Consider the system of equations:  pi = β0 + β0qi + β2ti + β3zi + ui qi = α0 + α1pi + α2ki + ԑi where p and q are endogenous variables. t, z and k are exogenous variables. u and ԑ are disturbance terms. And i is cross section.  Explain how you would go about estimating the stated system of equations.

Consider the model Y = ß0 + B₁X1 + ß₂X2 + B3X³ + B4X4 + €. If it is suggested to you that the two variables Z₁ = X₁ + X3 and Z2 = X₂ + X4 might be adequate to represent the data, what hypothesis, in the form C3 = 0, would you need to test? (Give the form of C.)

Determine if the given ordered pair is a solution to the given system of equations.

The Simple Linear Regression model is   Y = b0 + b1*X1 + u   and the Multiple Linear Regression model with k variables is:   Y = b0 + b1*X1 + b2*X2 + ... + bk*Xk + u   Y is the dependent variable, the X1, X2, ..., Xk are the explanatory variables, b0 is the intercept, b1, b2, ..., bk are the slope coefficients, and u is the error term,   Yhat represents the OLS fitted values, uhat represent the OLS residuals, b0_hat represents the OLS estimated intercept, and b1_hat, b2_hat,..., bk_hat, represent the OLS estimated slope coefficients. QUESTION 16 In a t-test, suppose a researcher sets the significance level at 0.5%. What does this mean?    The probability that the null hypothesis is true is 0.5% The researcher would be rejecting the null hypothesis, only if the p-value is less than 0.5% The researcher would be rejecting the null hypothesis, if the t-statistic is higher than 0.5 It does not mean anything, because the significance level can only be set at 5%     QUESTION 17 In an MLR…