiguous U.S.states in 1985 can predict the unemployment rate for the same states in 1995,and if this prediction can be improved upon by entering a binary variable for high impact minimum wage states.One labor economist labeled states as high impact if a large fraction of teenagers was affected by the 1990 and 1991 federal minimum wage increases.Your first regression results in the following output: = 3.19 + 0.27 × ,R2 = 0.21,SER = 1.031 (0.56)(0.07) (a)Sketch the regression line and add a 450 line to the graph.Interpret the regression results.What would the interpretation be if the fitted line coincided with the 450 line? (b)Adding the binary variable DhiImpact by allowing the slope and intercept to differ,results in the following fitted line: = 4.02 + 0.16 × - 3.25 × DhiImpact + 0.38 × (DhiImpact× ), (0.66)(0.09)(0.89)(0.11) R2 = 0.31,SER=0.987 The F-statistic for the null hypothesis that both parameters involving the high impact minimum wage variable are zero,is 42.16.Can you reject the null hypothesis that both coefficients are zero? Sketch the two regression lines together with the 450 line and interpret the results again. (c)To check the robustness of these results,you repeat the exercise using a new binary variable for the so-called mining state (Dmining),i.e. ,the eleven states that have at least three percent of their total state earnings derived from oil,gas extraction,and coal mining,in the 1980s.This results in the following output: = 4.04 + 0.15× - 2.92 × Dmining + 0.37 × (Dmining × ), (0.65)(0.09)(0.90)(0.10) R2 = 0.31,SER=0.997 How confident are you that the previously found effect is due to minimum wages?$ ,R2 = 0.21,SER = 1.031
(0.56)(0.07)
(a)Sketch the regression line and add a 450 line to the graph.Interpret the regression results.What would the interpretation be if the fitted line coincided with the 450 line?
(b)Adding the binary variable DhiImpact by allowing the slope and intercept to differ,results in the following fitted line: $There has been much debate about the impact of minimum wages on employment and unemployment.While most of the focus has been on the employment-to-population ratio of teenagers,you decide to check if aggregate state unemployment rates have been affected.Your idea is to see if state unemployment rates for the 48 contiguous U.S.states in 1985 can predict the unemployment rate for the same states in 1995,and if this prediction can be improved upon by entering a binary variable for high impact minimum wage states.One labor economist labeled states as high impact if a large fraction of teenagers was affected by the 1990 and 1991 federal minimum wage increases.Your first regression results in the following output: = 3.19 + 0.27 × ,R2 = 0.21,SER = 1.031 (0.56)(0.07) (a)Sketch the regression line and add a 450 line to the graph.Interpret the regression results.What would the interpretation be if the fitted line coincided with the 450 line? (b)Adding the binary variable DhiImpact by allowing the slope and intercept to differ,results in the following fitted line: = 4.02 + 0.16 × - 3.25 × DhiImpact + 0.38 × (DhiImpact× ), (0.66)(0.09)(0.89)(0.11) R2 = 0.31,SER=0.987 The F-statistic for the null hypothesis that both parameters involving the high impact minimum wage variable are zero,is 42.16.Can you reject the null hypothesis that both coefficients are zero? Sketch the two regression lines together with the 450 line and interpret the results again. (c)To check the robustness of these results,you repeat the exercise using a new binary variable for the so-called mining state (Dmining),i.e. ,the eleven states that have at least three percent of their total state earnings derived from oil,gas extraction,and coal mining,in the 1980s.This results in the following output: = 4.04 + 0.15× - 2.92 × Dmining + 0.37 × (Dmining × ), (0.65)(0.09)(0.90)(0.10) R2 = 0.31,SER=0.997 How confident are you that the previously found effect is due to minimum wages?$ = 4.02 + 0.16 × $There has been much debate about the impact of minimum wages on employment and unemployment.While most of the focus has been on the employment-to-population ratio of teenagers,you decide to check if aggregate state unemployment rates have been affected.Your idea is to see if state unemployment rates for the 48 contiguous U.S.states in 1985 can predict the unemployment rate for the same states in 1995,and if this prediction can be improved upon by entering a binary variable for high impact minimum wage states.One labor economist labeled states as high impact if a large fraction of teenagers was affected by the 1990 and 1991 federal minimum wage increases.Your first regression results in the following output: = 3.19 + 0.27 × ,R2 = 0.21,SER = 1.031 (0.56)(0.07) (a)Sketch the regression line and add a 450 line to the graph.Interpret the regression results.What would the interpretation be if the fitted line coincided with the 450 line? (b)Adding the binary variable DhiImpact by allowing the slope and intercept to differ,results in the following fitted line: = 4.02 + 0.16 × - 3.25 × DhiImpact + 0.38 × (DhiImpact× ), (0.66)(0.09)(0.89)(0.11) R2 = 0.31,SER=0.987 The F-statistic for the null hypothesis that both parameters involving the high impact minimum wage variable are zero,is 42.16.Can you reject the null hypothesis that both coefficients are zero? Sketch the two regression lines together with the 450 line and interpret the results again. (c)To check the robustness of these results,you repeat the exercise using a new binary variable for the so-called mining state (Dmining),i.e. ,the eleven states that have at least three percent of their total state earnings derived from oil,gas extraction,and coal mining,in the 1980s.This results in the following output: = 4.04 + 0.15× - 2.92 × Dmining + 0.37 × (Dmining × ), (0.65)(0.09)(0.90)(0.10) R2 = 0.31,SER=0.997 How confident are you that the previously found effect is due to minimum wages?$ - 3.25 × DhiImpact + 0.38 × (DhiImpact× $There has been much debate about the impact of minimum wages on employment and unemployment.While most of the focus has been on the employment-to-population ratio of teenagers,you decide to check if aggregate state unemployment rates have been affected.Your idea is to see if state unemployment rates for the 48 contiguous U.S.states in 1985 can predict the unemployment rate for the same states in 1995,and if this prediction can be improved upon by entering a binary variable for high impact minimum wage states.One labor economist labeled states as high impact if a large fraction of teenagers was affected by the 1990 and 1991 federal minimum wage increases.Your first regression results in the following output: = 3.19 + 0.27 × ,R2 = 0.21,SER = 1.031 (0.56)(0.07) (a)Sketch the regression line and add a 450 line to the graph.Interpret the regression results.What would the interpretation be if the fitted line coincided with the 450 line? (b)Adding the binary variable DhiImpact by allowing the slope and intercept to differ,results in the following fitted line: = 4.02 + 0.16 × - 3.25 × DhiImpact + 0.38 × (DhiImpact× ), (0.66)(0.09)(0.89)(0.11) R2 = 0.31,SER=0.987 The F-statistic for the null hypothesis that both parameters involving the high impact minimum wage variable are zero,is 42.16.Can you reject the null hypothesis that both coefficients are zero? Sketch the two regression lines together with the 450 line and interpret the results again. (c)To check the robustness of these results,you repeat the exercise using a new binary variable for the so-called mining state (Dmining),i.e. ,the eleven states that have at least three percent of their total state earnings derived from oil,gas extraction,and coal mining,in the 1980s.This results in the following output: = 4.04 + 0.15× - 2.92 × Dmining + 0.37 × (Dmining × ), (0.65)(0.09)(0.90)(0.10) R2 = 0.31,SER=0.997 How confident are you that the previously found effect is due to minimum wages?$ ),
(0.66)(0.09)(0.89)(0.11)
R2 = 0.31,SER=0.987
The F-statistic for the null hypothesis that both parameters involving the high impact minimum wage variable are zero,is 42.16.Can you reject the null hypothesis that both coefficients are zero? Sketch the two regression lines together with the 450 line and interpret the results again.
(c)To check the robustness of these results,you repeat the exercise using a new binary variable for the so-called mining state (Dmining),i.e. ,the eleven states that have at least three percent of their total state earnings derived from oil,gas extraction,and coal mining,in the 1980s.This results in the following output: $There has been much debate about the impact of minimum wages on employment and unemployment.While most of the focus has been on the employment-to-population ratio of teenagers,you decide to check if aggregate state unemployment rates have been affected.Your idea is to see if state unemployment rates for the 48 contiguous U.S.states in 1985 can predict the unemployment rate for the same states in 1995,and if this prediction can be improved upon by entering a binary variable for high impact minimum wage states.One labor economist labeled states as high impact if a large fraction of teenagers was affected by the 1990 and 1991 federal minimum wage increases.Your first regression results in the following output: = 3.19 + 0.27 × ,R2 = 0.21,SER = 1.031 (0.56)(0.07) (a)Sketch the regression line and add a 450 line to the graph.Interpret the regression results.What would the interpretation be if the fitted line coincided with the 450 line? (b)Adding the binary variable DhiImpact by allowing the slope and intercept to differ,results in the following fitted line: = 4.02 + 0.16 × - 3.25 × DhiImpact + 0.38 × (DhiImpact× ), (0.66)(0.09)(0.89)(0.11) R2 = 0.31,SER=0.987 The F-statistic for the null hypothesis that both parameters involving the high impact minimum wage variable are zero,is 42.16.Can you reject the null hypothesis that both coefficients are zero? Sketch the two regression lines together with the 450 line and interpret the results again. (c)To check the robustness of these results,you repeat the exercise using a new binary variable for the so-called mining state (Dmining),i.e. ,the eleven states that have at least three percent of their total state earnings derived from oil,gas extraction,and coal mining,in the 1980s.This results in the following output: = 4.04 + 0.15× - 2.92 × Dmining + 0.37 × (Dmining × ), (0.65)(0.09)(0.90)(0.10) R2 = 0.31,SER=0.997 How confident are you that the previously found effect is due to minimum wages?$ = 4.04 + 0.15× $There has been much debate about the impact of minimum wages on employment and unemployment.While most of the focus has been on the employment-to-population ratio of teenagers,you decide to check if aggregate state unemployment rates have been affected.Your idea is to see if state unemployment rates for the 48 contiguous U.S.states in 1985 can predict the unemployment rate for the same states in 1995,and if this prediction can be improved upon by entering a binary variable for high impact minimum wage states.One labor economist labeled states as high impact if a large fraction of teenagers was affected by the 1990 and 1991 federal minimum wage increases.Your first regression results in the following output: = 3.19 + 0.27 × ,R2 = 0.21,SER = 1.031 (0.56)(0.07) (a)Sketch the regression line and add a 450 line to the graph.Interpret the regression results.What would the interpretation be if the fitted line coincided with the 450 line? (b)Adding the binary variable DhiImpact by allowing the slope and intercept to differ,results in the following fitted line: = 4.02 + 0.16 × - 3.25 × DhiImpact + 0.38 × (DhiImpact× ), (0.66)(0.09)(0.89)(0.11) R2 = 0.31,SER=0.987 The F-statistic for the null hypothesis that both parameters involving the high impact minimum wage variable are zero,is 42.16.Can you reject the null hypothesis that both coefficients are zero? Sketch the two regression lines together with the 450 line and interpret the results again. (c)To check the robustness of these results,you repeat the exercise using a new binary variable for the so-called mining state (Dmining),i.e. ,the eleven states that have at least three percent of their total state earnings derived from oil,gas extraction,and coal mining,in the 1980s.This results in the following output: = 4.04 + 0.15× - 2.92 × Dmining + 0.37 × (Dmining × ), (0.65)(0.09)(0.90)(0.10) R2 = 0.31,SER=0.997 How confident are you that the previously found effect is due to minimum wages?$ - 2.92 × Dmining + 0.37 × (Dmining × $There has been much debate about the impact of minimum wages on employment and unemployment.While most of the focus has been on the employment-to-population ratio of teenagers,you decide to check if aggregate state unemployment rates have been affected.Your idea is to see if state unemployment rates for the 48 contiguous U.S.states in 1985 can predict the unemployment rate for the same states in 1995,and if this prediction can be improved upon by entering a binary variable for high impact minimum wage states.One labor economist labeled states as high impact if a large fraction of teenagers was affected by the 1990 and 1991 federal minimum wage increases.Your first regression results in the following output: = 3.19 + 0.27 × ,R2 = 0.21,SER = 1.031 (0.56)(0.07) (a)Sketch the regression line and add a 450 line to the graph.Interpret the regression results.What would the interpretation be if the fitted line coincided with the 450 line? (b)Adding the binary variable DhiImpact by allowing the slope and intercept to differ,results in the following fitted line: = 4.02 + 0.16 × - 3.25 × DhiImpact + 0.38 × (DhiImpact× ), (0.66)(0.09)(0.89)(0.11) R2 = 0.31,SER=0.987 The F-statistic for the null hypothesis that both parameters involving the high impact minimum wage variable are zero,is 42.16.Can you reject the null hypothesis that both coefficients are zero? Sketch the two regression lines together with the 450 line and interpret the results again. (c)To check the robustness of these results,you repeat the exercise using a new binary variable for the so-called mining state (Dmining),i.e. ,the eleven states that have at least three percent of their total state earnings derived from oil,gas extraction,and coal mining,in the 1980s.This results in the following output: = 4.04 + 0.15× - 2.92 × Dmining + 0.37 × (Dmining × ), (0.65)(0.09)(0.90)(0.10) R2 = 0.31,SER=0.997 How confident are you that the previously found effect is due to minimum wages?$ ),
(0.65)(0.09)(0.90)(0.10)
R2 = 0.31,SER=0.997
How confident are you that the previously found effect is due to minimum wages?

Definitions:

Dominant Strategy

A strategy in game theory that yields the best outcome for a player, regardless of what the other players do.

Payoff

The gain or loss that an investor or a player in a game receives as a result of a particular action or decision.

Nash Equilibrium

A concept in game theory where no player can benefit by changing their strategy if the strategies of the other players remain unchanged.

Payoff

The return or reward from an investment or decision, often evaluated in terms of profit or benefit gained.