|Constant|386.424***|402.407***|349.204***|385.594***|
|---|---|---|---|---|
|N|1,892|2,834|2,865|3,373|
|R2|0.38|0.39|0.43|0.37|

_Notes_ : All estimation results are accounting for PISA’s survey design as explained in Annex A. As usual, * p<.10, ** p<.05, *** p<.01. The references category for mother’s and father’s education level is unfinished primary; the reference category for number of books at home is less than 11; and the reference category for school size is less than 200 students.

As previously discussed in this paper, the share of students enrolled in private schools in Argentina has increased constantly since 2003, reaching 39 percent of total students in secondary school and 29 percent in primary and secondary school in 2014 (DINIECE, 2015). One of several potential explanations behind this trend could relate to significant differences in the quality of education services between private and public providers. In an alternative specification that did not include controls for institutional settings, public schools were found to be significantly and negatively correlated with student performance across all years, even when controlling for students’ individual and background characteristics (the results of this alternative specification are presented in Annex B). However, once we control for school autonomy variables, specifically those related to schools’ authority to fire teachers, determine courses, and formulate the school budget, the negative effects associated with public school vanish. The results presented in Table 4 show that, once controlling for differences in institutional settings, public schools prior to 2012 were not different than private ones, at least in their ability to produce learning outcomes. This suggests that whether a school is public or private is not, in itself, determinant of school performance. What really matters is the degree to which those schools have the necessary autonomy to implement education policies. Interestingly, in 2012, even controlling for institutional setting, students in public schools achieved substantially lower learning outcomes, putting them behind their peers in private schools by almost half a standard deviation.

With the exception of 2009, once controlling for individual and socioeconomic background, rural schools seem to be no different than urban ones in terms of learning outcomes. This is somewhat surprising, since rural schools tend to be smaller, putting them at a disadvantage versus larger schools, which are much more predominant in urban centers, especially in 2006 and 2009. In those two years, schools with 200 students or more had reading test scores between 0.25 and 0.6 standard deviations higher than schools with fewer than 200 students.

Four variables are of particular interest since they could capture—albeit somewhat imprecisely—part of the increase in inputs brought about by the education finance law of 2006. These variables are: (1) the availability of computers with connectivity, (2) the student-teacher ratio, (3) the proportion of teachers with completed tertiary education, and (4) the school director’s perception of whether instructional materials such as textbooks are adequately available. According to our results, a higher availability of a computer that is connected to the Internet—via a computer lab in the school—is positively related with higher reading test scores. However, by 2012, this is only significant at the 10 percent confidence level. Perhaps one of the most important results in our estimations is that the number of students per teacher has no effect on test scores in any of the PISA rounds. This has important budget and policy implications, since Argentina has a pupil-teacher ratio of 11, the lowest in the region and well below countries such as Chile (22), 17