![i.month naturally coded Imonth 1 omitted) Source Number of obs- Mode ї Residual .110725879 005613569 13 .008517375 Prob > F 0.0000 0.9517 0.9384 01093 000119438R-squared Adj R-squared- Total .116339448 60 .001938991Root HSE nGas [95% Conf. Interval] -.0411666 . 529831 -.0779791 0358667 020317 0702461 0442586 084409 0901632 0047944 0521291 0121249 0439756 -1.740829 0121922 0944495 0069186 -1 0.001 0.000 0.000 0.000 0.007 0.000 0.000 0.000 0.000 0.504 0.000 0. 088 0.000 0.076 - . 0656942 - .016639 . 7198389 -.0640606 0493193 0347479 0846762 0584984 098483 .1042926 0191185 0664854 0261185 0579853 .1873903 lnInc .3398232 - . 0918976-. Imonth 3 onth 6 Imonth 7 Imonth 8 Imonth 9 Imonth 10 Imonth 11 006687 0071734 0071729 0070783 0069959 0070235 0071203 0071363 006956 006964 .9584831 0224141 005886 055816 0300189 07033!5 0760337 -,0095297 0377728 -,0018687 0299658 -3.669048 7.30 cons](http://img.homeworklib.com/questions/46902c30-717f-11ea-a961-a5af5410eac2.png?x-oss-process=image/resize,w_560)
The coefficients for the month of observation, _Imonth_2, _Imonth3, etc. are mean effects (dummy variables) that shift the intercept of our demand equation for each month of the sample. In terms of what we know about gasoline demand, why might it be important to model different baseline gasoline consumption by month?
Homework Answers
It is very important to incorporate the mean effects of the different month for the gasoline consumption. This is because we know that gasoline consumption does depend on the month we are looking at.
Moreover, we also want to what difference in demand of gasoline exists between different month and how volatile are the demands in different month relatively.
Add Answer to:
The coefficients for the month of observation,
_Imonth_2, _Imonth3, etc. are mean effects (dummy variables) that...
Estimate from 1975-1980: Estimate from 2001 – 2006: a. Compare the estimated price elasticity during these...
Estimate from 1975-1980:
Estimate from 2001 – 2006:
a. Compare the estimated price elasticity during these
years with your estimate from 1975-1980 above.
b. Interpret the estimated coefficient on logged per
capita income (lnInc). Discuss the sign, magnitude and statistical
significance. What does this estimate tell us about how gasoline
demand in the 2000’s responded to changes in income?
(Please answer a & b completely) Thank
you!
[lnGas = ln(gascap)
lnP = ln(realprice)
lnInc = ln(inccap)
realprice = Real price...
The coefficients for the month of observation, _Imonth_2, _Imonth3, etc. are mean effects (dummy variables) that...
The coefficients for the month of observation,
_Imonth_2, _Imonth3, etc. are mean effects (dummy variables) that
shift the intercept of our demand equation for each month of the
sample. In terms of what we know about gasoline demand, why might
it be important to model different baseline gasoline consumption by
month?
. xi: reg lnGas lnP lnInc i.month if date >- 494 & date <- 554 i.month Imonth_1-12 (naturally coded; _Imonth_1 omitted) Source df MS Number of obs 61 F...
Interpret the coefficient on logged real gasoline price (lnP) in terms of the sign, magnitude and...
Interpret the coefficient on logged real gasoline price
(lnP) in terms of the sign, magnitude and statistical significance.
What does this estimate tell us about the average response of
gasoline demand to changes in prices from 1975-1980.
[lnGas = ln(gascap)
lnP = ln(realprice)
lnInc = ln(inccap)
realprice = Real price of gasoline (2000 $)
gascap = Gas demanded per capita (gallons per month)
inccap = Real income per capita (2000 $)
date = Year and month of observation (text)
year...
Interpret the coefficient on logged real gasoline price (lnP) in terms of the sign, magnitude and...
Interpret the coefficient on logged real gasoline price
(lnP) in terms of the sign, magnitude and statistical significance.
What does this estimate tell us about the average response of
gasoline demand to changes in prices from 1975-1980.
[lnGas = ln(gascap)
lnP = ln(realprice)
lnInc = ln(inccap)
realprice = Real price of gasoline (2000 $)
gascap = Gas demanded per capita (gallons per month)
inccap = Real income per capita (2000 $)
date = Year and month of observation (text)
year...
8. Dummy variables. Interpretation and t-test of coefficients of dummy variables. Example Question: Are earnings subject...
8. Dummy variables. Interpretation and t-test of coefficients of dummy variables. Example Question: Are earnings subject to ethnic discrimination? Using the Labor Force Participation 2011 data, we run the following regression: EARNINGS = B1 + B2S + B3 EXP + B.ETHWHITE + u, where EARNINGS is the hourly earnings in dollar, S is years of schooling, EXP is total work experience, and ETHWHITE is a dummy variable which equals to 1 if the individual is white and equals to otherwise....
Question 4 We will look at the possible effects of gender of an individual on educationol attainment. In the dataset is S years of schooling, ASVABC is composite score on the cognitive tests, SM is y...
Question 4 We will look at the possible effects of gender of an individual on educationol attainment. In the dataset is S years of schooling, ASVABC is composite score on the cognitive tests, SM is years of schooling of the respondent's mother, SF is years of schooling of the respondent's father, MALE is a dummy variable equal to 1 if the respondent was a male Some of the regression output has been deliberately hidden. Source I df MS Number of...
1) Using the table below, complete the questions that follow (econometrics) a) Using the table above,...
1) Using the table below, complete the questions that follow
(econometrics)
a) Using the table above, which coefficients are statistically
significant? And is the model significant?
b) Give me the equations to calculate the following a t-stat, an
f-stat, coefficient in an SLR, and a Standard Error.
c) What are the 6 Gauss-Markov Assumptions and what, when met,
do they say about our linear model.
d) What is the t-stat for a 95% confidence interval, with 522
degrees of freedom?...
A researcher is examining the effect of number of years in a particular job (tenure) on...
A researcher is examining the effect of number of years in a particular job (tenure) on the hourly wage (USD) earned. She estimates two regression models using data on 124 young women surveyed in 1988. In the first regression, she regressed logged hourly wage on logged tenure in the current job (years in current job). In the second regression she regressed logged hourly wage on logged tenure in the current job, as well as age, total years of schooling completed,...
Question 2 (15 marks in total] University students are expected to attend all classes within a...
Question 2 (15 marks in total] University students are expected to attend all classes within a course. But university administrators and teaching staff are aware that student attendance can be adversely impacted by a variety of factors including travel time. Also, when attendance rates drop, there are often concerns expressed that it is students most at risk of performing poorly who are not attending class. To better understand some of these issues, a sample of undergraduate students was drawn from...
A sample consists of 1,388 observations, where the unit of observation is an individual. packsi is...
A sample consists of 1,388 observations, where the unit of
observation is an individual. packsi is the number of packs of
cigarettes woman i smoked per day while pregnant, and bwghti is the
birth weight (in ounces) of the woman’s child. Given the
information found in the attached STATA output,
(1) The population model implied by the regression output
is
(2) In the space below, provide a variable that could possibly
affect your dependent variable, but was not accounted for...
Estimate from 1975-1980:
Estimate from 2001 – 2006:
a. Compare the estimated price elasticity during these
years with your estimate from 1975-1980 above.
b. Interpret the estimated coefficient on logged per
capita income (lnInc). Discuss the sign, magnitude and statistical
significance. What does this estimate tell us about how gasoline
demand in the 2000’s responded to changes in income?
(Please answer a & b completely) Thank
you!
[lnGas = ln(gascap)
lnP = ln(realprice)
lnInc = ln(inccap)
realprice = Real price...
The coefficients for the month of observation,
_Imonth_2, _Imonth3, etc. are mean effects (dummy variables) that
shift the intercept of our demand equation for each month of the
sample. In terms of what we know about gasoline demand, why might
it be important to model different baseline gasoline consumption by
month?
. xi: reg lnGas lnP lnInc i.month if date >- 494 & date <- 554 i.month Imonth_1-12 (naturally coded; _Imonth_1 omitted) Source df MS Number of obs 61 F...
Interpret the coefficient on logged real gasoline price
(lnP) in terms of the sign, magnitude and statistical significance.
What does this estimate tell us about the average response of
gasoline demand to changes in prices from 1975-1980.
[lnGas = ln(gascap)
lnP = ln(realprice)
lnInc = ln(inccap)
realprice = Real price of gasoline (2000 $)
gascap = Gas demanded per capita (gallons per month)
inccap = Real income per capita (2000 $)
date = Year and month of observation (text)
year...
Interpret the coefficient on logged real gasoline price
(lnP) in terms of the sign, magnitude and statistical significance.
What does this estimate tell us about the average response of
gasoline demand to changes in prices from 1975-1980.
[lnGas = ln(gascap)
lnP = ln(realprice)
lnInc = ln(inccap)
realprice = Real price of gasoline (2000 $)
gascap = Gas demanded per capita (gallons per month)
inccap = Real income per capita (2000 $)
date = Year and month of observation (text)
year...
8. Dummy variables. Interpretation and t-test of coefficients of dummy variables. Example Question: Are earnings subject to ethnic discrimination? Using the Labor Force Participation 2011 data, we run the following regression: EARNINGS = B1 + B2S + B3 EXP + B.ETHWHITE + u, where EARNINGS is the hourly earnings in dollar, S is years of schooling, EXP is total work experience, and ETHWHITE is a dummy variable which equals to 1 if the individual is white and equals to otherwise....
Question 4 We will look at the possible effects of gender of an individual on educationol attainment. In the dataset is S years of schooling, ASVABC is composite score on the cognitive tests, SM is years of schooling of the respondent's mother, SF is years of schooling of the respondent's father, MALE is a dummy variable equal to 1 if the respondent was a male Some of the regression output has been deliberately hidden. Source I df MS Number of...
1) Using the table below, complete the questions that follow
(econometrics)
a) Using the table above, which coefficients are statistically
significant? And is the model significant?
b) Give me the equations to calculate the following a t-stat, an
f-stat, coefficient in an SLR, and a Standard Error.
c) What are the 6 Gauss-Markov Assumptions and what, when met,
do they say about our linear model.
d) What is the t-stat for a 95% confidence interval, with 522
degrees of freedom?...
A researcher is examining the effect of number of years in a particular job (tenure) on the hourly wage (USD) earned. She estimates two regression models using data on 124 young women surveyed in 1988. In the first regression, she regressed logged hourly wage on logged tenure in the current job (years in current job). In the second regression she regressed logged hourly wage on logged tenure in the current job, as well as age, total years of schooling completed,...
Question 2 (15 marks in total] University students are expected to attend all classes within a course. But university administrators and teaching staff are aware that student attendance can be adversely impacted by a variety of factors including travel time. Also, when attendance rates drop, there are often concerns expressed that it is students most at risk of performing poorly who are not attending class. To better understand some of these issues, a sample of undergraduate students was drawn from...
A sample consists of 1,388 observations, where the unit of
observation is an individual. packsi is the number of packs of
cigarettes woman i smoked per day while pregnant, and bwghti is the
birth weight (in ounces) of the woman’s child. Given the
information found in the attached STATA output,
(1) The population model implied by the regression output
is
(2) In the space below, provide a variable that could possibly
affect your dependent variable, but was not accounted for...
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