metadata: authors: 0: author: Angel-Urdinola,Diego
1: author: Mayer Gukovas,Renata
count: World
docna: 0: docna: A skills-based human capital framework to
            understand the phenomenon of youth economic disengagement
docty: Policy Research Working Paper
abstracts: cdata!: This paper revisits traditional human
            capital models and proposes a new conceptual framework of
            human capital accumulation, anchored in skills development,
            to illustrate the phenomenon and implications of youth
            economic disengagement. In the framework, youth economic
            disengagement is defined as a state (temporary or permanent)
            where individuals stop accumulating human capital due to
            inadequate access and quality of opportunities for skills
            development through formal education and employment. Total
            economic disengagement is a rational choice that individuals
            make when (i) the formal education system and labor market
            do not contribute to build skills that are valued by the
            labor market, and (ii) the costs related to economic
            engagement (that is, studying and working) surpass its
            benefits. The phenomenon of economic disengagement has
            lifelong implications that not only constrain and restrain
            future earnings, but also undermine prospects for
            improvements in productivity and economic growth.
repnme: repnme: A skills-based human capital framework to
            understand the phenomenon of youth economic disengagement
display_title: A skills-based human capital
            framework to understand the phenomenon of youth economic disengagement
listing_relative_url: /research/2018/02/29610944/skills-based-human-capital-framework-understand-phenomenon-youth-economic-disengagement
topicv3: Education, Skills Development and Labor
            Market m1326135 1484,Labor Markets m1326488 855,Education m1327048 470,Gender and Skills m1327153 912,Human Capital Accumulation m1504139 2816
publishtoextweb_dt: 2018-02-20T00:00:00Z
no_of_pages: 23
author_keys: 0: author_key: 438716
1: author_key: 1241611
model_extractions: WPS8348 Policy Research Working Paper 8348 A Skills-Based Human Capital Framework to Understand the Phenomenon of Youth Economic Disengagement _Diego F. Angel-Urdinola Renata Mayer Gukovas_ Education Global Practice & Social Protection and Labor Global Practice February 2018
Policy Research Working Paper 8348

# **Abstract**

This paper revisits traditional human capital models and proposes a new conceptual framework of human capital accumulation, anchored in skills development, to illustrate the phenomenon and implications of youth economic disengagement. In the framework, youth economic disengagement is defined as a state (temporary or permanent) where individuals stop accumulating human capital due to inadequate access and quality of opportunities for skills development through formal education and employment.

Total economic disengagement is a rational choice that individuals make when (i) the formal education system and labor market do not contribute to build skills that are valued by the labor market, and (ii) the costs related to economic engagement (that is, studying and working) surpass its benefits. The phenomenon of economic disengagement has lifelong implications that not only constrain and restrain future earnings, but also undermine prospects for improvements in productivity and economic growth.

This paper is a product of the Education Global Practice and the Social Protection and Labor Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at dangelurdinola@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
A Skills-Based Human Capital Framework to Understand the Phenomenon of Youth Economic Disengagement Diego F. Angel-Urdinola and Renata Mayer Gukovas The World Bank<sup>1</sup> JEL Classification : I20, I25, J23, J24, J31

**Keywords** : Youth economic disengagement, human capital accumulation, skills development, wage determination, NEETs

**Corresponding Author:** Diego F. Angel-Urdinola (dangelurdinola@worldbank.org)

> 1 This paper was prepared as a background paper for the World Bank’s Brazil Skills and Jobs Program (P156683). The authors acknowledge technical support and strategic guidance from Truman Packard, Rita Almeida, Eduardo Rios-Nieto, and Mattias K. Lundberg. The authors also acknowledge valuable comments and contributions from participants during a seminar held at the World Bank in May 2017 as part the World Bank’s Human Development Learning Week.
# **I. Introduction**

There is a consensus in the literature that the process of human capital accumulation is a central determinant of economic growth (Acemoglu and Autor, 2012; Acemoglu, 2009; Goldin and Katz, 2007). Traditional human capital models build upon the assumption that an individual’s decision to invest in human capital is based on an examination of the net present value of the costs and benefits of such investments (Becker 1964, Mincer, 1974). In other words, Individuals invest in the development of their skills (i.e., pay to acquire skills and/or forgo earnings) to receive returns to the investments in subsequent periods (Veum, 1995). Individuals make most of their investments in skills when they are young. This feature occurs because forgone earnings are relatively low in early years and because the earlier investments are made, the more extended the period over which they can render returns (Ben-Porath, 1967 and Cunha and Heckman, 2007). As such, investment decisions made by individuals in their youth years are determinant and involve long-lasting consequences.

The processes and factors that determine human capital accumulation have been subject to recurrent study in the literature. While it remains complex to fully understand how human capital forms, there is a consensus that an individual’s abilities (innate or acquired) are the result of a series of factor inputs that constitute a human capital technology production function (Acemoglu and Autor, 2012; Acemoglu and Autor, 2010; Ben-Porath, 1967). While many attempts have been made to quantify and qualify such production function, there seems to be consensus in the literature that there are three main channels through which human capital forms: (i) home, especially for children below school-age, (ii) school, for school-aged children, and (iii) the labor market/on-thejob training, for individuals who make a transition from education into employment (Behrman et al., 2014; Keneneth et al, 2011; Acemoglu and Autor, 2012; Hanushek and Woessman, 2008; Veum 1995). In the light of this literature, the number of years of schooling and the number of years of employment experience have often been considered as the standard predictors of human capital endowments for individuals (Krueger and Lindahl, 2001; Barro, 2001; Barro and Sala-iMartin, 1995).<sup>2</sup>

> 2 Human capital has been often measured in the literature as the present value of the expected future labor incomes that could be generated over the lifetime of the people currently living, given their levels of educational attainment and experience (Jorgenson and Fraumeni, 1989, 1992a, 1992b).

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Youth economic disengagement has been traditionally understood as the phenomenon of having youth not in school and not in employment (i.e., not accumulating human capital), known as the NEET status (not in education, employment or training). The NEET represent a crisp representation of youth disengagement and a concern of policy makers who see in them a clear symptom of a population that undermines human capital accumulation potential – with significant economic and social exclusion repercussions (De Hoyos et al., 2013; Bynner and Parsons, 2002; Croxford and Raffe, 2000).

Some recent literature, however, has encountered nuisances to the classical wisdom of human capital accumulation and youth disengagement exposed above. Hanushek and Woesman (2008) and Hanuschek and Zhang (2009), for instance, argue that years of schooling is a poor proxy for human capital since it undermines both the quality of schooling received as well as the quality of the skills acquired. Also, while the conventional Mincerian wisdom expects wages to be an increasing concave function of employment experience, recent evidence indicates that some workers (compared to others with seemingly similar characteristics and controlling for the business cycle), are exposed to wage decreases as their employment experience increases due to churning characteristics of modern labor markets (Burdett et al., 2011). In summary, the emerging evidence indicates that access to education and employment, while necessary, is not a sufficient condition to assure human capital accumulation if they do not meet the essential quality requirements and if they do not contribute to build the individual’s skills set.

Based on this emerging evidence, this paper revisits traditional human capital models and proposes a conceptual framework of human capital accumulation, anchored on skills development, to understand youth economic disengagement. Economic disengagement is defined, beyond the NEET status, as a state (which could be temporary or permanent) where individuals stop accumulating human capital due to inadequate access and quality of opportunities for skills development and employment. Under these assumptions, the NEET population constitutes only the tip of the iceberg of a broader and far-reaching disengagement problem that affects a population of youth that was thought to be on the right track, and that is often ignored by statistics as well as policy makers.

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# **II. Conceptual Framework**

The conceptual framework presented in this section builds upon the previous literature on human capital under competitive markets (Becker 1964, Mincer, 1974). One individual achieves the optimal choice of human capital accumulation when the marginal benefits of investments in human capital equal the marginal costs of such investments. Marginal benefits of investments in human capital are expected to decrease as human capital increases, while the marginal costs are expected to increase. The market’s demand for human capital determines the returns of human capital investments, which are not uniform across all domains and skills (i.e., some activities are more skills-intensive than others) (Acemoglu and Autor, 2012). As markets are competitive, an increasing supply of human capital in the economy will tend to increase the relative output of skillintensive activities and hence reduce the skill premium that educated workers enjoy (Goldin and Katz, 2007).

Human capital augments effective units of labor and makes workers more productive. At the macro level, the aggregate production of the economy ( _Y_ ) is dependent on physical capital ( _K_ ); human capital ( _HK_ ), measured as efficiency units of labor; and technology ( _A_ ) (Goldin and Katz, 2007). The production function is assumed to have constant returns to scale on _K_ and _HK_ : At the micro level, ��<sup>�</sup> �<sup>denotes the human capital accumulated by an individual at age</sup> _a._ The model assumes that human capital accumulation has a life cycle skill formation (Behram et al. 2014; Cunha and Heckman, 2007). The stock of human capital accumulated at age _a,_ denoted by ��<sup>�</sup> �<sup>is dependent on the human capital accumulated until age ��1 and on the marginal</sup> human capital acquired at age _a_ . In other words, investments made in previous years influence the decisions individuals make concerning human capital investments today. Additionally, the framework allows the possibility that human capital depletes at an exogenous rate ��, which can vary with time: 4
dHK*,Cc d, <0 <!-- Start of picture text --> HC£(a)<br>_"Engagement<br>ePi disengagementPartial |<br><!-- End of picture text -->

<!-- Start of picture text --> i i a aa aaa ma aa aaa a<br>i ¢ Se i<br>[7 H : el<br>{377 See:;<br>i¢ Human capital :<br>if : 2 H<br>i depletion<br>IEEESSS SSS SNES<br><!-- End of picture text --> <!-- Start of picture text --> sit a<br>~ % | | |<br>15 18 23 29<br><!-- End of picture text -->
To understand the disengagement phenomenon, we have to study not only the mechanisms that allow individuals to build human capital, but also the decision processes that individuals face to invest in it. In this model, the investment is the time dedicated to study or work. Individuals choose to invest in human capital because they expect to receive the returns to their investments in the form of future earnings. In general, individuals make their decisions considering both their time and monetary restrictions, the expected returns to the investments, as well as the characteristics of the schooling system, the labor market, and the community. The benefit of working is hereby defined not only by the wage but also by the skills acquired on the job (i.e., onthe-job learning).

# _2.1. Maximizing the Utility Function_

Individual wages, denoted by ��, are determined by the maximum services of human capital that the individual can offer in the labor market at age _a_ and by its rental value in the market, denoted by ��. Individuals need to be employed to render wages.<sup>3</sup> In every period, individuals can choose to study, work, or stay idle. Let ��� and ��� denote the number of hours spent in formal education and working, respectively, which are bound by a time constraint _H._ Individuals may also be responsible for domestic activities and house-care, that needs to be outsourced while they study and/or work at an hourly cost, denoted by ��.

With a discount rate �, in every period, individuals maximize their utility function determined by a vector of consumption items, ��, _o_ ver their lifecycle, and subject to their maximum disposable income, ��: Where

> 3 The value of the parameter �� depends on contextual variables affecting labor productivity and price, such as labor market regulation, sector of specialization, factor technology, and other macroeconomic conditions.

6
Va Yo <!-- Start of picture text --> Ya _= Wahal + Yo<br>aU a*U<br>=~ >0 =, <0<br>aCq acz<br>QU au a*u a4U<br>l e < 0 12 e2 > 0<br>ant ang an'2 ane<br>«9 U(C,)U(Ca) = —©<br>au a aU 11 (Owe Owe au au<br>6 4$ —<br>ane + YmDesa Gt ace h h*\ (fre an& — ant = 6% *—w aCq ,& + 6 *— ant<br><!-- End of picture text --> <u>aw: aHKE</u> t <u>dHKa</u> ~~—~~ = a ~~—=a~~ [l]j- p ~~i—*~~ an},j an},J t=aPi <u>4an),j</u> aC, ht he
<!-- Start of picture text --> OHKa<br>J<br>an},<br>aU. OHK au aU. OHK,<br>6 %7— ang * +— ane “= 6° *B — aC,w% + 6 7*— ane * +—* ant, B<br>—= dioaVemax (5 t = OU wi Tf=at Pi)<br>aU . OHK au aU. OHK,<br>6 °—, + —4B > 6 °—w , + 6° + — 5 B V hE<br>ang — ane aCq ant ant<br>[0, H] A = 0<br>@HKq OHKq<br>ane — an<br><!-- End of picture text --> B>0O Yo Yo
working in the future. As such, there are no incentives for individuals to remain in school if they do not expect to work in the future.

# <u>The decision to start working</u>

Equation (9) provides some intuitive information about when individuals choose to join the labor market. According the system of equations presented above, ��� can become positive for a few reasons:

- a) When the potential future gains from working become more substantial than the benefits from studying one extra hour: when the gains in human capital acquired by staying in school diminish and the gains acquired in the labor market increase, ���� < ���� ; ���<sup>�</sup> ���<sup>�</sup>

- b) When the immediate gains from working at age � increase. If �� becomes attractive enough so that the utility brought by the consumption is larger than the disutility of an extra hour of work;

- c) When the present restrictions require the individual to enter the labor market. If �� becomes insufficient to pay for the minimum consumption and care.

Note that, according to the circumstances the individual faces, the outcome _work-and-study_ can fall at different points of the engagement spectrum. When the job provides excellent opportunities to acquire skills and complements those learned in school, the individual is closer to the full engagement trajectory. However, when individuals enter the labor market out of necessity, to a job that does not provide adequate opportunities for skills-development, they are abnegating potential human capital gains from an extra hour in school to work. When comparing time allocation statistics, these two types of individuals can have the same allocation, but completely different outcomes and implications for the society’s productivity.

# <u>The decision to quit school</u>

Still regarding equation (9), individuals will choose to leave school and stay only in the labor market, that is ��� �0, if ��<sup>��</sup> � ���� ���<sup>�</sup> �� �� � �� � ���� � for ∀ ��� ∈�0, ��. ���<sup>�</sup> ���<sup>�</sup> ���� ���<sup>�</sup> ~~�~~ ���<sup>�</sup> This can be a result of the following situations: 9
<u>OHKqg</u> | <u>OHKq e</u> < <u>l</u> ane ani,

Yo Wa Pa 5° ~~OU OU~~ <u>alg</u> *% + <u>anl,</u> ~~(se~~ a + <u>at)</u> We he =0 <u>OHKg au aU;</u> aq ~~—*~~ <u>ant,</u> B ~~-—~~ <u>an</u> = 6* ~~,—~~ <u>ACq (p</u> —wW,a) Wa > Pa Yo Yo + ha(Wal — d p*) Cy = ~~OU~~ d ~~OHKg~~ 6 ~~50,~~ a P — Wa) ~~<r~~ a hg SH-hag = CaS waha + Yo — palhé + ha)
If at least one of the three conditions above is not satisfied, individuals are better off being NEETs.

# <u>Disengaged employment</u>

Individuals may choose to work even if there is not any gain to their human capital from doing so. This outcome will occur if, in any period �, given the individual’s human capital, the wages obtained by the individual would allow them to consume more than if they stay idle, that is if ����� � ����� ��0. In this case, the individual will work an extra hour while the marginal utility of the consumption provided by their net wages is larger than the marginal disutility of being �� �� employed, �� ��� ��<sup>�</sup> �� ~~,~~ not necessarily investing _H_ and staying idle the rest of the ��� ���<sup>�</sup> time. Potentially, the individual may see his or her human capital deplete and be considered disengaged even while working.

# <u>Subsistence employment</u>

A final implication of the framework is that, even if conditions are entirely adverse, individuals may be forced to work. The lower �� and the lower �<sup>�</sup> , the lower the wage an individual will accept to work to be able to have positive consumption (i.e. subsistence employment).

# _2.2. The Human Capital Production Function_

The production function that individuals face when making human capital investment decisions is a complex system of technical, institutional, and price factors that influence the inputs that contribute to skills development. This framework assumes that human capital is mainly formed through education, acquisition of skills on the job, and intrinsic ability (i.e., to create and enterprise). The returns of these inputs (i.e. their marginal products) depend on several exogenous factors at the individual/family level (e.g. such as health and nutrition), community level (e.g. quality of available infrastructure), and macro level (e.g. government policies, technology, and public spending) (Behram et al. 2014 and Ben-Porath, 1967). In such context, the human capital production function can be described as follows: Where ����� , ��� denotes the skills acquired through formal education, ����� , ��� denotes the skills acquired through employment experience, and �� is a set exogenous factors at the 11
individual, family, community, and macro levels that influence the skills development process. The model assumes that education and employment are imperfect-substitute factor inputs in the production function. In other words, formal education cannot fully develop the skills individual can acquire while in the labor market and vice-versa. Finally, _U_ denotes the individual’s intrinsic ability, which is assumed to be age invariant.

# <u>Human capital accumulation through formal education</u>

The traditional approach in human capital development models is to assume that human capital accumulation through education is assured if students are enrolled at school (Behram et al. 2014; Barro and Sala-i-Martin, 1995). This proposed framework assumes that being at school is a necessary but not a sufficient condition for human capital accumulation through formal education. As expressed by equation (3), human capital accumulation contributes to increase individual earnings only if education attainment contributes to the improvement of the individual skills set. Based on the literature, we assume such skills sets can be cognitive, technical, or socioemotional (Cunningham and Villaseñor, 2016; Hanushek and Woessman, 2008; Heckman and Rubenstain, 2001).<sup>7</sup> In other words, human capital accumulation through formal education occurs only if the system has the capacity to produce additional cognitive, technical, and socio-emotional skills, denoted respectively by ���, ���, ���.

As formalized by Glewwe and Kremer (2006) in the context of formal education, skills development follows a production function that depends on the individual’s completed years of education, the quality of school inputs, and schooling prices. As such: Where _YS_ denotes the years of completed education, _Q_ represents education quality, _I_ and _H_ represent student and household characteristics, respectively, and _P_ represents the price of schooling. The quality of school inputs is influenced by exogenous factors (��). Additionally, school inputs _Q_ and schooling price _P_ are also influenced by education-specific policies, denoted by _EP._

> 7 This assumption is not in conflict with the idea that education also contributes to develop other sets of skills that, while more complex to monetize, have a great value to society (OECD, 2007; Feinstein et al, 2004).

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# <u>Human capital accumulation through employment experience</u>

Traditional models assume that every year of employment experience increases human capital (Becker, 1964; Mincer, 1974). Such increases, however, slow down with age, following a concave pattern throughout the worker’s employment cycle (Rubinstein and Weiss, 2007). The classical approach assumes that labor market experience ( _l_ ) could help workers develop firm� specific skills, �� as well as other cognitive, technical, and socio-emotional skills, denoted � � � respectively by ��, ��, ��.

Workers move from one job to another and/or to unemployment. A worker’s decision to change jobs will occur when, for a similar level of human capital, the new job offers a higher human capital rental value, ��, where ��~�����, �����. Workers who enter unemployment and become economically disengaged experience human capital decumulation at an exogenous rate 0 ��� �1, because they lose their firm-specific skills as well as socio-emotional skills (Burdett et al, 2011; Krueger and Mueller, 2012). Following standard search theory for labor markets with heterogenous workers and firms (Bontemps et al, 1999 and Burdett et al., 2011), employed and unemployed workers receive offers per a Poisson process with parameter �� �0. Also, job destruction shocks bring individuals into unemployment according to a Poisson process with parameter �� �0. Search is random and job offers are drawn from a distribution of firm job offers, ����. An individual will change jobs if the offer received values more his skills set than his current job, with a probability 1 ������, where �� its rental value in the market of the worker’s current job.

A job offer with a higher rental value will contribute to increase the worker’s wage. Also, moving to a better job is associated with positive skills development, as workers learn from their interactions with new peers, technologies, and work content. This is consistent with empirical evidence suggesting that the highest observed wage increases in a worker’s career occur when he changes jobs (Burdett et al., 2011; Rosen 1972).

While jobs provide workers with a wage, having a job may not a be sufficient condition for human capital development if the job does not contribute, over time, to build the worker’s skills set. Indeed, unless workers received meaningful training, as workers acquire more experience their 13
cognitive, technical skills tend to deplete and/or be less valued by the market as technologies change. On-the-job training, if relevant, can contribute to build a worker’s technical, cognitive, and socio-emotional skills (Veum, 1995; Mincer, 1988) as well as capital investments in technology that force workers to improve/adapt their skills to these technologies (Autor et al., 2003).

In this context, a worker’s capacity to build skills through employment experience can be formalized as follows: Where _YOE_ denotes the worker’s years of experience, _T_ is a parameter that denotes the quality and relevance of training provided to the worker by the firm; _IT_ denotes the firm’s investments in technology, ��� denotes the price of technology, �� denotes the price of providing on-the-job/life-long training, and _K is_ a parameter that denotes a worker’s contract security (e.g., no contract vs. fixed-term vs. open-ended). _LP_ and _EP_ denote labor and education policies, respectively. Implicitly, equation 15 suggests that workers’ skills development through employment experience occurs (i) when jobs provide adequate training opportunities along their careers, (ii) if workers move up into better jobs, and (iii) if workers are less exposed to jobdestruction shocks.

Equation 15 provides other important messages. First, job creation and job destruction shocks can vary over time and are dependent on exogenous factors at the individual, family, community/sector, and macro levels. Second, the quality of training provided by the firms as well as job creation and destruction shocks are influenced by the worker’s contract type as well as by labor and training policies, such as labor regulation, minimum wage policy, and TVET/apprenticeship regulation and prices.

# 2.3. _Policy Relevant Features of the Framework_

There are several features of the framework that seem pertinent to the design and implementation of youth, education, and labor policies. A first important implication of the framework is that economic disengagement can occur even if individuals spend time studying and working. Indeed, individuals can study and work for long periods of time and face a complete 14
stagnation in their human capital development. This occurs primarily if the formal education system and labor market do not contribute to build skills that are valued by the labor market. Therefore, it is insufficient to observe only the individuals’ time allocation to determine their engagement. A population with a low share of NEETs may still be disengaged and face stagnant productivity if the workers and students do not acquire skills.

A second implication is that policies and programs need to be implemented as early as possible in the life of beneficiaries. On the one hand, early investments in their human capital formation have the potential to bring returns for a longer period, throughout their productive lives (output effect). On the other hand, the increased marginal return to one hour invested may change the individual’s time allocation, increasing, even more, their human capital (substitution effect).

A third implication of the framework is that, even if studying/working do contribute to develop one’s human capital, individuals may choose to drop-out from school/work if the costs related to economic engagement surpasses its benefits. Individuals may drop-out from school (while accumulating human capital) if their level of income and transfers is not enough to cover their basic consumption needs and/or the costs of being out of the household (introduced in the model as a price of care). In such cases, individuals are forced to forgo potential future utility to consume today. The framework also suggests that the NEET state is a rational decision that some individuals make when (given their human capital) returns to employment are low while the transfers available allow them to have more utility than if employed (given that individuals who are employed can have their utility reduced because of the hours worked and may need to bear a cost of care). This result is relevant for women with low levels of human capital, who often account for most of the NEET population. In addition, it applies to teenage and young adults who have ceased to accumulate human capital in school and face a labor market that offers low wages and no learning opportunities, while still counting on transfers from the parents or the government.

This framework shows that the returns to investments in human capital diminish when the individual does not expect to work in the future. Moreover, it shows that individuals chose not to work when wages are low, the cost of care is high, and they have access to enough transfers to cover their consumption and domestic care duties. Considering these two facts, policies that improve the labor market conditions and reduce the cost of care impact the engagement of the current adult population, directly and indirectly, increase the investment in human capital of the younger generation by affecting their choice incentives.

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Another important implication is that government policies are fundamental to assure that time allocated to education and employment contributes to human capital development. For the case of education, policies should focus beyond assuring school enrollment, to proper quality of learning, that what is taught is valued by the labor market, and that access to education remains affordable. In the case of employment, policies should encourage firms to deliver meaningful thejob training, access technologies that increase workers’ productivity, give workers enough protection from employment risks, and enhance labor mobility.

Finally, the framework also implies that it is crucial to identify the constraints present in the economy and build policies in an integrated way. Providing transfers so that individuals can attend school might be insufficient to retain individuals in the education system if they do not feel they are acquiring skills that are rewarded by the labor market. On the other hand, improving the quality of education will be less effective if students cannot afford to study (if the price of tuition and/or the price to outsourcing care is high). Investments in education will also have lower returns if the skills acquired are not valued by the labor market, if they depreciate fast because there is no connection between school and work, and if individuals do not expect to work in the future. Since choices are made over the perceptions individuals have of the future, policies that raise awareness about the returns to investments in human capital might complement and increase the impacts of other policies.

# **III. Potential empirical approaches**

There are several empirical applications that could be developed using this proposed framework. A first application would be assessing wage determination beyond the standard Mincerian wage regressions (i.e., controlling for years of education and experience) using a skillsbased approach, so that: log ��������log �� � ����<sup>�</sup> ���� _for j = {c, t, s}_ (16) The estimates resulting from equation (16) would provide valuable information about how the market rewards skills, which could be used by policy makers (and firms) to adjust and develop their education and training programs.

16
<u>dHK(a)</u> ____ <u>as¢(h§.7a) as}(nb,va) aa)</u> *@ <u>aga) aca)</u> Ln (s/|hi) = Bo In(YOE) + B, In(T) + By In( LP) + Bz In( EP) + B, In(K) + Bs NUIT) + Beln(ya) Ln (sf|h&) = Bo n(VS) + B, In(Q) + Bz In(I) + Bz In(H) + By NCEP) + Bs In(P) + Beln(ya)

h!, = ag(w, — p2) + L(ht,Yq) + other policy variables hé =lq + E(hG, Yq) + other policy variables logw = logw, + [a;]'[s;] hét+hi<H E(hS, Ya) L(hb, Ya)
and employment. Economic disengagement can occur even if individuals spend time studying and working. The phenomenon of economic disengagement has lifelong implications that not only constrain and restrain future earnings, but also undermine prospects for improvements in productivity and economic growth.

Economic disengagement is a rational choice that individuals make when the formal education system and the labor market do not contribute to build skills that are valued by the labor market and when the costs related to economic engagement surpass its benefits. Indeed, individuals can study and work for long periods of time and face a complete stagnation in their human capital development. This occurs primarily if the formal education system and labor market do not contribute to build skills that are valued by the labor market and/or if individuals have low expectations to work in the future, given their human capital accumulation expectations. Under the model assumptions, however, total economic disengagement (i.e. the NEET population) constitutes only the tip of the iceberg of a broader and far-reaching disengagement problem that affects a population of youth studying in low-quality schools and/or working on low-quality jobs, and which are often ignored by statistics as well as policy makers.

There are several features of the framework that are policy pertinent. First, policies and programs to prevent economic disengagement need to be implemented early to prevent negative long-lasting impacts on human capital formation, labor market outcomes, and productivity. Second, government policies can contribute to improve the human capital production function. For the case of education, policies should aim to assure proper quality of learning, relevance of skills taught, and reduced affordability constraints. In the case of employment, policies should promote relevant on-the-job training, access to technologies that increase workers’ productivity, and adequate regulation that promotes workers’ upward mobility while protecting them in times of transition.

# **References**

- Acemoglu, D. (2009). _Introduction to Modern Economic Growth_ . Princeton and New York: Princeton University Press.

- Acemoglu, D. and D.Autor. (2010). “Skills, Tasks and Technologies: Implications for Employment and Earnings.” In Handbook of Labor Economics, Volume 4B, edited by

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