Suppose that our true regression model is quadratic, but we end up estimating a linear model instead. In other words, we should be estimating y=0+1x+2x2+u, but we instead estimate y=0+1x+ v. Which of the following will definitively result from estimating an incorrect functional form? Check all that apply. Hypothesis tests conducted using the linear model will be invalid We will have larger residuals for larger values of x It is impossible to estimate a quadratic model since OLS only applies to linear regression There will be a clear quadratic pattern between the residuals and x Our estimates will be biased since 2x2 will show up in the error tem of the linear model Our estimates will still be unbiased, but hypothesis tests will be invalid.

1. Suppose that our true regression model is quadratic, but we end up estimating a linear model
instead. In other words, we should be estimating y=0+1x+2x2+u, but we instead estimate y=0+1x+
v. Which of the following will definitively result from estimating an incorrect functional form? Check
all that apply. Hypothesis tests conducted using the linear model will be invalid We will have larger
residuals for larger values of x It is impossible to estimate a quadratic model since OLS only
applies to linear regression There will be a clear quadratic pattern between the residuals and x
Our estimates will be biased since 2x2 will show up in the error tem of the linear model Our
estimates will still be unbiased, but hypothesis tests will be invalid