Deck 13: Panel Data

Full screen (f)
exit full mode
Question
Panel data differs from time-series data in that panel data is observed

A)for a number of different individuals in a number of different time-periods.
B)for a given individual in a number of different time-periods.
C)for a number of different individuals in a given time-period.
D)for a given individual in a given time-period.
Use Space or
up arrow
down arrow
to flip the card.
Question
First-differenced models are preferable to pooled cross-section models because they

A)control for potential autocorrelation.
B)control for potential heteroskedasticity.
C)control for the random effects in the data.
D)remove the time constant component in the error term.
Question
The fact that panel data varies across both individuals and time-periods should allow us to ___________ by accounting for the time constant component in the error term.

A)generate unbiased parameter estimates
B)correctly estimate the true parameter values
C)control for autocorrelation
D)improve the efficiency of the parameter estimates
Question
If there is a pooled cross-section model with and intercept and five explanatory variables and there are 100 observations each year for three years

A)the sample size is 100.
B)there are 294 degrees of freedom.
C)the sample size is 294.
D)there are 300 degrees of freedom.
Question
Fixed-effects models are more appropriate than random-effects models when

A)the error terms are autocorrelated.
B)the independent variables are constant over time.
C)the time invariant component of the error term is correlated with any of the independent variables.
D)the error term is not constant.
Question
One can first-difference panel data in a two-period model by subtracting

A)the previous-period observation from the current-period observation for the dependent variable.
B)the previous-period observation from the current-period observation for the dependent variable and each independent variable.
C)the current-period observation from the previous-period observation for the dependent variable and each independent variable.
D)the current-period observation from the previous-period observation for the independent variable.
Question
Fixed-effects models

A)remove the time-variant component of the error term.
B)remove the time-invariant component of the error term.
C)work by first-differencing the data.
D)remove the heteroskedasticity in the data.
Question
Pooled cross-section models

A)control for individual fixed-effects.
B)combine observations over many different years.
C)control for unobserved heterogeneity.
D)control for random-effects.
Question
Treating each data point in panel data as an individual observation and not accounting for the fact that individuals are observed over many time periods is referred to as estimating a ____ model.

A)static time-series
B)heteroskedastic consistent
C)pooled cross-section
D)fixed-effects
Question
Fixed-effects models are preferable to pooled cross-section models because they

A)first-difference the data.
B)control for potential heteroskedasticity.
C)control for autocorrelation.
D)remove the time-invariant component of the error term.
Question
Fixed-effects models and first-differenced models

A)assume that the time-invariant component of the error term is not correlated with the independent variables.
B)both add dummy variables to control for individual observations.
C)do not provide identical results if there are more than two years of data.
D)do not completely remove the time-invariant component of the error term.
Question
Random-effects models improve on pooled cross-section models because they

A)do not take advantage of the panel data nature of the data.
B)have more degrees of freedom available.
C)improve the efficiency of the estimated coefficients.
D)correct for heteroskedasticity.
Question
Pooled cross-section models are not the preferred estimators for panel data models because they

A)are heteroskedastic.
B)are quasi-differenced.
C)do nothing to account for the time constant component of the error term.
D)create a dummy variable for each individual in the data set.
Question
Random-effects models are more appropriate than fixed-effects models when

A)the time invariant component of the error term is not correlated with one or more the independent variables.
B)dealing with panel data.
C)the error term is random.
D)the intercept is not constant.
Question
Fixed-effects models and first-differenced models

A)assume that the time-invariant component of the error term is not correlated with the independent variables.
B)both add dummy variables to control for individual observations.
C)control for unobserved heterogeneity.
D)do not completely remove the time-invariant component of the error term.
Question
Random-effects models are

A)almost never the appropriate model in economics because the unobserved heterogeneity is typically correlated with the independent variables.
B)typically more appropriate than fixed effects models in economics.
C)preferred when the error term is random.
D)difficult to interpret because the coefficient estimates are not true marginal effects.
Question
Fixed-effects models and first-differenced models

A)assume that the time-invariant component of the error term is not correlated with the independent variables.
B)both add dummy variables to control for individual observations.
C)provide identical results if there are only two years of data.
D)do not completely remove the time-invariant component of the error term.
Question
Random-effects models

A)assume that the time invariant component of the error term is not correlated with the independent variables.
B)first difference the data.
C)are impossible to estimate in STATA.
D)can only be estimated if the panel data only have two time periods.
Question
The biggest difference between fixed-effects and random-effects models is that

A)fixed effects models assume that the unobserved heteroskedasticity is uncorrelated with the independent variables.
B)random effects models do not completely remove the time-invariant component of the error term.
C)fixed effects models completely remove the time-variant component of the error term.
D)random effects models are random while fixed-effects models are fixed.
Question
Panel data differs from cross-section data in that panel data is observed

A)for a number of different individuals in a given time-period.
B)for a given individual in a number of different time-periods.
C)for a given individual in a given time-period.
D)for a number of different individuals in a number of different time-periods.
Question
What is a random-effects model? How do you estimate such a model? When is it a preferred estimator? Why? Explain.
Question
Suppose that in an effort to explain variation in wages,you collect a panel data set with 12,300 total observations over 3 different years with the independent variables as experience,education,married (dummy variable is 1 if married and 0 if not married)and male (dummy variable is 1 if male and 0 if female).
a)How do you estimate a fixed-effects model for these data? Explain in as much detail as possible.
b)What are the advantages of estimating a fixed-effects model?
c)What are the drawbacks of estimating a fixed-effects model for this scenario?
Question
What is a first-differenced model? How is it preferable to a pooled cross-section model? Explain.
Question
Using the National Longitudinal Survey of young women who were 14-26 years in 1968 with independent variables age (age in current year),grade (current grade completed),south (1 if south),ttl_exp (total work experience),tenure (job tenure,in years),and the dependent variable ln_wage (natural log of wage/GNP deflator).You obtain the following pooled cross section results in STATA. Using the National Longitudinal Survey of young women who were 14-26 years in 1968 with independent variables age (age in current year),grade (current grade completed),south (1 if south),ttl_exp (total work experience),tenure (job tenure,in years),and the dependent variable ln_wage (natural log of wage/GNP deflator).You obtain the following pooled cross section results in STATA.   a)Comment on the coefficient estimates and the statistical significance of the estimates.What type of model is this? What are the drawbacks of estimating this type of model? You then estimate a fixed effects model in STATA and obtain the following results   b)Explain how a fixed effects model is estimated and in what circumstances fixed effects models are the most appropriate option.Be specific. c)How do these results differ from the results in part a? d)Why was grade dropped? Be specific. Finally,you estimate a fixed effects model in STATA and obtain the following results   e)Explain how a random effects model is estimated and in what circumstances random effects models are the most appropriate option.Be specific. f)Why is grade not dropped from this specification but it was dropped for the fixed effects model? g)Which of the three models do you prefer? Why?<div style=padding-top: 35px>
a)Comment on the coefficient estimates and the statistical significance of the estimates.What type of model is this? What are the drawbacks of estimating this type of model?
You then estimate a fixed effects model in STATA and obtain the following results Using the National Longitudinal Survey of young women who were 14-26 years in 1968 with independent variables age (age in current year),grade (current grade completed),south (1 if south),ttl_exp (total work experience),tenure (job tenure,in years),and the dependent variable ln_wage (natural log of wage/GNP deflator).You obtain the following pooled cross section results in STATA.   a)Comment on the coefficient estimates and the statistical significance of the estimates.What type of model is this? What are the drawbacks of estimating this type of model? You then estimate a fixed effects model in STATA and obtain the following results   b)Explain how a fixed effects model is estimated and in what circumstances fixed effects models are the most appropriate option.Be specific. c)How do these results differ from the results in part a? d)Why was grade dropped? Be specific. Finally,you estimate a fixed effects model in STATA and obtain the following results   e)Explain how a random effects model is estimated and in what circumstances random effects models are the most appropriate option.Be specific. f)Why is grade not dropped from this specification but it was dropped for the fixed effects model? g)Which of the three models do you prefer? Why?<div style=padding-top: 35px>
b)Explain how a fixed effects model is estimated and in what circumstances fixed effects models are the most appropriate option.Be specific.
c)How do these results differ from the results in part a?
d)Why was grade dropped? Be specific.
Finally,you estimate a fixed effects model in STATA and obtain the following results Using the National Longitudinal Survey of young women who were 14-26 years in 1968 with independent variables age (age in current year),grade (current grade completed),south (1 if south),ttl_exp (total work experience),tenure (job tenure,in years),and the dependent variable ln_wage (natural log of wage/GNP deflator).You obtain the following pooled cross section results in STATA.   a)Comment on the coefficient estimates and the statistical significance of the estimates.What type of model is this? What are the drawbacks of estimating this type of model? You then estimate a fixed effects model in STATA and obtain the following results   b)Explain how a fixed effects model is estimated and in what circumstances fixed effects models are the most appropriate option.Be specific. c)How do these results differ from the results in part a? d)Why was grade dropped? Be specific. Finally,you estimate a fixed effects model in STATA and obtain the following results   e)Explain how a random effects model is estimated and in what circumstances random effects models are the most appropriate option.Be specific. f)Why is grade not dropped from this specification but it was dropped for the fixed effects model? g)Which of the three models do you prefer? Why?<div style=padding-top: 35px>
e)Explain how a random effects model is estimated and in what circumstances random effects models are the most appropriate option.Be specific.
f)Why is grade not dropped from this specification but it was dropped for the fixed effects model?
g)Which of the three models do you prefer? Why?
Question
Suppose that in an effort to explain variation in wages,you collect a panel data set with 12,300 total observations over 3 different years with the independent variables as experience,education,married (dummy variable is 1 if married and 0 if not married)and male (dummy variable is 1 if male and 0 if female).
a)How do you estimate a first-differenced model for these data? Explain in as much detail as possible.
b)What are the advantages of estimating a first-differenced model?
c)What are the drawbacks of estimating a first differenced model for this scenario?
Question
What is a fixed-effects model? How do you estimate such a model? When is it a preferred estimator? Why? Explain.
Question
Suppose that in an effort to explain variation in wages,you collect a panel data set with 12,300 total observations over 3 different years with the independent variables as experience,education,married (dummy variable is 1 if married and 0 if not married)and male (dummy variable is 1 if male and 0 if female).
a)How do you estimate a random-effects model for these data? Explain in as much detail as possible.
b)What are the advantages of estimating a random-effects model?
c)What are the drawbacks of estimating a random-effects model for this scenario?
Question
What is a pooled cross-section model? For what type of data would you estimate such a model? Are there any potential empirical issues associated with this approach? Explain.
Question
Suppose that in an effort to explain variation in wages,you collect a panel data set with 12,300 total observations over 3 different years and you estimate the following pooled cross-section model Suppose that in an effort to explain variation in wages,you collect a panel data set with 12,300 total observations over 3 different years and you estimate the following pooled cross-section model   a)How many individuals are included in your sample in each of the three years? How do you know? Explain. b)How do you interpret the estimated sample regression function? Explain. c)What is a potential shortcoming associated with this model? Explain. d)What would be the simplest way to address the issue raised in (b)? Why would this address the issue? Explain.<div style=padding-top: 35px>
a)How many individuals are included in your sample in each of the three years? How do you know? Explain.
b)How do you interpret the estimated sample regression function? Explain.
c)What is a potential shortcoming associated with this model? Explain.
d)What would be the simplest way to address the issue raised in (b)? Why would this address the issue? Explain.
Question
What is panel data? How does it differ from cross-section data? Time-series data? Explain.
Question
What does the error term look like for panel data? Explain each term in detail.
Unlock Deck
Sign up to unlock the cards in this deck!
Unlock Deck
Unlock Deck
1/31
auto play flashcards
Play
simple tutorial
Full screen (f)
exit full mode
Deck 13: Panel Data
1
Panel data differs from time-series data in that panel data is observed

A)for a number of different individuals in a number of different time-periods.
B)for a given individual in a number of different time-periods.
C)for a number of different individuals in a given time-period.
D)for a given individual in a given time-period.
A
2
First-differenced models are preferable to pooled cross-section models because they

A)control for potential autocorrelation.
B)control for potential heteroskedasticity.
C)control for the random effects in the data.
D)remove the time constant component in the error term.
D
3
The fact that panel data varies across both individuals and time-periods should allow us to ___________ by accounting for the time constant component in the error term.

A)generate unbiased parameter estimates
B)correctly estimate the true parameter values
C)control for autocorrelation
D)improve the efficiency of the parameter estimates
D
4
If there is a pooled cross-section model with and intercept and five explanatory variables and there are 100 observations each year for three years

A)the sample size is 100.
B)there are 294 degrees of freedom.
C)the sample size is 294.
D)there are 300 degrees of freedom.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
5
Fixed-effects models are more appropriate than random-effects models when

A)the error terms are autocorrelated.
B)the independent variables are constant over time.
C)the time invariant component of the error term is correlated with any of the independent variables.
D)the error term is not constant.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
6
One can first-difference panel data in a two-period model by subtracting

A)the previous-period observation from the current-period observation for the dependent variable.
B)the previous-period observation from the current-period observation for the dependent variable and each independent variable.
C)the current-period observation from the previous-period observation for the dependent variable and each independent variable.
D)the current-period observation from the previous-period observation for the independent variable.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
7
Fixed-effects models

A)remove the time-variant component of the error term.
B)remove the time-invariant component of the error term.
C)work by first-differencing the data.
D)remove the heteroskedasticity in the data.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
8
Pooled cross-section models

A)control for individual fixed-effects.
B)combine observations over many different years.
C)control for unobserved heterogeneity.
D)control for random-effects.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
9
Treating each data point in panel data as an individual observation and not accounting for the fact that individuals are observed over many time periods is referred to as estimating a ____ model.

A)static time-series
B)heteroskedastic consistent
C)pooled cross-section
D)fixed-effects
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
10
Fixed-effects models are preferable to pooled cross-section models because they

A)first-difference the data.
B)control for potential heteroskedasticity.
C)control for autocorrelation.
D)remove the time-invariant component of the error term.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
11
Fixed-effects models and first-differenced models

A)assume that the time-invariant component of the error term is not correlated with the independent variables.
B)both add dummy variables to control for individual observations.
C)do not provide identical results if there are more than two years of data.
D)do not completely remove the time-invariant component of the error term.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
12
Random-effects models improve on pooled cross-section models because they

A)do not take advantage of the panel data nature of the data.
B)have more degrees of freedom available.
C)improve the efficiency of the estimated coefficients.
D)correct for heteroskedasticity.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
13
Pooled cross-section models are not the preferred estimators for panel data models because they

A)are heteroskedastic.
B)are quasi-differenced.
C)do nothing to account for the time constant component of the error term.
D)create a dummy variable for each individual in the data set.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
14
Random-effects models are more appropriate than fixed-effects models when

A)the time invariant component of the error term is not correlated with one or more the independent variables.
B)dealing with panel data.
C)the error term is random.
D)the intercept is not constant.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
15
Fixed-effects models and first-differenced models

A)assume that the time-invariant component of the error term is not correlated with the independent variables.
B)both add dummy variables to control for individual observations.
C)control for unobserved heterogeneity.
D)do not completely remove the time-invariant component of the error term.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
16
Random-effects models are

A)almost never the appropriate model in economics because the unobserved heterogeneity is typically correlated with the independent variables.
B)typically more appropriate than fixed effects models in economics.
C)preferred when the error term is random.
D)difficult to interpret because the coefficient estimates are not true marginal effects.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
17
Fixed-effects models and first-differenced models

A)assume that the time-invariant component of the error term is not correlated with the independent variables.
B)both add dummy variables to control for individual observations.
C)provide identical results if there are only two years of data.
D)do not completely remove the time-invariant component of the error term.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
18
Random-effects models

A)assume that the time invariant component of the error term is not correlated with the independent variables.
B)first difference the data.
C)are impossible to estimate in STATA.
D)can only be estimated if the panel data only have two time periods.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
19
The biggest difference between fixed-effects and random-effects models is that

A)fixed effects models assume that the unobserved heteroskedasticity is uncorrelated with the independent variables.
B)random effects models do not completely remove the time-invariant component of the error term.
C)fixed effects models completely remove the time-variant component of the error term.
D)random effects models are random while fixed-effects models are fixed.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
20
Panel data differs from cross-section data in that panel data is observed

A)for a number of different individuals in a given time-period.
B)for a given individual in a number of different time-periods.
C)for a given individual in a given time-period.
D)for a number of different individuals in a number of different time-periods.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
21
What is a random-effects model? How do you estimate such a model? When is it a preferred estimator? Why? Explain.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
22
Suppose that in an effort to explain variation in wages,you collect a panel data set with 12,300 total observations over 3 different years with the independent variables as experience,education,married (dummy variable is 1 if married and 0 if not married)and male (dummy variable is 1 if male and 0 if female).
a)How do you estimate a fixed-effects model for these data? Explain in as much detail as possible.
b)What are the advantages of estimating a fixed-effects model?
c)What are the drawbacks of estimating a fixed-effects model for this scenario?
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
23
What is a first-differenced model? How is it preferable to a pooled cross-section model? Explain.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
24
Using the National Longitudinal Survey of young women who were 14-26 years in 1968 with independent variables age (age in current year),grade (current grade completed),south (1 if south),ttl_exp (total work experience),tenure (job tenure,in years),and the dependent variable ln_wage (natural log of wage/GNP deflator).You obtain the following pooled cross section results in STATA. Using the National Longitudinal Survey of young women who were 14-26 years in 1968 with independent variables age (age in current year),grade (current grade completed),south (1 if south),ttl_exp (total work experience),tenure (job tenure,in years),and the dependent variable ln_wage (natural log of wage/GNP deflator).You obtain the following pooled cross section results in STATA.   a)Comment on the coefficient estimates and the statistical significance of the estimates.What type of model is this? What are the drawbacks of estimating this type of model? You then estimate a fixed effects model in STATA and obtain the following results   b)Explain how a fixed effects model is estimated and in what circumstances fixed effects models are the most appropriate option.Be specific. c)How do these results differ from the results in part a? d)Why was grade dropped? Be specific. Finally,you estimate a fixed effects model in STATA and obtain the following results   e)Explain how a random effects model is estimated and in what circumstances random effects models are the most appropriate option.Be specific. f)Why is grade not dropped from this specification but it was dropped for the fixed effects model? g)Which of the three models do you prefer? Why?
a)Comment on the coefficient estimates and the statistical significance of the estimates.What type of model is this? What are the drawbacks of estimating this type of model?
You then estimate a fixed effects model in STATA and obtain the following results Using the National Longitudinal Survey of young women who were 14-26 years in 1968 with independent variables age (age in current year),grade (current grade completed),south (1 if south),ttl_exp (total work experience),tenure (job tenure,in years),and the dependent variable ln_wage (natural log of wage/GNP deflator).You obtain the following pooled cross section results in STATA.   a)Comment on the coefficient estimates and the statistical significance of the estimates.What type of model is this? What are the drawbacks of estimating this type of model? You then estimate a fixed effects model in STATA and obtain the following results   b)Explain how a fixed effects model is estimated and in what circumstances fixed effects models are the most appropriate option.Be specific. c)How do these results differ from the results in part a? d)Why was grade dropped? Be specific. Finally,you estimate a fixed effects model in STATA and obtain the following results   e)Explain how a random effects model is estimated and in what circumstances random effects models are the most appropriate option.Be specific. f)Why is grade not dropped from this specification but it was dropped for the fixed effects model? g)Which of the three models do you prefer? Why?
b)Explain how a fixed effects model is estimated and in what circumstances fixed effects models are the most appropriate option.Be specific.
c)How do these results differ from the results in part a?
d)Why was grade dropped? Be specific.
Finally,you estimate a fixed effects model in STATA and obtain the following results Using the National Longitudinal Survey of young women who were 14-26 years in 1968 with independent variables age (age in current year),grade (current grade completed),south (1 if south),ttl_exp (total work experience),tenure (job tenure,in years),and the dependent variable ln_wage (natural log of wage/GNP deflator).You obtain the following pooled cross section results in STATA.   a)Comment on the coefficient estimates and the statistical significance of the estimates.What type of model is this? What are the drawbacks of estimating this type of model? You then estimate a fixed effects model in STATA and obtain the following results   b)Explain how a fixed effects model is estimated and in what circumstances fixed effects models are the most appropriate option.Be specific. c)How do these results differ from the results in part a? d)Why was grade dropped? Be specific. Finally,you estimate a fixed effects model in STATA and obtain the following results   e)Explain how a random effects model is estimated and in what circumstances random effects models are the most appropriate option.Be specific. f)Why is grade not dropped from this specification but it was dropped for the fixed effects model? g)Which of the three models do you prefer? Why?
e)Explain how a random effects model is estimated and in what circumstances random effects models are the most appropriate option.Be specific.
f)Why is grade not dropped from this specification but it was dropped for the fixed effects model?
g)Which of the three models do you prefer? Why?
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
25
Suppose that in an effort to explain variation in wages,you collect a panel data set with 12,300 total observations over 3 different years with the independent variables as experience,education,married (dummy variable is 1 if married and 0 if not married)and male (dummy variable is 1 if male and 0 if female).
a)How do you estimate a first-differenced model for these data? Explain in as much detail as possible.
b)What are the advantages of estimating a first-differenced model?
c)What are the drawbacks of estimating a first differenced model for this scenario?
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
26
What is a fixed-effects model? How do you estimate such a model? When is it a preferred estimator? Why? Explain.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
27
Suppose that in an effort to explain variation in wages,you collect a panel data set with 12,300 total observations over 3 different years with the independent variables as experience,education,married (dummy variable is 1 if married and 0 if not married)and male (dummy variable is 1 if male and 0 if female).
a)How do you estimate a random-effects model for these data? Explain in as much detail as possible.
b)What are the advantages of estimating a random-effects model?
c)What are the drawbacks of estimating a random-effects model for this scenario?
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
28
What is a pooled cross-section model? For what type of data would you estimate such a model? Are there any potential empirical issues associated with this approach? Explain.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
29
Suppose that in an effort to explain variation in wages,you collect a panel data set with 12,300 total observations over 3 different years and you estimate the following pooled cross-section model Suppose that in an effort to explain variation in wages,you collect a panel data set with 12,300 total observations over 3 different years and you estimate the following pooled cross-section model   a)How many individuals are included in your sample in each of the three years? How do you know? Explain. b)How do you interpret the estimated sample regression function? Explain. c)What is a potential shortcoming associated with this model? Explain. d)What would be the simplest way to address the issue raised in (b)? Why would this address the issue? Explain.
a)How many individuals are included in your sample in each of the three years? How do you know? Explain.
b)How do you interpret the estimated sample regression function? Explain.
c)What is a potential shortcoming associated with this model? Explain.
d)What would be the simplest way to address the issue raised in (b)? Why would this address the issue? Explain.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
30
What is panel data? How does it differ from cross-section data? Time-series data? Explain.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
31
What does the error term look like for panel data? Explain each term in detail.
Unlock Deck
Unlock for access to all 31 flashcards in this deck.
Unlock Deck
k this deck
locked card icon
Unlock Deck
Unlock for access to all 31 flashcards in this deck.