ECON 3039 Labor Economics By Elliott Fan Economics, NTU Elliott Fan: Labor 2015 Fall Lecture 31

Card, DellaVigna, Malmendier (2011) Elliott Fan: Labor 2015 Fall Lecture 32

Four advantages of experiments Here are some advantages listed by advocates of RCTs: Has the potential for overcoming selection bias Can be policy relevant Transparency; easy to explain Allows you to test new ideas Elliott Fan: Labor 2015 Fall Lecture 33

Disadvantages of experiments Critics of RCTs point out problems such as: Context specificity Cost Human subject / ethical concerns Partial vs General equilibrium effects Duration of evaluation—can we wait? Attrition / compliance Is the mean enough? Externalities Elliott Fan: Labor 2015 Fall Lecture 34

Heckman and Smith 1995 JEP: Randomization Bias – the randomization alters the process of selection into the treatment, so that those who participate during an experiment differ from those who would have participated in the absence of an experiment. Substitution bias – members of the experimental control group cannot obtain substitutes for the treatment elsewhere. Elliott Fan: Labor 2015 Fall Lecture 35

Examples of randomized trials Elliott Fan: Labor 2015 Fall Lecture 36 Krueger (QJE, 1999) on STAR program Project STAR was a longitudinal study in which kindergarten students and their teachers were randomly assigned to one of three groups beginning in the 1985–1986 school year. Small classes (13–17 students per teacher), regular-size classes (22–25 students), and regular/aide classes (22–25 students) which also included a full-time teacher’s aide. Deal with two reactive effects -- ‘Hawthorne Effects’ and ‘John Henry Effects’

Examples of randomized trials Elliott Fan: Labor 2015 Fall Lecture 37 Krueger (QJE, 1999) on STAR program There is no ideal randomized trial in practice. However, you can somehow verify it.

Examples of randomized trials Elliott Fan: Labor 2015 Fall Lecture 38 Krueger (QJE, 1999) on STAR program Identification strategy (OLS) Identification strategy (2SLS)

Graphical presentation Elliott Fan: Labor 2015 Fall Lecture 39

Results Elliott Fan: Labor 2015 Fall Lecture 310

Examples of randomized trials Elliott Fan: Labor 2015 Fall Lecture 311 Krueger (QJE, 1999) on STAR program Deviations from an ideal experiment: Students in regular-size classes were randomly assigned again between classes with and without full-time aides at the beginning of first grade Approximately 10 percent of students switched between small and regular classes between grades, primarily because of behavioral problems or parental complaints. Some students and their families naturally relocate during the school year, actual class size varied more than intended in small classes (11 to 20) and in regular classes (15 to 30). Attrition -- around half of students who were present in kindergarten were missing in at least one subsequent year.

Examples of randomized trials Elliott Fan: Labor 2015 Fall Lecture 312 Duflo, Dupas, and Kremer (AER, 2011) on tracking and peer effects in Kenya To the extent that students benefit from high-achieving peers, tracking will help strong students and hurt weak ones. However, all students may benefit if tracking allows teachers to better tailor their instruction level. Lower-achieving pupils are particularly likely to benefit from tracking when teachers have incentives to teach to the top of the distribution.

Examples of randomized trials Elliott Fan: Labor 2015 Fall Lecture 313 Duflo, Dupas, and Kremer (AER, 2011) on tracking and peer effects in Kenya Literature: There is a rough consensus that tracking helps high-achieving students. The consensus, however, is weaker for low-achieving students. Selection bias would be serious in cases using inappropriate comparisons. Attrition constitutes another difficulty.

Examples of randomized trials Elliott Fan: Labor 2015 Fall Lecture 314 Duflo, Dupas, and Kremer (AER, 2011) on tracking and peer effects in Kenya The experiment design: In 2005, 140 primary schools in western Kenya received funds to hire an extra grade one teacher. Of these schools, 121 had a single first-grade class, which they split into two sections, with one section taught by the new teacher. In 60 randomly selected schools, students were assigned to sections based on initial achievement. In the remaining 61 schools, students were randomly assigned to one of the two sections. They find that tracking students by prior achievement raised scores for all students, even those assigned to lower achieving peers.

Examples of randomized trials Elliott Fan: Labor 2015 Fall Lecture 315 Duflo, Dupas, and Kremer (AER, 2011) on tracking and peer effects in Kenya

Examples of randomized trials Elliott Fan: Labor 2015 Fall Lecture 316 Duflo, Dupas, and Kremer (AER, 2011) on tracking and peer effects in Kenya Identification strategy (OLS) for estimating the tracking effect: y ij is the endline test score of student i in school j; T j is a dummy equal to 1 if school j was tracking; and X ij is a vector including a constant and child and school control variables.

Examples of randomized trials Elliott Fan: Labor 2015 Fall Lecture 317 Duflo, Dupas, and Kremer (AER, 2011) on tracking and peer effects in Kenya To identify potential differential effects for children assigned to the lower and upper section, they use: B ij is a dummy variable that indicates whether the child was in the bottom half of the baseline score distribution in her school.

Overall effect of tracking (SR) Elliott Fan: Labor 2015 Fall Lecture 318

Overall effect of tracking (LR) Elliott Fan: Labor 2015 Fall Lecture 319

Examples of randomized trials Elliott Fan: Labor 2015 Fall Lecture 320

Peer effect Elliott Fan: Labor 2015 Fall Lecture 321