Chapter 7. The Economics of Tracking in Education Tracking refers to the practice of dividing students by ability or achievement. Students may be tracked within schools by placing them into different classrooms based on achievement which is the typical practice in countries such as the United States or Canada. Alternatively students could be streamed into different schools with either vocational or academic emphases as has been practiced commonly in Europe. Proponents of tracking argue that tracking can increase the efficiency of schooling by focusing on the needs of distinct groups of students. Opponents main concerns relate to perpetuating and aggravating inequality. Evaluating effects of tracking on average student achievement and the distribution of achievement is difficult in part because of variations from study to study and from country to country in the characteristics of the tracking system. Early work largely in the United States and Britain used variation across and within schools and often found that tracking increased inequality in achievement. But more recent work in the United States has questioned these findings suggesting that careful attention to endogenous placement of students into classrooms and endogenous use of tracking across schools changes results dramatically. Experimental studies on within school tracking in the United States have produced mixed results and one experiment in Kenya suggests that tracking can boost the achievement of both low achieving and high achieving students. A large body of work now uses geographical variation across regions countries grades and time to identify the effects of tracking. These studies for the most part suggest that tracking aggravates inequality in outcomes. These results are fairly strong and may be identifying the more dramatic effects that obtain when students are separated into vocational schools and more academically oriented schools as opposed to the effects of within school tracking. The paper concludes with an outline of how future research might better categorize and rigorously evaluate the real world nuances of tracking.