Consider the following structural model:31 Bo + B1y2 + B₂²1 +21Suppose now that there are two exogenous variables excluded from the model: 22 and 23.The assumptions that 2₂ and 23 do not appear in the model and are uncorrelated with the error ₁ are known asThe linear combination that is most highly correlated with y2 is given by the reduced form equation for y2:Y2 = πO +1Z1 +T2Z2 + N3Z3+V2E(v2) = 0, Cov(21, v2) = 0, Cov(22, 2) = 0, and Cov(23, 12) = 0.overidentifying restrictionsexclusion restrictions2SLSrank conditions The linear combination that is most highly correlated with 32 is given by the reduced form equation for y2:Y2 = πO +1Z1 +T2Z2 + N3Z3+V2E(v2) = 0, Cov(21, v2) = 0, Cov(22, 2) = 0, and Cov(23, v2) = 0.Which of the following is the best IV for y2?Oy₂ = πO + #1²1 + 7222 + 7323Oy₂ = πO + 121 +222 +2Oy₂ = πO+π121 +222 +7323 +22Oy₂ = πO + 1²1 + 7222overidentifying restrictionsO T2 #0 and 3 #0O T1 #0 and ₂ #0 or π3 #0O π₁ #0 or π₂ #0 and T3 #0O π₂0 or π3 #0exclusion restrictions2SLSrank conditionsWhat is the least restrictive assumption we need to impose on the parameters in order for the instrument y to not be perfectly correlated with z₁?

Answered: Image /qna-images/answer/2c13305e-8f09-4fcc-9735-d0cdb1d0945d.jpg

Answered: Consider the following structural…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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Problem 1P

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19.2)
Which of the following graphs shows interaction between X₁ and x2 in their effects on y? a) y x2=1 x2=0 x1 b) y x2=0 x2=1 x1 O b) O neither a) nor b) O a) and b) a) cannot be determined without also having the regression output
Let Y=Z3+ € denote the standard form of the multivariate regression model where Y is a matrix of n observations on m dependent variables, Z is the nx (r + 1) design matrix, 3 is the matrix of regression coefficients and denotes the error matrix. Let Σ denote the m × m covariance matrix of any row of e and assume the rows are independent. The least square estimate for 3 is 3 = (Z'Z)-¹Z'Y. The projection matrix is H = Z(Z'Z)-¹Z'. Let the ith column of 3 be denoted by 3, and the i, jth element of Σ by oij. Define the sample covariance matrix of the residuals by Prove (e) E(Σ) = Σ (f) cov(₁,3)=0 1 n-p-1
Each of 25 teenage girls with one brother was asked to provide her own height (y), in inches, and the height (x), in inches, of her brother. The scatterplot below displays the results. Only 22 of the 25 pairs are distinguishable because some of the (x,y) pairs were the same. The equation of the least-squares regression line is ŷ = 35.1 + 0.427x.*Girls are on the y-axis and brothers are on the x-axis* a.) Draw the least-squares regression line on the scatterplot above. b.) One brother’s height was x = 67 inches and his sister’s height was y = 61 inches. Circle the point on the scatterplot above that represents this pair and draw the segment on the scatterplot that corresponds to the residual for it. Give a numerical for the residual. c.) Suppose the point x = 84 , y = 71 is added to the data set. Would the slope of the least squares regression line increase, decrease, or remain about the same?Explain. Would the correlation increase, decrease, or remain about the same? Explain.
4.1#28 Determine whether the association between the tuwo Variables is positive or negative. The number of times a pencil is sharpened and its length.
I would like to know what is so complex about this problem? My question keep getting rejected.
Express the model Y₁ = Bo + Bixi + B₁x² + €i i=1,2,..., 5 where the &; have mean zero, variance o² and are uncorrelated, as a general linear model in matrix form by specifying Y, X, 3 and e.
Consider a simple linear regression model, Y₁ = Bo + B₁X₁ + ₁ for i=1,2,...,n with the usual random error term (&) assumptions. Suppose that hypotheses Ho: P₁ = 0 against H₁:₁ <0 were tested and Ho: B₁ = 0 was rejected. Assume ₁e₁² = 0. ei i) Briefly explain what the conclusion of the test means for the values of Y given the values of X. -1 ii) Draw an example of a scatter plot with the fitted regression line for the problem mentioned above. iii) Calculate and interpret the correlation coefficient for the problem at hand.
Only for b and c show the calculation please
5.3.8. Explain why the Frobenius matrix norm on Cnxn must satisfy the par- allelogram identity.
Consider the following panel model to examine the effect of retirement on consumption expenditure, consit, of individual i over years t=1,…,3: (B1) log⁡(consit) = β0 + β1retiredit + β2ageit + β3marriedit + β4healthit + δ1Yr2t + δ2Yr3t + ai + uit Where: retiredit is a dummy variable equal to 1 if individual i is retired on year t and 0 otherwise ageit is the individual's age in years marriedit is an indicator variable for whether the individual is married (1) or not (0) in year t healthit is an indicator variable equal to 1 if the individual is in 'good health' and 0 otherwise Yr2 is a dummy variable equal to 1 in year t=2 and 0 otherwise Yr3 is a dummy variable equal to 1 in year t=3 and 0 otherwise Using the information above, answer the following 3 questions. [i] Give two (2) examples of the kind of variables captured by the term ai in Model (B1). [ii] What is the crucial assumption we must make so that the random effects (RE) estimator is consistent? Under this assumption, why is…
. Let Y Z3+ e denote the standard form of the multivariate regression model where Y is a matrix of n observations on m dependent variables, Z is the nx (r + 1) design matrix, 3 is the matrix of regression coefficients and denotes the error matrix. Let Σ denote the m x m covariance matrix of any row of € and assume the rows are independent. The least square estimate for 3 is 3 (Z'Z)-¹Z'Y. The projection matrix is H = Z(Z'Z)-¹Z'. Let the ith column of 3 be denoted by 3, and the i, jth element of Σ by dij. Define the sample covariance matrix of the residuals by = Prove (a) E(3) = 3 (b) cov (3,3)= Σ (3₁3) = Oik (Z'Z)-¹ 1 n-p-1

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