**<u>Table 4 Household Surveys</u>**

|**y**<br>**Countr**|**Survey**|**Year**|
|---|---|---|
|Brazil|Pesquisa Nacional por Amostra de Domicílios (PNAD)|2004|
|Colombia|Encuesta de Calidad de Vida (ECV)|2003|
|Mexico|de los Hogares (MxFLS)<br>Encuesta Nacional Sobre Niveles de Vida|2002|
|Peru|Encuesta Nacional de Hogares (ENAHO)|2004|

# <u>Estimating Education Costs</u>

In Mexico, tuition fee is estimated using weighted aggregate data from the household expenditure survey. The sample size is about 600 on tuition for tertiary education, which lends credibility to the estimate of tuition in both public and non-governmental institutions. For the other countries, the household and expenditure surveys contain few and spurious information. In Colombia, the tertiary education institutions are by law required to report the tuition fee to the Ministry of Education for every authorized degree program. For this study, we use the average tuition level of higher education programs in public and non-governmental from 2003. Ideally, this should be weighted by the number of students in each program, but this information was not available. This may introduce a bias in the estimate if there is a systematic difference in the tuition level of small programs compared to large programs. For both Brazil and Peru, we equally searched for government databases, but did not find any available source. We therefore, had to resort to primary data collection. We searched the websites of all tertiary education institutions listed in Wikipedia in Brazil (123 institutions) and Peru (64). We obtained tuition information for non-governmental institutions for 20 institutions in Brazil, and 6 in Peru. Further, we surveyed by telephone another 12 Peruvian institutions.<sup>16</sup> Hence, the tuition estimate for Peru is the average of the tuition fee in those 18 (non-governmental) institutions.

The varying data sources and types of data to estimate education cost of the nongovernmental institutions constitute the study’s main weakness. In particular, for Brazil and Peru, we advice against drawing any conclusion based on the affordability indicators, because of the low level of representativeness of the information for the education cost of the non-governmental sector.<sup>17</sup> 16 The information on tuition is either: (i) overall average of all disciplines offered, or (ii) the average of a low-cost degree, most often a degree in education, and a high-cost degree, most often engineering or medical. When tuition differed upon the income level of the student, we computed the average of the tuition across the income groups, hence tantamount to the assumption of an equal distribution of students. For the telephone survey, we rely on admission officers’ response.

17 For both countries, the estimates involve only a set of the many tertiary education institutions existing in each country. The findings for these countries are therefore preliminary. Further research is required to establish a reliable and representative estimate on the affordability of tertiary education in these two countries. Nevertheless, we felt it important to report these preliminary estimates for two reasons: (i) they highlight the lack of information regarding the household costs of attending tertiary education, and (ii) the preliminary estimates add to the findings for Colombia and Mexico.

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