xuebaunion@vip.163.com

3551 Trousdale Rkwy, University Park, Los Angeles, CA

留学生论文指导和课程辅导

无忧GPA：https://www.essaygpa.com

工作时间：全年无休-早上8点到凌晨3点

微信客服：xiaoxionga100

微信客服：ITCS521

程序代写案例-SET 3

时间：2021-04-06

PROBLEM SET 3 - EC551 (A1)

Spring 2021 – Daniele Paserman

Due: no later than Thursday, 4/8/2021 at 11:59pm Eastern time

Problem Set must be uploaded on Blackboard in the appropriate section.

Please submit your problem set as a single PDF file titled PS3_[LastName][Firstname].pdf.

Example: PS3_PasermanDaniele.pdf.

Remarks:

All work handed must be your own, with the exception that you are encouraged to discuss your

papers with each other but must turn in separate work demonstrating independent thought and

investigation.

Answers must not be poems, so try to keep your answers short. But don’t forget to explain your

results, because a single number without any explanation or the appropriate algebraic passages

will be graded lower.

Introduction

The file MinimumWage_ByState_2011-2019.dta (also available in .csv format)

contains information on the minimum wage in each US state and the District of Columbia

between 2011 and 2019. The data is taken from:

https://www.dol.gov/agencies/whd/state/minimum-wage/history. In cases in which there is more

than one minimum wage in a state, the value in the table is the highest possible value.

The file ps3_cps2011-2019.dta is a Stata file with a raw extract of the CPS for the months

of February, May, August and November between 2011 and 2019. Notice that the data is raw.

For the analysis, you will have to make sure that you clean the data (identify missing values

and categorical variables and eventually transform the data in a way that is amenable to

regression analysis).

I have also made available two additional data sets:

- cb_2018_us_state_5m.shp. This is called a shape file, and contains information

on the geographic coordinates of US states, which can then be used to draw maps in

Stata.

- cb_2018_us_state_crosswalk.dta. This is a Stata file with a crosswalk

between the state codes used in the shape file and the states codes used in the minimum

wage data set and in the CPS.

In the Problem Set, you will be asked to perform a number of analyses to describe the evolution

of minimum wage laws across states, and its impact on employment, wages, and family

outcomes.

Part A: Mapping the Minimum Wage (15 points)

In this part, you are asked to graph the data on minimum wages into a map. To create maps, you

will need to install the user-written commands spmap, shp2dta and mif2dta. See here for a starter

on how to create maps in Stata: https://www.stata.com/support/faqs/graphics/spmap-and-maps/

[The default maps created by Stata tend look a bit distorted relative to maps that you may be

familiar with. This has to do with the well-known problem of rendering in two dimensions maps

of the surface of the Earth, an ellipsoid. To make more familiar maps, you can also download the

user written command geo2xy]

1) Using the MinimumWage_ByState_2015-2019.dta file, create in Stata a

cloropleth map of minimum wages by state in 2011, 2015 and 2019, for the 48

contiguous US states (excluding Alaska and Hawaii). Comment on the results. Which

states tend to have high minimum wages? Which states tend to have low minimum

wages?

2) Create a new variable equal to the change in the minimum wage by state between 2011

and 2019 (you will probably have to use the egen command in Stata). Map this variable

and comment on the results. Which states had the largest absolute increase in the

minimum wage? Which ones had the lowest?

3) Run a regression of the absolute change in the minimum wage on the minimum wage in

2011. Comment on the results. How do these results relate to the maps you drew in

questions 1 and 2?

Part B: The effect of the minimum wage on employment (36 points)

For this part of the problem set, load the CPS data, and merge it by state and year with the

minimum wage data using the merge command. Define the effective minimum wage in a state

as the maximum between the state minimum wage and the federal minimum wage, which was

$7.25 throughout this period. Create a variable equal to ln(effective minimum wage). We will

call this lnܯܹ݅݊ܽ݃݁௦௧.

4) (6 points) Consider the following model:

ܧ݈݉ݕ݁݀௦௧ = ߚ + ߚଵ lnܯܹ݅݊ܽ݃ ௦݁௧ + ݑ௦௧ (1)

Under what assumptions does this model yield a consistent estimate of the causal effect

of the minimum wage on employment? Do you think these assumptions are likely to be

satisfied in this context?

5) (6 points) Consider instead the alternative model:

ܧ݈݉ݕ݁݀௦௧ = ߚ + ߚଵ lnܯܹ݅݊ܽ݃ ௦݁௧ + ߜ௦ + ߛ௧ + ݑ௦௧ (2)

where ߜ௦ represents state fixed effects and ߛ௧ represents time fixed effects. Under what

assumptions does this model yield a consistent estimate of the causal effect of the

minimum wage on employment? Do you think these assumptions are likely to be

satisfied in this context? Give an example

6) (6 points) Estimate the models in parts 4) and 5), using the sample of all individuals

between 15 and 64 year old, and report the results in a table that looks like Table 1 below.

(Make sure to also report the number of observations and the mean of the dependent

variable). Comment on the results. Are the results consistent with the textbook model of

the minimum wage?

Table 1: Baseline Model

Part (4): without fixed effects Part (5): with fixed effects lnܯܹ݅݊ܽ݃ ௦݁௧ Coefficient

(standard error)

Coefficient

(standard error)

Number of

observations

Mean of the

dependent variable

State fixed effects No Yes

Time fixed effects No Yes

7) (6 points) Estimate the model in part (5) for:

a) Only individuals with less than a high school degree.

b) Only individuals with at most a high school degree.

c) Teenagers (ages 15-19).

d) Blacks or Hispanics.

Report the results in Table 2 below. Comment on the results. Why are we interested in

these subgroups? Are the results for the different subgroups consistent with the textbook

model?

Table 2: Minimum wage and employment – Different Samples

Full sample

(same as

column 2,

part 6)

High school

dropouts

High school

or less

Teenagers Black or

Hispanic

lnܯܹ݅݊ܽ݃ ௦݁௧ Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Number of

observations

Mean dependent

variable

State fixed

effects

Yes Yes Yes Yes Yes

Time fixed

effects

Yes Yes Yes Yes Yes

8) (12 points) An economist thinks that equation (2) (from part 5) does not yield consistent

estimates of the effect of the minimum wage on employment because there may be other

variables that affect employment rates and are correlated with the minimum wage. She

therefore suggests that you estimate the following model:

ܧ݈݉ݕ݁݀௦௧ = ߚ + ߚଵ lnܯܹ݅݊ܽ݃ ௦݁௧ + ߚଶԢ ܺ௦௧ + ߚଷᇱܼ௦௧ + ߜ௦ + ߛ௧ + ݑ௦௧,

where ܺ௦௧ is a vector of individual characteristics and ܼ௦௧ is a vector of time-varying state

characteristics. Estimate the model above, report the results in Table 3 below, and comment

on what you find. but make sure to follow the following guidelines:

- You are free to choose any variables you want in ܺ௦௧ and ܼ௦௧, but remember that

you want to include variables that will plausibly address your economist friend’s

concerns: variables that are likely to affect the employment rate, but also may be

correlated with the minimum wage. Explain your rationale for including these

variables.

- You should have at least one variable in the ܺ௦௧ vector and one variable in the ܼ௦௧

vector. For variables in ܺ௦௧, you will have to simply choose variables in the CPS

sample. For variables in ܼ௦௧, you can either construct them from the CPS sample, or

merge them into the data set from other sources (but state clearly what the sources are).

These can be demographic characteristics (e.g., the share of the population with a

certain characteristic), economic characteristics (e.g., the share of workers employed

in the hospitality industry), political characteristics (the share of votes for the

Democratic candidate in the previous presidential election), etc.

- Make sure to include the variables correctly in the regression equation (make sure

that you drop missing values; transform discrete variables into a series of dummy

variables; make any non-linear transformations if necessary, etc.).

Table 3: Minimum wage and employment – Different Samples, With Controls

Full sample High school

dropouts

High school

or less

Teenagers Black or

Hispanic lnܯܹ݅݊ܽ݃ ௦݁௧ Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Number of

observations

Mean dependent

variable

Control variables Yes Yes Yes Yes Yes

State fixed

effects

Yes Yes Yes Yes Yes

Time fixed

effects

Yes Yes Yes Yes Yes

Part C: The effect of the minimum wage on hourly wages (12 points)

For this part, you will work with the sample of workers who are paid by the hour. Replace the

hourly wage variable (hourwage) to be equal to missing if the hourly wage is equal to 999.99 or

if the hourly wage has been allocated (based on the qhourwag variable).

9) Estimate regressions similar to those of part 8), but using ln(hourwage) as the dependent

variable. Report the results in Table 4 below and comment on what you find.

10) Some economists suggest that one can calculate the elasticity as labor demand as:

߲݈݊ܮ

߲݈݊ݓ

= ߲ ln ܮ߲ lnܯܹ

߲ lnݓ

߲ lnܯܹ .

Use the estimates in parts 8 and 9 and the margins command in Stata (see also Problem

Set 1) to estimate the elasticity of labor demand using this formula, for the 5 different

samples. What do these elasticity estimates imply for the effect of a minimum wage

increase on the earnings of these different groups (earnings = employment×wages)?

Table 4: Minimum wage and ln (wages) – Different Samples, With Controls

Full sample High school

dropouts

High school

or less

Teenagers Black or

Hispanic lnܯܹ݅݊ܽ݃ ௦݁௧ Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Number of

observations

Mean dependent

variable

Control variables Yes Yes Yes Yes Yes

State fixed

effects

Yes Yes Yes Yes Yes

Time fixed

effects

Yes Yes Yes Yes Yes

Part D: The effect of the minimum wage on the distribution of wages (10 points)

We will now study how the minimum wage affects the whole distribution of wages. Create a

new variable equal to the difference between the hourly wage of individual ݅ in state ݏ at time ݐ

and the 2019 effective minimum wage. Call this variable diff2019.

݂݂݀݅2019,௦,௧ = ݓ௦௧ െ ܯܹ݅݊ܽ݃݁௦,ଶଵଽ .

Split the sample into two: states in which the effective minimum wage did not increase between

2011 and 2019 (including the states in which there is no minimum wage); and states in which the

minimum wage did increase between 2011 and 2019.

11)

a. Draw a histogram of diff2019 in years 2011-2013 in states that did not

increase the minimum wage. Restrict the sample to values of diff2019 between

-11 and +15. Use the width and start options of the histogram command

to have bins of width equal to $1 and starting at whole dollar values. Use the

xline option to superimpose a vertical line at 0.

b. Repeat part a), but now for the year 2019.

c. Repeat parts a) and b), but now for the sample of states that did increase the

minimum wage between 2011 and 2019.

Comment on the four histograms. How did the entire distribution of wages change in

states that increased the minimum wage between 2011 and 2019? What about states that

did not increase the minimum wage? Would you say that today the minimum wage is

binding in states that have not increased the minimum wage since 2011?

Part E: Who gets paid the minimum wage? (12 points)

In this part, we will split the sample on the basis of the variable relate, the relationship with

the head of the household. Divide the sample into five groups:

a) Heads of household with dependents. Heads of households (relate==101), spouses

(relate ==201) or unmarried partners (relate==1114) in households in which there are any

dependent children, foster children, or other relatives.

b) Heads of household without dependents. Heads of household, spouses or unmarried

partners in households in which there are no dependent children, foster children, or other

relatives.

c) Children. Children (relate==301) or foster children (relate==1242) of the head of

household.

d) Other relatives. Other relatives of the head of household (parents, siblings,

grandparents, other relatives)

e) Other nonrelatives. Other nonrelatives of the head of household, including

housemates, roomers/boarders and other nonrelatives.

[Hint: you can uniquely identify every household in the sample by the combination of year,

month and the variable serial. Then, use the egen command in the Stata to identify households

with and without dependents.]

Define a person as a minimum wage recipient if their wage is at most $0.99 higher than the

effective minimum wage in the state.

12) For the whole population of 15-64 years olds, what fraction of minimum wage recipients

are heads with dependents, heads without dependents, children, other relatives and other

nonrelatives?

13) Repeat part 12, but now do it separately for a) states that did not increase the minimum

wage, for the years 2011-2013; b) states that did not increase the minimum wage, for

2019; c) states that did increase the minimum wage, for the years 2011-2013; d) states

that did increase the minimum wage, for 2019. Comment on the results. Is it correct to

say that the minimum wage is an ineffective tool for combating poverty, because the

beneficiaries of the minimum wage are mostly teenagers, many of which are potentially

in relatively affluent households?

Part F: Final thoughts

14) Summarize briefly (no more than half a page!) what you have learned from this problem

set about the minimum wage. Has the evidence in this problem set made you more or less

likely (or no change) to support a gradual increase in the federal minimum wage to $15

per hour?

学霸联盟

Spring 2021 – Daniele Paserman

Due: no later than Thursday, 4/8/2021 at 11:59pm Eastern time

Problem Set must be uploaded on Blackboard in the appropriate section.

Please submit your problem set as a single PDF file titled PS3_[LastName][Firstname].pdf.

Example: PS3_PasermanDaniele.pdf.

Remarks:

All work handed must be your own, with the exception that you are encouraged to discuss your

papers with each other but must turn in separate work demonstrating independent thought and

investigation.

Answers must not be poems, so try to keep your answers short. But don’t forget to explain your

results, because a single number without any explanation or the appropriate algebraic passages

will be graded lower.

Introduction

The file MinimumWage_ByState_2011-2019.dta (also available in .csv format)

contains information on the minimum wage in each US state and the District of Columbia

between 2011 and 2019. The data is taken from:

https://www.dol.gov/agencies/whd/state/minimum-wage/history. In cases in which there is more

than one minimum wage in a state, the value in the table is the highest possible value.

The file ps3_cps2011-2019.dta is a Stata file with a raw extract of the CPS for the months

of February, May, August and November between 2011 and 2019. Notice that the data is raw.

For the analysis, you will have to make sure that you clean the data (identify missing values

and categorical variables and eventually transform the data in a way that is amenable to

regression analysis).

I have also made available two additional data sets:

- cb_2018_us_state_5m.shp. This is called a shape file, and contains information

on the geographic coordinates of US states, which can then be used to draw maps in

Stata.

- cb_2018_us_state_crosswalk.dta. This is a Stata file with a crosswalk

between the state codes used in the shape file and the states codes used in the minimum

wage data set and in the CPS.

In the Problem Set, you will be asked to perform a number of analyses to describe the evolution

of minimum wage laws across states, and its impact on employment, wages, and family

outcomes.

Part A: Mapping the Minimum Wage (15 points)

In this part, you are asked to graph the data on minimum wages into a map. To create maps, you

will need to install the user-written commands spmap, shp2dta and mif2dta. See here for a starter

on how to create maps in Stata: https://www.stata.com/support/faqs/graphics/spmap-and-maps/

[The default maps created by Stata tend look a bit distorted relative to maps that you may be

familiar with. This has to do with the well-known problem of rendering in two dimensions maps

of the surface of the Earth, an ellipsoid. To make more familiar maps, you can also download the

user written command geo2xy]

1) Using the MinimumWage_ByState_2015-2019.dta file, create in Stata a

cloropleth map of minimum wages by state in 2011, 2015 and 2019, for the 48

contiguous US states (excluding Alaska and Hawaii). Comment on the results. Which

states tend to have high minimum wages? Which states tend to have low minimum

wages?

2) Create a new variable equal to the change in the minimum wage by state between 2011

and 2019 (you will probably have to use the egen command in Stata). Map this variable

and comment on the results. Which states had the largest absolute increase in the

minimum wage? Which ones had the lowest?

3) Run a regression of the absolute change in the minimum wage on the minimum wage in

2011. Comment on the results. How do these results relate to the maps you drew in

questions 1 and 2?

Part B: The effect of the minimum wage on employment (36 points)

For this part of the problem set, load the CPS data, and merge it by state and year with the

minimum wage data using the merge command. Define the effective minimum wage in a state

as the maximum between the state minimum wage and the federal minimum wage, which was

$7.25 throughout this period. Create a variable equal to ln(effective minimum wage). We will

call this lnܯܹ݅݊ܽ݃݁௦௧.

4) (6 points) Consider the following model:

ܧ݈݉ݕ݁݀௦௧ = ߚ + ߚଵ lnܯܹ݅݊ܽ݃ ௦݁௧ + ݑ௦௧ (1)

Under what assumptions does this model yield a consistent estimate of the causal effect

of the minimum wage on employment? Do you think these assumptions are likely to be

satisfied in this context?

5) (6 points) Consider instead the alternative model:

ܧ݈݉ݕ݁݀௦௧ = ߚ + ߚଵ lnܯܹ݅݊ܽ݃ ௦݁௧ + ߜ௦ + ߛ௧ + ݑ௦௧ (2)

where ߜ௦ represents state fixed effects and ߛ௧ represents time fixed effects. Under what

assumptions does this model yield a consistent estimate of the causal effect of the

minimum wage on employment? Do you think these assumptions are likely to be

satisfied in this context? Give an example

6) (6 points) Estimate the models in parts 4) and 5), using the sample of all individuals

between 15 and 64 year old, and report the results in a table that looks like Table 1 below.

(Make sure to also report the number of observations and the mean of the dependent

variable). Comment on the results. Are the results consistent with the textbook model of

the minimum wage?

Table 1: Baseline Model

Part (4): without fixed effects Part (5): with fixed effects lnܯܹ݅݊ܽ݃ ௦݁௧ Coefficient

(standard error)

Coefficient

(standard error)

Number of

observations

Mean of the

dependent variable

State fixed effects No Yes

Time fixed effects No Yes

7) (6 points) Estimate the model in part (5) for:

a) Only individuals with less than a high school degree.

b) Only individuals with at most a high school degree.

c) Teenagers (ages 15-19).

d) Blacks or Hispanics.

Report the results in Table 2 below. Comment on the results. Why are we interested in

these subgroups? Are the results for the different subgroups consistent with the textbook

model?

Table 2: Minimum wage and employment – Different Samples

Full sample

(same as

column 2,

part 6)

High school

dropouts

High school

or less

Teenagers Black or

Hispanic

lnܯܹ݅݊ܽ݃ ௦݁௧ Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Number of

observations

Mean dependent

variable

State fixed

effects

Yes Yes Yes Yes Yes

Time fixed

effects

Yes Yes Yes Yes Yes

8) (12 points) An economist thinks that equation (2) (from part 5) does not yield consistent

estimates of the effect of the minimum wage on employment because there may be other

variables that affect employment rates and are correlated with the minimum wage. She

therefore suggests that you estimate the following model:

ܧ݈݉ݕ݁݀௦௧ = ߚ + ߚଵ lnܯܹ݅݊ܽ݃ ௦݁௧ + ߚଶԢ ܺ௦௧ + ߚଷᇱܼ௦௧ + ߜ௦ + ߛ௧ + ݑ௦௧,

where ܺ௦௧ is a vector of individual characteristics and ܼ௦௧ is a vector of time-varying state

characteristics. Estimate the model above, report the results in Table 3 below, and comment

on what you find. but make sure to follow the following guidelines:

- You are free to choose any variables you want in ܺ௦௧ and ܼ௦௧, but remember that

you want to include variables that will plausibly address your economist friend’s

concerns: variables that are likely to affect the employment rate, but also may be

correlated with the minimum wage. Explain your rationale for including these

variables.

- You should have at least one variable in the ܺ௦௧ vector and one variable in the ܼ௦௧

vector. For variables in ܺ௦௧, you will have to simply choose variables in the CPS

sample. For variables in ܼ௦௧, you can either construct them from the CPS sample, or

merge them into the data set from other sources (but state clearly what the sources are).

These can be demographic characteristics (e.g., the share of the population with a

certain characteristic), economic characteristics (e.g., the share of workers employed

in the hospitality industry), political characteristics (the share of votes for the

Democratic candidate in the previous presidential election), etc.

- Make sure to include the variables correctly in the regression equation (make sure

that you drop missing values; transform discrete variables into a series of dummy

variables; make any non-linear transformations if necessary, etc.).

Table 3: Minimum wage and employment – Different Samples, With Controls

Full sample High school

dropouts

High school

or less

Teenagers Black or

Hispanic lnܯܹ݅݊ܽ݃ ௦݁௧ Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Number of

observations

Mean dependent

variable

Control variables Yes Yes Yes Yes Yes

State fixed

effects

Yes Yes Yes Yes Yes

Time fixed

effects

Yes Yes Yes Yes Yes

Part C: The effect of the minimum wage on hourly wages (12 points)

For this part, you will work with the sample of workers who are paid by the hour. Replace the

hourly wage variable (hourwage) to be equal to missing if the hourly wage is equal to 999.99 or

if the hourly wage has been allocated (based on the qhourwag variable).

9) Estimate regressions similar to those of part 8), but using ln(hourwage) as the dependent

variable. Report the results in Table 4 below and comment on what you find.

10) Some economists suggest that one can calculate the elasticity as labor demand as:

߲݈݊ܮ

߲݈݊ݓ

= ߲ ln ܮ߲ lnܯܹ

߲ lnݓ

߲ lnܯܹ .

Use the estimates in parts 8 and 9 and the margins command in Stata (see also Problem

Set 1) to estimate the elasticity of labor demand using this formula, for the 5 different

samples. What do these elasticity estimates imply for the effect of a minimum wage

increase on the earnings of these different groups (earnings = employment×wages)?

Table 4: Minimum wage and ln (wages) – Different Samples, With Controls

Full sample High school

dropouts

High school

or less

Teenagers Black or

Hispanic lnܯܹ݅݊ܽ݃ ௦݁௧ Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Coefficient

(std. error)

Number of

observations

Mean dependent

variable

Control variables Yes Yes Yes Yes Yes

State fixed

effects

Yes Yes Yes Yes Yes

Time fixed

effects

Yes Yes Yes Yes Yes

Part D: The effect of the minimum wage on the distribution of wages (10 points)

We will now study how the minimum wage affects the whole distribution of wages. Create a

new variable equal to the difference between the hourly wage of individual ݅ in state ݏ at time ݐ

and the 2019 effective minimum wage. Call this variable diff2019.

݂݂݀݅2019,௦,௧ = ݓ௦௧ െ ܯܹ݅݊ܽ݃݁௦,ଶଵଽ .

Split the sample into two: states in which the effective minimum wage did not increase between

2011 and 2019 (including the states in which there is no minimum wage); and states in which the

minimum wage did increase between 2011 and 2019.

11)

a. Draw a histogram of diff2019 in years 2011-2013 in states that did not

increase the minimum wage. Restrict the sample to values of diff2019 between

-11 and +15. Use the width and start options of the histogram command

to have bins of width equal to $1 and starting at whole dollar values. Use the

xline option to superimpose a vertical line at 0.

b. Repeat part a), but now for the year 2019.

c. Repeat parts a) and b), but now for the sample of states that did increase the

minimum wage between 2011 and 2019.

Comment on the four histograms. How did the entire distribution of wages change in

states that increased the minimum wage between 2011 and 2019? What about states that

did not increase the minimum wage? Would you say that today the minimum wage is

binding in states that have not increased the minimum wage since 2011?

Part E: Who gets paid the minimum wage? (12 points)

In this part, we will split the sample on the basis of the variable relate, the relationship with

the head of the household. Divide the sample into five groups:

a) Heads of household with dependents. Heads of households (relate==101), spouses

(relate ==201) or unmarried partners (relate==1114) in households in which there are any

dependent children, foster children, or other relatives.

b) Heads of household without dependents. Heads of household, spouses or unmarried

partners in households in which there are no dependent children, foster children, or other

relatives.

c) Children. Children (relate==301) or foster children (relate==1242) of the head of

household.

d) Other relatives. Other relatives of the head of household (parents, siblings,

grandparents, other relatives)

e) Other nonrelatives. Other nonrelatives of the head of household, including

housemates, roomers/boarders and other nonrelatives.

[Hint: you can uniquely identify every household in the sample by the combination of year,

month and the variable serial. Then, use the egen command in the Stata to identify households

with and without dependents.]

Define a person as a minimum wage recipient if their wage is at most $0.99 higher than the

effective minimum wage in the state.

12) For the whole population of 15-64 years olds, what fraction of minimum wage recipients

are heads with dependents, heads without dependents, children, other relatives and other

nonrelatives?

13) Repeat part 12, but now do it separately for a) states that did not increase the minimum

wage, for the years 2011-2013; b) states that did not increase the minimum wage, for

2019; c) states that did increase the minimum wage, for the years 2011-2013; d) states

that did increase the minimum wage, for 2019. Comment on the results. Is it correct to

say that the minimum wage is an ineffective tool for combating poverty, because the

beneficiaries of the minimum wage are mostly teenagers, many of which are potentially

in relatively affluent households?

Part F: Final thoughts

14) Summarize briefly (no more than half a page!) what you have learned from this problem

set about the minimum wage. Has the evidence in this problem set made you more or less

likely (or no change) to support a gradual increase in the federal minimum wage to $15

per hour?

学霸联盟