With regards to financing, the combination of high economic growth and high levels of investment as mandated by the education finance law of 2006 has led to unprecedented increases in resources for the education sector over the last decade. The increase in investment in education as a share of GDP from less than 3 percent in 2003 to close to 6 percent in 2013, paired with an average GDP growth rate of 6 percent over that same period (World Bank, 2014), has translated into a rise in public spending on education from about 500 million pesos to nearly 1.6 billion pesos (Albornoz, 2015). As with any education system, these resources have principally financed teacher salaries, followed by infrastructure and other capital investments such as information and communications technology (ICT) and other school equipment.

Concerning spending on teachers, there is evidence that this period witnessed both large increases in teacher numbers and teacher salaries. While the student base expanded by about 10 percent between 2003 and 2013 (DINIECE, 2004, and DINIECE, 2015), the recent teacher census revealed that the number of teachers expanded by more than 20 percent over roughly the same period (DINIECE, 2015). This has given Argentina a pupil-teacher ratio of 11, the lowest in Latin America after Cuba (OECD, 2013). With regards to teacher salaries, Bezem, Mezzadra, and Rivas (2012) find evidence that real salaries (in 2001 pesos) rose on average by 76 percent between 2003 (450 pesos) and 2012 (794 pesos). Still, this is less than the overall tripling of public resources for education, implying that the increased sectoral financing has meant a substantial rise in other schooling inputs. In particular, there was a large expansion in public school buildings constructed: 1,751, the most in half a century (Aboldornoz, 2015). The investment in ICT has also been impressive, representing as much as 50 percent of the infrastructure investment in the years 2011 and 2012 (Albornoz, 2015).

# _3.2 Trends in PISA Results_

The OECD’s Program for International Student Assessment (PISA) was first carried out in 2000, and since then a new edition has come out every three years. More than 70 countries have participated in PISA to date, making it the preferred dataset for cross-country comparisons. PISA is a standardized test assessing three subject areas: mathematics, reading, and science. It is not based on the curriculum of any particular education system. Rather, it evaluates students’ ability to apply their knowledge and competences to problem solving. By construction, PISA had a mean of 500 and a standard deviation of 100 among OECD countries in 2000, in each subject area (see Annex A for more details on PISA’s design).

This study uses micro data at the student level from 2000, 2006, 2009, and 2012, years in which Argentina participated in the PISA survey. PISA results are composed of a random sample of 15-year-olds who are attending school. The students are selected by a two-stage sampling strategy—first, by randomly selecting schools, and then by selecting 15-year-olds within the schools, also at random. In the case of Argentina, samples are representative at the national level only (DINIECE, 2004).<sup>3</sup>

> 3 A look at the sample suggests different degrees of representativeness in the editions considered. Using the survey’s expansion factors, the weighted sample accounted in 2000 for more than 90 percent of the total 15-year-old population enrolled. Nevertheless, there is an important number of missing values. Fortunately the missing values are not for the learning outcome results but for variables capturing school characteristics and socioeconomic background where, in some cases, more than 40 percent of the observations report missing values in 2000. A first concern is the randomness of missing values. Intuitively, missing at random sounds like a very strong assumption. The missing

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