2 - Binghamton University
Doc File 83.50KByte
Spring 2007, Econ 466
Total: 100 points, Time: 2 hours
Answer all questions. Write clearly and legibly. Good Luck!!
1. Consider the following linear regression model often known as the Classical Linear Regression Model
[pic], t =1, …, n (1)
a) [3 points] What are the basic assumptions of the model?
b) [5 points] You believe that [pic], but your friend thinks that [pic]. Who is correct? Explain.
c) [3 points] In which case [pic] represents the elasticity of Y with respect to X?
d) [6 points] In which case this model represents the “linear probability model”? What are the disadvantage of the model?
e) [8 points] If E(ut) = 0 but V(ut) = [pic] is replaced by [pic] =[pic], t =1, …, n, what are the problems with the OLS estimator of [pic]? How would you estimate [pic] in this model taking the above heteroskedasticity problem into account? Show all the necessary steps.
f) [8 points] Consider the model in (1). If E(ut) = 0 but the assumption that [pic]’s are independent over observation is replaced by [pic] ................
In order to avoid copyright disputes, this page is only a partial summary.
To fulfill the demand for quickly locating and searching documents.
It is intelligent file search solution for home and business.
- how to do logarithms manually
- how to explain statistical significance
- how to explain your personality
- how to explain standard deviation results
- how to explain p value
- how to calculate logarithms manually
- how to explain correlation results
- how to explain central dogma
- how to explain cause and effect
- how to explain weighted grades
- how to add logarithms equations
- how to add logarithms with different bases