Financial Health of the Spanish Educational Private Institutions

Education is of vital importance for the competitiveness and growth of a country, but it is affected by the amount of public and private investment, in particular, by governments and the economic leverage of citizens to pay tuitions. The financial crisis, originated in 2008, had some degree of impact in the European education system, which has not been completely understood. Spain is one of the countries that has suffered most from its impact, as reflected in the report of the Organization for Economic Cooperation and Development (OECD) of 2016, see [1]. While in most European countries public spending on education has remained stable at 11%, in Spain public spending on education has fallen from 9% to 8% from 2008 to 2013. The expenditure per student was below the OECD average in all stages, from primary to university. Nevertheless, such data are usually known for the public sector whereas the impact of the private sector is neglected. Here we want to focus on precisely the Spanish private educational sector, since a considerable percentage of students in Spain received education in private institutions, turning it a good case-study for understanding the impact of economy in education. Our work examines the financial efficiency of more than 4.000 Spanish private institutions divided into four educational levels: pre-primary, primary, secondary and higher education, in the period 2013- 2016. Their evolution is evaluated at three distinct stages: efficiency levels; efficiency patterns; and efficiency determinants. Our results clarify which are the profile of institutions that are most efficient, and which are not, giving some insight about the improvements which could be applied to raise their effectiveness. To this end, we take as a starting point the financial statements of each institution, considering variables that allow us to interpret measures of leverage, liquidity, profitability, management and evaluation of the institution. The main mathematical tool used is a nonparametric deterministic method for measuring efficiency, the Multidirectional Efficiency Analysis (MEA) of Bogetoft and Hougaard [2], in combination with other techniques. In contrast with the standard DEA, MEA also allows to investigate changes in efficiency patterns. Since the selection of relevant variables is of major importance, a combination of techniques to choose the most meaningful ones is used, namely, through Principal Component Analysis and to avoid loss of information (under-fitting) or the adding random noise (over-fitting), the RV coefficient is computed, see [3]. Comparisons between groups with different levels of efficiency are made by calculating an index that measures the effort to obtain input resources in a sequence of years.publishe