The dynamics of wage discrimination

and gender equity

in Moroccan labor market

SAMI ZOUARI

High Institute of Industrial ManagementUniversity of Sfax, TunisiaMobile: +216 25 241 804

Fax: +216 74 460 744Email: sami.zouari@isgis.rnu.tn

Research Capacity building on Gender and Work in the MENA Region

Second Research Seminar

March 15, 2010

SOFITEL Hotel, Maadi, Cairo, Egypt

Objectives

* The present study aims to highlight wage evolution in Moroccan labor market during the last two decades.

* It will be giving a quantitative idea on labor market issues in Morocco with focus on gender wage gap.

* Provides recommendations in order to avoid any form of discrimination against women in all recruitment steps.

Introduction

By having the same abilities and productivity level, twoworkers should be equally remunerated with noconsideration to their sex nor their ethnicity.

However, on the labor market, with the samecharacteristics, man and woman are receiving differentsalaries advantaging man: We are talking here aboutwage discrimination.

Question:

How could this gender wage gap be explained ?

Outline

1. Theoretical framework

2. The evolution of Moroccan women situation during the last two decades

3. Methodology

4. Descriptive statistics and empirical study

5. Conclusion and recommendations

1. Theoretical framework

1. Taste discrimination [Becker (1957)]

(Displeasure feeling)

2. Statistic discrimination [Phelps (1972); Arrow (1973)]

(Absence of information)

3. Interest discrimination [Lazear et Rosen (1990)] :

(Increasing benefits)

2. The evolution of Moroccan women

situation during the last two decades

2. The evolution of Moroccan women situation during the last two decades

2.1. Social context

Islamic ideology: relationship betweenman and woman based on the image of womanas a “spouse and mother”.

Family ideology: members within thefamily are considered with reference to their sex.According to this ideology man are superior towomen.

2.2. Legislation

* Morocco has ratified the Convention of Elimination of all Forms of Discrimination Against Women (CEDAW) in June 21st, 1993.

* Based on “equal work, equal wage” principal, gender discrimination has been prohibited.

* Moroccan Government has ratified International Labour Conventions in order to guarantee gender remuneration equity (ie. Convention N°100 of June 29th, 1951).

* The new Moroccan labor code protects feminist special rights (maternity, hard work, nocturnal work, etc.).

2. The evolution of Moroccan women situation during the last two decades

2.3. Political environment

* Since 1962, the Moroccan legislation has guaranteed many political rights for female citizens such as: Right to vote and to put her candidacy to the elections, right to the strike, liberty of expression, opinion, association and to adhere to all political or union organizations of her choice.

* Morocco has ratified, successively, the International Convention of Women Political Rights in November 22nd, 1976, and the International Pact of Political and Civil Rights in 1979.

* The percentage of women in the total number of deputies was 0.9% in 1993 and has risen to 10.8% in 2002. Whereas, in the Government, women represented 9.75% in 1995 and became 8% in 2002.

2. The evolution of Moroccan women situation during the last two decades

2.4. Economic context

* Moroccan female have shifted from a passive role in the society toward a very active actors within the socioeconomic development.

* In the mid 1970’s, female participation was so important especially in the labour intensive industries where women are more competitive.

* In the 1980’s, economic recession stopped the continued increasing in female labour force participation since industries were in crises and men were more likely to be employed than women.

* Development occurred during the 1990’s have turned the attention toward the gender consideration in economic and public policies establishment.

* After 2000, ...

2. The evolution of Moroccan women situation during the last two decades

0

10

20

30

40

50

60

70

80

90

Labor force participation and unemployment rates within MENA and OECD countries by sex

Labor force participation rate MALE

Labor force participation rate FEMALE

Unemployment rate MALE

Unemployment rate FEMALE

21.3

32.3 32

23.6

56.5

95 96.1

68.7

15 - 24 25 - 34 35 - 44 45 and above

Moroccan Activity rate by sex and age cohorts, 2008

Female Male

0

5

10

15

20

25

M F M F M F M F M F

15 - 24 25 - 34 35 - 44 45 and above

Total

Un

em

plo

ym

en

t ra

te

Age cohort

Moroccan unemployment rate by sex and age cohorts

2008

2000

3. Methodology

3. Methodology __________________________________________________________

Gain function estimation for men and women:

immimimxw

iffififxw

3. Methodology __________________________________________________________

Average wage gap between men and women will be then:

(the reference is the dominant group)

)ˆˆ()(ˆfmffmmfm

xxxww

3

ff

2

mm

1

fmfm )ˆ(x)ˆ(x)xx(ww

3. Methodology __________________________________________________________

Oaxaca and Ransom (1994):

(the reference is the overall group)

3. Methodology __________________________________________________________

1. Wage gap du to characteristic differences between men

and women (endowments).

2. Additional remuneration attributed to men du to the

differences in their characteristics vs. the global group

(favoritism toward men).

3. Women loss of earning vs. the whole sample

(discrimination against women)

Selection problem (Heckman, 1979)

iii uzI

participet doesn' individual 0 ,0I

participes individual 0 ,0I

i

i

iuzif

iuzif

ii

ii

)z(

)z(

i

ii

3. Methodology___________________________________________________________

By using Heckman (1979) method, it will be possible to control for selection

when estimating the wage function.

Heckman procedure consists in estimating lambda for each individual from

the participation equation using Probit model. Then, lambda will be

introduced as a regressor in the wage equation

iiiiˆxw

3. Methodology __________________________________________________________

The average gender wage gap will be then :

In the equation above, the first two terms correspond to pure favoritism

toward males and pure discrimination against females, the third term is the

human capital component. The last term measures the contribution of

selection effects to the observed gender wage gap.

:

ˆˆˆˆˆˆ

or

xxww ffffmmmmfm

)ˆˆˆˆ()()ˆ()ˆ( ffmmfmffmmfm xxxxww

3. Methodology __________________________________________________________

Neuman and Oaxaca (2004) have decomposed the selectivity

term shown in the previous equation.

This could help by identifying other kinds of discrimination as

given by the following equation:

)6()5(

0

)4(

0 )ˆˆ(ˆ)ˆˆ(ˆ)ˆˆ(ˆˆˆˆˆfmfffmfmmffmm

3. Methodology___________________________________________________________

4. The effects of gender differences in the variables that determine

professional employment

5. The achieves of gender differences in the parameters of the Probit

selectivity equation on the male/female wage differential

6. The consequences of gender differences in the wage response to the

probability of professional employment. In other words, it reflects the wage

gap effects of gender differences in the correlation between the selectivity

equation error term and the wage equation error term as well as gender

differences in wage variability

3. Methodology___________________________________________________________

4. Descriptive statistics and empirical study

4.1. Descriptive statistics___________________________________________

Morocco Living Standard Measurement Studies

1990/91 1998/99

Total sample :IndividualsHouseholds

196773349

304575129

Selected sample:Individuals 1944 3847

Urban 66% 74%

Men 1563 2925

Women 381 922

4.1. Descriptive statistics___________________________________________

4.1. Descriptive statistics___________________________________________

Table 3 : Estimation of the weekly wage logarithm for Male, Female and both, 15 - 64, by sector (public - private),

Morocco, 1991

Variables

Public et private Public Private

Male Female Total Male Female Total Male Female Total

Experience

0,071

(0,005)***

0,032

(0,012)**

0,070

(0,005)***

0,070

(0,009)***

0,022

(0,023)

0,072

(0,009)***

0,067

(0,007)***

0,023

(0,014)

0,065

(0,006)***

Experience

square

-0,001

(0,000)***

0,000

(0,000)

-0,001

(0,000)***

-0,001

(0,000)***

0,000

(0,000)

-0,001

(0,000)***

-0,001

(0,000)***

0,000

(0,000)

-0,001

(0,000)***

Primary non

accompli

0,131

(0,043)***

0,184

(0,120)

0,213

(0,042)***

0,273

(0,083)***

1,129

(0,270)***

0,438

(0,084)***

0,096

(0,051)*

0,032

(0,137)

0,163

(0,049)***

Primary

0,316

(0,050)***

0,827

(0,147)***

0,451

(0,049)***

0,619

(0,078)***

1,410

(0,206)***

0,757

(0,077)***

0,151

(0,065)**

0,424

(0,214)**

0,281

(0,064)***

Secondary 1st

cycle

0,661

(0,063)***

1,283

(0,137)***

0,803

(0,059)***

0,858

(0,082)***

1,782

(0,205)***

1,002

(0,080)***

0,513

(0,103)***

1,112

(0,196)***

0,685

(0,093)***

Vocational

0,806

(0,077)***

1,363

(0,157)***

0,935

(0,071)***

0,927

(0,094)***

1,812

(0,212)***

1,069

(0,090)***

0,764

(0,137)***

1,218

(0,265)***

0,927

(0,125)***

Secondary 2nd

cycle

1,086

(0,101)***

1,579

(0,183)***

1,197

(0,090)***

1,168

(0,117)***

1,986

(0,226)***

1,295

(0,107)***

1,140

(0,191)***

1,805

(0,386)***

1,352

(0,175)***

University

1,536

(0,080)***

1,927

(0,177)***

1,683

(0,076)***

1,616

(0,093)***

2,247

(0,239)***

1,779

(0,092)***

1,870

(0,219)***

2,277

(0,318)***

2,047

(0,182)***

Area (dummy =

1 if urban)

0,074

(0,036)**

0,088

(0,110)

0,002

(0,036)

0,255

(0,068)***

0,633

(0,237)***

0,234

(0,070)***

0,027

(0,043)

-0,005

(0,126)

-0,059

(0,042)

N 1563 381 1944 551 138 689 1012 243 1255

R2 47,76 48,75 45,02 50,17 58,84 47,30 28,30 34,31 26,66

SD is between parenthesis.

*** Significant at 1%, ** Significant at 5%, * Significant at 10%

4.2. Empirical study___________________________________________________________________________

Table 4 : Estimation of the weekly wage logarithm for Male, Female and both, 15 - 64, by sector (public - private), Morocco, 99

Variables

Public et Private Public Private

Male Female Total Male Female Total Male Female Total

Experience

0,078

(0,004)***

0,039

(0,008)***

0,071

(0,004)***

0,079

(0,008)***

0,043

(0,018)**

0,070

(0,007)***

0,077

(0,005)***

0,040

(0,009)***

0,071

(0,004)***

Experience

square

-0,001

(0,000)***

-0,001

(0,000)***

-0,001

(0,000)***

-0,001

(0,000)***

0,000

(0,000)

-0,001

(0,000)***

-0,001

(0,000)***

-0,001

(0,000)***

-0,001

(0,000)***

Primary non

accompli

0,081

(0,031)**

0,270

(0,065)***

0,179

(0,028)***

0,163

(0,068)**

0,138

(0,174)

0,228

(0,067)***

0,077

(0,036)**

0,281

(0,072)***

0,179

(0,032)***

Primary

0,188

(0,036)***

0,486

(0,071)***

0,310

(0,033)***

0,309

(0,063)***

0,527

(0,162)***

0,413

(0,062)***

0,171

(0,043)***

0,471

(0,080)***

0,296

(0,038)***

Secondary 1st

cycle

0,556

(0,046)***

0,876

(0,075)***

0,666

(0,040)***

0,654

(0,061)***

1,063

(0,127)***

0,726

(0,058)***

0,505

(0,066)***

0,796

(0,098)***

0,635

(0,055)***

Vocational

0,652

(0,113)***

1,166

(0,196)***

0,843

(0,100)***

0,753

(0,114)***

1,286

(0,233)***

0,888

(0,108)***

0,632

(0,218)***

1,239

(0,309)***

0,912

(0,182)***

Secondary 2nd

cycle

0,850

(0,059)***

1,145

(0,105)***

0,980

(0,053)***

0,916

(0,070)***

1,310

(0,151)***

1,007

(0,067)***

0,839

(0,099)***

1,208

(0,168)***

1,016

(0,087)***

University

1,289

(0,064)***

1,565

(0,109)***

1,415

(0,056)***

1,298

(0,073)***

1,833

(0,152)***

1,422

(0,069)***

1,420

(0,124)***

1,390

(0,197)***

1,506

(0,107)***

Area (dummy =

1 if urban)

0,118

(0,028)***

0,111

(0,078)

0,054

(0,027)**

0,398

(0,060)***

0,983

(0,255)***

0,378

(0,062)***

0,093

(0,033)***

0,069

(0,085)

0,023

(0,031)

N 2925 922 3847 753 233 986 2172 689 2861

R2 43,38 43,87 41,42 47,05 52,10 42,63 27,12 23,90 24,81

SD is between parenthesis.

*** Significant at 1%, ** Significant at 5%, * Significant at 10%

4.2. Empirical study___________________________________________________________________________

Table5 : Gender wage gap evolution in Morocco, 1991 – 1999

Total Public Private

1991 1999 1991 1999 1991 1999

ln(MWW) - ln(FWW) 34,6% 30,9% 31,5% 21,8% 37,5% 33,5%

Justified wage gap -1,1% 1,5% -5,4% -13,1% 0,8% 5,9%

Unjustified wage gap 35,7% 29,4% 36,9% 34,9% 36,7% 27,6%

Figure 8 : Weekly wage gap decomposition, Morocco,

1991-1999

-40%

-20%

0%

20%

40%

60%

80%

100%

1991 1999 1991 1999 1991 1999

Total Public Privé

Po

urc

en

tag

e

Ecart de salaire expliqué Ecart de salaire inexpliqué

5. Conclusion and recommendations

* Gender wage gap has been declining during the last two decades(in the public more than in the private sector)

* Women in the public sector are more educated than men which could explain the negative wage gap in that sector

* Developing a positive discrimination process

* Necessity of abolition of any discrimination form on the labour market

* More governmental and associative effort is more likely to be essential in order to improve female education

* More investigation need to be done to highlight selection problem and discrimination among youth

Thank you !