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Why Has Unemployment in Algeria Been Higher than in MENA and Transition Countries?

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This paper analyzes the determinants of labor market performance in Algeria. When the model is estimated with panel data on a sample of MENA and transition countries for 1995- 2005, the results suggest that lower growth in labor productivity in Algeria is associated with higher unemployment than the sample average, though recent positive terms of trade shocks have helped Algeria reduce the differential. Labor market rigidities and labor taxation do not seem to explain why unemployment is higher in Algeria than in other countries. The results are robust to various panel econometric methods and instrumental variable estimates.
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CERDI, Etudes et Documents, E 2008.03
Document de travail de la série
Etudes et Documents
E 2008.03
Why Has Unemployment in Algeria Been Higher than in
MENA and Transition Countries?
Kangni Kpodar
(*)
1
30 p.
(*) International Monetary Fund
Author’s E-Mail address: kkpodar@imf.org
1
The author is grateful to Domenico Fanizza and Erik De Vrijer for their extensive comments, discussions,
and critical readings. He would like also to thank Florent Bresson, Boileau Loko, Gabriel Sensenbrenner,
and seminar participants at CERDI (University of Auvergne) for useful comments and suggestions. Luisa
LaFleur and Anne Grant provided helpful editing. The views expressed herein are those of the author and
should not be attributed to the IMF, its Executive Board or its management.
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Why Has Unemployment in Algeria Been Higher than in MENA and Transition Countries?
Abstract
This paper analyzes the determinants of labor market performance in Algeria. When the
model is estimated with panel data on a sample of MENA and transition countries for 1995–
2005, the results suggest that lower growth in labor productivity in Algeria is associated with
higher unemployment than the sample average, though recent positive terms of trade shocks
have helped Algeria reduce the differential. Labor market rigidities and labor taxation do not
seem to explain why unemployment is higher in Algeria than in other countries. The results
are robust to various panel econometric methods and instrumental variable estimates.
JEL Classification Numbers:
J01, E24, 040
Keywords:
Unemployment, Labor market institutions, Macroeconomic shocks
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Contents Page
I. Introduction.................................................................................................................................4
II. Stylized Facts.............................................................................................................................4
III. Determinants of Labor Market Performance .........................................................................10
A. Labor Market Institutions....................................................................................................10
B. Macroeconomic Shocks.......................................................................................................14
IV. Econometric Estimates...........................................................................................................17
A. The Model ...........................................................................................................................17
B. Data and Methodology ........................................................................................................18
C. Results .................................................................................................................................20
V. Conclusion and Policy Recommendations ..............................................................................25
Tables:
1. Public Employment Programs in Algeria, 1999.........................................................................8
2. Algeria and Selected Economies: Tax Wedge as a Percent of Labor Cost, 2005....................14
3. Mean Comparison Test: Algeria and the Sample Average, 1995–2005 ..................................19
4. Determinants of the Unemployment Rate Differential between Algeria and Other Countries,
1995–2005 ...............................................................................................................................21
5. Determinants of the Unemployment Rate Differential between Algeria and Other Countries:
Alternative Estimates, 1995–2005...........................................................................................23
6. Factors Affecting the Unemployment Rate Differential Between Algeria and the two
Subgroups of Countries: MENA and Transition Countries, 1995–2005.................................24
Figures:
1. Trends in Labor Market Participation, Total Population, and Population Growth, 1980–2004 5
2. Female Participation and Share in Total Population and Labor Force, 1980–2004 ..................6
3. Share of Employment by Sector in Total Employment, 1994–2005 .........................................7
4. MENA and Transition Countries: Trends in Total and Youth Unemployment Rates, 1995–
2005 ...........................................................................................................................................9
5. Unemployment by Age, Gender, and Education, 2005............................................................10
6. MENA and Transition Countries: Rigidity of Employment Index, 2005 ................................12
7. MENA and Transition Countries: Labor Productivity, 1989–2004.........................................15
Annexes
I. Data Sources .............................................................................................................................29
II. The Sample ..............................................................................................................................30
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I. I
NTRODUCTION
In recent years Algeria has experienced encouraging economic growth, but though
unemployment has declined substantially, it is still high. For the last five years, real
nonhydrocarbon GDP grew on average by 5.5 percent but the unemployment rate, though cut in
half, still reached 15.3 percent in 2005. Compared with unemployment rates in other Middle East
and North Africa (MENA) countries and in Eastern European transition countries, Algeria’s is
above the average for both groups.
Why is unemployment so high in Algeria? Do labor market institutions matter? Is it affected by
macroeconomic shocks?
The literature asserts that stricter labor market regulation and higher taxation of labor deter job
creation and increase unemployment. The effect, however, is somewhat ambiguous for labor
market regulation, because it also tends to reduce worker dismissals. Studies have also found that
macroeconomic shocks are critical in determining the unemployment rate. Higher productivity
growth, a moderate inflation rate, a lower real interest rate, and favorable terms of trade shocks
are expected to reduce unemployment.
The intent of this paper is to investigate the extent to which these factors account for high
unemployment in Algeria. The results suggest that lower growth of labor productivity in Algeria
is associated with a higher unemployment rate differential between Algeria and the sample of
MENA and transition countries, while positive terms of trade shocks helped Algeria to reduce the
differential. Labor market rigidities and taxation do not appear to explain the differential.
The paper is organized as follows: Section 2 looks at recent labor market developments in
Algeria. Section 3 briefly reviews the determinants of the unemployment rate, namely labor
market institutions, and macroeconomic shocks. Section 4 presents the model, the data, and the
results. Section 5 concludes with some policy recommendations.
II. S
TYLIZED
F
ACTS
Labor supply and labor demand
Population growth has been declining in Algeria since the 1980s, suggesting that the country has
been undergoing a demographic transition (Figure 1). It decreased from an annual rate of 3.3
percent in 1980 to 1.5 percent in 2004—1 percentage point lower than the MENA average. The
drop in population growth resulted mainly from a sharp decline in the fertility rate, falling from 7
children per woman in 1980 to 2.5 in 2004.
The growth of the working age population is thus declining but with a lag, temporarily increasing
the share of potential workers in the population. While the population grew on average by 2.3
percent a year from 1980 through 2004, the working age population increased by 3.4 percent
annually, raising the labor supply and creating the potential for employment and growth.
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Figure 1. Trends in Labor Market Participation, Total Population, and Population Growth, 1980–2004
(Percent)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
Population growth, Working age population growth
0
10
20
30
40
50
60
70
Participation rate
Population growth
Working age (15-64) population growth
Participation rate
Sources: World Bank (2006); ILO (2006).
At the same time, labor force participation has increased as young and female workers entered,
putting pressure on the labor market. The participation rate increased by 10 percentage points
between 1980 and 2004, mainly from young workers. Their contribution to labor force growth is
currently high because they account for nearly 50 percent of the active population. In addition,
increasing female participation is affecting the size and gender composition of the labor force.
While the share of women in the total population was roughly constant between 1980 and 2004,
their share in the labor force rose by almost 50 percent and the female participation rate increased
by 70 percent (Figure 2), though it remained below that of men. Possible reasons for the rise in
female participation could be not only declining fertility rates but also increasing education. Also,
job prospects for women have improved, owing to explicit government policies to facilitate their
participation in the labor force (Assaad and El-Hamidi, 2001).
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Figure 2. Female Participation and Share in Total Population and Labor Force, 1980–2004
(Percent)
0
10
20
30
40
50
60
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
Female population as a share of total population, Female labor force as a share of
total labor force
0
5
10
15
20
25
30
35
40
Female participation rate
Female population (percent of total
population)
Female labor force (percent of total
labor force)
Female participation rate
Sources: World Bank (2006), ILO (2006) and author's calculations.
Labor market outcomes are determined not only by supply but also by demand. When Algeria
was a centrally planned economy, the public sector provided most jobs. Since the 1980s, the
country has progressively abandoned its model of a planned and centralized economy and has set
up an ambitious program of economic and social reforms to promote private sector development
and economic growth.
Although public sector employment is falling, government spending is still the main engine of
employment creation. Figure 3 shows that government employment as a share of total
employment is shrinking as the country moves to a market-based economy. In 2005, 18 percent
of total employment was in the public sector, compared with 23 percent five years earlier.
2
But in
agriculture and public works, where employment has been growing, labor productivity has been
low and activities have been sustained by public spending, thanks to growing hydrocarbon
revenues.
In 2001 the government launched a three-year Economic Recovery Program (ERP) to boost
demand and generate jobs through public investment in infrastructure and support to agricultural
production and to small and medium-sized enterprises. The ERP goal was to create nearly
850,000 jobs between 2001 and 2004. The authorities estimated that the ERP actually generated
728,000 jobs and launched a supplementary program for 2005–09.
3
The Organization for
Economic Cooperation and Development (OECD, 2004), however, suggests that results have
been mixed because the long-term impact of ERP on growth and employment is not clear.
2
Here the public sector includes only the civil service.
3
See the report on the ERP available at http://www.cg.gov.dz/psre/bilanpsre.htm.
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Figure 3. Share of Employment by Sector in Total Employment, 1994–2005
(Percent)
0
5
10
15
20
25
30
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Agriculture
Industry
Construction and public works
Government
Work at home
Other
Source: IMF staff estimates (2006).
The evidence that public employment programs helped to push down unemployment is still
unclear and more information is needed. According to the latest estimates, public employment
programs created 1.4 million jobs between 1997 and 2001 (Ait Youness and Annane, 2004), but
most of them were temporary jobs. For instance, under the program for local employment
(Emplois salariés d’initiative locale [ESIL]) designed to provide low-skilled youth with
minimum qualifications and experience, firms were granted subsidies as incentives to hire the
unemployed. However, the retention rate at the end of the subsidy period was weak (Table 1). In
addition, most of the employment programs actually cost 25 percent to over 100 percent more
than was projected.
Trends in unemployment
The Algerian total and youth unemployment rates have decreased markedly since 2000, but both
remain high (Figure 4). Total unemployment was cut in half, from 30 percent in 2000 (the highest
rate since the late 1980s) to 15.3 percent in 2005, and youth unemployment dropped from 48
percent in 2001 to 31 percent in 2005. Nevertheless unemployment in Algeria is still higher than
the averages for other MENA countries and for transition countries. In 2004, for instance,
unemployment in Algeria was 7 percentage points higher than the MENA average.
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Table 1. Public Employment Programs in Algeria, 1999
Program Description Target
Number of
Jobs Created
(full-time job
equivalent)
Share of
Permanent Jobs
(percent)
Projected
Annual Cost
per Job
( DA)
Actual Cost
per Job
(DA)
ESIL
Subsidies are granted to firms
as incentives to hire the
unemployed.
Low-skilled young workers 68,300 7 28,571 35,580
AIG
The program provides
compensation to people
working in community-based
activities.
Poor people n.a. n.a. 68,421 37,333
TUPHIMO
Labor-intensive activities such
as road maintenance.
Unskilled unemployed persons 7,174 n.a. 50,000 82,038
CPE
Firms may hire the
unemployed at no cost for one
year; the salary is paid by the
government.
Skilled young workers 12,191 15 64,800 147,000
ANSEJ
Interest subsidies, subsidies,
and financing are provided to
microenterprise projects.
Young people who wish to set up
independent activities that fit in with
their professional qualifications.
39,260 n.a. n.a. 1,123,540
Sources: Conseil National Economique et Social (www.cnez.dz); Musette, Isli, and Hammouda (2003); and author’s calculations.
Notes: Program abbreviations: ESIL: the program for local employment (Emplois salariés d’initiative locale); AIG: the plan regarding general
interest activities (Activité d’intérêt général); (iii) TUPHIMO: the program for public works requiring intensive labor (Travaux d’utilipublique à
haute intensité de main-d’oeuvre); CPE: the pre-employment contract (Contrat pré-emploi; and (v) ANSEJ: the Agence Nationale de Soutien à
l’Emploi des Jeunes (ANSEJ).
Recent economic growth has probably contributed to the fall in unemployment. Algeria’s
economy started to recover in 1995: real nonhydrocarbon GDP growth averaged –1.3 percent
from 1992 to 1994 but 3 percent from 1995 to 2001 and then 5.7 percent from 2002 to 2005,
partly because the surge in international oil prices affected domestic demand. Implementation of
the 1994 reform program supported by the IMF and the World Bank helped the country achieve
higher economic growth and push inflation down.
However, whether the 2004–05 reduction in unemployment is permanent has yet to be seen.
Significant numbers of the new jobs are in the work at home category. Work at home, which
includes the military and irregular employment, has risen dramatically, especially in 2004, when
it increased by 34 percent, in part due to the occurrence of Ramadan shortly after the annual
household survey was conducted,
4
and possible measurement issues. Without the rise in work at
home in 2004 and 2005, the unemployment rate would have been about 22 percent in 2004 and
21 percent in 2005 (Kpodar, 2007).
4
The fact that between 2003 and 2004 female employment increased by 45 percent while male employment
increased by 12 percent could support this hypothesis.
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Figure 4. MENA and Transition Countries: Trends in Total and Youth Unemployment Rates, 1995–2005
(Percent)
Source: Algerian authorities (2005); World Bank (2006); and IMF estimates.
Total Unemployment Rate
0
5
10
15
20
25
30
35
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
Algeria
MENA countries
(excluding Algeria)
Transition countries
Youth Unemployment Rate (15-24)
0
10
20
30
40
50
60
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
MENA countries
(excluding Algeria)
Transition countries
Algeria
Profile of the unemployed
In 2005, when the unemployment rate was 31 percent, young people were most likely to be
unemployed, suggesting that unemployment in Algeria is essentially a phenomenon of the
insertion into the labor market of new entrants. The unemployment rate tends to decrease with
age (see Figure 5), ranging from 34 percent for people between 15 and 19 to less than 5 percent
for people over 50 years old. People under 30 account for 70 percent of the unemployed. This is
not surprising; unemployment in developing countries generally falls disproportionately on the
young.
In 2005 in Algeria, the unemployment rate for women (17.5 percent) was close to that of men (15
percent), though in most MENA countries, female unemployment is higher than male, perhaps
reflecting social factors. One explanation may be that the public sector in Algeria is a major
employer of women: in 2003 it accounted for 56 percent of female employment and only 37
percent of male employment.
The likelihood of being unemployed increases with education. In 2005, secondary school and
university graduates had the highest unemployment rates, possibly because of a skills mismatch
but also possibly because young people, who tend to be more educated than their elders, are more
likely to be unemployed. Higher-educated women are more likely to be unemployed than higher-
educated men.
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Figure 5. Unemployment by Age, Gender, and Education, 2005
(Percent)
Source: Algerian authorities.
34.3
29.9
22.7
12.7
7.4
4.3
4.1
3.1
2.3
0
5
10
15
20
25
30
35
40
15-
19
20-
24
25-
29
30-
34
35-
39
40-
44
45-
49
50-
54
55-
59
Unemployment rate
0
5
10
15
20
25
30
35
40
45
15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59
Male
Female
3.4
16.6
12.5
1.9
5.5
20.5
24
11.8
0
5
10
15
20
25
30
No education Primary Secondary Higher
education
Total
Male
Female
III. D
ETERMINANTS OF
L
ABOR
M
ARKET
P
ERFORMANCE
The economic literature discusses two broad categories of factors underlying labor market
performance: labor market institutions and macroeconomic shocks. The first category is related to
labor market regulation and labor taxation. The second covers productivity growth, the real
interest rate, the inflation rate, and terms of trade shocks. In this section we briefly examine how
relevant each of these factors is in explaining the unemployment rate differential between Algeria
and other countries.
A. Labor Market Institutions
Regulation
Labor market regulation provides important social protections for workers (World Bank, 2004).
Whether covering hiring contracts, severance pay, unemployment benefits, grounds for dismissal,
the right to unionize, or the scope for collective bargaining, regulation aims to protect workers
from arbitrary, unfair, or discriminatory actions by their employers while addressing potential
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market failures stemming from insufficient information and inadequate insurance against risk.
Blanchard (1998a) argues that some employment protection may also be desirable because job
contracts are incomplete: “If workers sink some cost in the relation, say to spend some time and
money training for job-specific skills, firms, once the cost is sunk, may have excessive
bargaining power. Firing costs may then reestablish the balance and lead workers to invest the
right amount in the relation.”
However, more employment protection raises the cost of labor and favors more privileged
insiders. Excessive regulation increases nonsalary costs for business because it implies
administrative costs: firms must pay the costs associated with layoffs or keep workers in jobs that
are no longer productive. It also undermines the ability of firms to adjust to changes in
technology and product demand, therefore reducing their efficiency. Moreover, regulation
generally increases the bargaining power of incumbent workers while reducing job creation and
labor market flexibility.
Stricter employment protection may thus have an ambiguous impact on overall employment
because it reduces both creation and destruction of jobs. The impact on unemployment may not
be small for vulnerable groups, such as women and youths, that are likely to experience high
unemployment rates when regulation is too restrictive. Stricter regulation may also lead to an
increase in the length of unemployment because job turnover is relatively low in such an
environment.
While excessive labor market regulation is likely to depress labor demand, it also affects labor
supply. It is well known that unemployment benefits may reduce labor supply, through a decline
in the participation rate, and raise the duration of unemployment. The availability of generous
unemployment benefits reduces the cost of unemployment relative to employment and might be a
disincentive to work: an unemployed person would have less incentive to take a job for which the
salary is lower than, or even just above, the unemployment benefits he or she could get, thus
extending unemployment either to search for a better job or to substitute leisure for work.
There is no clear evidence that regulation hampers labor market outcomes. Scholars have
typically found either an adverse effect or no effect of employment protection on the
unemployment rate or employment ratio. While Blanchard (1998b) and Nickell (1997), among
others, find no effect of job security on unemployment, Lazear (1990) and Scarpetta (1996) find
positive effects. Similarly, Heckman and Pages (2000) provide evidence that job security
regulations in Latin American countries reduce employment and promote inequality between
workers. Nunziata (2002) finds that stricter employment protection does not seem to have a
significant impact on the level of unemployment, although it increases its persistence.
Algeria ranks relatively high on the standard indicators of labor market rigidities used by the
World Bank in international comparisons (Figure 6). Algeria’s Rigidity of Employment Index,
5
an indicator that takes into account the difficulty of hiring and firing, is one of the highest in the
MENA region, and labor market regulation is stricter in Algeria than in most transition countries.
5
The index takes values between 0 and 100, with higher values implying more rigid regulation.
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Given the ambiguous effect of job security on unemployment, whether or not greater
employment protection explains higher unemployment in Algeria remains an empirical issue.
Figure 6. MENA and Transition Countries: Rigidity of Employment Index, 2005
0 10 20 30 40 50 60 70
Saudi Arabia
Czech Republic
Lebanon
Jordan
Hungary
Poland
Yemen
Slovak Republic
Bulgaria
Lithuania
Pakistan
Albania
Macedonia
Estonia
Algeria
Egypt
Tunisia
Turkey
Croatia
Ukraine
Morocco
Latvia
Romania
Slovenia
Source: World Bank (2006).
Algeria’s severance pay requirements are, however, relatively modest. Since 1994 severance
payments have been set at a minimum of one month’s wages for each year of tenure, up to a
maximum of six months of salary. Recent data suggest that employers pay laid-off workers on
average three months of salary—not too high relative to MENA standards. Dyer (2005) points
out that Algeria has a more modest system than Morocco and Tunisia, but within the MENA
region, only Algeria has a functioning unemployment insurance system in which formal sector
workers and employers participate through a mandatory payroll tax.
Though severance pay legislation in Algeria may not be stricter than in other countries, some
nonprice restrictions may be costly for firms wanting to adjust their labor force. Among them are
the need for prior authorization, the notification period, and an appeal procedure that has time and
money costs that may be larger than the transfer itself. For example, it takes on average six
months to lay off a worker; when there are
collective dismissals
, the employer has to negotiate
with the unions which workers will be laid off. When a firm is privatized, the employer is not
allowed to lay any worker off right after the takeover. Moreover, to allow a laid-off worker to
receive unemployment benefits, the employer must pay the unemployment insurance system 80
percent of the worker’s monthly wage for each year of tenure up to 12.
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Taxation
The more elastic the labor supply or demand curve, the more the labor tax will adversely affect
employment. An increase in labor taxation generally reduces growth in employment, but the
effects depend on the elasticity of the curve. If labor supply is perfectly elastic to wages, the
burden of a tax increase will be borne by the employers because the workers will not accept any
decrease in wages, and labor demand would then be reduced. If labor supply is perfectly inelastic,
the increase in labor tax would be offset by a corresponding decrease in wages, leaving the
employment level unaffected.
Labor taxes are more harmful for low wage earners. An increase in taxes cannot be fully
accommodated by a decrease in wages for some workers because the minimum wage sets the
floor when it is enforced. This suggests that employers would incur part or all of the financial
burden of a higher tax, and that they would reduce employment for this category of workers.
Empirical evidence suggests that labor taxation has a detrimental effect on employment, although
the magnitude may differ (Daveri and Tabellini, 2000; IMF, 2003; Nickel, 2003; Nunziata,
2002).
A common measure of the tax burden on labor is the tax wedge, which is defined as the
difference between workers’ take-home pay and the costs of employing them, including income
taxes and social security contributions (OECD, 2006). It is calculated as follows:
(
' sec
' sec
)
100
( ' sec )
Central government income tax
Employee s social urity contributions
Employer s social urity contributions
Payroll tax
Tax wedge
Gross earnings Employer s social urity contrib
utions Payroll tax
+
+
+
=
+ +
In Algeria, social security contributions account for 34 percent of the gross wage, 9 percent of
which is paid by the employee. The 1 percent payroll tax was abolished in 2006.
Currently the tax wedge for a single person with average earnings accounts for 41 percent of total
labor costs in Algeria, relatively close to the levels in transition economies (Table 2). Estimates
of the family tax wedge in fact suggest that labor taxation tends to be lower in Algeria than in
transition countries, so unemployment may not be a taxation issue.
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Table 2. Algeria and Selected Economies: Tax Wedge as a Percent of Labor Cost, 2005
Country
Single Person
Tax Wedge
1
Family Total
Tax Wedge
2
Algeria
41
28
Czech Republic
44
27
Estonia
40
*
Hungary
51
40
Latvia
42
**
Lithuania
43
**
Poland
44
42
Slovak Republic
38
23
Slovenia
43
**
Turkey
43
43
1
Single persons without children at the income level of the average worker.
2
Average single worker without children and one-earner married couple with two children.
Sources: OECD (2006); World Bank (2005); and author's calculations.
*Data from 2001.
**Data from 2003.
B. Macroeconomic Shocks
Productivity growth
In the short run there may be a trade-off between productivity growth and employment. Labor
productivity is the value of a unit of output produced by a worker. A decline in productivity
would imply that more workers would be needed to produce the same volume of output. While
this could help reduce unemployment, for several reasons the effect is unlikely to be sustainable:
Wages may tend to adjust slowly to changes in productivity. If wages are rigid,
declining productivity would increase the cost of labor and force firms to reduce
their demand for labor.
Low productivity makes the country less competitive. As a result, a decrease in
labor productivity could reduce export growth and ultimately trim employment by
suppressing economic growth.
Finally, lower productivity growth eventually means lower output growth and a
slowdown in domestic demand that in turn would push employment down.
Faster growth of labor productivity is often associated with lower unemployment. A rise in labor
productivity increases potential GDP by allowing more output to be produced with the same
number of workers and by decreasing the cost of labor to firms, which would promote job
creation. Higher productivity would also translate into higher wages, thus raising domestic
demand. If firms see the demand for their products go up, they respond by increasing production
and hiring more workers. As mentioned, growing labor productivity also makes the export sector
more competitive and stimulates economic growth and employment creation.
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Aside from its positive effect on labor demand, growth in labor productivity may also impact
labor supply. Because labor productivity growth is reflected in higher real wages, as predicted by
the standard neoclassical theory, workers will increase their labor supply. Nevertheless, the effect
is not as clear as one might expect, because all workers do not necessarily choose to work more.
Because the marginal utility of leisure outweighs that of income for some workers, they may
work less and gain more leisure without losing any income. As a result, the effect of labor
productivity on the aggregate labor supply may be ambiguous.
Most studies on the link between productivity growth and unemployment to date have found a
negative relationship. These studies used growth of either labor productivity or total factor
productivity (TFP) as a measure of productivity growth. Using data on OECD countries from
1960 to 1995 Nunziata (2002) found that negative TFP shocks are correlated with higher
unemployment. Blanchard and Wolfers (2000) argued that a decline in TFP accompanied by slow
adjustment of wages to the new equilibrium could have pushed up unemployment in Europe in
the 1970s. Similarly, Fitoussi and others (2000) found evidence that among OECD countries
those with slower labor productivity growth tended to experience higher unemployment. This
result is corroborated by the IMF (2003).
Algeria’s labor productivity is low. Though its growth has resumed since 2001 after declining in
the 1990s (see Figure 7), labor productivity is still below the average of MENA and transition
countries. Interestingly, the recent slight increase in productivity coincided with the decline in
unemployment. Lower labor productivity growth may thus explain why Algeria has experienced
higher unemployment than other countries.
Figure 7. MENA and Transition Countries: Labor Productivity, 1989–2004
3.80
3.90
4.00
4.10
4.20
4.30
4.40
1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
GDP per worker (in Log)
Algeria
MENA countries (excluding
Algeria)
Transition countries
Source: Groningen Growth and Development Centre (www.ggdc.net).
Real interest rate
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Increases in the real interest rate could have harmful effects on employment. A rise in the interest
rate owing to a contractionary monetary policy both slows down domestic demand and increases
the cost of capital. The resultant decreased domestic demand and capital accumulation cause
labor demand to fall. Blanchard and Wolfers (2000) pointed out that real interest rate increases in
the 1980s in Europe could have negatively affected capital accumulation, maintaining high levels
of unemployment in that period (see also Fitoussi and others, 2000). However, Nickell (1998)
suggested that the negative effect of a real interest rate increase on employment is likely to be
small.
6
A higher real interest rate may not only lower labor demand but also increase labor supply,
probably leading to an increase in unemployment. Lucas and Rapping (1969) incorporated the
intertemporal substitution hypothesis into a model explaining labor supply. The main idea of
intertemporal substitution is that the labor supply depends on all past and expected future wages
over the lifetime of current workers. If, due to an increase in the real interest rate, workers expect
future real wages to decrease relative to present wages, they will increase their labor supply.
However, tests of the intertemporal substitution hypothesis have yielded mixed results. While
Hall (1980) and Dutkowsky and Foote (1982) support the hypothesis, Card (1991) suggests that
careful consideration of the wealth effects associated with wage changes will undermine the
predictions of the lifecycle model.
7
Moreover, using U.S. data Mankiw, Rotemberg, and
Summers (1985) find no evidence of intertemporal substitution in labor supply.
Inflation
The Phillips curve suggests a short-run tradeoff between the unemployment rate and the rate of
inflation. An unexpected increase in prices reduces real wages, leading to an increase in the
demand for labor and a decline in unemployment. In the 1970s, however, the experience of
stagflation with high rates of both inflation and unemployment weakened the hypothesis of a
stable trade-off between the two. Critics argued that rational and well-informed workers would
realize that their real wages were falling and would ask for a nominal wage increase to
compensate for higher prices. The increase in real wage demands tends to reverse the drop in
unemployment. In the long run, the unemployment rate tends toward a level that is consistent
with a stable rate of inflation, i.e., the natural unemployment rate or the nonaccelerating inflation
rate of unemployment (NAIRU). Under the natural rate of unemployment theory, inflation would
begin to accelerate if unemployment were to fall below NAIRU.
6
It is likely that a rise in the interest rate will cause the relative cost of capital to increase, encouraging firms to
increase their use of labor. This may partially offset the negative effect of the interest rate increase on employment
through lower domestic demand.
7
The lifecycle model implicitly assumes that the marginal utility of wealth is constant. Card (1991) underlines that
the realization of wages provides new information that generates an update in the distribution of future wages and
brings about a revision in the forecast of the marginal utility of wealth. Unfortunately, there are no closed form
expressions for the marginal utility of wealth in an uncertain environment. Thus, the component of the change in
labor supply attributable to wealth effects is usually treated as a “nuisance”, and is eliminated by an instrumental
variables procedure.
halshs-00556938, version 1 - 18 Jan 2011
17
Difficulties arise in attempting to estimate the NAIRU because the rate changes over time.
Moreover, Akerlof and others (1996) show that the NAIRU itself depends on the inflation rate. In
the long run a steady rate of moderate inflation permits maximum employment and output; zero
inflation measurably increases the natural unemployment rate and correspondingly reduces
output.
8
Fitoussi and others (2000) found that changes in the rate of inflation tend to be negatively
correlated with unemployment in a sample of OECD countries.
Terms of trade
Favorable terms of trade shocks boost domestic demand and increase employment. A positive
terms of trade shock implies that export prices are rising or import prices are falling, suggesting
that more units of imports can be exchanged for a unit of exports. This has a direct effect on real
incomes. It would increase domestic demand, economic growth, and thus employment.
A change in the terms of trade may also affect labor supply decisions, but the effect is
ambiguous. Labor supply may decrease after a positive terms of trade shock due to the wealth
effect. At the same time, the increase in labor demand would raise wages, which would stimulate
labor supply. The overall effect of positive terms of trade shocks is likely to be a reduction in
unemployment.
In Algeria favorable terms of trade shocks reduced unemployment mainly by increasing labor
demand. Buoyant oil revenues have enabled the government to invest heavily in public
infrastructure, which has increased employment in the construction and public works sectors.
IV. E
CONOMETRIC
E
STIMATES
A. The Model
The 2003 World Economic Outlook (WEO) model provides a good framework for investigating
the determinants of unemployment. Building on related studies, the IMF (2003) looked at the
relationship between unemployment and labor market institutions in a sample of 20 OECD
countries for 1960–98 while controlling for various macroeconomic variables. The basic
specification is as follows:
, , 1 , , , , ,
1 1
J K
i t i i t j j i t k k i t i t
j k
u u X Z
α λ β γ ε
= =
= + + + +
8
They authors argue that wage rigidity interferes with the ability of some firms to make adjustments in real wages,
leading to inefficient reductions in employment when inflation approaches zero. Using U.S. data they find that
targeting zero inflation will lead to a large inefficiency in the allocation of resources, because the difference in the
sustainable rate of unemployment between operating with steady 3 percent inflation and steady zero percent inflation
is estimated at 1 to 2.6 percentage points.
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18
where
,
i t
u
is the unemployment rate at time t in country i;
i
α
is a country-specific effect;
j
X
is a
set of macroeconomic variables (productivity growth, the real interest rate, terms of trade shocks,
and inflation);
k
Z
is a vector of labor market institutional indicators; and
,
i t
ε
is an error term.
9
A modified version of this model is used to test why Algeria has experienced higher
unemployment than comparable countries, such as those in the MENA region and Eastern
European transition countries. Obviously, limited availability makes it impossible to use time
series data to assess the determinants of unemployment in Algeria at a macro level. Assuming
that the 2003 WEO model is valid for the sample considered, we try to explain the
unemployment rate differential between Algeria and other countries by differences in the
determinants of labor market performance. The model is as follows:
' ' ' ' '
, , , 1 , 1 , , , , , , , , ,
1 1
( ) ( ) ( )
J K
DZA t i t i DZA t i t j j DZA t j i t k k DZA t k i t i t
j k
u u u u X X Z Z
α λ β γ ε
= =
= + + + +
where the subscript DZA refers to Algeria. According to this model, if the coefficient of a given
variable is significant, this would imply that the variable accounts for the differential between
Algeria and the sample average.
B. Data and Methodology
Panel data are used as in IMF (2003). The sample consists of 24 countries (excluding Algeria), of
which 10 are in the MENA region and 14 in Eastern Europe.
10
Annual data for 1995–2005 are
used except for labor market institutions indicators, for which one observation per country is
available.
Productivity growth is measured by the change in output per worker—the most commonly used
indicator for international comparisons of productivity. Two main reasons explain why labor
productivity growth is more often used than TFP growth: (i) labor productivity growth is a more
general measure of productivity growth because it can be decomposed into capital deepening (an
increase in the amount of capital per worker), human capital accumulation, and TFP growth; (ii)
in contrast to TFP growth, data on labor productivity growth are easily available and do not
require any assumptions about the stock of capital and the elasticity of output with respect to
capital.
The indicators of labor market institutions used are hiring and firing costs, the employment
rigidity index, the percentage of managers ranking labor market regulation as a business
9
The full specification includes interactive terms and linear, and quadratic forms.
10
See Annex 2 for the list of countries. Turkey and Pakistan are not officially MENA countries but are included in
the sample.
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19
constraint, and the tax wedge.
11
Terms of trade shocks are defined as the percentage change in the
terms of trade weighted by the trade openness of the country. Table 3 reports the difference
between Algeria and the sample average for some variables. For example, between 1995 and
2005, unemployment in Algeria was 15 percentage points higher than the sample average while
labor productivity grew almost 5 percentage points less than the sample average.
Table 3. Mean Comparison Test: Algeria and the Sample Average, 1995–2005
(Percent, unless otherwise noted)
Unemployment rate 15.2
(30.69)***
Employment rigidity index 4.5
(4.87)***
Tax wedge 2.0
(3.28)***
Labor productivity growth -4.6
(6.28)***
Real interest rate -5.1
(4.34)***
Inflation -15.6
(2.30)**
Terms of trade shocks 3.9
(3.07)***
Notes: Absolute value of t statistics in parentheses;
*** significant at 1 percent, ** significant at 5
percent.
Three panel data estimators are considered. First, a random effect model is used so that we can
control for country heterogeneity using country-specific dummies and estimate the effects of the
time-invariant variables included in the model. However, the random effect model assumes that
country-specific effects are not correlated with the right-hand side variables. But it is likely to be
a strong assumption when dealing with labor market issues, so we also use a fixed effect model to
check the robustness of the result obtained by the random effect model. Finally, because
attempting to assess the effect of labor productivity growth on the unemployment rate raises
endogeneity issues that need to be addressed, we run an instrumental variable regression using
the System GMM estimator that allows us to control for reverse causation, omitted variable bias,
and measurement errors.
11
The 2003 WEO model takes into account variables such as union density, bargaining coordination, benefit
replacement rate, and central bank independence. But because the necessary data were not available, these variables
were excluded from our specification.
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C. Results
Labor market institutions did not seem to explain the differential in unemployment rates. Table 4
sets out the results of using the random effect model. In columns 1 to 3, only institutional
variables are introduced and none of them are significant, suggesting that the differential between
Algeria and the sample average was not due to stricter labor market regulation and a larger tax
wedge. One explanation might be the ambiguous effects of labor market flexibility on the
unemployment rate and the fact that the tax wedge in Algeria is not much higher than the sample
average.
12
Furthermore, the complexity of labor market regulation may not be fully captured by
one composite indicator. This result however does not imply that a more flexible labor market
would not help to reduce the unemployment rate. Keep in mind that the results are based on past
data and should not be treated as stable.
Civil violence in Algeria did account for the differential. It disrupted economic activity, caused
population movements, and increased unemployment. To take this factor into account, we add a
dummy equal to 1 for the years 1995 to 2001 and 0 thereafter. Its coefficient is positive and
significant (column 4), suggesting that political instability had increased the differential.
13
Macroeconomic shocks do matter, especially labor productivity growth. Labor productivity
growth in Algeria is almost 5 percent lower than the sample average, and the coefficient is
negative and significant (column 5). This suggests that lower productivity growth in Algeria
widened the gap between Algeria’s unemployment rate and that of other countries. This holds
even controlling for initial conditions (column 6). The coefficient of the lagged unemployment
rate is correlated with the current unemployment rate, suggesting that the differential tends to
persist over time. While the real interest rate and inflation proved not to be significant in
explaining the differential, positive terms of trade shocks induced by rising oil prices helped
Algeria reduce the differential.
14
12
Taking into account the interaction between the employment rigidity index and the tax wedge does not change the
results.
13
A similar result is found using the International Country Risk Guide (ICRG) index of political stability, though the
index is not available for all countries in the sample.
14
To control the unemployment rate differential for demographic factors, the population growth rate differential is
introduced, but the coefficient is nonsignificant. The main reason is probably the lag between population growth and
labor force growth. Introducing lagged population growth would, however, lead to endogeneity issues. Because the
lagged dependent variable is intended to control for initial conditions, omitting past population growth is not likely to
affect the results.
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21
Table 4. Determinants of the Unemployment Rate Differential between Algeria and Other Countries, 1995–2005
Random Effects
(1) (2) (3) (4) (5) (6)
Hiring costs (as a percent of salary) 0.10
(0.23)
Firing costs (weeks of wages) -0.04
(0.04)
Tax wedge 0.04 0.09 0.08 0.07 -0.35
(0.20) (0.18) (0.23) (0.16) (0.36)
Employment rigidity index 0.06 0.06 -0.03
(0.12) (0.11) (0.15)
Managers ranking labor regulations -0.23
as a business constraint (percent) (0.27)
Political instability dummy 4.90*** 5.80*** 2.68***
(0.50) (0.64) (0.35)
Labor productivity growth (lagged) -8.18** -4.69***
(3.65) (1.78)
Real interest rate 0.03
(0.03)
Inflation (log) -0.06
(1.90)
Terms of trade shocks (lagged) -0.07***
-0.06***
(0.02) (0.01)
Unemployment rate (lagged) 0.97***
(0.03)
Constant 12.96***
14.02***
15.13***
10.47***
9.41*** -2.30***
(2.11) (1.63) (1.92) (1.53) (1.78) (0.50)
Observations 167 167 144 167 111 135
Number of countries 21 21 17 21 15 19
R-squared 0.11 0.05 0.06 0.12 0.23 0.98
Notes: Standard errors in parentheses; *** significant at 1 percent, ** significant at 5 percent, * significant at 10 percent.
In sum, as long as Algeria experiences continuous terms of trade growth, that will offset the
unfavorable effect of lower productivity growth on the unemployment differential with other
countries and allow the country to reduce unemployment more rapidly than other countries.
Nevertheless, persistent lower productivity growth compared to other countries raises doubts
about the durability of the employment gains.
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22
The results are robust to fixed effects estimations (Table 5).
15
Using fixed effects estimations that
do not assume that country-specific effects are exogenous does not alter the results (columns 1
and 2). Given the relatively large time dimension of the data, we deal with likely error correlation
by means of a fixed effect model with AR(1) correction; all variables keep their signs and are
significant (column 3).
16
The fixed-effect estimates, however, may be subject to endogeneity bias. The main argument is
related to the likely endogeneity of labor productivity growth, because the causality may also run
from unemployment to labor productivity. Higher unemployment could actually reduce the return
on education and discourage investment in human capital, lowering future productivity. Also,
higher unemployment is found to depress economic growth (Daveri and Tabellini, 2000) and thus
labor productivity.
Other factors motivate the use of instrumental variable estimates: The lagged dependent variable
may be correlated with the error term, leading to endogeneity issues. Also, omitted variables bias
and measurement errors are likely to weaken the fixed-effects regressions.
Studies dealing with the determinants of productivity growth offer a range of variables that could
be used as instruments. Levine (1997) argues that financial development contributes to
productivity improvements by improving resource allocation and lowering transaction costs, both
of which facilitate more specialization and promote exchange. Beck, Levine, and Loayza (2000)
find that financial development is positively associated with TFP growth in a broad sample of
countries. The findings of IMF (2006) also suggest that financial development stimulates
productivity growth, proxied by either labor productivity or TFP growth. Financial development,
trade openness, and investments in human and physical capital are found to be beneficial to
productivity increases (IMF, 2006).
While financial development, trade openness, physical capital accumulation, and human capital
accumulation are good candidates to instrument labor productivity growth, valid instruments
should be correlated with the endogenous regressor but uncorrelated with the error term.
Financial development and human capital accumulation are unlikely to directly affect the
unemployment rate, but trade openness and physical capital accumulation are likely to do so.
17
Trade openness may increase unemployment in the short run due to a lack of labor market
flexibility or a change in the skills employers need. Physical capital accumulation may have a
direct effect on employment growth because capital and labor are substitutes.
15
As the indicators of labor market regulation are not significant, these are dropped from the model. This allows for
the use of the fixed-effect estimator.
16
The standard Durbin-Watson statistic is not appropriate for testing first-order autocorrelation when the panel is
unbalanced. The Baltagi-Wu locally best invariant (LBI) is the relevant statistic; however, exact critical values are
not available in the literature. A value of the Baltagi-Wu LBI-statistic significantly below 2 (1.71 in Table 5)
indicates that correction for serial correlation may be necessary.
17
Financial development and capital accumulation stimulate productivity and economic growth, which in turn help
reduce unemployment. An increase in the financial sector size is unlikely to directly affect the unemployment rate
because this sector is not labor-intensive.
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Table 5. Determinants of the Unemployment Rate Differential between Algeria and Other Countries: Alternative
Estimates, 1995–2005
Fixed Effects
Fixed Effects
with AR(1)
Correction
System
GMM
(1) (2)
(3)
(4) (5)
Political instability dummy 5.75*** 2.99***
2.52***
2.61*** 2.68***
(0.64) (0.41)
(0.58)
(0.35) (0.35)
Labor productivity growth (lagged) -7.76** -4.97**
-5.73***
-4.58*** -4.84***
(3.66) (1.94)
(1.81)
(1.74) (1.82)
Real interest rate 0.03
(0.03)
Inflation (log) -0.10
(1.90)
Terms of trade shocks (lagged) -0.07*** -0.06***
-0.06***
-0.06*** -0.06***
(0.02) (0.01)
(0.01)
(0.01) (0.01)
Unemployment rate (lagged) 0.86***
0.89***
0.99*** 0.98***
(0.07)
(0.10)
(0.03) (0.03)
Constant 9.95*** -0.76
-1.09
-2.54*** -2.37***
(0.57) (1.02)
(0.90)
(0.48) (0.47)
Observations 111 135
116
135 135
Number of countries 15 19
19
19 19
R-squared 0.49 0.81
0.72
Baltagi-Wu LBI
1.71
AR(2)
0.41 0.38
Hansen test
0.18 0.13
Notes: Standard errors in parentheses; *** significant at 1 percent, ** significant at 5 percent, * significant at 10 percent.
To address the issues raised by the endogenous right-side variable and the use of the lagged
dependent variable as an explanatory variable, we use the System GMM estimator developed by
Blundell and Bond (1998).
18
We also take advantage of the availability of both internal (lagged
values) and external instruments for labor productivity growth. Columns 4 and 5 of Table 5
present the results. In column 4, all the right-side variables are instrumented by their lagged
values. In column 5, labor productivity growth is instrumented by the degree of financial
development (measured by the ratio of private credit to GDP) and human capital accumulation
(measured by the secondary school enrollment rate); internal instruments are used for all other
variables except political instability, which is assumed to be exogenous in all regressions.
The results confirm the previous findings. The negative labor productivity growth differential
increased the unemployment rate differential between Algeria and the sample average, and the
18
See Bond, Hoeffler, and Temple (2001) for a description of the System GMM estimator and its application to
growth models.
halshs-00556938, version 1 - 18 Jan 2011
24
positive terms of trade shocks differential reduced the unemployment rate differential.
19
The
Hansen overidentification test shown in Table 5 does not reject the exogeneity of the instruments,
and the second autocorrelation test (also shown in Table 5) does not reject the null hypothesis of
no autocorrelation.
Table 6. Factors Affecting the Unemployment Rate Differential Between Algeria and the two Subgroups of
Countries: MENA and Transition Countries, 1995–2005
System GMM
(1)
(2)
(3) (4)
Political instability dummy 2.64***
2.68***
2.73***
2.70***
(0.34)
(0.35)
(0.35) (0.34)
Labor productivity growth (lagged) -7.23***
-4.78***
-5.24***
-8.40***
(2.27)
(1.82)
(1.84) (2.41)
Terms of trade shocks (lagged) -0.06***
-0.06***
-0.06***
-0.06***
(0.01)
(0.01)
(0.01) (0.01)
Unemployment rate (lagged) 0.98***
0.98***
0.97***
0.97***
(0.03)
(0.03)
(0.03) (0.03)
Labor productivity growth (lagged)*MENA 6.23*
7.35**
(3.60)
(3.66)
Terms of trade shocks (lagged)*MENA
-0.01
-0.02
(0.02)
(0.02)
Unemployment rate (lagged)*MENA
0.02 0.03
(0.02) (0.02)
Constant -2.49***
-2.38***
-2.34***
-2.55***
(0.47)
(0.47)
(0.46) (0.46)
Observations 135
135
135 135
Number of countries 19
19
19 19
AR(2) 0.80
0.38
0.37 0.94
Hansen test 0.45
0.12
0.42 0.57
Notes: Standard errors in parentheses; *** significant at 1 percent, ** significant at 5 percent, * significant at
10 percent. The baseline regression is that in column 5 of Table 5. MENA is a dummy variable equal to 1 for
MENA countries and 0 otherwise.
To examine whether the factors explaining the unemployment differential between Algeria and
MENA countries are different from those explaining the differential between Algeria and Eastern
European transition countries, we add an interactive term between each macroeconomic variable
and a dummy variable equal to 1 for MENA countries and 0 otherwise. The coefficient of the
interactive term between productivity growth and the MENA dummy is positive and significant
(Table 6). For instance, when Algeria is compared with other MENA countries, the marginal
19
Following Blanchard and Wolfers (2000), we tested interactions between labor market institutions and
macroeconomic shocks, but without significant results.
halshs-00556938, version 1 - 18 Jan 2011
25
impact of the labor productivity growth differential is –1.05 compared with –8.40 for the group
of transition countries (column 4). This suggests that labor productivity growth was most
important in accounting for the differential between Algeria and Eastern European countries.
20
V. C
ONCLUSION AND
P
OLICY
R
ECOMMENDATIONS
This paper looks at the factors underlying the gap between Algeria’s unemployment rate and that
of other MENA and transition countries over 1995–2005. The econometric results suggest that
slower labor productivity growth in Algeria increased the differential relative to the sample
average. In contrast, positive terms of trade shocks resulting from rising oil prices led to a
decrease in the gap. Neither labor market regulation nor the tax wedge seems to be more harmful
to Algeria than to other countries.
The following actions could be considered to improve employment in Algeria:
The government should pursue growth-enhancing policies that will create conditions for
enough long-term employment to absorb the growing work force and reduce
unemployment.
Structural reforms to increase productivity are critical to ensure a durable reduction in
unemployment. Promoting financial development, trade liberalization, private investment,
and human capital accumulation would contribute to productivity growth. Private sector-
led growth and investment should be the main engine of job creation, but this is unlikely
to occur where labor productivity is low. Productivity improvements and moderate wage
increases would stimulate employment growth.
Though labor market regulations seem not to be a major issue, easing restrictions on
hiring and firing would make the Algerian labor market more flexible and help reduce
unemployment. Specifically, shortening the notification period and the length of the
procedure for dismissal, lowering employer contributions intended to allow laid-off
workers to receive unemployment benefits, removing the obligation to maintain the
employment and activity of privatized firms, and allowing the employer to choose which
workers to lay off without constraints could make the labor market more flexible and
make it easier to create jobs. Broadening unemployment insurance coverage would help
lessen the social impact of these measures.
Similarly, though the tax burden on labor in Algeria does not seem to be a key factor in
explaining unemployment, given Algeria’s high unemployment rate, the fiscal space
provided by higher oil revenues could be used to lessen the tax burden on labor-intensive
activities to stimulate job creation.
20
We test also the interactive terms between labor market regulation indicators, inflation, interest rate and the
MENA dummy, but the results are not significant.
halshs-00556938, version 1 - 18 Jan 2011
26
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Scarpetta, S., 1996, “Assessing the Role of Labor Market Mobility in Europe: An Empirical
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pp. 43–98.
World Bank, 2004, MENA Development Report: Unlocking the Employment Potential in the
MENA (Washington: World Bank).
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Annex I. Data Sources
Variable Sources
Hiring costs (as a percent of salary)
Firing costs (weeks of wage)
Employment rigidity index
World Bank Doing Business Indicators
Database (2006)
Tax wedge
OECD (2006), World Bank (2005), and
author’s calculations
Labor productivity growth
Groningen Growth and Development
Centre, World Development Indicators
(2006)
Percentage of managers ranking labor
regulations as a key business constraint
Real interest rate
Inflation
Terms of trade shocks
World Development Indicators (2006)
Unemployment rate
World Development Indicators (2006),
Algerian authorities
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Annex II. The Sample
Eastern European
transition countries
MENA countries
Albania
Algeria
Bulgaria
Egypt, Arab Rep.
Croatia
Jordan
Czech Republic
Lebanon
Estonia
Morocco
Hungary
Pakistan*
Latvia
Saudi Arabia
Lithuania
Syrian Arab Republic
Macedonia, FYR
Tunisia
Poland
Turkey*
Romania
Yemen, Rep.
Slovak Republic
Slovenia
Ukraine
* Countries not officially listed as MENA countries.
halshs-00556938, version 1 - 18 Jan 2011
... SeeRodrik (1993) for a comprehensive overview of the trade policy reforms in developing countries.2 On the effect of trade openness on unemployment and inequality in developing countries, see, for instance,Revenga (1997) andAirola and Juhn (2008) for the case of Mexico,Currie and Harrison (1997) for Morocco,Goldberg and Pavcnik (2004) for Colombia,Kpodar (2007) for Algeria,Peluffo (2013) for Uruguay,Nicita (2008) for Madagascar,Balat and Porto (2007) for Zambia,Hasan et al. (2012) for India and Menezes-Filho and Muendler (2011) and Dix-Carneiro and Kovak (2017) for Brazil. SeeBellon (2016) for an cross-country study.3 ...
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