Consider a simple linear regression model, wage =
+
data-mathml="%3Cmath%20style%3D%22font%2Dfamily%3A%27Times%20New%20Roman%2C%20serif%27%22%20xmlns%3D%22http%3A%2F%2Fwww%2Ew3%2Eorg%2F1998%2FMath%2FMathML%22%3E%3Cmstyle%20mathsize%3D%2215px%22%3E%3Cmsub%3E%3Cmi%3E%26%23946%3B%3C%2Fmi%3E%3Cmn%3E1%3C%2Fmn%3E%3C%2Fmsub%3E%3C%2Fmstyle%3E%3C%2Fmath%3E" src="@@PLUGINFILE@@/ppg__cognero__Ch_02_The_Simple_Regression_Model__media__2178f37b-7097-4048-b5c1-72c13ed8ae28.PNG" style="vertical-align:middle;" />male + u, where male is a binary variable (1 if a person is male, and 0 otherwise). Now suppose that we know being a male means there is a lower probability of attaining higher education, another factor that is also expected to affect wage. Which of the key assumptions made to establish unbiasedness of OLS estimates do not hold?
A. Linear in parameters
B. Random sampling
C. Sample variation in the explanatory variable
D. Zero conditional mean
Answer: D
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