Education as a dimension of human development: A Provincial-level Education Index for Ecuador

Notes: MYS = mean years of schooling index; EYS = expected years of schooling index: PEI = Provincial-level Education Index: CV2 = squared of the coefficient of variation. https://doi.org/10.1371/journal.pone.0270932.t003 PLOS ONE Education as a dimension of Human development PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 14 / 27

Finally, Fig 5 shows the PEI values of those Ecuadorian provinces which had the best and worst educational development, together with the values of the educational component of the HDI of LAC countries that had an upper-middle income in 2014. As can be seen, the educa- tional development of Ecuadorian provinces with a poorer PEI was lower than that of all the countries analyzed, except Paraguay, whose education index was lower than the PEI of Los Rı´os and Orellana. Regarding the provinces with the highest PEI, Tungurahua and Guayas were only outperformed by Peru and Costa Rica, while only Costa Rica showed better results than Loja and Pastaza. It is worth highlighting the case of Pichincha, which displayed greater educational well-being than all the LAC countries considered. Discussion and conclusions The Provincial-level Education Index shows an increase in the educational development of Ecuador’s provinces in the period under analysis. Yet despite this overall improvement, differ- ences continue to exist. Thus, 12 of the 21 Ecuadorian provinces had a medium educational development in 2014 (PEI between 0.606 and 0.657), while the rest reached a high educational development (PEI between 0.677 and 0.751), according to the thresholds calculated from the distribution of the UNDP´s HDI educational index for that year. It is also worth mentioning Table 4. Descriptive summaries of education indicators. Mean years of schooling Expected years of schooling 2006 2014 2006 2014 Mean 7.233 8.118 12.879 13.974 Standard deviation 0.809 0.881 0.642 0.480

Variation coefficient 0.112 0.108 0.050 0.034 Square of the variation coefficient 0.013 0.012 0.002 0.001 Maximum 9.285 10.248 14.284 14.768 Minimum 5.902 6.144 11.549 12.979 Range 3.383 4.104 2.735 1.789 Note: approximate results for the provinces of Amazonia in 2006 due to lack of representativeness in the survey. https://doi.org/10.1371/journal.pone.0270932.t004 Fig 4. Provincial contribution to educational development overall inequality (%). https://doi.org/10.1371/journal.pone.0270932.g004 PLOS ONE Education as a dimension of Human development PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 15 / 27

that, with the exception of Pichincha, whose PEI was 0.751, the rest of the provinces were still far from 0.784, the threshold that determines the level of very high educational development. In addition to Pichincha, the provinces with the highest PEI values in 2014 were Pastaza, Loja, Guayas, Tungurahua, and El Oro. At the other end of the scale were Chimborazo, Coto- paxi, Sucumbı´os, and Los Rı´os, which displayed the lowest values. Esmeraldas and Cañar wit- nessed the greatest increase in their PEI. When comparing the educational development of Ecuadorian provinces with that of LAC countries with the same socioeconomic characteristics (Paraguay, Dominican Republic, Mexico, Colombia, Belize, Brazil, Jamaica, Panama, Peru, and Costa Rica) it is worth noting that Tungurahua and Guayas were only surpassed by Peru and Costa Rica. Also, the cases of Pastaza and Loja must be highlighted, as they had a PEI only lower than that of Costa Rica. Finally, above all, Pichincha outstands for having a higher edu- cational development than all the countries considered. All LAC countries analyzed presented better educational development than the provinces with the lowest PEI–with the exception of Paraguay, whose education index was lower than the PEI of Los Rı´os and Orellana. Our results are consistent with the data provided by official statistics regarding variables such as the literacy rate or the percentage of people in households with children who do not go to school. Thus, Pichincha presented the lowest rate of illiteracy in 2014, followed by Guayas

and Loja (3.7%, 5.65%, and 5.8%, respectively), whereas the highest values corresponded to Chimborazo (19.4%) and Cotopaxi (13.7%), with Esmeraldas and Cañar evidencing the great- est reduction in illiteracy rates (from 13.4% to 8.5% and from 15.3% to 9.6%) during the study period [91]. In addition, Pichincha and Loja had the lowest percentage of people in households with children who did not go to school (0.5%), followed by Guayas (0.8%), while Chimborazo (1.1%) and Sucumbı´os (1.6%) had the highest [91]. A wide range of reasons may lie behind our results. First, there is the need to consider the actual production structure and level of economic development of the various provinces. Amongst those evidencing the highest PEI values during the studied period, Pichincha, together with Guayas and Tungurahua, form part of the group of provinces displaying the greatest economic development [100]. These provinces have traditionally benefitted from bet- ter opportunities in terms of access to education and have also enjoyed a better-quality educa- tion system [101]. They also have the largest number of technical and technological institutes (over half of those in Ecuador are in Pichincha and Guayas), as well as the highest number of students enrolled at these institutions (over 65% between the two provinces) [102]. Bearing in Fig 5. Comparison between the values of the Provincial-level Education Index of the provinces with the highest and lowest value of said index and the values of the

education index of the Human Development Index for countries with an upper-middle income in Latin-America and the Caribbean. 2014. Note: Upper-middle income countries in 2014 are those with a gross national income per capita of between $4,126 and $12,735 according to the World Bank classification in 2014 [99]. https://doi.org/10.1371/journal.pone.0270932.g005 PLOS ONE Education as a dimension of Human development PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 16 / 27

mind the important role played by the oil sector in Ecuador’s provincial economic structure [100] and the economic boom that the country experienced during the study period, it comes as no surprise that certain oil provinces, such as Pastaza, evidenced some of the highest PEI values. This was mainly due to the favorable evolution of oil prices, which generated a signifi- cant amount public resources that were devoted to education, encouraging families to enroll their children in school. Sucumbı´os, the most populated province in Amazonia, was amongst those to have recorded the lowest PEI values, even though it also exhibited a high degree of production specialization in the oil sector. This may be due to the existence of a dynamic labor market that significantly increases the opportunity costs of education, thereby leading to school lagging, dropout, and child labor. Finally, Chimborazo, one of the poorest provinces in the country (together with Bolı´var, Orellana, and Sucumbı´os) [100] showed the worst PEI value. With a high percentage of indigenous population, its economy is based on a subsistence model in which the agricultural sector, crafts and tourism are activities which tend to generate unskilled labor. Added to this is the strong rural component of the remaining provinces that had a worse PEI value (Cotopaxi and Los Rı´os), which is exacerbated by the fact that the least qualified teachers tend to be concentrated in rural schools [48], and where there are also diffi- culties regarding access and inadequate school infrastructure (drinking water, electricity, and

sanitation). Other reasons behind our results might be due to the policies implemented by the country’s authorities at different administrative levels, the effects of which have begun to be felt during the study period. We are aware that no impact evaluation analyses have been carried out for most of them [103] and that therefore we cannot establish a cause-effect relation to determine what part of the observed effect might correspond to any given policy (net effect). However, said policies might account for the reduction in inequality in education, as already highlighted in some studies [28]. Among these policies, the Ten-Year Education Plan 2006–2015, which aimed to achieve quality basic education for all by 2015, is noteworthy. It also included the second of the Millen- nium Development Goals: achieving universal primary education by 2015 [42]. But, above all, mention should be made of the education reforms undertaken by the Ecuadorian government at all levels of education with the entry into force of the LOES of 2010 and the LOEI of 2011. In addition, some free education policies were implemented with the aim of universalising basic education. These policies mainly affected decentralization in administrative, curricular, and financial decision making, and justified the coordination between the requirements of local development and what is offered by educational institutions, having economic consequences in the area [104]. This boosted parental participation in schools and led to an improvement in the

way education is perceived by families [41]. In addition, the increase in the number of years of compulsory education at pre-school level helped to improve equity, as evidenced by our find- ings concerning the expecting years of schooling indicator. Various studies [105–108] show that early-childhood education exerts a positive effect on the likelihood of children being schooled afterwards, and in terms of preventing them from falling behind or dropping out. Early-child- hood education also seems to positively impact learning outcomes in the early years of primary education, with these effects proving to be greater in the case of children from poor families. Expanding access to early-childhood education is key to enhancing the effectiveness of the edu- cation system and curbing inequality [56], as the literature has evidenced the positive effects that early-childhood education has on disadvantaged children [109]. Secondly, there is the need to consider a series of fee-free policies in education implemented during the period covered in this research, and which might have led to improvements in the component related to expected years of schooling, the estimation of which involves attendance and enrolment rates. PLOS ONE Education as a dimension of Human development PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 17 / 27

Prominent among these policies are, on the one hand, the waiving of school fees at all edu- cational levels, which was gradually implemented from 2007 onwards. And, on the other hand, the provision of free schoolbooks, which initially covered the first to the tenth year of General Basic Education, and which was later extended to all levels of non-schooled education [110, 111]. Added to it is the program of free schoolbooks in ancestral languages Kukayus Pedagógi- cos, which has been developed mainly in the provinces of the Sierra region (Pichincha, Coto- paxi, Imbabura, Tungurahua, Bolı´var, Chimborazo, Cañar, Azuay, and Loja), where a large part of the country’s indigenous population lives. Also, the Programa de Alimentación Escolar, which begun in 1999, must be highlighted, as it provides breakfast and lunch for children in vulnerable households, offering two meals a day in schools–only one after 2007– for students of Initial Education and General Basic Education in urban and rural areas. All provinces improved their coverage over the period, both in the textbook and school meals programs, and the provinces that initially displayed a lower PEI (Chimborazo and Cotopaxi in the former, and Azuay and Los Rı´os, in the latter, respectively) (S7 Table) showed the greatest increase. Mention should be made of the Hilando el Desarrollo program, through which the uniforms of students in state schools at the levels of Initial Education and General Basic Education are paid. This program promotes school enrolment, since, as uniforms are compulsory in Ecua-

dor, not having one might pose a hurdle to attending school and urge children to drop out. The program, which begun in 2007 and which is still in place today, also promotes associations of small craftsmen and women in micro-textile firms to make uniforms in the local area by granting microcredits, training, and technical assistance. Guayas and Pichincha, two of the provinces with the highest PEI values, evidence the greatest reduction in the percentage of stu- dents benefiting from free uniforms between 2009 and 2012 (-11.1 and -10.8, respectively) (S7 Table). It is worth noting that the results of an assessment of the program’s impact in five prov- inces of the Costa region indicated that the program had no effect on school enrolment, although it did show negative effects vis-à-vis attendance [112]. These results could be due to the sunk costs fallacy and to parental disappointment with schools, which, after promising a uniform, failed to supply one. Other aspects that influenced the results were the poor quality of the uniforms provided by the program, and the stigmatization suffered by the children who wore it [112]. Overall, the results obtained might be shedding light on certain progress in terms of improvements in interprovincial educational equality, although differences can still be observed. Although the aforementioned policies correspond to the central government and are imple- mented at the national level, they could be behind our results–especially those related to cer- tain provinces that have shown a better performance in the PEI between the two periods

studied−. Although all these policies have been an important incentive for the access and con- tinuity of children in the school system throughout the country, the greatest effort has been made in rural areas [113]. As a result, some of the provinces with the highest proportion of rural population have also been some of the ones that have shown the best evolution in their PEI. In addition, it should be noted that most of the provincial governments of Costa and Sierra continued to allocate their own budget to some of these programs −such as free text- books−, which made it possible to reach a greater number of students [114] (S7 Table). Institu- tions play a key role in the way societies distribute the benefits and costs of public policies implemented at different levels of government. Without them, there is little likelihood that the necessary change will take place. The fact that some institutions work better than others at the regional/local level may cause a national program/policy to obtain better results in some prov- inces than in others (inclusive institutions vs. extractive institutions) [115]. Together with these central government policies implemented at a national scale, some sub- national governments also developed various initiatives. Such is the case of Pichincha which, PLOS ONE Education as a dimension of Human development PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 18 / 27

between 2004 and 2007, introduced a program of free schoolbooks: Sí a la Educación Básica (Sílabas). Since 2006, this program has also been in place in the provinces of Azuay and Man- abı´. In Guayas, the Más Libros program is still being implemented today [110, 116]. Finally, the effects of the Bono de Desarrollo Humano (BDH) must also be considered. Most of the studies which assess the impact of CCT programs in LAC countries report significant effects in the increase of school enrolment and in the reduction in child labor. This is the case of some research conducted in countries with upper-middle income in the region, the results of which reflect the positive effects that these programs have on school attendance and enrol- ment, as occurred in Oportunidades (formerly Progresa) in Mexico [117, 118], Familias en Acción in Colombia [119] or Bolsa Escola in Brazil [120]. In Ecuador, BDH’s achievements have been highlighted by studies that find significant effects in the reduction of activity and child labor rates, delaying children’s entry into the labor force [121]. This conclusion is sup- ported by the fact that such transfers considerably increase school enrollment, and that this effect is four times greater in households that perceive this conditionality as an obligation com- pared to those who feel that the transfer is not conditional [122]. During 2009–2014, the BDH had greater coverage in some of the provinces where the education index shows a clear improvement −such as Esmeraldas, Loja, Morona Santiago,

Tungurahua, and Zamora Chinchipe−. The beneficiaries’ fear of being sanctioned in the event of a verification of conditionality in education has probably contributed to the results achieved [123]. Finally, it is worth mentioning that, even though no cause-effect relation may be inferred from our study, the convergence in educational development of Ecuadorian provinces is con- sistent with studies that point to a process of income convergence at a provincial level in Ecua- dor in the period covered in this research, and which underpin the importance of reducing inequalities in education in order to achieve such a convergence [45,124, 125]. In spite of this, the convergence in education obtained should be considered with the cau- tion that the lack of representativeness of the Amazonian provinces in the fifth round of the LSMS implies. In line with certain authors who consider that a sample can be valid without being representative [126, 127] our analysis of the causes behind the results obtained will bring us closer to the scientific objective of understanding the territorial dynamics of educational development in the Ecuadorian provinces. In any case, the main limitation in our work is the lack of data. The fact that the latest available round of the LSMS corresponds to the period 2013–2014 does not −for the time being− allow us to analyze the consequences of Ecuador’s educational policies with a greater perspective, particularly if we consider that the outcomes of educational policies do not tend to emerge in the short term. In a similar vein, the LSMS’s lack

of representativeness for a higher level of disaggregation (Ecuadorian cantons) prevented us from delving more deeply into the dynamics of educational inequalities in Ecuador. We are also aware that using only two indicators is perhaps a reductionist way of understanding a country’s educational development. Nevertheless, the fact that they are the indicators used by the UNDP allows our technique to be used for drawing comparisons, such as those made in this work between the educational development of the Ecuadorian provinces and that of the upper-middle income LAC countries. It should also be noted that the use of the mean years of schooling variable in the comparison of educational development between countries has been criticized by several authors [9, 128]. The reason lies in the errors that can occur in the inter- pretation of the results due to the existing heterogeneity between countries’ educational sys- tems. However, this criticism does not make sense in this work, since the PEI is calculated for provinces that have the same educational system. Finally, although the LSMS did allow for the estimation of the education indicators used in this research, the results must be analyzed with the due caution required for a study that is based on the use of a survey. PLOS ONE Education as a dimension of Human development PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 19 / 27

If no new rounds of the LSMS were to be conducted, an alternative to continue analyzing the evolution of the country’s educational development would be to use an employment survey, such as the Ecuador Employment, Unemployment and Underemployment Survey. Although these types of household surveys focus on labor issues and are less ambitious than the LSMS, they also include demographic and socioeconomic aspects of the surveyed population [75]. Furthermore, considering that each generation grows up with higher levels of education than past generations [129], it would be interesting to analyze the effect of age on educational development in Ecuadorian provinces. Since it is to be expected that the provinces with the highest mean age are also those with the lowest mean years of schooling, the estimation of an Educational Index at the provincial level by age groups–following the procedure described in this paper–could be a future line of research. This estimate could complement the information on the territorial pattern of education in Ecuador provided in this paper. In addition, the design of educational indices based on other educational variables, such as enrollment rates at different educational levels, could also be an interesting complement to the Provincial-level Education Index. Finally, new indexes could be designed to show educational inequality between subpopulations determined by characteristics such as geographic location (rural vs. urban) or gender. This would allow a deeper understanding of Ecuador’s sociodemo- graphic reality and its horizontal inequalities.

Conclusions Using the latest micro-databases available for the LSMS, we estimated a Provincial-level Edu- cation Index which showed a favorable evolution in educational development in Ecuadorian provinces as well as a slight reduction in inequality amongst them. However, despite this gen- eral improvement, there are still differences at the provincial level. Our findings are consistent with the production structure and socioeconomic features of Ecuadorian provinces and evidence the effects that certain public policies might have had in the field of education. Nevertheless, the country’s efforts in terms of implementing policies aimed at reducing poverty (National Plans for Good Living and the BDH), on the one hand, and those which seek to improve human capital and its capabilities (Ten-Year Education Plan 2006–2015, and the latest educational reforms), on the other, might not have proved sufficient to bring Ecuador out of the middle-income trap [70] in which it has been immersed for over 60 years [130]. In other words, Ecuador is caught in a low productivity growth, which keeps the country trapped between low income and high income due to structural problems that are hard to overcome. These problems prevent the country from boosting its level of development in general, and its level of educational development, in particular. Although it is true that, dur- ing the boom in oil prices (2007–2014), Ecuador experienced a period of economic growth which triggered a reduction in poverty and a redistribution of educational opportunities, cer-

tain structural problems still remain. Although investment in education increased during the years of the study, rising from 2.3% of GDP in 2006 to 4.7% in 2014 [91], the country must still address various issues. Firstly, a greater investment in school infrastructure is necessary, given that both the difficulties in accessing educational services and their quality partly account for differences between urban, rural, and indigenous areas. These differences only heighten the risk of poverty and social exclusion in certain provinces in the country. Secondly, continuous teacher training should be improved in order to enable teachers to successfully respond to society’s new demands. Also, teacher mobility between urban and rural areas should be fos- tered [131], and, finally, external standardized tests to measure students’ learning outcomes and academic performance that would provide guidelines to improve curricula should be applied [41]. A further issue that requires action is the high degree of segregation (urban-rural PLOS ONE Education as a dimension of Human development PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 20 / 27

and ethnic income), which is mainly observed in General Basic Education, and which evi- dences major differences between provinces. All of this would help to build a fairer education system and to expand equal opportunities [132]. These are just some of the challenges that Ecuador’s education policies must face in the coming decades. In order to gain insight into the distribution of a country’s well-being, it is necessary to ana- lyze the distribution of its educational outcomes, as well as their evolution over time. In LAC, a region with large gaps in access to education, the analysis of educational attainment is particu- larly important [133]. Education data provided by LSMSs offer valuable information for authorities to implement public policies aimed at improving citizens’ living conditions [47]. However, data are worthless if their interpretation is not based on knowledge of the underlying reality. Thus, as this research has shown for Ecuador, understanding the educational situation behind the microdata provided by a country’s household survey and, in particular, by a LSMS, allows for the definition of educational development indices at the national and subnational levels. The values of these indices could provide a guide for the design and implementation of policies to ensure coverage of educational demand and excellence in education, as well as the equality inherent in the right to education for all. Supporting information S1 Table. Structure of the National Education System (non-university education) in Ecua-

dor affecting the fifth round 2005–2006 and sixth round 2013–2014 of the Ecuadorian Liv- ing Standards Measurement Survey. (DOCX) S2 Table. Structure of the National Education System (non-university education) in Ecua- dor affecting the sixth round 2013–2014 of the Ecuadorian Living Standards Measurement Survey. (DOCX) S3 Table. Procedure for estimating the mean years of schooling indicator in the fifth round of the LSMS (2005–2006). (DOCX) S4 Table. Procedure for estimating the mean years of schooling indicator in the sixth round of the LSMS (2013–2014). (DOCX) S5 Table. Values of the mean years of schooling and expected years of schooling indicators. 2006 and 2014. (DOCX) S6 Table. Values of the provincial-level education index and of its components, and annual average variation. 2006 and 2014. (DOCX) S7 Table. Percentage of students benefiting from free schoolbooks, school meals and uni- forms. (DOCX) Acknowledgments We thank the editor and the two anonymous reviewers, whose valuable comments and sugges- tions helped us to improve the quality of the manuscript. PLOS ONE Education as a dimension of Human development PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 21 / 27

Author Contributions Conceptualization: Marta Guijarro-Garvi, Bele´n Miranda-Escolar, Yira Tatiana Cedeño- Mene´ndez. Data curation: Marta Guijarro-Garvi, Bele´n Miranda-Escolar, Yira Tatiana Cedeño-Mene´n- dez, Pedro Benito Moyano-Pesquera. Formal analysis: Marta Guijarro-Garvi. Funding acquisition: Bele´n Miranda-Escolar, Yira Tatiana Cedeño-Mene´ndez. Investigation: Marta Guijarro-Garvi, Bele´n Miranda-Escolar, Yira Tatiana Cedeño- Mene´ndez. Methodology: Marta Guijarro-Garvi. Software: Marta Guijarro-Garvi, Yira Tatiana Cedeño-Mene´ndez, Pedro Benito Moyano- Pesquera. Visualization: Pedro Benito Moyano-Pesquera. Writing – original draft: Marta Guijarro-Garvi, Bele´n Miranda-Escolar, Yira Tatiana Cedeño-Mene´ndez. Writing – review & editing: Marta Guijarro-Garvi, Bele´n Miranda-Escolar, Yira Tatiana Cedeño-Mene´ndez, Pedro Benito Moyano-Pesquera. References 1. United Nations Development Programme (UNDP). Human Development Report 1990. New York: Oxford University Press; 1990. 2. Schultz T. Capital Formation by Education. Journal of Political Economy. 1960; 68(6): 570–583. 3. Schultz T. Education and Economic Growth. In: Henry NB, editor. Social Forces Influencing American Education. Chicago: University of Chicago Press; 1961. pp. 46–88. 4. Schultz T. Reflections on Investment in Man. Journal of Political Economy. 1962; 70(5), Part 2: 1–8. 5. Mincer J. On-the-job Training: Costs, Returns and Some Implications. Journal of Political Economy. 1962; 70(5), Part 2: 50–79.

primer año de operacio´ n. International Food Policy Research Institute; 2000. 54 p. PLOS ONE Education as a dimension of Human development PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 22 / 27

17. Kakwani N, Soares F, Son H. Cash Transfers for School-Age Children in African Countries: Simulation of impacts on Poverty and School Attendance. Development Policy Review. 2006; 24(5): 553–569. 18. Dearden L, Emmerson C, Frayne Ch, Meghir C. Conditional Cash Transfers and School Dropout Rates. The Journal of Human Resources. 2009; 44(4): 828–857. 19. Radcliffe SA. Development for a Postneoliberal Era? Sumak Kawsay, Living Well and the Limits to Decolonisation in Ecuador. Geoforum. 2012; 43(2): 240–249. 20. Gudynas E, Acosta A. El Buen Vivir ma´ s alla´ del desarrollo. Revista Que´ Hacer. 2011; 181: 70–8. 21. Hidalgo-Capita´n AL, Cubillo-Guevara AP. Seis debates abiertos sobre el sumak kawsay. I´conos. Revista de Ciencias Sociales. 2014; 48: 25–40. 22. Leo´n M. Del discurso a la medicio´ n: Propuesta metodolo´gica para medir el Buen Vivir en Ecuador. Quito: Instituto Nacional de Estadı´stica y Censos (INEC); 2015. 94 p. 23. Asamblea Nacional de Ecuador. Constitucio´ n de la Repu´ blica del Ecuador. Decreto Legislativo 0, Registro Oficial 449, Quito (20 de octubre de 2008). 24. Secretarı´a Nacional de Planificacio´n y Desarrollo (SNPD). Plan Nacional de Desarrollo 2007–2010. Quito: Secretarı´a Nacional de Planificacio´n y Desarrollo; 2007. 25. Secretarı´a Nacional de Planificacio´n y Desarrollo (SNPD). Plan Nacional de Desarrollo/Plan Nacional para el Buen Vivir, 2009–2013: Construyendo un Estado Plurinacional e Intercultural. Quito: Secre- tarı´a Nacional de Planificacio´ n y Desarrollo; 2009.

26. Secretarı´a Nacional de Planificacio´n y Desarrollo (SNPD). Plan Nacional de Desarrollo/Plan Nacional para el Buen Vivir, 2013–2017. Quito: Secretarı´a Nacional de Planificacio´ n y Desarrollo; 2013. 27. World Bank. Equidad y Acceso a Oportunidades para los Niños y Adolescentes de Ecuador. Quito: Banco Mundial; 2014. 28. Izurieta G, Ramı´rez-A´ lvarez J. Desigualdad Multidimensional: dina´mica entre Educacio´n e Ingresos en el Ecuador durante el Perı´odo 2000–2014. Analitika. Revista de Ana´ lisis Estadı´stico. 2017; 14(2): 49–79. 29. United Nations Development Programme (UNDP); 2022 [cited May 2022]. Database. Available from: http://hdr.undp.org/en/indicators. 30. Modrego F, Berdegue´ J. A Large-Scale Mapping of Territorial Development Dynamics in Latin Amer- ica. World Development. 2015; 73: 11–31. 31. Lessmann C. Spatial inequality and development: Is there an inverted-U relationship? CESifo Working Paper No. 3622. Munich: Center for Economic Studies and Ifo Institute (CESifo); 2011. 32. Sagar AD, Najam A. The Human Development Index: A Critical Review. Ecological Economics. 1998; 25(3): 249–264. 33. Grimm M, Harttgen K, Klasen S, Misselhorn M. A Human Development Index by Income Groups. World Development. 2008; 36(12): 2527–2546. 34. Harttgen K, Klasen S. A Human Development Index by Internal Migrational Status. Journal of Human Development and Capabilities. 2011; 12(3): 393–424. 35. Harttgen K, Klasen S. A Household-Based Human Development Index. World Development. 2012; 40 (5): 878–899.

36. Permanyer I. Using Census Data to Explore the Spatial Distribution of Human Development. World Development. 2013; 46: 1–13. 37. Chaurasia A R. Empirics of Human Development in India, 1990–2015. Indian Journal of Human Devel- opment. 2019; 13(2): 135–158. 38. Smits J, Permanyer I. The Subnational Human Development Database. Scientific Data. 2019; 6: 190038. https://doi.org/10.1038/sdata.2019.38 PMID: 30860498 39. Stewart F. Horizontal Inequalities: A Neglected Dimension of Development. Working Paper No. 1. Oxford: Centre for Research on Inequality, Human Security, and Ethnicity (CRISE); 2004. 40. Arcos C. Polı´tica pu´ blica y reforma educativa en el Ecuador. In: Arcos Cabrera C, Espinosa B, edi- tores. Desafı´os para la educacio´ n en el Ecuador: calidad y equidad. Quito: FLACSO Sede Ecuador; 2008. pp. 29–63. 41. Ponce J. Polı´ticas educativas y desempeño. Una evaluacio´n de impacto de programas educativos focalizados en Ecuador. Quito: FLACSO Sede Ecuador; 2010. 42. Paladines C. Perspectivas de cambio en la Educacio´n Ba´sica y en el Bachillerato: Ecuador 2007– 2013. Praxis Educativa (Arg). 2015; 19(3) septiembre-diciembre: 13–31. 43. Garcı´a-Aracil A, Winter C. Gender and ethnicity differentials in school attainment and labor market earnings in Ecuador. World Development. 2006; 34(2): 289–307. PLOS ONE Education as a dimension of Human development PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 23 / 27

44. Bastidas M. Educacio´n Intercultural Bilingu¨ e en el Ecuador: Un estudio de la demanda social. Alteri- dad. Revista de Educacio´ n. 2015; 10(2) julio-diciembre: 180–189. 45. Sarmiento S. Evolucio´n de la desigualdad de ingresos en Ecuador, perı´odo 2007–2015. Analitika. Revista de Ana´ lisis Estadı´stico. 2017; 13(1): 49–79. 46. Atuesta B, Mancero X, Tromben V. Herramientas para el ana´ lisis de las desigualdades y del efecto redistributivo de las polı´ticas pu´blicas. Documentos de Proyectos. Santiago de Chile: Naciones Uni- das. Comisio´ n Econo´mica para Ame´ rica Latina y el Caribe (CEPAL); 2018. 47. World Bank Group. World Development Report 2021: Data for Better Lives. Washington, DC: World Bank Group; 2021. 349 p. 48. Esteves A. Introduccio´n. In: Arcos Cabrera C, Espinosa B, editores. Desafı´os para la educacio´n en el Ecuador: calidad y equidad. Quito: FLACSO Sede Ecuador; 2008. pp. 9–25. 49. Corte´ s R, Giacometti C. Polı´ticas de educacio´ n y su impacto sobre la superacio´ n de la pobreza infantil. Serie Polı´ticas Sociales. Santiago de Chile: Naciones Unidas. Proyecto CEPAL/UNICEF Pobreza infantil; 2010. 81 p. 50. United Nations Education, Scientific and Cultural Organization (UNESCO). Las polı´ticas educativas de Ame´ rica Latina y el Caribe. Santiago de Chile: Oficina Regional de Educacio´ n para Ame´ rica Latina y el Caribe; 2013. 46 p. 51. Rivas A, Sa´nchez B. Polı´ticas y resultados educativos en Ame´rica Latina: un mapa comparado de siete paı´ses (2000–2015). Relieve. 2016; 22(1).

52. Martinic S. Conflictos polı´ticos e interacciones comunicativas en las reformas educativas en Ame´ rica Latina. Revista Iberoamericana de Educacio´ n. 2001; 27: 17–33. 53. Organisation for Economic Co-operation and Development (OECD). Education Policy Outlook 2019: Working Together to Help Students Achieve their Potential. Paris: OECD Publishing; 2019. 614 p. 54. Casassus J. La reforma basada en esta´ndares: un camino equivocado. In: Bellei C, Contreras D, Valenzuela JP, editores. Ecos de la revolucio´ n pingu¨ ina. Avances, debates y silencios en la reforma educacional. Santiago de Chile: UNICEF-Universidad de Chile; 2010. pp. 85–110. 55. Espı´nola V, Claro JP. El sistema nacional de aseguramiento de la calidad: una reforma basada en esta´ ndares. In: Bellei C, Contreras D, Valenzuela JP, editores. Ecos de la revolucio´n pingu¨ina. Avances, debates y silencios en la reforma educacional. Santiago de Chile: UNICEF-Universidad de Chile; 2010. pp. 51–84. 56. United Nations Education, Scientific and Cultural Organization (UNESCO). Situacio´ n Educativa de Ame´rica Latina y el Caribe: Hacia la educacio´n de calidad para todos al 2015. Santiago de Chile: Ofi- cina Regional de Educacio´ n para Ame´rica Latina y el Caribe; 2013. 208 p. 57. Alfonso M, Bos MS, Duarte J, Rondo´ n C. Panorama general de la educacio´ n en Ame´rica Latina y el Caribe. In: Cabrol M, Sze´kely M, editores. Educacio´ n para la transformacio´ n. Washington DC: Banco Interamericano de Desarrollo; 2012. pp. 1–49.

58. Ley Orga´nica de Educacio´n (LOE), Ley No. 127 de 15 de abril de 1983. Registro Oficial N.˚ 484 de 3 de mayo de 1983, Quito. 59. Reglamento General de la Ley Orga´nica de Educacio´n. Decreto Ejecutivo No. 935 de 10 de julio de 1985. Suplemento del Registro Oficial n.˚ 226 de 11 de julio de 1985, Quito. 60. Ley Orga´nica de Educacio´n Intercultural (LOEI), Ley No. 0 de 11 de enero de 2011. Suplemento del Registro Oficial N.˚ 417 de 31 de marzo de 2011, Quito. 61. Ley Orga´nica Reformatoria de la Ley Orga´ nica de Educacio´ n Intercultural de 9 de marzo de 2021. Suplemento del Registro Oficial N.˚ 434 de 19 de abril de 2021, Quito. 62. Ley Orga´nica de Educacio´n Superior (LOES), Ley No. 16. Registro Oficial N.˚ 77 de 15 de mayo de 2000, Quito. 63. Ley Orga´nica de Educacio´n Superior (LOES), Ley No. 0 de 4 de agosto de 2010. Suplemento del Registro Oficial n.˚ 298 de 12 de octubre de 2010, Quito. 64. Ley Orga´nica Reformatoria a la Ley Orga´ nica de Educacio´ n Superior de 12 de julio de 2018. Suple- mento del Registro Oficial N.˚ 297 de 2 de agosto de 2018, Quito. 65. Decreto Ejecutivo No. 129, de 14 de septiembre de 1998, por el que se crea el Bono Solidario. Regis- tro Oficial No. 29 de 18 de septiembre de 1998, Quito. 66. Decreto Ejecutivo No. 347, de 25 de abril de 2003, por el que se cambia el Programa Bono Solidario por Programa Bono de Desarrollo Humano. Registro Oficial No. 76 de 7 de mayo de 2003, Quito. 67. Fiszbein A, Schady N. Conditional Cash Transfers: Reducing Present and Future Poverty. Washing- ton DC: The World Bank; 2009. PLOS ONE

Education as a dimension of Human development PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 24 / 27

68. Cecchini S, Filgueira F, Robles C. Sistemas de proteccio´ n social en Ame´ rica Latina y el Caribe: Una perspectiva comparada. Serie Polı´ticas Sociales. Santiago de Chile: Naciones Unidas. Comisio´n Econo´mica para Ame´ rica Latina y el Caribe (CEPAL); 2014. 50 p. 69. Palacio Ludeña MG. Institutionalizing Segregation: Women, Conditional Cash Transfers, and Paid Employment in Southern Ecuador. Population and Development Review. 2019; 45(s1): 245–273. 70. Sari VA. Educational Assistance and Education Quality in Indonesia: The Role of Decentralization. Population and Development Review. 2019; 45(s1): 123–154. 71. Lucero S, Burbano R. Transferencias variables segu´n composicio´ n familiar. Una propuesta para el Bono de Desarrollo Humano. Cuestiones Econo´micas. 2018; 28(1:2): 125–154. 72. Decreto Ejecutivo No. 804 por el que se establece operatividad del programa de transferencias mone- tarias del sistema de proteccio´ n social integral. Suplemento del Registro Oficial No. 529 de 12 de julio de 2019, Quito. 73. United Nations. Household Sample Surveys in Developing and Transition Countries. Studies in Meth- ods, Series F No. 96 ST/ESA/STAT/SER.F/96. New York: Department for Economic and Social Affairs. Statistics Division; 2005. 655 p. 74. World Bank. Measuring Consumption Through Household Surveys. Understanding Household Sur- veys C4D2-Training; 2019 [cited October 2021] Centre for Development Data. Available from: https:// www.worldbank.org/en/programs/lsms/brief/measuring-consumption-through-household-surveys.

75. Gasparini L, Cicowiez M, Sosa W. Pobreza y desigualdad en Ame´rica Latina. Buenos Aires: Temas Grupo Editorial; 2012. 76. World Bank. Living Standards Surveys in Developing Countries. ECV Working Paper No. 1. Washing- ton D.C: World Bank; 1980. 77. Peet ED, Fink G, Fawzi W. Returns to education in developing countries: Evidence from de the living standards and measurement study surveys. Economics of Education Review. 2015; 49: 69–90. 78. Instituto Nacional de Estadı´stica y Censos (INEC). Metodologı´a de la Encuesta de Condiciones de Vida 2013–2014, Sexta Ronda. Quito: INEC; Abril 2015. 84 p. 79. Instituto Nacional de Estadı´stica y Censos (INEC). Homologacio´ n Metodolo´ gica del Ca´ lculo de Pobreza, Desigualdad e Indicadores Sociales, a partir de la Encuesta de Condiciones de Vida. Quito: INEC; 2007. 16 p. 80. Instituto Nacional de Estadı´stica y Censos (INEC). Base de datos de la Encuesta de Condiciones de Vida 2005–2006, Quinta Ronda. Quito: INEC; 2007. 81. Instituto Nacional de Estadı´stica y Censos (INEC). Base de datos de la Encuesta de Condiciones de Vida 2013–2014, Sexta Ronda. Quito: INEC; 2014. 82. Instituto Nacional de Estadı´stica y Censos (INEC). Metodologı´a de la Encuesta de Condiciones de Vida 2005–2006, Quinta Ronda. Quito: INEC; 2006. 83. Schafer JL, Graham JW. Missing Data: Our View of the State of the Art. Psychological Methods. 2002; 7(2): 147–177. PMID: 12090408 84. United Nations Development Programme (UNDP). The Real Wealth of Nations: Pathways to Human

Development. Human Development Report 2010. New York: Oxford University Press; 2010. 238 p. 85. United Nations Education, Scientific and Cultural Organization (UNESCO). Education Indicators. Technical Guidelines. UNESCO; 2009. 50 p. 86. Instituto Nacional de Estadı´stica y Censos (INEC). Encuesta de Condiciones de Vida 2013–2014, Sexta Ronda. Quito: INEC; 2014. 87. Van Hoeven LR, Janssen MP, Roes KCB, Koffijberg H. Aiming for a representative sample: Simulating random versus purposive strategies for hospital selection. BMC Medical Research Methodology. 2015; 15(90): 1–9. https://doi.org/10.1186/s12874-015-0089-8 PMID: 26497748 88. Ebrahim S, Smith GD. Commentary: Should we always deliberately be non-representative? Interna- tional Journal of Epidemiology. 2013; 42(4): 1022–1026. https://doi.org/10.1093/ije/dyt105 PMID: 24062291 89. Ministerio Coordinador de Desarrollo Social. Divisio´n polı´tico-administrativa. Definiciones del Sistema de Indicadores Sociales del Ecuador (SIISE). Quito: Secretarı´a Nacional de Planificacio´ n y Desar- rollo; 2019. 90. Instituto Nacional de Estadı´stica y Censos (INEC); 2020 [cited January 2020]. Proyecciones de Pobla- cio´n 2010–2020. INEC. Available from: https://www.ecuadorencifras.gob.ec/proyecciones- poblacionales/. 91. Secretarı´a Nacional de Planificacio´n y Desarrollo (SNPD); 2020 [cited March 2020]. Sistema Integrado de Conocimiento y Estadı´stica Social de Ecuador. Database. Available from http://www. conocimientosocial.gob.ec/home.jsf. PLOS ONE Education as a dimension of Human development

PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 25 / 27

92. United Nations Development Programme (UNDP). Sustaining Human Progress: Reducing Vulnerabili- ties and Building Resilience. Human Development Report 2014. New York: Oxford University Press; 2014. 239 p. 93. United Nations Development Programme (UNDP). Work for Human Development. Human Develop- ment Report 2015. New York: Oxford University Press; 2015. 288 p. 94. Domı´nguez R, Guijarro M. Gender Inequality and Economic Growth in Spain: An Exploratory Analysis. The Review of Regional Studies. 2009; 39(1): 23–48. 95. Ferna´ndez-Sa´ez J, Ruiz-Cantero MT, Guijarro-Garvi M, Rodenas-Calatayud C, Martı´-Sempere M, Jime´ nez-Alegre MD. Tiempos de equidad de ge´ nero: descripcio´ n de las desigualdades entre comuni- dades auto´ nomas, España 2006–2014. Gaceta Sanitaria. 2016; 30(4): 250–257. 96. Goerlich FJ. Desigualdad, diversidad y convergencia: (algunos) instrumentos de medida. Valencia: Instituto Valenciano de Investigaciones Econo´ micas; 1998. 97. Shorrocks AF. Inequality Decomposition by Factor Components. Econometrica. 1982; 50(1): 193– 211. 98. Permanyer I, Garcı´a J, Esteve A, Mccaa R. Human Development Index-like Small Area Estimates for Africa Compute from IPUMS-International Integrated Census Microdata. Journal of Human Develop- ment and Capabilities. 2015; 16(2): 245–271. 99. World Bank; 2020 [cited March 2020]. World Bank GNI per capita Operational Guidelines & Analytical Classifications. Available from: https://datahelpdesk.worldbank.org/knowledgebase/articles/90651

100. Mendieta Muñoz R, Răileanu-Szeles M, Beltra´n Romero P, Piedra Peña JA. Explaining the regional economic heterogeneity in Ecuador. Bulletin of the Transylvania University of Braşov. Series V: Eco- nomic Sciences. 2015; 8(57): 399–406. 101. Ramo´n-Mendieta MG, Ochoa-Moreno WS, Ochoa-Jime´nez DA. Growth, Clusters, and Convergence in Ecuador: 1993–2011. In: Cuadrado-Roura JR, Aroca P, editors. Regional Problems and Policies in Latin America. Heidelberg: Springer-Verlag; 2013. pp. 323–337. 102. Tomaselli A. La educacio´ n te´cnica en el Ecuador. El perfil de sus usuarios y los efectos en la inclusio´ n laboral y productiva. Serie Polı´ticas Sociales. Santiago de Chile: Naciones Unidas. Comisio´n Eco- no´mica para Ame´rica Latina y el Caribe (CEPAL); 2018. 49 p. 103. Khandker SR, Koolwal GB, Samad HA. Handbook on Impact Evaluation. Quantitative Methods and Practices. Washington DC: The International Bank for Reconstruction and Development/The World Bank; 2010. 104. Samaniego J. Currı´culo y pedagogı´a del bachillerato en Ecuador. In: Arcos Cabrera C, Espinosa B, editores. Desafı´os para la educacio´ n en el Ecuador: calidad y equidad. Quito: FLACSO Sede Ecua- dor; 2008. pp. 227–274. 105. Myers RG. The Twelve Who Survive: Strengthening Programmes of Early Childhood Development in the Third World. 1st ed. London: Routledge; 1992. 106. Myers RG. In search of quality in programmes of early childhood care and education (ECCE). Back- ground paper prepared for the Education for All Global Monitoring Report 2005. United Nations Educa-

tion, Scientific and Cultural Organization (UNESCO); 2004. 107. Paxson C, Schady N. Cognitive Development among Young Children in Ecuador: The Roles of Wealth, Health, and Parenting. Journal of Human Resources. 2007; 42(1): 49–84. 108. Schady N. El desarrollo infantil temprano en Ame´ rica Latina y el Caribe: acceso, resultados y eviden- cia longitudinal de Ecuador. In: Cabrol M, Sze´ kely M, editores. Educacio´n para la transformacio´n. Washington DC: Banco Interamericano de Desarrollo; 2012. pp. 53–92. 109. Van Huizen T, Plantenga J. Do children benefit from universal early childhood education and care? A meta-analysis of evidence from natural experiments. Economics of Education Review. 2018; 66: 206– 222. 110. Ministerio de Educacio´ n. Rendicio´ n de Cuentas 2016. Quito: Ministerio de Educacio´ n del Ecuador; 2016. 111. Ministerio de Educacio´ n y Consejo Nacional de Educacio´ n. Plan Decenal de Educacio´ n del Ecuador 2006–2015: Rendicio´ n de cuentas enero-junio 2007. Quito: Ministerio de Educacio´n del Ecuador; 2007. 112. Hidalgo D, Onofa M, Oosterbeek H, Ponce J. Can provision of free school uniforms harm attendance? Evidence from Ecuador. Journal of Development Economics. 2013; 103: 43–51. 113. Ministerio de Educacio´ n. Rendicio´ n de Cuentas 2008. Quito: Ministerio de Educacio´ n del Ecuador; 2009. 114. Ministerio de Educacio´ n. Rendicio´ n de Cuentas 2010. Quito: Ministerio de Educacio´ n del Ecuador; 2011. PLOS ONE Education as a dimension of Human development PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 26 / 27

115. Acemoglu D, Robinson JA. Why Nations Fail: The Origins of Power, Prosperity and Poverty. 1st ed. New York: Crown; 2012. 116. Centro de Investigaciones Sociales del Milenio. Objetivos de Desarrollo del Milenio. Estado de situa- cio´n 2006: provincias de Azuay y de Manabı´. Quito: AECI/CONCOPE/ONU; 2006. 117. Schultz T. School subsidies for the Poor: Evaluating the Mexican Progresa Poverty Program. Journal of Development Economics. 2004; 74(1): 199–250. 118. Behrman JR, Sengupta P, Todd PE. Progressing through Progresa: An Impact Assessment of a School Subsidy Experiment in Rural Mexico. Economic Development and Cultural Change. 2005; 54 (1): 237–275. 119. Attanasio O, Battistin E, Fitzsimons E, Mesnard A, Vera-Herna´ndez M. How Effective Are Conditional Cash Transfers? Evidence from Colombia. IFS Briefing Note No. 54. London: Institute for Fiscal Stud- ies; 2005. 120. Cardoso E, Portela Souza A. The Impact of Cash Transfers on Child Labor and School Attendance in Brazil. Working Paper No. 407. Nashville: Department of Economics. Vanderbilt University; 2004. 52 p. 121. Edmonds V, Shady N. Poverty Alleviation and Child Labor. American Economic Journal: Economic Policy. 2012; 4(4): 100–124. 122. Schady N, Araujo MC. Cash transfers, conditions, school enrollment, and child work: evidence from a randomized experiment in Ecuador. Policy Research Working Paper Series 3930. The World Bank; 2006. 123. Ministerio de Inclusio´ n Econo´mica y Social. Reporte Nacional del Viceministerio de Aseguramiento no

Contributivo y Movilidad Social. Quito: Ministerio de Inclusio´n Econo´ mica y Social del Ecuador; 2014. 124. Raileanu-Szeles M, Mendieta-Muñoz R. Analyzing the Regional Economic Convergence in Ecuador. Insights from parametric and nonparametric models. Romanian Journal of Economic Forecasting– XIX. 2016; (2): 43–65. 125. Flores-Chamba J, Correa-Quezada R, A´ lvarez-Garcı´a J, Del Rı´o-Rama MC. Spatial Economic Con- vergence and Public Expenditure in Ecuador. Symmetry. 2019; 11(2) 130: 1–18. 126. Richiardi L, Pizzi C, Pearce N. Commentary: Representativeness is usually not necessary and often should be avoided. International Journal of Epidemiology. 2013; 42: 1018–1022. https://doi.org/10. 1093/ije/dyt103 PMID: 24062290 127. Rothman KJ, Gallacher JEJ, Hatch EE. Why representativeness should be avoided. International Journal of Epidemiology. 2013; 42: 1012–1014. https://doi.org/10.1093/ije/dys223 PMID: 24062287 128. Pelinescu E. The impact of human capital on economic growth. Procedia Economics and Finance. 2015; 22: 184–190. 129. Sakdiyakorn M, Golubovskaya M, Solnet D. Understanding Generation Z through collective con- sciousness: Impacts for hospitality work and employment. International Journal of Hospitality Manage- ment. 2021; 94: 1–13. 130. Domı´nguez R, Caria S. Ecuador en la trampa de la renta media. Revista Problemas del Desarrollo. 2016; 187(47): 89–112. 131. Aguilar-Gordo´n FR. Fundamento, evolucio´n, nodos crı´ticos y desafı´os de la educacio´ n ecuatoriana actual. Actualidades Investigativas en Educacio´n. 2019; 19: 1–31.

132. Murillo FJ, Martı´nez-Garrido C. Segregacio´n escolar por nivel socioecono´mico en Ecuador y sus pro- vincias. Revista Cientı´fica RUNAE. 2017; 2: 31–50. 133. Cruces G, Garcı´a C, Gasparini L. Inequality in Education Evidence for Latin America. Working Paper No. 2011/93. Helsinki: UNU World Institute for Development Economics Research (UNU-WIDER); 2011. PLOS ONE Education as a dimension of Human development PLOS ONE | https://doi.org/10.1371/journal.pone.0270932 July 8, 2022 27 / 27