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book Introduction to Econometrics 3rd Edition by James Stock, Mark Watson cover

Introduction to Econometrics 3rd Edition by James Stock, Mark Watson

Edition 3ISBN: 978-9352863501
book Introduction to Econometrics 3rd Edition by James Stock, Mark Watson cover

Introduction to Econometrics 3rd Edition by James Stock, Mark Watson

Edition 3ISBN: 978-9352863501
Exercise 6
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). Use the definition of the sample variance and covariance to show that
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). Use this result to fill in the steps of the derivation in Appendix of Equation (12.4).
Appendix
Derivation of the Formula for the TSLS Estimator in Equation (12.4)
The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). , and the second stage is to regress Y i on
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). is the formula for the OLS estimator in Key Concept 4.2, with
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). replacing X i. That is,
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). , where
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). , is the sample variance of
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). and
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). is the sample covariance between Y i and
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4).
Because X i is the predicted value of X i from the first-stage regression,
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). , the definitions of sample variances and covariances imply that
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). (Exercise 12.4). Thus, the TSLS estimator can be written as
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). . Finally,
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). is the OLS slope coefficient from the first stage of TSLS, so
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). Substitution of this formula for
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). into the formula
Consider TSLS estimation with a single included endogenous variable and a single instrument. Then the predicted value from the first-stage regression is     Use the definition of the sample variance and covariance to show that     Use this result to fill in the steps of the derivation in Appendix of Equation (12.4). Appendix Derivation of the Formula for the TSLS Estimator in Equation (12.4)  The first stage of TSLS is to regress X i on the instrument Z i by OLS and then compute the OLS predicted value     , and the second stage is to regress Y i on     by OLS. Accordingly, the formula for the TSLS estimator, expressed in terms of the predicted value     is the formula for the OLS estimator in Key Concept 4.2, with     replacing X i. That is,     , where     , is the sample variance of     and     is the sample covariance between Y i and      Because X i is the predicted value of X i from the first-stage regression,     , the definitions of sample variances and covariances imply that    (Exercise 12.4). Thus, the TSLS estimator can be written as     . Finally,     is the OLS slope coefficient from the first stage of TSLS, so     Substitution of this formula for     into the formula     yields the formula for the TSLS estimator in Equation (12.4). yields the formula for the TSLS estimator in Equation (12.4).
Explanation
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For a TSLS regression, we have:
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Introduction to Econometrics 3rd Edition by James Stock, Mark Watson
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