The dynamics of Peruvians who do not study or work: who they are, how they are doing and how they have changed

JOSÉ A. TAVERA

Pontificia Universidad Católica del Perú, Lima

[email protected]

TILSA ORÉ

Stony Brook University, Nueva York

[email protected]

RAMIRO MÁLAGA

Stony Brook University, Nueva York

[email protected]

Abstract. We analyze the dynamics of the Peruvian NEET population during the last two decades using data from the Peruvian National Household Surveys. We identify the NEET population and its characteristics, classifying it by intensity. We find that the NEET population is primarily urban, made up of women and individuals who have just finished high school. Additionally, we find that a large proportion of women in the NEET population are willing to work. Finally, we observe that the proportion of NEET among the young population is declining over time.

Keywords: Peru; youth unemployment; out-of-school youth; NEET.

Acronyms

APROLAB Support for Professional Training for Employment Integration (Apoyo a la Formación Profesional para la Inserción Laboral, also known as Capacítate Perú)

CAPLAB Labor Training and Development (Capacitación Laboral y Desarrollo)

ENAHO National Household Survey (Encuesta Nacional de Hogares)

ENIGH National Survey on Household Income and Expenses (Encuesta Nacional de Ingresos y Gastos de los Hogares), Mexico

ENOE National Survey on Occupation and Employment (Encuesta Nacional de Ocupación y Empleo), Mexico

ETET School-to-Work Transition Survey (Encuesta sobre la Transición de la Escuela al Trabajo)

Eurofound European Foundation for the Improvement of Living and Working Conditions

INEI National Institute of Statistics and Information (Instituto Nacional de Estadística e Informática)

MIMDES Ministry for Women and Social Development

MTPE Ministry of Labor and Promotion of Employment.

NEET Youth population not in employment, education or training

NiNi Youths that neither work nor study (Jóvenes que ni estudian ni trabajan)

PEEL Labor Statistics and Studies Program (Programa de Estadística y Estudios Laborales)

SENEP National Employment Service (Servicio Nacional de Empleo)

SOVIO Vocational Guidance and Occupational Information Service (Servicio de Orientación Vocacional y de Información Ocupacional)

1. Introduction

In the public policy arena, the youth employment situation has never been far from the agenda of the government agencies tasked with promoting employment. Among other reasons, it is important as a key stage in the transition to employment. An active and educated youth population will be reflected in a highly productive adult workforce further down the line. Conversely, inactive youths face difficulties in completing the educational stage and entering the labor market.

In Peru, recent literature indicates that, as of 2012, 17.94% of urban youths were NEET (youths aged 15-29 that do not study, work, or participate in any kind of vocational training) and that this group was largely composed of women (Málaga, Oré & Tavera, 2014).1 NEETs are heterogeneous, differing not only in terms of age but also access to educational and employment opportunities and especially the desire to work. Factors that contribute to the risks of becoming part of the NEET group include low level of education, severe disability, large family, and, in particular, lack of financial assistance from family or friends. NEET youths are largely concentrated among middle-income families.

The National Institute of Statistics and Informatics (Instituto Nacional de Estadística e Informática, INEI, 2013) provides a brief statistical analysis of the NEET population in Peru based on sample information from household surveys, but does not discuss its implications. As far as we are aware, there are no existing studies that exhaustively analyze NEET composition in Peru over time, or which performs detailed analysis using census information to identify the geographical and sociodemographic distribution of this group with precision. The study most similar to ours in terms of methodology or data analysis is that by Gómez and Campos (2011) for the case of Mexico; however, our research differs since it includes a typology analysis by NEET intensity, which allows us to better identify the different dimensions of this problematic.

In this study, we identify, characterize, and analyze the NEET population and its evolution over the last two decades. To this end, we use information from census data (available for 1993 and 2007; INEI, 1993, 2007) and from the National Household Survey (Encuesta Nacional de Hogares, ENAHO) for the last two decades (INEI, 1997-2003, 2004-2013). The census information allows us to geographically locate the NEETs and precisely identify their main sociodemographic characteristics, while the information taken from the surveys enables an examination of this population’s evolution and the changes it has undergone. In addition, we classify and analyze the evolution of the NEET population by intensity level (NEET Type 1: conventionally unemployed youths; NEET Type 2: out-of-work youths with a desire to work, and; NEET Type 3: disengaged/unmotivated out-of-work youths with no desire to work).

The results of the analysis show that not only do females account for the largest proportion of the NEET population, but they are also the fastest-growing group. The NEET rates are especially high among populations of 17-18 year olds with exactly 11 years of education (complete secondary); this may be symptomatic of a lack of vocational guidance activities available for youths that finish the basic education stage. It can also be seen that the NEET Type 2 population (chiefly made up of females) gradually declines over the years, while the NEET Type 3 population (hard core) increases.

Following this introduction, the second section of this paper presents the relevant definitions on which our analysis is based; the third describes the methodology and the data; the fourth presents the census and sample statistical analysis (based on the Peruvian household surveys); the fifth outlines the results and presents the policy diagnosis and implications; and the fifth sets out the conclusions.

2. Definitions and conceptual framework

2.1 Youths not in employment, education or training

2.1.1 Background

The identification of the problematic of youths not in employment, education, or training (NEET) goes back to the 1980 and 1990s, when countries such as the United Kingdom began to show considerable interest in analyzing this population group. At present, there is no internationally accepted definition of NEET with respect to age, with ranges varying between 15-24 and 15-34 (European Foundation for the Improvement of Living and Working Conditions, Eurofound, 2012).

The United Kingdom’s Office for National Statistics defines a NEET individual as one aged between 16-24 who is not in education, employment, or training. Those who do not study or participate in training programs are understood to be persons who are not engaged in any form of work-based learning, are neither enrolled in nor continually attend education courses, are not waiting for a new cycle of study to begin, and do not attend vocational education courses (courses that lead to technical or professional careers).

For the Japanese case, Genda (2007) defines NEET as youths aged between 15 and 34 who are single (unmarried). The definition includes this civil status to take into account the possibility that a spouse may stop working following a joint decision made by the couple, or simply due to the provision of financial support by the other spouse.

Meanwhile, for the case of Mexico, Gómez and Campos (2011) analyze the youth population that neither work nor study, which they define as a group of individuals aged 15 to 20 years old.

In the Hispanic world, the term used for youths that do not work or study, and who usually fall within similar age ranges, is NiNi. This term is generally comparable to its English-language equivalent, NEET. One difference in how the two terms are defined concerns the inclusion by the English-language term of youths who are not engaged in training, alongside those who do not work or study. The Spanish-language definition does not specifically include this subgroup; this is explained by the limited or non-existence of public policies related to training in Spanish-speaking countries, Peru among them. However, in this paper we consider the term NEET to be interchangeable with its Spanish-language equivalent, NiNi.

2.1.2 Definition

Taking into account the background information provided, the definition of NEET that we use for the purposes of this study is the population aged 15-29 that does not work (is unemployed or inactive), does not study (is not classed as a student), and, where any form or training exists, does not participate in it.

No distinction is made between married and unmarried youths in this definition. It should be noted that our definition differs from that of the INEI in terms of the age range of the population analyzed; we selected our range so that the results of this study are comparable to some degree with those of other studies, such as that of Gómez and Campos (2011) for the Mexican case.

Moreover, our classification encompasses all individuals who do not work - that is, all of those who have not received remuneration for at least one hour of work during the week prior to the survey (per the definition of the Ministry of Labor and Promotion of Employment, MTPE). Thus, youths who carry out work within the home, whether domestic chores or caring for dependents (children or the elderly); those who contribute to other productive activities or to family businesses on an unpaid basis; and those engaged in activities such as art, music, or sports, are included as youths who do not work.

Youths considered as “non-NEET” are defined as those who work for at least one hour per week and/or are students and/or attend a training program. In this study, the analysis variable we use is the percentage of NEETs constructed on the basis of the ratio of NEET youths to the overall youth population.

It must be noted that NEET youths are not to be considered idle or unproductive, for the following reasons: a) the category of NEET includes all youths who do not study and who do not participate in paid work; as such, it includes many youths who possibly do not study because they are not able to do so, probably due to economic or other barriers. Moreover, it includes all youths who may be engaged in non-remunerated work, such as domestic chores or unpaid family activities (Peña, 2010); b) NEET youths, especially young adults (aged 25-29) may not work or study due to being overqualified or because of a sharp reduction in labor demand. This phenomenon can be observed in countries like Spain, where many degree-educated youths do not work due to a lack of job opportunities or do not study because the associated expenses outweigh the prospective benefits (El País, 2013); c) finally, certain psychological factors may exert an influence on youths, making it difficult for them to participate in the education system and/or the labor market. A lengthy spell of unemployment or alternating spells in and out of work can damage the self-esteem of youths, prompting demotivation and disengagement from the social environment. On the other hand, more personal factors such as a lack of social skills, isolation, or depression may also be behind non-participation in employment, education, or training. This is very often the case in Japan (Rahman, 2006).

Thus, within the NEET group, it is important to single out one subgroup in particular: youths who not only not do not work or study, but do not wish to do so - that is, those who belong to the NEET hard core and face more severe problems of disengagement and vulnerability.

This distinction is particularly important in countries like Peru, where the NEET group is found to be mainly female. Many youths may be engaged in full-time housekeeping or childcare as the product of an optimal decision regarding family economics or a lack of alternatives for the care of their children. Thus, there are many NEET youths who, despite belonging to this group, are not part of the above-mentioned hard core.

2.1.3 Types of NEET: classification criteria

The NEET population is anything but homogeneous; it is not possible to consider NEET youths as a single group facing the same problems. Thus, in the literature, NEET youths are usually sorted into subgroups. Eurofound (2012) identifies six NEET subgroups: the conventionally unemployed; the unavailable (those with family responsibilities, disabilities, or illness); the disengaged and discouraged (who neither work nor study, have given up on their attempts to find work, and are neither constrained nor incapable of doing so); opportunity-seekers, who wish to work but are waiting for an opportunity that meets their expectations; and voluntary NEETs (who may be travelers, engaged in artistic activities, or engaged in self-directed learning).

Moreover, it is possible to distinguish vulnerable NEETs (those at risk of being marginalized due to insufficient education and social capital) from non-vulnerable NEETs (youths who are not at risk of marginalization because they have an acceptable level of education and do not belong to social minorities).

In this study, we base our classification of NEETs on Genda (2007), which is associated with the level of intensity of NEET status.2 Thus, we subdivide the NEET group into three types:

a)NEET Type 1: youths who do not work or study and are not in training, but who are actively seeking jobs; conventionally unemployed youths.

b)NEET Type 2: youths who do not work or study and are not actively looking for jobs, but do wish to work.

c)NEET Type 3: youths who do not work or study and do not wish to work; inactive and/or disengaged youths.3

2.2 What is known about NEET youths in Peru?

The existing literature on the youth population in Peru addresses general topics such as employment and youth unemployment, and public policy suggestions for this population (Saavedra & Chacaltana, 2001; Ñopo, Robles & Saavedra, 2002; Ministerio de Trabajo y de Promoción del Empleo, MTPE 2004; Chacaltana, 2006; Jaramillo, Galdo & Montalva, 2009; Organización Internacional del Trabajo, OIT, 2007, 2010, 2013a, 2013b; Chacaltana & Ruiz, 2012). Moreover, some studies touch on the problematic of NEETs, but they do not cover it in any depth (Chacaltana & Ruiz, 2012; OIT, 2013a, 2013b).

A more concrete effort is that by INEI (2013), which presents statistical information on the NEET population; however, it lacks an in-depth analysis of the problematic of the group. According to the INEI, as of 2011, 18.7% of the Peruvian youth population (aged between 14-30) is NEET, with a higher proportion in urban areas than in rural ones (20% and 14.6%, respectively). Moreover, women account for a larger share of the NEET group than men. In order of geographical region, the coast has the highest percentage of NEETs, followed by the Amazonian lowlands and then the highlands.

In a previous study carried out on the basis of the School-to-Work Transition Survey (Encuesta sobre la Transición de la Escuela al Trabajo, [INEI, 2012a]) for the urban population, Málaga, Oré and Tavera (2016), we found that 17.94% of Peruvian urban youths (aged between 15-21) are NEET, and that this group is primarily composed of women (74%). This high percentage may be explained by women’s contribution to the household economy through household chores and the care of dependent family members.

Moreover, we show that the NEET group is rather heterogeneous, and identify some factors that could increase the likelihood of belonging to the group, such as low level of education, severe disability, large family, and, in particular, a family or friends who provide financial assistance to the NEET individual. Finally, the poorest (who have to work to survive) and the wealthiest (who, because of their higher level of education, are subject to a higher opportunity cost of leisure) are less affected by the NEET phenomenon.

The study whose analysis of the NEET population most closely resembles the present analysis is Gómez & Campos (2011), for Mexico. These authors also analyze the youth population aged between 15-29, and use census information from 1990, 2000, and 2010. In addition, they use information from Mexico’s National Survey on Household Income and Expenses (Encuesta Nacional de Ingresos y Gastos de los Hogares, ENIGH) for the period 1992-2010, and from the National Survey on Occupation and Employment (Encuesta Nacional de Ocupación y Empleo de México, ENOE) for the period 2005-2010.

Gómez and Campos (2011) find that almost one third - 28.9% - of the Mexican youth population was NEET as of 2010, but that this proportion has decreased over the last decade. As with the Peruvian case, females make up the largest proportion of the NEET population in Mexico; however, this proportion has been trending downwards. The decrease in the percentage of women in the NEET group is associated with increases in both labor supply and in school attendance by the female population. Education is a factor that limits the percentage of males in the NEET population, while the decision to engage in domestic chores accounts for the higher proportion of females in the group.

3. Database and Methodology

In this study, we performed a descriptive analysis of NEETs using the census and sample information available for Peru: from the two most recent population censuses (INEI, 1993, 2007). On the basis of this information, we divided the NEET population by age ranges, sex, years of education, and, geographical environment and spatial distribution. In turn, the information from ENAHO for the years 1997-2003 and 2004-2013 served to describe the temporal and typological trends of NEETs (INEI, 1997-2003, 2004-2013).

3.1 Description of the databases

The census information corresponds to Peru’s 9th and 11th (the most recent) population censuses,4 and enables a descriptive analysis and identification of the NEET population based on the stated variables. Carrying out such an analysis using the ENAHO sample information would not be feasible due to the sample’s inherent limitations.

The 9th Population Census, conducted on July 11, 1993 (INEI, 1993) recorded 22,639,443 inhabitants in Peru, while the 11th Population Census, carried out from October 21 to November 4, 2007 (INEI, 2007), counted 28,220,764 inhabitants. The 14-year lapse between the two censuses allows a comparison of the changes in the NEET population of practically two different generations of youths, since those aged 15 in 1993 will have been 29 in 2007.

The sample information taken from ENAHO considers two periods, with a different sample design having been used for each: one for 1997-2003 and other from 2004 to date. The survey with the second sample design has been applied nationwide on a continual basis from May 2003, and features rural, urban, and departmental levels of inference.5 The sample size varies from 21 thousand to 26 thousand private dwellings (corresponding to the periods 2004 and 2012, respectively), of which between 15,500,000 and 18,900,000 correspond to non-panel household samples, and between 6,500,000 and 7,500,000 to the panel sample.

The ENAHO information is more elaborate than that of the censuses, containing questions on employment status and education, which allows identification of types of NEET that cannot be discerned in the census.

3.2 Methodology

In this study, we conduct our analysis using a descriptive statistical method. To this end, we use two sources of information: census and sampling. The census information allows us to compare two generations of youths and go into greater depth in the breakdown by age, sex, marital status, geographical environment, years of education, and even geographical distribution. The sample information taken from the ENAHOs uses the MTPE’s methodology to calculate the employment situation, and allows us to review the evolution of NEET youths and changes over time. It is important to note that the respective percentages of NEET youths taken from the ENAHOs and the censuses are not directly comparable given the differences in the design of the respective questionnaires. In the censuses, the questions on employment status and years of education are more basic than in the ENAHOs. For this, among other reasons, individuals classed in the censuses as unemployed may be considered to be employed in the ENAHOs, which suggests that the percentage of NEET youths may be overestimated in the former.

The analysis conducted on the basis of the ENAHOs corresponds to information available for the years 1997-2003 and 2004-2013, unlike the INEI (2013) paper, which studies the years 2004 to 2011. Much more important, however, is that our analysis and figures differ from those of INEI (2013), in terms of the age range we deem to constitute the youth population. INEI (2013) considers youths aged between 14-30 as young, while the age range we use in our study is 15-29, as in Gómez and Campos (2011).

In addition, we analyze NEET youths in a disaggregated manner based on the aforementioned three types - that is, by level of intensity.

4. Spatial and temporal analysis of the NEET population

4.1 Analysis of the NEET population using census information

According to the 2007 census, the Peruvian population rose to 28.2 million inhabitants, 24.3% higher than was recorded 14 years earlier in the 1993 census. The Peruvian youth population - those aged between 15-29 - increased to 7.5 million people by 2007, 20% greater than the figure recorded in 1993. As a proportion of the overall population, youths accounted for 27.5% in 2007, one percentage point less than in 1993.

As of 2007, 26% of the youth population was classified as NEET, nine percentage points lower the 1993 figure (see Table 1). This represents a significant increase in terms of the employment transition of youths. At the start of the 1990s, the Peruvian economy was recovering from a severe crisis, while in the second half of the 2000s the country experienced a period of economic growth.

In both censuses, more than 70% of NEETs were females (see Table 2), with a slight increase (two percentage points) from 1993 to 2007.

Table 1
NEET and non-NEET population, 1993 and 2007

	1993 Census		2007 Census
	Number	%	Number	%
NEET	2,194,366	34.9	1,959,336	25.9
Non-NEET	4,101,905	65.1	5,594,868	74.1
Total	6,296,271	100.0	7,554,204	100.0

Source: INEI (1993, 2007); compiled by authors.

Table 2
NEET population by sex, 1993 and 2007

	1993 Census		2007 Census
	Number	%	Number	%
Women	1,579,816	72.0	1,451,884	74.1
Men	614,550	28.0	507,452	25.9
Total NEET	2,194,366	100.0	1,959,336	100.0

Source: INEI (1993, 2007); compiled by authors.

In terms of urban versus rural environments, Table 3 shows a significant decrease in the population of urban NEETs, compared with a slight reduction of their counterparts in rural areas. The most significant reduction, of close to 12 percentage points, applies to women in the urban environment, followed by urban-based males and then by rural-dwelling females.

Table 3
NEET and non-NEET population by environment and sex, 1993 and 2007

	Urban environment				Rural environment
	Women	Men	Total		Women	Men	Total
	Women	Men	%	N°	Women	Men	%	N°
1993 Census
NEET (%)	44.4	22.0	33.5	1,569,831	64.3	14.0	38.6	624,535
Non-NEET (%)	55.6	78.0	66.5	3,109,414	35.7	86.0	61.4	992,491
Total	2,410,501	2,268,744	100.0	4,679,245	791,690	825,336	100.0	1,617,026
2007 Census
NEET (%)	32.9	13.1	23.2	1,372,863	58.5	14.7	35.7	586,473
Non-NEET (%)	67.1	86.9	76.8	4,538,264	41.5	85.3	64.3	1,056,604
Total	3,011,038	2,900,089	100.0	5,911,127	786,414	856,663	100.0	1,643,077

Source: INEI (1993, 2007); compiled by authors.

In the case of males in the rural environment, the ratio of NEETs to the total youth population remained similar, and even increased slightly, between 1993 and 2007. In the case of women, on the other hand, this ratio declined sharply. However, the ratio of female NEETs in the rural environment was greater than that recorded in the urban environment at both times (1993 and 2007); it is noteworthy that in the case of females, the difference between NEET ratios in rural versus urban areas had widened by 2007. Tables A1 to A8 in the Annex provide more information about the NEET population by age group, sex, marital status, and years of education.

Figures 1 and 2 show the percentage of NEET youths among all youths of their respective sex; the information is broken down by age, sex, and whether or not they have a partner6 for the years 1993 and 2007, respectively. In the case of females, the NEET percentage is seen to increase steadily with age, while in the case of males it peaks at age 18. Analysis of youths with a partner shows that the percentage of male NEETs out of young males overall remains at very low levels, never exceeding 7% despite a slight upward trend; the proportion of female NEETs in a relationship is also increasing: in 1993, female NEET 29-year-olds accounted for 50% of all women of that age, while female NEETs without a partner made up only 10% (60%-50% in Figure 1) of women aged 29. Thus, being a female increases the likelihood of being a NEET in the case of those with a partner, and this pattern can be observed in both 1993 and 2007.

Figure 1
NEET population by age, 1993
(as a percentage of youths of the same sex)

Source: INEI (1993); compiled by authors.

Figure 2
NEET population by age, 2007
(as a percentage of youths of the same sex)

Source: INEI (2007); compiled by authors.

Figures 3 and 4 show the percentage of NEET youths out of the overall population of youths of their respective age and geographical environment (urban and rural), differentiated by sex, for 1993 and 2007. It is notable that in 1993 the percentage of NEET females was greater in the rural than in the urban environment, while the reverse was the case for males. In 2007, the percentage of female NEETs remained higher than that of their rural counterparts, while for males the percentages for both environments was similar.

Figure 3
NEET population by environment and age, 1993
(as a percentage of youths of the same sex and environment)

Source: INEI (1993); compiled by authors.

Figure 4
NEET population by environment and age, 2007
(as a percentage of youths of the same sex and environment)

Source: INEI (2007); compiled by authors.

Figures 5 and 6 show that the NEET percentage fell markedly for females and males with ten years of education (incomplete secondary), but was higher among those with eleven years of education (complete education).

Figure 5
NEET population by years of education, 1993
(as a percentage of youths of the same sex)

Source: INEI (1993); compiled by authors.

Figure 6
NEET population by years of education, 2007
(as a percentage of youths of the same sex)

Source: INEI (2007); compiled by authors.

Overall, the downward trend in the percentage of NEETs with years of education is more pronounced in 2007, although for that year a slight increase in the ratio of NEETs among youths with incomplete and complete education (14 to 16 years of education) can be seen; also observable is a lower ratio of NEETs among youths with incomplete secondary (ten years of education), soon after leaving school - possibly to enter the labor market directly.

Figures 5 and 6, for 1993 and 2007, respectively, show a clear peak in the NEET percentage for youths with complete secondary education, and then, in the case of 2007, an upturn for youths with 16 years of education (with complete higher non-university education or incomplete university education).

Given these peaks, it is important to analyze the group that has completed secondary education. In 1993, 26.5% of all NEET youths had completed exactly 11 years of education (that is, a complete basic education). This proportion increased to 30.5% in 2007. Moreover, among those youths with exactly 11 years of education, the percentage of NEETs declined from 40.1% to 29.2% between 1993 and 2007. Although this decrease is positive, the fact that almost 30% of youths with complete secondary education are NEETs is still a cause for concern, as is the fact that of this group, it is precisely those who finish their basic education who remain inactive and do not return to their studies.

The high incidence of youths with complete basic education in the NEET group is indicative of a problem that is vocational in character. Having finished their basic education, these youths do not work and likewise fail to go on to higher education. This may be because they have trouble in identifying their professional interests and, thus, in deciding what type of work-oriented education or what type of job to pursue.

Figures 5 and 6 also show that the ratios of NEETs are higher in the case of young women with incomplete basic education - that is, females who dropped out of school. This segment of the population is sizable; close to half of NEET youths have not completed their education. School dropout is an important issue to analyze; indeed, Gómez and Campos (2011) find that the school dropout rate is a significant factor in explaining the NEET problem in Mexico.

For the Peruvian case and using the census information, it was found that those who dropped out of basic education represented 39.9% of all youths in 2007. This is even more pronounced within the NEET group: school dropouts represent 45.5% of the total, and 47.9% and 38.2% of the female and male NEET populations, respectively. While high, these proportions of youth dropouts are somewhat lower for 2007 than for 1993, when 52.8% of all youths and 53.9% of NEET youths had dropped out. Breaking down the NEET population by sex, it is seen that 58.4% of female NEETs and 43% of male NEETs were dropouts in 1993.

Table 4 shows the ratio of NEETs out of the youth population that obtained a certain level of basic education, but dropped out (did not complete their studies), for both census periods. Around 3 million youths (who represent 27% and 23% of the total school dropout population in 1993 and 2007, respectively) started but did not finish their basic education; almost half of this group were females. Between 1993 and 2007, the ratio of NEETs among school dropouts fell from 34.2% to 29.5%; despite this decrease, it is concerning that almost a third of youths who dropped out are not engaged in any form of paid employment. Considering that almost half of NEET youths have not completed their basic education, school dropout also has a significant effect on the likelihood of becoming a NEET.

Table 4
NEET population by completed years of education and sex, 1993 and 2007
(in percentages)

Completed years of education	Total			Females		Males
Completed years of education	Youths	NEET	NEETs with partners	NEET	NEETs with partners	NEET	NEETs with partners
1993 Census
0(1)	0.4	0.5	0.7	0.6	0.7	0.3	0.2
1-6	25.6	32.5	40.9	37.4	42.2	20.7	29.2
7-10	27.3	21.4	24.6	21.1	24.4	22.4	26.1
11	22.1	26.5	20.9	23.4	20.1	34.0	27.6
12 and over	24.7	19.1	13.0	17.6	12.6	22.7	16.9
Total	100.0	100.0	100.0	100.0	100.0	100.0	100.0
Total	5,928,572	1,986,243	898,376	1,409,831	808,959	576,412	89,417
2007 Census
0	1.9	4.6	4.2	4.8	4.4	3.9	2.8
1-6	15.0	25.5	29.2	28.1	29.9	18.0	23.8
7-10	24.9	19.9	21.7	19.8	21.7	20.2	21.6
11	27.1	30.5	27.3	28.1	26.6	37.3	33.1
12 and over	31.1	19.5	17.6	19.1	17.4	20.5	18.7
Total	100.0	100.0	100.0	100.0	100.0	100.0	100.0
Total	7,554,204	1,959,336	1,090,310	1,451,884	958,153	507,452	132,157

Note: (1) 104,399 youths did not answer this question, 1.73% of the youth population (none of these were recorded as having 0 years of education; this explains the discrepancy as compared with the 2007 data).
Source: INEI (1993, 2007); compiled by authors.

By sex, it can be seen that of the dropouts, the ratio of female NEETs is more than triple that of their male counterparts. Moreover, of the group of NEET dropouts, almost one-third of the female constituents have a partner, compared with less than a third of males. The impact of school dropout on women is found to be greater, considering also that this places a further restriction on their entry into the labor market and leaves them subordinated to the employment decisions of their spouses.

Given the importance of education, we analyze the group of youths with at least one year of university education separately. As of 2007, 31.1% of youths had completed 12 or more years of education. Of the group identified as NEET, 19.5% of youths possess this level of education; when differentiated by sex, 20.5% of male NEETs and 19.1% of females have completed at least one year of higher education. As shown, the ratio of female NEETs with higher education is lower than males.

In 1993, only 24.7% of youths had completed at least one year of higher education. Meanwhile, of the NEET group, 19.1% finished at least 12 years of education, and, significantly, 22.7% of male NEETs and 17.6% of females had completed some form of higher education. The ratio of NEETs in the group of youths with some higher education fell by nearly ten percentage points between 1993 and 2007, from 25.9% to 16.3%

Both sexes experienced this substantial improvement, with a near-10% decline in the ratio recorded for males and females between the time periods, to 9.2% and 22.8%, respectively. It is important to note that, in 2007, the majority of NEET women who had completed higher education had a partner (60.1%), compared with the 41.1% recorded in 1993. This may be explained by the greater employment integration of higher-educated single females between the two periods evaluated, which would mean that it would be attached women who retain their NEET status.

4.1.1 Spatial distribution of the NEET population

For 2007, Table 5 shows the distribution of the population by departments and the ratios of NEETs for each one out of the total youth populations; moreover, it breaks down this population by sex and by whether or not they have a partner. It can be seen that outside of Lima, where the figure is around 20%, the ratio of NEETs is more than 23% in 22 departments and above 30% in nine of them, of which Cajamarca and Piura stand out for their proportions in excess of 35%.

Table 5
Ratio of NEET population by department, with partner, by sex, 2007

	Total NEET population		Male NEETs			Female NEETs
Department	No.	Percentage of youth population	No.	Percentage of male youth population	Attached (% of male youth population)	No.	Percentage of female youth population	Attached (% of female youth population)
Amazonas	33,239	34.15	7,109	14.23	4.72	26,130	52.30	39.57
Ancash	82,898	30.06	20,811	15.00	4.22	62,087	44.76	28.88
Apurímac	27,830	28.94	7,266	15.17	6.45	20,564	42.94	31.33
Arequipa	66,120	20.37	19,484	12.14	2.73	46,636	29.07	18.35
Ayacucho	43,159	27.56	11,830	14.96	5.23	31,329	39.61	27.24
Cajamarca	129,735	35.23	26,277	14.31	4.70	103,458	56.34	35.25
Callao	58,079	23.99	16,557	13.93	3.12	41,522	34.92	21.80
Cusco	70,501	23.04	18,436	12.06	4.11	52,065	34.06	24.19
Huancavelica	34,520	30.67	9,061	16.28	6.21	25,459	45.73	29.10
Huánuco	64,088	31.82	13,439	13.23	3.50	50,649	49.85	32.40
Ica	46,008	23.25	10,470	10.59	2.42	35,538	35.96	24.56
Junín	83,697	24.72	19,545	11.49	2.80	64,152	37.71	26.17
La Libertad	128,497	28.99	29,142	13.24	3.18	99,355	45.12	28.43
Lambayeque	87,792	29.17	20,609	14.10	2.93	67,183	45.98	27.33
Lima.	491,189	20.32	138,760	11.68	2.45	352,429	29.67	18.43
Loreto	82,434	32.98	23,190	18.43	5.49	59,244	47.09	33.78
Madre de Dios	8,339	24.05	2,043	11.30	3.85	6,296	34.82	29.79
Moquegua	10,641	24.43	3,605	16.35	4.24	7,036	31.91	21.89
Pasco	23,563	28.73	5,898	14.08	3.58	17,665	42.16	29.14
Piura	157,356	35.06	39,452	17.68	4.33	117,904	52.84	33.48
Puno	93,705	27.00	31,664	18.22	5.83	62,041	35.69	22.63
San Martín	60,755	29.93	11,764	11.04	3.16	48,991	45.99	39.38
Tacna	18,410	21.56	6,300	14.89	3.45	12,110	28.63	18.12
Tumbes	18,818	32.67	5,152	17.34	3.97	13,666	45.99	36.15
Ucayali	37,963	30.90	9,588	15.61	5.43	28,375	46.20	33.98
Total	1,959,336	25.94	507,452	13.51	3.52	1,451,884	38.65	25.23

Source: INEI (2007); compiled by authors.

The percentage of male NEET youths out of the entire male youth population is below 20% across all departments, with the highest percentages in Loreto (18.4%) and Puno (18.2%). On average, only 3.5% of young men are NEETs with partners, with Apurímac and Huancavelica the departments with the highest NEET percentages, both at more than 6%. The lowest ratios of male NEETs are found in Ica (10.6%), San Martín (11%), Madre de Dios (11.3%), Junín (11.5%), Lima (11.7%), and Cusco and Arequipa (both 12.1%).

In the case of females, with the exception of Tacna (28.6%), Arequipa (29.1%) and Lima (29.6%), the ratio of NEETs among young women exceeds 30% in all cases. The highest female NEET ratio is recorded in the department of Cajamarca (56.3 %), followed by Piura (52.8%), Amazonas (52.3%), and Huánuco (49.9%). Amazonas also has the highest proportion of female NEETs with partners (39.6%). Overall, according to the 2007 census, 25.2% of NEET women across all departments have a partner. The geographical differences in the prevalence of NEETs among the youth population for the two census periods, 1993 and 2007, is set out in figures 7 and 8, which illustrate the information in departmental maps, where the darkest shades denote the largest percentage of NEETs in the youth population, by sex. Based on the data from the two censuses, it is evident that NEETs are more prevalent in the female population than the male.

Figure 7
NEET population by sex, 1993 (as a percentage of youths of the same sex)

Figure 8
NEET population by sex, 2007 (as a percentage of youths of the same sex)

The maps in figures 7 and 8 also show that between 1993 and 2007, there was a decline in the percentage of NEET youths, both for the case of men and for women. Likewise, in both censuses it can be seen that the NEET problem was more pronounced in the coastal and jungle departments for males, and in the north of the country for women. The geographical dimension of the NEET population must be taken into account in the policies aimed at this group.

4.2 Evolution of the NEET population: analysis using sampling information (ENAHO)

In the last subsection we presented specific figures for the NEET population, by sex and environment (rural and urban), years of education, and geographical location. In this subsection, we use information from ENAHOs (INEI, 1997-2003, 2004-2013); and, unlike INEI (2013), we add a classification of NEET types and analyze the evolution of each. Moreover, the Annex (tables A9 and A10) provides information on the same figures pertaining to the NEET population, calculated on the basis of ENAHO information from 1997 to 2003. We do not present an analysis for the period 1997-2013, mainly because of the aforementioned change in methodology in 2004, which could cause discrepancies in the variables.

It should be noted that we find differences in NEET ratios from the 2007 census compared with those calculated on the basis of ENAHO sample information (the 2007 ratio of NEETs according to the census is 25.9%, while according to the annual ENAHO database for 2007, it is 17.6%).7 This is because of differences in the designs of the questionnaires, which tend to be more simple and limited in the censuses and more extensive and detailed in the surveys. This gives rise to differences in the construction of the variables and, thus, to different results.

Table 6 shows the figures obtained from the 2004-2013 ENAHOs on the youth population, NEET population, proportions by sex, and ratios of the female and male NEET population. On average, taking this source as a reference, 64.3% of NEET youths are females, and the figure was at its lowest level (62.3%) in 2013.

Table 6
Evolution of the NEET population, overall NEET ratio and by sex, 2004-2013

Year	Total youths	NEET youths
Year	Total youths	NEET youths	NEET females	NEET (% of youth population)	NEET males (%)(1)	NEET females (%)(1)
2004	7,568,236	1,548,441	64.3	20.5	14.3	26.9
2005	7,631,722	1,695,499	63.1	22.2	16.1	28.6
2006	7,639,582	1,435,756	66.9	18.8	12.3	25.5
2007	7,648,941	1,343,334	67.8	17.6	11.3	23.9
2008	7,792,925	1,341,472	68.0	17.2	10.9	23.6
2009	7,849,329	1,304,841	66.2	16.6	11.1	22.2
2010	7,771,632	1,229,113	63.9	15.8	11.2	20.6
2011	7,818,097	1,276,262	65.5	16.3	11.1	21.7
2012	8,260,753	1,341,236	62.8	16.2	11.8	20.9
2013	8,298,178	1,428,679	62.3	17.2	12.6	22.1

Note: (1) Percentage of NEET youths out of the entire youth population of the same sex.
Source: INEI (2004, 2013); compiled by authors.

In the figures for Table 6, it can be seen that the overall NEET ratio peaked in 2005 (22.2%) before falling steadily and bottoming out in 2010 (15.8%), then climbing back up to 17.2% in 2013. The downward trend can clearly be seen in the ratios of male and female NEETs, most markedly in the case of females. The ratio of female NEETs over the ten years analyzed fell by more than four percentage points, while that of their male counterparts dropped by less than two percentage points.

The evolution of these ratios can be seen more clearly in Figure 9. The ratio of NEETs went down slightly over the period of evaluation, with the largest decrease occurring between 2005 and 2007. As is to be expected, the ratio of NEET women is higher than that of men, but displayed a marked downward trend through to 2010. For both sexes, there was an upturn in the ratio in 2013.

Figure 9
NEET population by age, 2004-2013
(as a percentage of youths of the same sex)