Lesson 11 Regressions Part II Ka-fu Wong C2007 ECON1003: Analysis of Economic Data Lesson 11-1
Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson11-1 Lesson 11: Regressions Part II
Does watching television rot your mind? Zavodny, Madeline(2006): Does watching television rot your mind? Estimates of the effect on test scores economias of education Review25(5):565-573 a Television is one of the most omnipresent features of Americans lives. The average american adult watches about 15 h of television per week, accounting for almost one -half of free time a The substantial amount of time that most individuals spend watching television makes it important to examine its effects on society including human capital accumulation and academic achievement Ka-fu Wong C2007 ECON1003: Analysis of Economic Data Lesson 11-2
Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson11-2 Does watching television rot your mind? ◼ Zavodny, Madeline (2006): “Does watching television rot your mind? Estimates of the effect on test scores,” Economics of Education Review, 25 (5): 565–573 ◼ Television is one of the most omnipresent features of Americans’ lives. The average American adult watches about 15 h of television per week, accounting for almost one-half of free time. ◼ The substantial amount of time that most individuals spend watching television makes it important to examine its effects on society, including human capital accumulation and academic achievement
Data regression model a This analysis uses three data sets to examine the relationship between television viewing and test scores: the national Longitudinal Survey of Youth 1979(NLSY the hsb survey and the NELS. Each survey includes test scores and a question about the number of hours of television watched by young adults Test Scorer a +hOurs of Tv +INdividual characteristics + Family Background in t dOther Uses of Timeit+t it Gil Test score of individual i at time t Ka-fu Wong C2007 ECON1003: Analysis of Economic Data Lesson 11-3
Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson11-3 Data & Regression model ◼ This analysis uses three data sets to examine the relationship between television viewing and test scores: the National Longitudinal Survey of Youth 1979 (NLSY), the HSB survey and the NELS. Each survey includes test scores and a question about the number of hours of television watched by young adults. Test score of individual i at time t
Summary of samples from data sets HSB NElS Number of individuals 2477 14.988 6255 Type of data Cross-section Panel Panel Time period 1980,1982 1988,1990,1992 Age of respondents 16-19 13-22 12-20 Sibling structure 239 sibling pairs 432 twin pairs None Test score AFQT Vocabulary, reading, math Reading, math TV variable Hours per week Hours per weekday Hours per weekday, weekend y Categorical or linear L Categorical (7) Categorical (6 or 7) Ka-fu Wong C2007 ECON1003: Analysis of Economic Data Lesson 11-4
Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson11-4 Summary of samples from data sets
Regression results <0<0.05<01 Test Scorei a+hOurs of TV +iNdividual Characteristics +2, Family Backgroundit dOther Uses of Timeit +tIt+ cir All Male F emale NLSY: AFOTscore (A)TⅤonl .007* 012 (.001) (.002) (.002) (B)A+individual 007 007 008* characteristics (.001) (.002 (.002 (C)B+family background . 003*3. .002 .005* (.001) (.002) (.001) (D)C+other uses of time -.003 -.002 (.001) (.002) 002 Number of observations 2477 1309 1168 Ka-fu Wong C2007 ECON1003: Analysis of Economic Data Lesson 11-5
Ka-fu Wong © 2007 ECON1003: Analysis of Economic Data Lesson11-5 Regression results **p<0.01; *p<0.05; †p<0.1