UNEMPLOYMENT, STATUS IN EMPLOYMENT AND WAGES IN MOROCCO
BOUDARBAT, Brahim* Abstract
High unemployment rates among educated workers in Morocco and many other developing countries is a serious issue. The worsening unemployment problem among educated workers in Morocco started with the cuts to public sector hiring under structural adjustment policies implemented in 1983. Thus, this paper analyzes the evolution of the determinants of employment and the status in employment and wages in this country after 1983 using a cohort approach. Estimates based on microdata from the 1998 Moroccan labour force survey confirm the deterioration in employment of educated workers after 1983. The results also show that the contraction of employment opportunities has increased the probability of considering self-employment as an alternative to unemployment, except for university graduates who still prefer paid work and, consequently, risk long periods of unemployment. Results also exhibit a significant decline over time in returns to education, whereas paid employment opportunities and wages have improved for uneducated workers.
JEL classification: J24, J31, J38, J42, J45, J60
Key words: Morocco, public sector, adjustment policies, unemployment, education.
1.Introduction
During the last two decades, Morocco has experienced a significantly worsening unemployment problem in urban areas, particularly among educated workers. The urban unemployment rate increased by 8 points between 1982 and 1994, rising from 12.3% to 20.3%. In rural areas, the unemployment rate increased from 9.5% to 10.8%
during the same period, but sharply diminished thereafter to reach 3.9% in 2002 versus 18.3% in urban areas. This deterioration of urban employment mainly involves educated workers. In 2002, the overall unemployment rate was 34% among workers with secondary diplomas and 32.2% among university graduates as opposed to only 5.6% among uneducated workers. This phenomenon is not unique to Morocco but is commonly observed in many other developing countries. Upadhyay (1994) refers to many examples in countries from Asia, Africa and Latin America, where unemployment is widespread among educated workers. This situation is often related
* Brahim Boudarbat, Assistant professor, School of Industrial Relations, Université de Montréal, Canada, and IZA (Germany), Email: [email protected]
Acknowledgement: I would like to thank Thomas Lemieux, Claude Montmarquette and André Martens for helpful comments and suggestions. I also would like to thank David Green, Dwayne Benjamin and seminar participants at the University of Montreal, the University of British Columbia, the University of Ottawa, and the Canadian Economics Association 2002 Conference in Calgary for useful comments on an earlier version of this paper. Many thanks also go to the Moroccan Department of Statistics for providing data used in this paper.
to the share and the evolution of the organized sectors in employment, but also and more often to the behaviour of workers with regard to job search strategies and investment in education.
In Morocco, educated workers typically work in the public sector.1 However, recruitment in the public sector declined abruptly after 1983 under structural adjustment policies dictated by the International Monetary Funds (IMF). New employment positions created since 1983 do not exceed 15,000 annually (13,000 in 2004) as opposed to between 30,000 and 50,000 between 1976 and 1982. This reduction of employment in the public sector seems to be the starting point of the deterioration in the employment of educated workers. Indeed, the representativeness of workers with a university education in the unemployed population (given by their share in the unemployed population minus their share in the labour force) increased from – 3% in 1984 to +7.7% in 2002. Despite the sharp reduction of employment in the Moroccan public sector, educated workers still show a strong desire for employment in the public sector, since over four out of ten of the university unemployed seek employment exclusively in this sector. The public sector pays higher wages and offers better employment conditions compared to the private (mostly informal) sector, which influences the workers’ behaviour; workers likely prefer employment with the former and do little to pursue alternative options.
One of the aims of the structural adjustment policies was to assign to the private sector a more important role in the economy, especially in employment. Hence, employment policies after the 1983 adjustment programs aimed at boosting labour demand in the private sector and at encouraging educated workers to seek employment in this sector.2 However, noticing that unemployment kept worsening among educated workers, in a second phase the government aimed at driving educated workers toward self-employment by implementing different programs which primarily benefit university and vocational training graduates. Henceforth, the government considers self-employment as the appropriate alternative to unemployment for educated workers.
In addition, the government hopes that small projects initiated by educated workers will contribute to creating paid work and then to reducing the overall unemployment rate.
Several studies have addressed the situation in the Moroccan labour market (Agénor and El Aynaoui, 2003; Boudarbat, 2004; Bougroum, Ibourk and Trachen, 1999;
Combarnous, 1999; Lane, Hakim and Miranda, 1999, for instance). However, to our knowledge, there is no study that examines the effects of changing labour market conditions on labour market outcomes, especially with regard self-employment and wages. This paper tries to fill this gap. For this purpose, we use a cohort approach to
1 In 1998, the share of this sector in the employment of university graduates in urban areas was 65%.
2For instance, in 1983 the government promulgated the industrial investments code which provides incentives to the creation of jobs, such as grants of a premium to industrial SME for each stable job created during their first four years of establishment.
show the impact of the structural adjustment policies on the Moroccan labour market.
The cohort approach is used with cross-section data from the 1998 Moroccan labour force survey. However, we adjust for selection biases to obtain correct conclusions with these data.
The remainder of the paper is organized as follows. Section 2 reviews the main features of the Moroccan labour market and provides some explanations for the worsening unemployment problem among educated workers. In Section 3, we present an empirical model jointly estimating (1) the employment equation, (2) the status in employment equation, and (3) the wage equation. Section 4 presents data and empirical results. Data is for a representative sample of 42,663 urban workers drawn from the 1998 Moroccan labour force survey. As anticipated, our results suggest that when controlling for observed characteristics, the decision to consider self-employment is negatively correlated with the probability of finding employment. The results also indicate that the probability of being self-employed has increased since 1983 for all education groups except for university workers. Finally, the results show a decrease in returns to education, especially to secondary diplomas and university degrees, whereas wages and employment opportunities significantly improved for uneducated and poorly educated workers. The latter result can be explained mainly by the continuous decrease in the share of uneducated workers in the labour force as a result of the improvement in the schooling rate among young people contrasted with little change in the structure of the economy still favourable to uneducated workers. The latter have, in addition, profited from the successive and substantial rises in the minimum wage during the 1980s and 1990s. Section 5 concludes the study.
2.Overview of the Moroccan Labour Market
In 2002, the size of the Moroccan labour force was 10.7 million, representing 50.7%
of the population sector aged 15 and older. The labour force participation rate is much higher in rural areas (58.5%) than in urban areas (45.4%), and for men (77.3%) than for women (24.9%). A main feature of the Moroccan labour force is the preponderance of uneducated workers. About seven out of every ten workers (67.6%) never attended school or did not complete the first six years of elementary education. This characteristic describes 88.8% of rural workers versus 48.4% of urban workers and 70.9% of female workers versus 66.5% of male workers. The share of workers with secondary diplomas and university degrees is 10.3% and is higher among women (13.6% versus 9.2% for men). The low level of schooling of the labour force is consistent with the high rate of illiteracy, which is 49% in the population sector aged 15 and older.
Over time, Morocco has experienced a significantly worsening unemployment problem. The unemployment rate almost doubled between 1971 and 1994, rising from 8.8% to 16% before falling to 11.6% in 2002. The number of job-seekers reached 1332 thousand in 1994 compared to 216 thousand in 1971 (see Table 1). This deterioration in employment particularly affected urban areas, where the unemployment rate (18.3%
in 2002) has been above 20% for several years. Conversely, the unemployment rate in rural areas was the lowest in 2002 and the number of job-seekers in 2002 was only 53
thousand greater than the corresponding number in 1971. As a matter of fact, the pressure on the labour market was much higher in urban areas since the size of the urban population increased from 3.4 million in 1960 to more than 16 million in 2001 for a total growth of 381%, versus only 56% in rural areas during the same period. In addition, since 1994, the size of the urban population has been higher than the size of the rural population. Yet, the two areas differ with regard to the structure of employment. Rural areas are dominated by non-remunerated employment,3 which accounts for 52.6% of total employment (84.1% of employed women) in these areas versus only 5.5% in urban areas (5.1% of employed women). By gender, the unemployment rate among women declined spectacularly over time, falling from 23.1% in 1994 to 12.5% in 2002, versus 16% to 11.6% for men. However, the performance of women remains poor in the urban labour market in view of the fact that their unemployment rate in 2002 was 24.2% as opposed to 16.6% for men.
The worsening unemployment problem also involves educated workers. In 2002, the unemployment rate among uneducated workers and those who did not complete the first six years of elementary education was only 5.6% versus 34% among workers with secondary diplomas and 32.2% among university graduates. Basically, workers with all levels of education face high risks of unemployment, as shown in Table 2. The employment situation of educated workers started to worsen in the early 1980s. For comparison purposes, Figures 1 and 2 depict the evolution of the shares of workers with university education and uneducated workers in the urban labour force and the urban unemployed population between 1978 and 2002. The share of university workers in the labour force continuously increased over time, rising from 2.9% in 1978 to 12.7% in 2002, whereas their share in the unemployed population increased more rapidly during the same period, from 0.4% to 20.4%. The gap between the two shares widened over time, a fact that resulted in university workers being increasingly over- represented in the unemployed population since 1987. On the other hand, uneducated workers enjoy better employment opportunities, given that their share in the unemployed population is consistently 13 to 19 points lower than their share in the labour force (Figure 2). Workers also experience long spells of unemployment. In 2002, the average duration of unemployment was 37.6 months for all unemployed workers pooled and 45.2 months for unemployed workers holding secondary diplomas or university degrees. In addition, 52% of unemployed workers were still seeking their first jobs. This proportion was 80.9% among unemployed workers holding secondary diplomas or university degrees.
Many arguments are given to explain the situation in the Moroccan labour market and other developing labour markets. The rapid growth of the population, particularly the educated population, is naturally one of the factors to blame. The population of Morocco has tripled over the last 50 years due particularly to a high birth rate and a low mortality rate. The mortality rate among children under 5 decreased from 22% in 1960 to 4.3% in 2002 as a result of the improvement in food quality and sanitary conditions. The increase in the population size was paralleled by a substantial
3 Unpaid family workers
improvement in the schooling of young people. For instance, primary school enrolment increased from 47% in 1975 to 88% in 2000. Thus, the share of uneducated workers in the labour force significantly decreased over time, as depicted in Figure 2. Naturally, increased schooling raises the preference for protected employment in the formal sector (Orivel, 1995; Gaude, 1997; Combarnous, 1999).4 This aspiration contrasts with the little change in the structure of the Moroccan economy, which is still favourable to uneducated workers. For instance, the share of the agricultural sector in the GDP has consistently ranged between 15% and 20% since 1970, and this sector is still the largest employer with 44.4% of total employment in 2002.
In the literature, developing labour markets are often described as consisting of two sectors: a formal/primary sector paying high wages but with limited employment opportunities and informal/secondary sector offering unlimited employment opportunities but paying low wages (see, for example, Harris and Todaro, 1970;
Stiglitz, 1974 and 1976; Eaton & Neher, 1975). Harris and Todaro (1970) explain the high urban unemployment rate in developing countries by the substantial wage differential between urban and rural areas, which encourages some rural workers to migrate to urban areas. The unemployed are blamed because they voluntarily choose unemployment in order to improve their economic position rather than take available low paid jobs in the secondary sector (Eaton & Neher, 1975). However, in the current context this explanation seems more appropriate for uneducated workers than for educated ones, given the great employment opportunities in the informal sector (including agriculture) in developing countries. In the specific case of university graduates, and given the strong preference for employment in the public sector exhibited by these workers, Boudarbat (2004) rather considers a dual labour market where the public sector and the private sector are the two employers. Given the substantial wage gap between the two sectors, he shows that educated workers find it optimal to prolong their unemployment episodes in order to find jobs in the public sector. This argument regarding job-search strategies is also supported by Bougroum, Ibourk and Trachen’s study (1999) which, in addition, points the finger at the inefficiency of investment in university programs, since many students attend university simply because they have no other options. In the same vein, Rama (1998) argues that the line between being unemployed and working in the informal sector is very thin for educated workers. Workers seeking employment in the formal sector may decline employment opportunities in the informal sector or may report themselves as unemployed if they do not. Lane, Hakim and Miranda (1999) blame the fast growth of the urban labour force contrasted with an inadequate labour demand, and the structural shift in the employment composition of manufacturing to low-paying industries linked to the export sector, which ultimately favoured uneducated and poorly educated workers. Indeed, increased foreign trade (especially with the European Union) has stimulated the production in sectors for which Morocco has a comparative advantage and which are intensive in unskilled (and cheap) labour (mainly agriculture and garment industries). The trade reform in Morocco, which reduced the barriers to
4 Orivel (1995) even argues that some rural parents prevent their children from receiving an education in order to keep them in or close to their families.
imports, was initiated precisely in 1983, the same year the adjustment policies were implemented (see Currie and Harrison, 1997, for an overview of this trade reform).
Upadhyay (1994) evokes government subsidies to education in developing countries as an explanation for the high unemployment rate among educated workers in these countries. Upadhyay argues that such subsidies have increased the demand for higher education at the expense of investment in physical capital, which results in too much education being produced relative to the needs of the labour market. Hence, one may observe a situation where employment opportunities are very good for unskilled workers but very limited for skilled ones. In Morocco, education in public universities is free and students are allowed to repeat grades they fail (sometimes indefinitely). The government also provides scholarships to most students, which attracts students to university education even when there is no connection with the needs of the labour market.
The sharp reduction of recruitment in the public sector under structural adjustment policies implemented in 1983 is quoted as a key factor in the worsening unemployment problem among university graduates. Indeed, the worsening employment situation of educated workers parallels the slowdown of recruitment in the public sector, the principal employer for educated workers in developing countries. Because of the adjustment and austerity policies adopted by Morocco since August 1983 under the aegis of the IMF, there was first a cancellation of more than 19,000 new positions in the public sector forecast in the budget of 1983, then a cap on recruitment for subsequent years. In the 2004 budget, the government envisaged creating 13,000 new positions5 (less than 11,000 in 2002) versus more than 50,000 in 1976 and more than 45,000 in 1982. As depicted in Figure 1, the share of workers with a university education in the unemployed population started its rise immediately after the implementation of the adjustment policies. Despite the reduction of employment in the public sector, Table 3 shows that this sector remains the preferred one for seeking employment for a great proportion of unemployed university graduates. Indeed, 42.3%
of university graduates in urban areas seek employment only in the public sector, versus 1.2% of workers with no degree/certificate. This proportion is also high among unemployed workers with secondary diplomas.
3.Model of Employment Status and Wages
This study aims at analyzing the determinants of employment, the status in employment (i.e. paid worker versus self-employed) and wages in the Moroccan labour market. The study also examines how these determinants changed after 1983, the date of the implementation of the structural adjustment policies in Morocco. We predict that the scarcity of paid employment will drive more workers toward self-employment as alternative to unemployment. The government has implemented many programs to encourage and facilitate this shift. These programs were specifically developed after 1983 to put a stop to the worsening unemployment problem. In addition, the worsening
5 The transformation of existing positions from occasional into tenured accounts for 6000 of them.
employment conditions of educated workers are intuitively expected to have negative effects on the wages paid to these workers (Beaudry and DiNardo, 1991).
To achieve the goals of the study, we use a cohort approach with cross-section data from the Moroccan labour force. A crucial issue in the study is accounting for selection biases that might distort our results. As indicated above, employment and status in employment may be correlated since the self-employment choice can depend upon available paid employment opportunities. Also, the analysis of the determinants of the status in employment must account for the fact that this status is censored for unemployed workers. Additionally, given the fact that wages are observed only for paid workers, there are two possible sources of selection bias in estimates of the wage equation: being employed and being a paid worker. The model we propose below makes it possible to correct for those different selection biases. It is composed of three freely correlated equations, one for each for the three studied subjects. For convenience we omit the subscript i related to the individual.
Employment criterion:
*
1 1 1
e = X ß +e (1)
An individual is employed (e=1) if e* ≥0, and is not employed (e=0) if e* <0. Employment status criterion:
*
2 2 2
a =X ß +e (2)
An individual is a paid worker (a=1) if a*≥0, and is self-employed (a=0) if a*<0.
Wage equation:
3 3 3
y= X ß +e (3)
Equations (1) and (2) are reduced-form selection equations. e* and a* are latent variables, y is the log of the monthly wage, X1, X2 and X3 denote vectors of independent variables, ß1, ß2 and ß3 are vectors of parameters to be estimated, and e1, e2 and e3denote unobserved error components. The censure occurs at two levels.
First, the status in employment is observed only if the worker is employed (i.e. a is observed iff e=1). Second, wages are observed only for paid workers (i.e. y is observed iff e=1 and a=1).6 Thus, we have a censored model with two criteria for selectivity (see Maddala, 1983, pp. 278–283, for further examples and explanations on multiple criteria for selectivity). The model is given by Equations (1), (2) and (3).
6 Unfortunately, the Moroccan labour force survey does not collect earnings of the self- employed. This data limitation makes it impossible to account for these earnings in the workers’
decisions with regard to status in employment.
The random terms e1, e2 and e3 are freely correlated, with the vector
(
e ,e ,e '1 2 3)
following a trivariate normal distribution with mean zero and variance-covariance matrix:
σ σ σ ρ
= Σ
33 23 13 12
1 1
.
We follow Ham (1982)7 in estimating the model in two steps. The two-step estimation is computationally more attractive than the maximum likelihood method and produces consistent parameter estimates. The first stage of the approach involves the estimation of a censored bivariate probit defined by Equations (1) and (2). The corresponding log-likelihood function is:
l=
∑ [ ( ) ]
=
− Φ
0
1
ln 1 e
X β +
(
1 1β 2β ρ2 12)
e 1 a 0
ln F X , X ,
==
−
∑
+
(
1 1β 2 2β ρ12)
e 1 a 1
ln F X , X ,
==
∑
where Φ
( )
. is the distribution function of the univariate standard normal, and F is the distribution function of the bivariate standard normal.In the second stage, we estimate the selection-corrected wage equation by including in the set of covariates two correction terms derived from the first stage. As shown by Ham (1982), the expectation of the monthly log of the wage (y), conditional on being employed and being a paid worker, is:
E(y | e* ≥ 0, a* ≥ 0) = X3ß3 – σ 13λ1 – σ 23 λ2 (4)
where: λ1=φ
(
X1 1β Φ) ( )X*1 / F X(
1 1β , X2β ρ2, 12)
( ) ( ) ( )
λ2=φ X2β Φ2 X*2 / F X1 1β , X2β ρ2, 12
(
β ρ β)
ρ* 2
1 2 2 1 1 12
X = X − X / 1−
(
β ρ β)
ρ* 2
2 1 1 2 2 12
X = X − X / 1−
and φ
( )
. and Φ( )
. are the density and distribution functions of the univariate standard normal, respectively, and F is the distribution function of the bivariate standard normal. Notice that if the correlation coefficient ρ12 is equal to zero, λ1 and λ2 are simply inverse Mill's Ratios.
7 The method is an extension of the two-stage estimator for one selection rule proposed by Heckman (1979).
Parameter estimates from the first stage are used to form consistent estimates, λˆ1 and ˆ2
λ , of λˆ1 and λˆ2. Then, consistent estimates of ß3, σ13, and σ23 are obtained by least squares estimation of:
y = X3β3 - σ13 λˆ1 - σ23 λˆ2 + e3 (5) where e3 = ε3 + σ13 (λˆ1 - λ1) + σ23 (λˆ2-λ2)
Finally, consistent estimates of s33 and the standard errors of the least squares slopes are obtained using formulas from Ham (1982).
In this paper we adopt the same cohort approach used by Angrist and Lavy (1997) to analyse the evolution of labour-market conditions after the implementation of the structural adjustment policies in 1983. Indeed, we include in the sets of covariates a dummy variable that takes the value 1 if a worker entered the labour force in 1983 or later, and cross this variable with education levels. Our data source provides information on labour force entry.
4.Data and Empirical results
We use data from the Moroccan Labour Force Survey (LFS) conducted in urban areas in 1998. The LFS is an annual cross-section survey aiming at collecting key information on labour force participation, employment and unemployment. Rural areas were included in the survey only starting in 1999. Prior to 1999, data on rural areas came from the census that was conducted once every 10 years. Information on educational achievement is given by two variables. The first, called level of education, indicates the highest level of education attended and specifies whether a worker received a vocational training. Levels are: (i) none (uneducated), (ii) first stage of elementary education (grades 1–6), (iii) second stage elementary education (grades 7–
9), (iv) secondary (grades 10–12) and (v) university. A worker is classified into a stage of education if she attended any year of this stage regardless of completion or not of this stage. The second variable is the highest degree/certificate obtained. There are eight aggregated groups: (i) none (includes uneducated workers as well as those who did not complete the first stage of elementary education), (ii) elementary (stage 1 or stage 2 completed), (iii) level 1 (lower) of vocational training, (iv) level 2 (medium) of vocational training, (v) secondary, (vi) technician (technical post-secondary training or third and forth (higher) levels of vocational training), (vii) university, and (viii) higher institutes.8
The 1998 LFS surveyed more than 130,000 individuals living in urban areas. The size of the available sample of workers in the labour force is 42,663. Like in other developing labour markets, some workers enter the labour force very young and others continue to work at very old age. In the data file supplied by the Moroccan Department of Statistics, there are workers as young as 7 and workers as old as 98. In total, 629
8 Higher institutes are of the same level as universities. They provide technical and professional education (engineering schools for instance).
workers are aged under 15 and 767 above 65. We removed these people from our sample and focus our study on “adults” aged 15 to 65 at the time of the survey. We also trim all wage observations with monthly wages below MAD9 500. The final sample consists of 41,282 workers: 7946 are unemployed, 13,985 are employed unpaid workers (mainly self-employed) and 19,351 are paid workers. Descriptive statistics are presented in Table 4.
Women represent 24% of the sample, a proportion that agrees with the overall low participation of women in the labour force. With regard to schooling, uneducated and poorly educated workers (less than 6 years of elementary education) represent more than 50% of our sample. The unemployment rate is 19%, which is exactly the same as the official rate produced by the Moroccan department of statistics for the year 1998.
Despite the sharp slowdown in recruitment in the public sector since 1983, this sector remains a key employer in the Moroccan labour market with a share of 22% of total employment and 37% of paid employment in urban areas. The share of paid workers in the employed population is relatively low (only 58%). The average number of weekly hours is 48 for paid workers versus 54 for unpaid workers. The average monthly wage is MAD 2,383, that is to say 44% higher than the minimum monthly wage (MAD 1,651) evaluated on the basis of average weekly hours (47.74) and the minimum hourly wage in force in 1998 (MAD 7.98). However, only 5% of employees are paid more than MAD 5,000. All parameter estimates are reported in Tables 5a and 5b for the censored bivariate probit given by Equations (1) and (2), and in Tables 6a and 6b for the selection-adjusted wages equation. In all equations, we control for the region of residence (there are 16 regions in Morocco represented by 15 dummy variables in the sets of covariates). In addition, we control for the month of observation in the employment equation (11 dummy variables). Concerning education, we provide results for the two available variables: the level of education and the highest degree/certificate obtained. As can be seen, results are very comparable between the two specifications.
An important fact that emerges from all tables is that the covariances between unobserved random terms in the three equations of the model are statistically significant at the 1% level, a fact that supports our approach to correcting for selection biases.
Employment and Status in Employmen.- Parameter estimates in Table 5a show that being female has no effect on the probability of finding employment. Given the fact that the unemployment rate is much higher among women than among men in urban areas, this result suggests that observed differences between the genders are due to differences in their characteristics rather than to discrimination against women. For instance, women in the urban labour force are, on average, more educated than men (46% of women are uneducated or poorly educated versus 53% of men, and 7% of women hold university degrees versus only 3.6% of men), whereas education increases the unemployment risk as shown below. However, when employed, women are more likely to be paid workers compared to men, a status that is probably associated with their degree of risk aversion, but also with their willingness to reconcile family and
9 MAD = Moroccan dirham. MAD 9 are worth about $1 US.
work. On the other hand, being born in rural areas increases the likelihood of employment but has no effect on the likelihood of being a paid worker. An explanation for the effect on employment may be a sele ction process since some workers born in rural areas migrate to urban areas when they find jobs there or in anticipation of better employment opportunities. Yet, it is possible that some workers born in rural areas migrated to urban areas before entering the labour force. It is also known that rural workers are less demanding in terms of wages, conditions or duration of work when seeking jobs. Being single lowers the probability of employment but increases the probability of being a paid worker. Naturally, single workers are still young (26 years on average versus 41 years for non-singles), so many of them are still looking for their first jobs. Experience in paid work is also desired (even required) before considering self-employment. Thus, increased age simultaneously increases the probability of employment and the probability of self-employment. Also, in the Moroccan context, single workers (and young people in general) are usually supported by their families, so they may consider long durations of unemployment in order to find good jobs.
Indeed, only 6% of single workers in our sample are heads of households. In addition, in the Moroccan context marital status is somewhat an endogenous variable, especially for men, since it may be inconceivable to consider marriage before finding a job to support the family.
Another interesting issue that emerges from Table 5a is that the probability of employment is not affected by the adjustment policies of 1983. These policies may have affected employment among graduates but not the overall employment level.
However, the preference for paid work significantly increased after 1983 in spite of many programs introduced by the government to encourage self-employment. With regard to education, we notice that increased schooling generally lowers the probability of employment and, at the same time, increases the likelihood of being a paid worker (education levels and degrees/certificates are sorted from the lowest to the highest level). The risk of unemployment is highest among workers with university degrees.
The only exception is workers holding degrees from higher institutes who continue to enjoy the best employment opportunities of all workers (including uneducated ones).
However, these workers represent only 2% of the labour force. Another significant issue that emerges from the results in Table 5a is that receiving a vocational training reduces the probability of employment, except when this training is preceded by university studies. Thus, at any level of elementary and secondary education, vocational training has a significant negative effect on employment. This contrasts with the policy of the government, which considers vocational training the best medium to meet labour market needs and to improve employment among young workers. It is also unpredicted that vocational training graduates prefer paid work, since the probability of being a paid worker increases with this training at all stages of education. The results for the effects of education on employment status agree with those from previous studies, which show that more schooling increases the preference for protected (paid) employment (e.g., Orivel, 1995; Gaude, 1997; Combarnous, 1999). Those results can also explain the increased preference for paid work after 1983, which in fact might simply be connected with the increased schooling of the labour force.
In order to examine the possible change in employment conditions of educated workers after 1983, Table 5b depicts bivariate probit estimates when crossing “Year 1983” with degrees/certificates. The results clearly show that employment has worsened for all groups of educated workers, particularly for university graduates and workers with higher vocational training. Conversely, employment of uneducated and poorly educated workers has improved since the estimated coefficient of the variable
“Year 1983” is now positive and significant. The non-significance of the same coefficient in Table 5a is due to the contrasting evolution in the employment of educated and uneducated workers. In spite of this of this result, we cannot assert that the worsening unemployment problem of educated workers is directly linked to the slowdown of recruitment in the public sector. Indeed, the variable “Year 1983” might simply reflect a trend in the Moroccan labour market that would have occurred even if the adjustment policies were not implemented. Nonetheless, if we assume that recruitment in the public sector remained at the same level as prior to 1983, this sector would have created on average about 20,000 new additional positions per year, that is to say 400,000 positions between 1983 and 2002.10 Holding all else constant, the unemployment rate in 2002 would fall to less than 8% versus 11.6% currently. Also, if positions in the public sector were created only in urban areas, the unemployment rate in these areas would fall to about 11% versus 18.3% currently. Evidently, these predictions are partial since employment in the private sector as well as workers’
behaviour is most likely to react to any change in employment the public sector.
With regard to paid work, the results in Table 5b suggest that the probability of being a paid worker has significantly decreased for all groups of educated workers except for university graduates and workers with lower level vocational training. The result concerning university graduates might relate either to these workers’ inflexible behaviour or to the nature of university programs which make it difficult for graduates to set up viable businesses. The decrease in the probability of being a paid worker mainly affected workers with medium and upper levels of vocational training, a fact that may be a consequence of the government policy that considers vocational training graduates the best candidates for self-employment. In addition to granting loans at preferential interest rates to young educated entrepreneurs, the government instituted substantial tax exemptions to benefit young entrepreneurs holding vocational training diplomas.11 However, this policy excludes workers with lower level vocational training. In addition, an investigation by the Moroccan Vocational Training Department (Département de la Formation Professionnelle, 1996) indicates that most young entrepreneurs consider this policy to have been determinant in their decision to create their own businesses.
10 The public sector created on average more than 35,000 new positions a year between 1975 and 1982 versus less than 15,000 annually thereafter.
11 The government also listed 20 trades that could be practised only by graduates holding vocational training diplomas or by experienced workers who succeed at professional aptitude tests. However, this regulation, which aimed at protecting graduates from competition from uneducated workers or those trained on-the-job, has never been implemented.
Wage Equatio.- Tables 6a and 6b depict the selection-adjusted wage equation estimates. The variable age is used as a proxy for work experience. Age squared allows the non-linearity of earnings toward the end of the work life to be accounted for.
Estimates of the coefficients of the correction terms are jointly significant at the level 1%, a fact that provides evidence for the existence of selection biases. The male -female wage gap is estimated at 13.4% when using levels of education and 17.3% when using degrees/certificates. The public sector pays notably higher wages than the private sector—this wage differential is estimated at 23%.12 Boudarbat (2004) evaluates this differential at 42.5% for university graduates when accounting for job search behaviour. Also, Agénor and El Aynaoui (2003) estimate the gap at between 150% and 200% when taking into account non-wage compensation such as working conditions and pension plans. Interestingly, the elastic ity of the monthly wage with respect to weekly worked hours is not significant. This is not surprising, given the characteristics of the Moroccan labour market. Indeed, negotiations, if there are any, between workers and employers often concern monthly wages instead of hourly wages. It is also not surprising that workers compare jobs based on monthly wages regardless of the number of hours of work and working conditions. In addition, notions of part time work and hourly wage are not common in Moroccan jargon except for some very specific occupations.
Naturally, increased schooling increases earnings. It is interesting to see how vocational training pays at all stages of education except when it is associated with university education, a result that contrasts with the one from employment equation estimates. Thus, vocational training graduates experience high unemployment risk, but are awarded high wages once employed. By degree/certificate, the return to higher education ranges between 122% for university graduates and 127% for higher-institute graduates. In order to capture the possible effect of the unemployment driving down wages, Table 6b shows estimates when controlling for the period after 1983. The main remark concerns the significant decline in the returns to education after 1983, a result that is probably explained by the decreased share of the public (high-wage) sector in the employment of educated workers. Conversely, wages generally increased for uneducated and poorly educated workers. Once again, university graduates were among the most affected by the downward trend of wages paid to educated workers.
Angrist and Lavy (1997) obtain the same result regarding the reduced return to education for young workers, which they explain by the switch of the language of instruction from French to Arabic in the public elementary and secondary schools since the early 1980s. On the other hand, uneducated workers have profited from the consecutive substantial increases in the minimum wage.13 The minimum hourly wage in manufacturing, trade and the liberal professions increased from MAD 1.4 in 1977 to MAD 7.98 in 1996, for an average increase of 9.6% per year. In conclusion, educated workers are undergoing the negative effects of combined factors, a situation which raises the question about the rationality of investment in education in Morocco.
12 By way of comparison with a developed labour market, Gunderson, Hyatt and Riddell (2000) show that government wages on average are estimated to be between 7% and 10% higher than in the private sector in Canada.
13 Seven increases during the 1980s and five during 1990s.
5.Conclusion
High unemployment among educated workers in developing countries is an important and fascinating problem. The analysis of the Moroccan case can create a better understanding of the functioning of developing labour markets in general. In this country, the deterioration of the situation of educated workers parallels the slowdown of employment in the public sector since 1983 under structural adjustment policies.
Yet, it is not clear to what degree theses policies contributed to that deterioration. The present investigation uses microdata from the 1998 Moroccan labour force survey to analyze the determinants of employment, paid employment and wages and their evolution after 1983. Estimates support the contraction of employment opportunities for educated workers, particularly for university graduates. The latter are the main candidates for employment in the public sector. This contraction has encouraged more educated workers to consider self-employment as an alternative to unemployment.
Results also suggest that returns to education decreased over time, especially with respect to secondary diplomas and university degrees. An attention-grabbing result is that paid employment opportunities and wages significantly improved for uneducated and poorly educated workers. Natural explanations for this fact include the continuous decrease in the share of uneducated workers in the labour force and the successive and substantial rises in the minimum wage during the 1980s and 1990s. This result may also reflect an increased degree of informalization of the Moroccan labour market.
Finally, the model could be improved if earnings were also collected from self- employed workers. Intuitively, the decision regarding the status in employment is expected to also depend upon the earnings gap between paid and self employment.
References
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Table 1: Evolution of Unemployment between 1971 and 2000
Urban Rural Total
1971 1982 1994 2002 1971 1982 1994 2002 1971 1982 1994 2002 Number of
unemployed workers (thousands)
216 322 920 1,017 133 320 412 186 349 642 1,332 1,203 Unemploy-ment rate
(%) 15.0 12.3 20.3 18.3 5.2 9.5 10.8 3.9 8.8 10.7 16.0 11.6 Men 14.4 11.7 17.1 16.6 5.2 10.0 10.9 4.7 8.2 10.7 14.1 11.3 Women 19.1 14.2 29.6 24.2 5.3 6.5 10.5 1.7 12.1 10.7 23.1 12.5
Table 2: Unemployment Rate by Highest Degree in 2002 (%)
Degree %
None 5.6
Certificate of elementary education 20.7 Vocational training, specialisation (lower) level 35.6 Vocational training, qualification (medium) level 28.4
Secondary diploma 34.0
Technicians (higher level of vocational training) 18.0
University degree 32.2
Total 11.6
Source: Direction de la Statistique, Royaume du Maroc (2003).
Table 3: Preferred sector for searching employment, urban areas in 1998 (%)
Degree/Certificate Any sector Public
sector
Private
sector Total
None 60.26 1.17 38.57 100
Elementary education 65.93 6.12 27.95 100
Secondary 55.64 36.22 8.14 100
University 51.29 42.31 6.41 100
Higher institute 32.65 41.35 25.99 100
Technicians (higher level of vocational training) 46.27 21.97 31.76 100 Vocational training, qualification (medium)
level 48.2 10.03
41.77 100 Vocational training, specialisation (medium)
level 42.78 4.12
53.11 100
Total 58.57 11.57 29.86 100
Note: These figures are calculated by the author based on the 1998 Moroccan Labor Force Survey data file.
Table 4: Descriptive Statistics
Whole sample Unemployed Non paid workers Paid workers
Variable Mean Mean Mean Mean
Age 33.72 (11.11) 26.93 (7.27) 35.21 (12.31) 35.46 (10.43)
Female 0.24 0.30 0.18 0.26
Single 0.49 0.87 0.41 0.40
Head of household 0.40 0.08 0.47 0.49
Born in rural area 0.29 0.14 0.36 0.30
Entered the L.F in or
after 1983 0.58 0.88 0.47 0.53
Education level:
Uneducated 0.24 0.08 0.35 0.23
Elementary, 1st stage 0.29 0.25 0.34 0.26
Elementary, 1st stage
+ V.T. 0.01 0.01 0.01 0.00
Elementary, 2nd stage 0.14 0.19 0.15 0.12
Elementary, 2nd stage 0.03 0.06 0.02 0.03
+ V.T.
Secondary 0.10 0.14 0.08 0.10
Secondary + V.T. 0.07 0.08 0.02 0.10
University 0.08 0.15 0.03 0.08
University + V.T. 0.05 0.04 0.01 0.08
Degree/certificate Uneducated or elementary education not completed
0.51 0.32 0.67 0.47
Elementary 0.26 0.34 0.25 0.23
V.T., Specialisation
(level 1) 0.01 0.02 0.01 0.01
V.T., Qualification
(level 2) 0.05 0.09 0.02 0.06
Secondary 0.03 0.06 0.02 0.03
University 0.04 0.10 0.01 0.04
V.T., Technician
(level 3) 0.07 0.06 0.01 0.12
Higher institutes 0.02 0.01 0.01 0.04
Employed 0.81 0.00 1.00 1.00
Paid workers (among
employed workers) 0.58 - 0.00 1.00
Public sector (among
employed workers) 0.22 - 0.00 0.37
Weekly hours - - 53.72 (17.07) 47.74 (14.38)
Wages (in MAD) - - - 2,382.79
(3,561.3)
# Observations 41,282 7,946 13,985 19,351
Notes : V.T.= Vocational training. Data are weighted.
Table 5a: Censored Bivariate Probit estimates
(1) (2)
Employed Paid worker Employed Paid worker
Coef. Std.
Err. Coef. Std.
Err. Coef. Std.
Err. Coef. Std.
Err.
Constant 1.031* 0.161 0.338** 0.147 0.943* 0.160 0.422* 0.145
Age 0.019* 0.002 -0.003* 0.001 0.019* 0.002 -
0.003* 0.001
Female -0.011 0.019 0.265* 0.018 0.015 0.019 0.240* 0.018
Born in rural areas 0.150* 0.022 0.018 0.017 0.199* 0.021 -0.022 0.016
Single -0.641* 0.026 0.192* 0.022 -0.640* 0.026 0.196* 0.022
Head of household 0.421* 0.028 0.106* 0.022 0.419* 0.028 0.010* 0.022
Year 1983 0.002 0.029 0.087* 0.023 -0.016 0.029 0.107* 0.023
Education level:
Elementary, 1st stage -0.167* 0.029 0.157* 0.020 - - - -
Elementary, 1st stage + V.T. -0.506* 0.082 0.170** 0.080 - - - -
Elementary, 2nd stage -0.365* 0.032 0.272* 0.024 - - - - Elementary, 2nd stage + V.T. -0.815* 0.044 0.806* 0.045 - - - -
Secondary -0.547* 0.035 0.478* 0.027 - - - -
Secondary + V.T. -0.578* 0.039 1.243* 0.040 - - - -
University -0.908* 0.036 0.916* 0.034 - - - -
University + V.T. -0.314* 0.045 1.384* 0.049 - - - -
Degree/Certificate:
Elementary - - - - -0.313* 0.020 0.234* 0.017
V.T., Specialisation
(lower level) - - - - -0.544* 0.078 0.274* 0.078
V.T., Qualification
(medium level) - - - - -0.651* 0.033 0.853* 0.039
Secondary - - - - -0.695* 0.039 0.748* 0.045
V.T., Technician
(higher level) - - - - -0.264* 0.033 1.387* 0.041
University - - - - -0.933* 0.035 0.976* 0.045
Higher institutes - - - - 0.213* 0.078 0.838* 0.057
ρ12 -0.920* 0.028 -0.917* 0.029
Mean log L -0.89 -0.884
# Observations 41,28 33,33 41,28 33,33
Notes: The reference group for education is “Uneducated”. * Significant at the level 1%. In both equations, we control for 16 regions of residence. In addition, we control for the month of observation in the employment equation.
Table 5b: Censored Bivariate Probit estimates
Employed Paid worker
Coef. Std. Err. Coef. Std. Err.
Constant 0.7663* 0.1608 0.3047** 0.1440
Age 0.0194* 0.0016 -0.0022** 0.0010
Female 0.0207 0.0189 0.2404* 0.0182
Born in rural areas 0.2055* 0.0213 -0.0084 0.0159
Single -0.6225* 0.0253 0.1991* 0.0224
Head of household 0.4166* 0.0283 0.0991* 0.0226
Year 1983 0.1628* 0.0342 0.2558* 0.0265
Degree/Certificate:
Elementary -0.1267* 0.0427 0.4527* 0.0272
V.T., Specialisation (lower level) -0.0703 0.2656 0.1659 0.1856 V.T., Qualification (medium level) -0.1050 0.0957 1.2777* 0.0760
Secondary -0.1209 0.1307 0.9835* 0.0954
V.T., Technician (higher level) 0.5570* 0.1067 1.7621* 0.0689
University 0.1726 0.1479 1.0726* 0.0969
Higher institutes 0.6234* 0.2263 1.0780* 0.0839
Year 1983 x
Elementary -0.2145* 0.0475 -0.3586* 0.0345
V.T., Specialisation (lower level) -0.5516** 0.2763 0.0574 0.2055
V.T., Qualification (medium level) -0.6311* 0.1023 -0.6261* 0.0882
Secondary -0.6523* 0.1368 -0.3546* 0.1075
V.T., Technician (higher level) -0.9750* 0.1122 -0.6404* 0.0853
University -1.2137* 0.1518 -0.1788 0.1088
Higher institutes -0.4905** 0.2415 -0.4582* 0.1128
ρ12 -0.8829* 0.0346
Mean log L -0.8817
# Observations 41,282 33,336
Notes: The reference group for education is “Uneducated”. * Significant at the level 1%. **
Significant at the level 5%. In both equations, we control for 16 regions of residence. In addition, we control for the month of observation in the employment equation.
Table 6a and 6b. Wage Equations
Table 6a (+) Table 6b (++)
(1) (2)
Coef. Std.
Err.
Coef. Std.
Err.
Coef. Std.
Err.
Constant 6.40* 0.11 6.41* 0.10 6.23* 0.11
Age 0.03* 0.00 0.03* 0.00 0.04* 0.00
Age squared -0.00* 0.00 -0.00* 0.00 -0.00* 0.00
Female -0.13* 0.02 -0.17* 0.01 -0.18* 0.01
Public sector 0.23* 0.01 0.24* 0.01 0.23* 0.01
log weekly hours -0.00 0.01 0.017 0.01 0.02 0.01
Education level:
Elementary 1 0.23* 0.02 - -
Elementary 1+ V.T. 0.42* 0.07 - -
Elementary 2 0.43* 0.02 - -
Elementary 2+ V.T. 0.76* 0.05 - -
Secondary 0.65* 0.03 - -
Secondary + V.T. 1.01* 0.05 - -
University 1.33* 0.05 - -
University + V.T. 1.23* 0.06 - -
Year 1983 0.08* 0.02
Degree/Certificate:
Elementary - - 0.34* 0.01 0.43* 0.02
V.T., Specialisation (lower level) - - 0.49* 0.06 0.44* 0.11 V.T., Qualification (medium level) - - 0.60* 0.04 0.60* 0.05
Secondary - - 0.75* 0.04 0.96* 0.06
V.T., Technician (higher level ) - - 0.87* 0.04 0.86* 0.05
University - - 1.22* 0.05 1.40* 0.06
Higher institutes - - 1.27* 0.04 1.35* 0.05
Year 1983 x
Elementary -0.19* 0.03
V.T., Specialisation (lower level) -0.10 0.13
