The output variable is only available for the year 2017. All input and control variables (except dummies) are averaged for the period 2000 to 2015. This seems to make sense because the output variable reflects the effects of past investments in the education sector. In addition, it may take some time for the input to impact on the output, so the input variable is delayed with respect to the output. Since resources necessary to improve access and quality require sustained investments over a relatively long period, considering the average expenditure over the last 15 years allows past investments into the education system to be taken into consideration. The data set used is then a cross‐section covering the period 2000‐ 2015 for the input and control variables and the year 2017 for the output variable. Data are collected from three main sources: The World Development Indicators, the UNESCO Institute of Statistics (UIS), and the OECD Creditor Reporting System (OECD‐CRS). Table 1 presents descriptive statistics of the data.

**Table 1 Descriptive Statistics**

|Variable|Obs|Mean|Std. Dev.|Min|Max|Coef. of<br>Variation|
|---|---|---|---|---|---|---|
|**Output (y)**|||||||
|Learning‐Adjusted Years of Schooling (lays)|157|7.895|2.683|2.275|12.905|2.942|
|**Input (x)**|||||||
|Total public expenditure per school‐age individual PPP|||||||
|(expeduc)|175|2862.225|3852.216|29.981|22448.080|0.743|
|**Control variables (z)**|||||||
|Share of aid in public education expenditure (odashare)|178|0.047|0.094|0|0.648|0.500|
|Unemployment rate (unemploy)|186|9.008|6.151|0.650|31.994|1.464|
|Primary Completion Rate (pcr)|180|87.370|18.761|25.734|138.222|4.657|
|Student to Trained Teacher Ratio (sttrm)|217|40.546|23.586|8.730|221.937|1.719|
|High‐Income country|217|0.355|0.480|0|1|0.740|
|Upper Middle‐Income country|217|0.143|0.351|0|1|0.407|
|Lower Middle‐Income country|217|0.244|0.431|0|1|0.567|
|Low‐Income country|217|0.258|0.439|0|1|0.588|

To increase the size of the sample and improve the reliability of the econometric regressions, all countries with data available will be considered, including high‐income countries. In addition to increasing the sample size, including high‐income countries allows to benchmark all countries and to compare developed and developing countries in terms of efficiency.

Data presented in Table 1 show large heterogeneity in terms of public education spending. The spending per school‐age individual varies from $US 30 in the Central African Republic to $US 22,448 in Qatar. The LAYS also varies from a lowest of 2.27 years in South Sudan to a highest of 12.90 years in Singapore. The coefficient of variation, which is a measure of the inequality in the distribution of a variable shows that there is higher inequality with respect to the LAYS compared to the public expenditure per school‐age individual. This may imply that certain countries may not necessarily be translating their spending into quality education properly, when compared to others. Table 2 shows that low‐income countries have the lowest spending per individual and the lowest LAYS. The spending per school‐age individual and the LAYS both increase with respect to income (as shown by the income groups).

8