Econometrics Assignment 1

Assignment  1
[1]  Download  the  data  file  CHICK6.csv  from  Assignment  1.
[2] Load the CHICK6.csv data into R and rename it so that it includes your own name or initials (for example,
we  might  name  our  dataset  JunfuCHICK6 ).
[3] Generate the mean and the standard deviation for the variables Y, PC, PB, and YD  from the CHICK6.csv
data  set.
[4]  You  are  going  to  run  a  regression  (in  [5])  where  Y  is  the  dependent  variable,  and  PC,  PB,  and  YD  are
the  independent  variables.  Discuss  whether  you  think  the  independent  variable  PB  will  have  a  negative  or
positive  eect  on  the  dependent  variable.  In  your  decision,  try  to  use  as  much  economic  theory  as  you  can  —
theory  is  what  motivates  what  variables  are  included  in  a  model  and  what  sign  we  anticipate  for  the  model’s
estimates.
[5]  Estimate  the  model  in  R  and  present  the  results.
[6]  Interpret  the  results  for  the  coefficient  PB  from  your  model.  Make  sure  to  include  whether  or  not  the
result  aligned  with  your  expectations. 

Econ 4650, Spring 2019
Assignment

1

Introduction

Welcome to Assignment 1!

It is suggested you do the following before attempting this assignment*

• Read the appropriate textbook chapters (Chapter 1 & Chapter 2 in the Custom Text;
Chapter 17 & Chapter 1 in the full text)

• Read the Econ_4650_Sprin_2019_Intro_to_R in Module 1.a
• Install the software R
• Read OrdinaryLeastSquares pdf in Module 1.b
• Take a deep breath!

*Note, You may also watch the Module 1 video tutorials, but this is not required. Also, please note that
there have been adjustments to the number of assignments and the structure of the course since the time the
videos were made.

Definitions for Annual Consumption of Chicken Data

Y = per capita chicken consumption (in pound) in a given year

PC = the price of chicken (in cents per pound) in a given year

PB = the price of beef (in cents per pound) in a given year

YD = U.S. per capita disposable income (in hundred of dollars) in a given year

Assignment 1

[1] Download the data file CHICK6.csv from Assignment 1.

[2] Load the CHICK6.csv data into R and rename it so that it includes your own name or initials (for example,
we might name our dataset JunfuCHICK6 ).

[3] Generate the mean and the standard deviation for the variables Y, PC, PB, and YD from the CHICK6.csv
data set.

[4] You are going to run a regression (in [5]) where Y is the dependent variable, and PC, PB, and YD are
the independent variables. Discuss whether you think the independent variable PB will have a negative or
positive e�ect on the dependent variable. In your decision, try to use as much economic theory as you can –
theory is what motivates what variables are included in a model and what sign we anticipate for the model’s
estimates.

[5] Estimate the model in R and present the results.

[6] Interpret the results for the coe�cient PB from your model. Make sure to include whether or not the
result aligned with your expectations.

1

Rectangle

FreeText
Principles of Econometrics

EAR

Y

9.7

.3

3.

0.1

7.8

2

75

.4

2.2

4

.6

3

.72

134

4

5.4

5

5

.6

6

.

2.4

13

.5

7

3.6

8

49

9

2

51.5

4

5.6

10

1.31

35

11

11

12

.6

4

13

.49

18

14

238.4

35

15

.1

0.3

16

.2

17

.5

64

18

57.7

52

19

59

18

9.5

20

3.4

27

21

48

22

71

23

28

36

24

60

25

89

26

60

27

43

62

28

29

85

OBS		Y	PC	PB	YD	TEMP	PRP
1	1	9	7			4		3	4	2		14	8			5	–	1	6		10
	19	38.69		49		15	54.98	-4				13
1976	42.02	45.5	145.7		59	–	24
1977	42.	71	45.3	145.9	65.	17	16		12
1978	44.75	49.3	178.8	72.24	1	43
1979		48		35	50		22	79.67	1	52
1980	48.47	53.5		23	88.22		21	147.5
1981	50.37	53.8	234.7	97.65	161.2
1982		51.5		238.4	104.	26				18
1983	52.55	56	234.1			11	179.7
1984	54.61	61.5	235.5	123.19	171.4
19	85	56.42	56.2	2		28	130.37	170.8
1986		57.7	63.1	226.8	1	36	188.8
1987	61.94	53.1	142.41	199.4
1988	63.8		62		25	152.97	46	194
19	89	66.88		64	265.7	162.57	32	193.5
1990	70.34			60	281	171.31	224.9
1991	73.26	288.3	176.09	224.2
1992	76.39	284.6	184.94		20
1993	78.		27	27.1		29	188.72	209.1
1994	79.65	26.2	282.9	195.55	209.5
1995	79.27	26.9	284.3	202.87	206.1
1996	80.61	280.2	210.91	233.7
1997	83.1	33.2	279.5	219.4	245
1998	83.76	33.4	277.1	231.61	242.7
1999	88.98	39.5	287.8	239.68	241.4
2000	90.08	306.4	254.69	258.2
2001	89.71	43.4	337.7	262.24	74	269.4
2002	94.37	43.9	331.5	271.45	265.8

Econ 4650, Spring 2019
Assignment

1

Introduction

Welcome to Assignment 1!

It is suggested you do the following before attempting this assignment*

• Read the appropriate textbook chapters (Chapter 1 & Chapter 2 in the Custom Text;
Chapter 17 & Chapter 1 in the full text)

• Read the Econ_4650_Sprin_2019_Intro_to_R in Module 1.a
• Install the software R
• Read OrdinaryLeastSquares pdf in Module 1.b
• Take a deep breath!

*Note, You may also watch the Module 1 video tutorials, but this is not required. Also, please note that
there have been adjustments to the number of assignments and the structure of the course since the time the
videos were made.

Definitions for Annual Consumption of Chicken Data

Y = per capita chicken consumption (in pound) in a given year

PC = the price of chicken (in cents per pound) in a given year

PB = the price of beef (in cents per pound) in a given year

YD = U.S. per capita disposable income (in hundred of dollars) in a given year

Assignment 1

[1] Download the data file CHICK6.csv from Assignment 1.

[2] Load the CHICK6.csv data into R and rename it so that it includes your own name or initials (for example,
we might name our dataset JunfuCHICK6 ).

[3] Generate the mean and the standard deviation for the variables Y, PC, PB, and YD from the CHICK6.csv
data set.

[4] You are going to run a regression (in [5]) where Y is the dependent variable, and PC, PB, and YD are
the independent variables. Discuss whether you think the independent variable PB will have a negative or
positive e�ect on the dependent variable. In your decision, try to use as much economic theory as you can –
theory is what motivates what variables are included in a model and what sign we anticipate for the model’s
estimates.

[5] Estimate the model in R and present the results.

[6] Interpret the results for the coe�cient PB from your model. Make sure to include whether or not the
result aligned with your expectations.

1

Rectangle

FreeText
Principles of Econometrics

EAR

Y

9.7

.3

3.

0.1

7.8

2

75

.4

2.2

4

.6

3

.72

134

4

5.4

5

5

.6

6

.

2.4

13

.5

7

3.6

8

49

9

2

51.5

4

5.6

10

1.31

35

11

11

12

.6

4

13

.49

18

14

238.4

35

15

.1

0.3

16

.2

17

.5

64

18

57.7

52

19

59

18

9.5

20

3.4

27

21

48

22

71

23

28

36

24

60

25

89

26

60

27

43

62

28

29

85

OBS		Y	PC	PB	YD	TEMP	PRP
1	1	9	7			4		3	4	2		14	8			5	–	1	6		10
	19	38.69		49		15	54.98	-4				13
1976	42.02	45.5	145.7		59	–	24
1977	42.	71	45.3	145.9	65.	17	16		12
1978	44.75	49.3	178.8	72.24	1	43
1979		48		35	50		22	79.67	1	52
1980	48.47	53.5		23	88.22		21	147.5
1981	50.37	53.8	234.7	97.65	161.2
1982		51.5		238.4	104.	26				18
1983	52.55	56	234.1			11	179.7
1984	54.61	61.5	235.5	123.19	171.4
19	85	56.42	56.2	2		28	130.37	170.8
1986		57.7	63.1	226.8	1	36	188.8
1987	61.94	53.1	142.41	199.4
1988	63.8		62		25	152.97	46	194
19	89	66.88		64	265.7	162.57	32	193.5
1990	70.34			60	281	171.31	224.9
1991	73.26	288.3	176.09	224.2
1992	76.39	284.6	184.94		20
1993	78.		27	27.1		29	188.72	209.1
1994	79.65	26.2	282.9	195.55	209.5
1995	79.27	26.9	284.3	202.87	206.1
1996	80.61	280.2	210.91	233.7
1997	83.1	33.2	279.5	219.4	245
1998	83.76	33.4	277.1	231.61	242.7
1999	88.98	39.5	287.8	239.68	241.4
2000	90.08	306.4	254.69	258.2
2001	89.71	43.4	337.7	262.24	74	269.4
2002	94.37	43.9	331.5	271.45	265.8

Econ 4650, Spring 2019
Assignment

1

Introduction

Welcome to Assignment 1!

It is suggested you do the following before attempting this assignment*

• Read the appropriate textbook chapters (Chapter 1 & Chapter 2 in the Custom Text;
Chapter 17 & Chapter 1 in the full text)

• Read the Econ_4650_Sprin_2019_Intro_to_R in Module 1.a
• Install the software R
• Read OrdinaryLeastSquares pdf in Module 1.b
• Take a deep breath!

*Note, You may also watch the Module 1 video tutorials, but this is not required. Also, please note that
there have been adjustments to the number of assignments and the structure of the course since the time the
videos were made.

Definitions for Annual Consumption of Chicken Data

Y = per capita chicken consumption (in pound) in a given year

PC = the price of chicken (in cents per pound) in a given year

PB = the price of beef (in cents per pound) in a given year

YD = U.S. per capita disposable income (in hundred of dollars) in a given year

Assignment 1

[1] Download the data file CHICK6.csv from Assignment 1.

[2] Load the CHICK6.csv data into R and rename it so that it includes your own name or initials (for example,
we might name our dataset JunfuCHICK6 ).

[3] Generate the mean and the standard deviation for the variables Y, PC, PB, and YD from the CHICK6.csv
data set.

[4] You are going to run a regression (in [5]) where Y is the dependent variable, and PC, PB, and YD are
the independent variables. Discuss whether you think the independent variable PB will have a negative or
positive e�ect on the dependent variable. In your decision, try to use as much economic theory as you can –
theory is what motivates what variables are included in a model and what sign we anticipate for the model’s
estimates.

[5] Estimate the model in R and present the results.

[6] Interpret the results for the coe�cient PB from your model. Make sure to include whether or not the
result aligned with your expectations.

1

Rectangle

FreeText
Principles of Econometrics

EAR

Y

9.7

.3

3.

0.1

7.8

2

75

.4

2.2

4

.6

3

.72

134

4

5.4

5

5

.6

6

.

2.4

13

.5

7

3.6

8

49

9

2

51.5

4

5.6

10

1.31

35

11

11

12

.6

4

13

.49

18

14

238.4

35

15

.1

0.3

16

.2

17

.5

64

18

57.7

52

19

59

18

9.5

20

3.4

27

21

48

22

71

23

28

36

24

60

25

89

26

60

27

43

62

28

29

85

OBS		Y	PC	PB	YD	TEMP	PRP
1	1	9	7			4		3	4	2		14	8			5	–	1	6		10
	19	38.69		49		15	54.98	-4				13
1976	42.02	45.5	145.7		59	–	24
1977	42.	71	45.3	145.9	65.	17	16		12
1978	44.75	49.3	178.8	72.24	1	43
1979		48		35	50		22	79.67	1	52
1980	48.47	53.5		23	88.22		21	147.5
1981	50.37	53.8	234.7	97.65	161.2
1982		51.5		238.4	104.	26				18
1983	52.55	56	234.1			11	179.7
1984	54.61	61.5	235.5	123.19	171.4
19	85	56.42	56.2	2		28	130.37	170.8
1986		57.7	63.1	226.8	1	36	188.8
1987	61.94	53.1	142.41	199.4
1988	63.8		62		25	152.97	46	194
19	89	66.88		64	265.7	162.57	32	193.5
1990	70.34			60	281	171.31	224.9
1991	73.26	288.3	176.09	224.2
1992	76.39	284.6	184.94		20
1993	78.		27	27.1		29	188.72	209.1
1994	79.65	26.2	282.9	195.55	209.5
1995	79.27	26.9	284.3	202.87	206.1
1996	80.61	280.2	210.91	233.7
1997	83.1	33.2	279.5	219.4	245
1998	83.76	33.4	277.1	231.61	242.7
1999	88.98	39.5	287.8	239.68	241.4
2000	90.08	306.4	254.69	258.2
2001	89.71	43.4	337.7	262.24	74	269.4
2002	94.37	43.9	331.5	271.45	265.8

Econ 4650, Spring 2019
Assignment

1

Introduction

Welcome to Assignment 1!

It is suggested you do the following before attempting this assignment*

• Read the appropriate textbook chapters (Chapter 1 & Chapter 2 in the Custom Text;
Chapter 17 & Chapter 1 in the full text)

• Read the Econ_4650_Sprin_2019_Intro_to_R in Module 1.a
• Install the software R
• Read OrdinaryLeastSquares pdf in Module 1.b
• Take a deep breath!

*Note, You may also watch the Module 1 video tutorials, but this is not required. Also, please note that
there have been adjustments to the number of assignments and the structure of the course since the time the
videos were made.

Definitions for Annual Consumption of Chicken Data

Y = per capita chicken consumption (in pound) in a given year

PC = the price of chicken (in cents per pound) in a given year

PB = the price of beef (in cents per pound) in a given year

YD = U.S. per capita disposable income (in hundred of dollars) in a given year

Assignment 1

[1] Download the data file CHICK6.csv from Assignment 1.

[2] Load the CHICK6.csv data into R and rename it so that it includes your own name or initials (for example,
we might name our dataset JunfuCHICK6 ).

[3] Generate the mean and the standard deviation for the variables Y, PC, PB, and YD from the CHICK6.csv
data set.

[4] You are going to run a regression (in [5]) where Y is the dependent variable, and PC, PB, and YD are
the independent variables. Discuss whether you think the independent variable PB will have a negative or
positive e�ect on the dependent variable. In your decision, try to use as much economic theory as you can –
theory is what motivates what variables are included in a model and what sign we anticipate for the model’s
estimates.

[5] Estimate the model in R and present the results.

[6] Interpret the results for the coe�cient PB from your model. Make sure to include whether or not the
result aligned with your expectations.

1

Rectangle

FreeText
Principles of Econometrics

EAR

Y

9.7

.3

3.

0.1

7.8

2

75

.4

2.2

4

.6

3

.72

134

4

5.4

5

5

.6

6

.

2.4

13

.5

7

3.6

8

49

9

2

51.5

4

5.6

10

1.31

35

11

11

12

.6

4

13

.49

18

14

238.4

35

15

.1

0.3

16

.2

17

.5

64

18

57.7

52

19

59

18

9.5

20

3.4

27

21

48

22

71

23

28

36

24

60

25

89

26

60

27

43

62

28

29

85

OBS		Y	PC	PB	YD	TEMP	PRP
1	1	9	7			4		3	4	2		14	8			5	–	1	6		10
	19	38.69		49		15	54.98	-4				13
1976	42.02	45.5	145.7		59	–	24
1977	42.	71	45.3	145.9	65.	17	16		12
1978	44.75	49.3	178.8	72.24	1	43
1979		48		35	50		22	79.67	1	52
1980	48.47	53.5		23	88.22		21	147.5
1981	50.37	53.8	234.7	97.65	161.2
1982		51.5		238.4	104.	26				18
1983	52.55	56	234.1			11	179.7
1984	54.61	61.5	235.5	123.19	171.4
19	85	56.42	56.2	2		28	130.37	170.8
1986		57.7	63.1	226.8	1	36	188.8
1987	61.94	53.1	142.41	199.4
1988	63.8		62		25	152.97	46	194
19	89	66.88		64	265.7	162.57	32	193.5
1990	70.34			60	281	171.31	224.9
1991	73.26	288.3	176.09	224.2
1992	76.39	284.6	184.94		20
1993	78.		27	27.1		29	188.72	209.1
1994	79.65	26.2	282.9	195.55	209.5
1995	79.27	26.9	284.3	202.87	206.1
1996	80.61	280.2	210.91	233.7
1997	83.1	33.2	279.5	219.4	245
1998	83.76	33.4	277.1	231.61	242.7
1999	88.98	39.5	287.8	239.68	241.4
2000	90.08	306.4	254.69	258.2
2001	89.71	43.4	337.7	262.24	74	269.4
2002	94.37	43.9	331.5	271.45	265.8

Econ 4650, Spring 2019
Assignment

1

Introduction

Welcome to Assignment 1!

It is suggested you do the following before attempting this assignment*

• Read the appropriate textbook chapters (Chapter 1 & Chapter 2 in the Custom Text;
Chapter 17 & Chapter 1 in the full text)

• Read the Econ_4650_Sprin_2019_Intro_to_R in Module 1.a
• Install the software R
• Read OrdinaryLeastSquares pdf in Module 1.b
• Take a deep breath!

*Note, You may also watch the Module 1 video tutorials, but this is not required. Also, please note that
there have been adjustments to the number of assignments and the structure of the course since the time the
videos were made.

Definitions for Annual Consumption of Chicken Data

Y = per capita chicken consumption (in pound) in a given year

PC = the price of chicken (in cents per pound) in a given year

PB = the price of beef (in cents per pound) in a given year

YD = U.S. per capita disposable income (in hundred of dollars) in a given year

Assignment 1

[1] Download the data file CHICK6.csv from Assignment 1.

[2] Load the CHICK6.csv data into R and rename it so that it includes your own name or initials (for example,
we might name our dataset JunfuCHICK6 ).

[3] Generate the mean and the standard deviation for the variables Y, PC, PB, and YD from the CHICK6.csv
data set.

[4] You are going to run a regression (in [5]) where Y is the dependent variable, and PC, PB, and YD are
the independent variables. Discuss whether you think the independent variable PB will have a negative or
positive e�ect on the dependent variable. In your decision, try to use as much economic theory as you can –
theory is what motivates what variables are included in a model and what sign we anticipate for the model’s
estimates.

[5] Estimate the model in R and present the results.

[6] Interpret the results for the coe�cient PB from your model. Make sure to include whether or not the
result aligned with your expectations.

1

Rectangle

FreeText
Principles of Econometrics

EAR

Y

9.7

.3

3.

0.1

7.8

2

75

.4

2.2

4

.6

3

.72

134

4

5.4

5

5

.6

6

.

2.4

13

.5

7

3.6

8

49

9

2

51.5

4

5.6

10

1.31

35

11

11

12

.6

4

13

.49

18

14

238.4

35

15

.1

0.3

16

.2

17

.5

64

18

57.7

52

19

59

18

9.5

20

3.4

27

21

48

22

71

23

28

36

24

60

25

89

26

60

27

43

62

28

29

85

OBS		Y	PC	PB	YD	TEMP	PRP
1	1	9	7			4		3	4	2		14	8			5	–	1	6		10
	19	38.69		49		15	54.98	-4				13
1976	42.02	45.5	145.7		59	–	24
1977	42.	71	45.3	145.9	65.	17	16		12
1978	44.75	49.3	178.8	72.24	1	43
1979		48		35	50		22	79.67	1	52
1980	48.47	53.5		23	88.22		21	147.5
1981	50.37	53.8	234.7	97.65	161.2
1982		51.5		238.4	104.	26				18
1983	52.55	56	234.1			11	179.7
1984	54.61	61.5	235.5	123.19	171.4
19	85	56.42	56.2	2		28	130.37	170.8
1986		57.7	63.1	226.8	1	36	188.8
1987	61.94	53.1	142.41	199.4
1988	63.8		62		25	152.97	46	194
19	89	66.88		64	265.7	162.57	32	193.5
1990	70.34			60	281	171.31	224.9
1991	73.26	288.3	176.09	224.2
1992	76.39	284.6	184.94		20
1993	78.		27	27.1		29	188.72	209.1
1994	79.65	26.2	282.9	195.55	209.5
1995	79.27	26.9	284.3	202.87	206.1
1996	80.61	280.2	210.91	233.7
1997	83.1	33.2	279.5	219.4	245
1998	83.76	33.4	277.1	231.61	242.7
1999	88.98	39.5	287.8	239.68	241.4
2000	90.08	306.4	254.69	258.2
2001	89.71	43.4	337.7	262.24	74	269.4
2002	94.37	43.9	331.5	271.45	265.8

Econ 4650, Spring 2019
Assignment

1

Introduction

Welcome to Assignment 1!

It is suggested you do the following before attempting this assignment*

• Read the appropriate textbook chapters (Chapter 1 & Chapter 2 in the Custom Text;
Chapter 17 & Chapter 1 in the full text)

• Read the Econ_4650_Sprin_2019_Intro_to_R in Module 1.a
• Install the software R
• Read OrdinaryLeastSquares pdf in Module 1.b
• Take a deep breath!

*Note, You may also watch the Module 1 video tutorials, but this is not required. Also, please note that
there have been adjustments to the number of assignments and the structure of the course since the time the
videos were made.

Definitions for Annual Consumption of Chicken Data

Y = per capita chicken consumption (in pound) in a given year

PC = the price of chicken (in cents per pound) in a given year

PB = the price of beef (in cents per pound) in a given year

YD = U.S. per capita disposable income (in hundred of dollars) in a given year

Assignment 1

[1] Download the data file CHICK6.csv from Assignment 1.

[2] Load the CHICK6.csv data into R and rename it so that it includes your own name or initials (for example,
we might name our dataset JunfuCHICK6 ).

[3] Generate the mean and the standard deviation for the variables Y, PC, PB, and YD from the CHICK6.csv
data set.

[4] You are going to run a regression (in [5]) where Y is the dependent variable, and PC, PB, and YD are
the independent variables. Discuss whether you think the independent variable PB will have a negative or
positive e�ect on the dependent variable. In your decision, try to use as much economic theory as you can –
theory is what motivates what variables are included in a model and what sign we anticipate for the model’s
estimates.

[5] Estimate the model in R and present the results.

[6] Interpret the results for the coe�cient PB from your model. Make sure to include whether or not the
result aligned with your expectations.

1

Rectangle

FreeText
Principles of Econometrics

EAR

Y

9.7

.3

3.

0.1

7.8

2

75

.4

2.2

4

.6

3

.72

134

4

5.4

5

5

.6

6

.

2.4

13

.5

7

3.6

8

49

9

2

51.5

4

5.6

10

1.31

35

11

11

12

.6

4

13

.49

18

14

238.4

35

15

.1

0.3

16

.2

17

.5

64

18

57.7

52

19

59

18

9.5

20

3.4

27

21

48

22

71

23

28

36

24

60

25

89

26

60

27

43

62

28

29

85

OBS		Y	PC	PB	YD	TEMP	PRP
1	1	9	7			4		3	4	2		14	8			5	–	1	6		10
	19	38.69		49		15	54.98	-4				13
1976	42.02	45.5	145.7		59	–	24
1977	42.	71	45.3	145.9	65.	17	16		12
1978	44.75	49.3	178.8	72.24	1	43
1979		48		35	50		22	79.67	1	52
1980	48.47	53.5		23	88.22		21	147.5
1981	50.37	53.8	234.7	97.65	161.2
1982		51.5		238.4	104.	26				18
1983	52.55	56	234.1			11	179.7
1984	54.61	61.5	235.5	123.19	171.4
19	85	56.42	56.2	2		28	130.37	170.8
1986		57.7	63.1	226.8	1	36	188.8
1987	61.94	53.1	142.41	199.4
1988	63.8		62		25	152.97	46	194
19	89	66.88		64	265.7	162.57	32	193.5
1990	70.34			60	281	171.31	224.9
1991	73.26	288.3	176.09	224.2
1992	76.39	284.6	184.94		20
1993	78.		27	27.1		29	188.72	209.1
1994	79.65	26.2	282.9	195.55	209.5
1995	79.27	26.9	284.3	202.87	206.1
1996	80.61	280.2	210.91	233.7
1997	83.1	33.2	279.5	219.4	245
1998	83.76	33.4	277.1	231.61	242.7
1999	88.98	39.5	287.8	239.68	241.4
2000	90.08	306.4	254.69	258.2
2001	89.71	43.4	337.7	262.24	74	269.4
2002	94.37	43.9	331.5	271.45	265.8