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The following two equations were estimated using the data in MEAPSINGLE. The key explanatory variable is lexppp, the log of expenditures per student at the school level. math4 = 24.49 + 9.01 lexpp – 422 free – .752 Imedinc – .274 pctsgle (.071) (59.24) (4.04) n = 229, R² = .472, R² (5.358) (.161) 462. 149.38 + 1.93 lexppp – .060 free – 10.78 Imedinc – .397 pctsgle + .667 read4 (3.76) math4 (41.70) (2.82) (.054) (.111) (.042) n = 229, R = .749, R = .743. (i) If you are a policy maker trying to estimate the causal effect of per-student spending on math test performance, explain why the first equation is more relevant than the second. What is the estimated effect of a 10% increase in expenditures per student? (ii) Does adding read4 to the regression have strange effects on coefficients and statistical signifi- cance other than Brexppp? (iii) How would you explain to someone with only basic knowledge of regression why, in this case, you prefer the equation with the smaller adjusted R-squared?

The following two equations were estimated using the data in MEAPSINGLE. The key explanatory variable is lexppp, the log of expenditures per student at the school level. math4 = 24.49 + 9.01 lexpp – 422 free – .752 Imedinc – .274 pctsgle (.071) (59.24) (4.04) n = 229, R² = .472, R² (5.358) (.161) 462. 149.38 + 1.93 lexppp – .060 free – 10.78 Imedinc – .397 pctsgle + .667 read4 (3.76) math4 (41.70) (2.82) (.054) (.111) (.042) n = 229, R = .749, R = .743. (i) If you are a policy maker trying to estimate the causal effect of per-student spending on math test performance, explain why the first equation is more relevant than the second. What is the estimated effect of a 10% increase in expenditures per student? (ii) Does adding read4 to the regression have strange effects on coefficients and statistical signifi- cance other than Brexppp? (iii) How would you explain to someone with only basic knowledge of regression why, in this case, you prefer the equation with the smaller adjusted R-squared?

ENGR.ECONOMIC ANALYSIS
ENGR.ECONOMIC ANALYSIS
14th Edition
ISBN:9780190931919
Author:NEWNAN
Publisher:NEWNAN
Chapter1: Making Economics Decisions
Section: Chapter Questions
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The following two equations were estimated using the data in MEAPSINGLE. The key explanatory variable is lexppp, the log of expenditures per student at the school level. math4 = 24.49 + 9.01 lexpp – 422 free – .752 Imedinc – .274 pctsgle (.071) (59.24) (4.04) n = 229, R² = .472, R² (5.358) (.161) 462. 149.38 + 1.93 lexppp – .060 free – 10.78 Imedinc – .397 pctsgle + .667 read4 (3.76) math4 (41.70) (2.82) (.054) (.111) (.042) n = 229, R = .749, R = .743. (i) If you are a policy maker trying to estimate the causal effect of per-student spending on math test performance, explain why the first equation is more relevant than the second. What is the estimated effect of a 10% increase in expenditures per student? (ii) Does adding read4 to the regression have strange effects on coefficients and statistical signifi- cance other than Brexppp? (iii) How would you explain to someone with only basic knowledge of regression why, in this case, you prefer the equation with the smaller adjusted R-squared?
Transcribed Image Text:The following two equations were estimated using the data in MEAPSINGLE. The key explanatory variable is lexppp, the log of expenditures per student at the school level. math4 = 24.49 + 9.01 lexpp – 422 free – .752 Imedinc – .274 pctsgle (.071) (59.24) (4.04) n = 229, R² = .472, R² (5.358) (.161) 462. 149.38 + 1.93 lexppp – .060 free – 10.78 Imedinc – .397 pctsgle + .667 read4 (3.76) math4 (41.70) (2.82) (.054) (.111) (.042) n = 229, R = .749, R = .743. (i) If you are a policy maker trying to estimate the causal effect of per-student spending on math test performance, explain why the first equation is more relevant than the second. What is the estimated effect of a 10% increase in expenditures per student? (ii) Does adding read4 to the regression have strange effects on coefficients and statistical signifi- cance other than Brexppp? (iii) How would you explain to someone with only basic knowledge of regression why, in this case, you prefer the equation with the smaller adjusted R-squared?
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