We would like to analyze the relationship between wealth (eg. The number of cattle or other assets) and child labour, us
Posted: Sat Feb 26, 2022 11:25 am
We would like to analyze the relationship between wealth (eg.
The number of cattle or other assets) and child labour, using
household data collected in several villages in rural Africa.
Suppose we have data on Y and X where Y; is the number of hours
worked by child i in village v and X;y is family wealth.
i. Explain how this is related to the concept of Panel Data.
ii. Explain how you could estimate the relationship between
wealth and child labour using pooled OLS, Random Effect (RE) and
Fixed Effect (FE) estimators. Write down the estimation equations
and the conditions needed to guarantee consistency. Compare the FE
and the OLS estimators: Is either of these two estimators based on
weaker assumptions than the other?
iii. Describe one example how conventional exogeneity (often
called "contemporaneous" exogeneity) could be violated.
iv. Are there any variables that you would like to include as
control variables? Why? Why would you not want to include the
variable "Number of hours child attended school"?
V. An alternative estimator would be OLS with village-dummy
variables. Can you explain under which conditions on the sampling
process (i.e., data collection process the estimates of these
village-dummies would be consistent?
VI. Now suppose that you were able to re-interview the same
households two years later again, such that you have data on Yit
and Xit where the subscript t refers to time. How could this
additional data help you to deal with any remaining concerns about
endogeneity?
The number of cattle or other assets) and child labour, using
household data collected in several villages in rural Africa.
Suppose we have data on Y and X where Y; is the number of hours
worked by child i in village v and X;y is family wealth.
i. Explain how this is related to the concept of Panel Data.
ii. Explain how you could estimate the relationship between
wealth and child labour using pooled OLS, Random Effect (RE) and
Fixed Effect (FE) estimators. Write down the estimation equations
and the conditions needed to guarantee consistency. Compare the FE
and the OLS estimators: Is either of these two estimators based on
weaker assumptions than the other?
iii. Describe one example how conventional exogeneity (often
called "contemporaneous" exogeneity) could be violated.
iv. Are there any variables that you would like to include as
control variables? Why? Why would you not want to include the
variable "Number of hours child attended school"?
V. An alternative estimator would be OLS with village-dummy
variables. Can you explain under which conditions on the sampling
process (i.e., data collection process the estimates of these
village-dummies would be consistent?
VI. Now suppose that you were able to re-interview the same
households two years later again, such that you have data on Yit
and Xit where the subscript t refers to time. How could this
additional data help you to deal with any remaining concerns about
endogeneity?