Understanding Firm Demand for
Temporary Labour in Developing Countries
MARIYA ALEKSYNSKA
(joint with Janine Berg)
ILO
DEVELOPING AND IMPLEMENTING POLICIES FOR A BETTER FUTURE AT WORK
GENEVA,
JULY 2015
I. Introduction
 Temporary employment prompts policy concerns
 Most of the research done for developed countries
 What factors explain the use of temporary labour in
developing countries? Is this part of development or
firm preference? Do labour market institutions play
a role?
II. Hypotheses
Flexibility
Cost saving
Technology
o Fluctuations in
demand (seasonality,
business cycle)
o Competition
o External shocks
o Hiring costs
(recruitment and
firm-specific training
vs screening)
o On-the-job (wages,
bonuses, paid leave,
social security etc)
o Termination costs
(especially as
compared to
terminating
permanent contracts)
o Extent of
standardisation
o Computerization
o Firm-specific knowhow
Balancing stability and
flexibility of workforce:
core vs periphery
III. Data Description
 World Bank Enterprises Survey
 118 countries, over 72,000 observations, 2006-2014
 Other data sources: WB for GDP, ILO for unemployment
and EPL data
IV. Descriptive Statistics
Incidence of temporary employment, as % of total wage
employment, in private sector, circa 2010
 The mean share of temporary workers is 11%
 Only about 40% of all firms employ temporary
labour
 Among those that do, the mean share is 27,5%
Distribution of the firm-level number of temporary employees,
as % of total employment, in firms employing
at least 1 temporary worker
0
1
Density
2
3
Kernel density estimate
0
.2
.4
.6
.8
1
temporary employees as % of all employees, employed by a firm in fiscal year
kernel = epanechnikov, bandwidth = 0.0230
Firms that do not employ temporary labour are smaller in size and
those not offering training; they have otherwise largely similar
characteristics to firms employing temporary workers.
Incidence of temporary employment, by sector
M/S
Sector
Mean percent of temporary
workers per firm
M
Textiles
0.24
M
Leather
0.32
M
Garments
0.27
M
Food
0.28
M
Metals and machinery
0.25
M
Electronics
0.25
M
Chemicals and pharmaceuticals
0.22
M
Wood and furniture
0.31
M
Non-metallic and plastic materials
0.28
M
Auto and auto components
0.20
M
Other manufacturing
0.25
S
Retail and wholesale trade
0.26
S
Hotels and restaurants
0.29
S
Construction, Transportation
0.39
S
Other services
0.26
Incidence of temporary employment, by sector
M/S
Sector
Mean percent of temporary
workers per firm
M
Textiles
0.24
M
Leather
0.32
M
Garments
0.27
M
Food
0.28
M
Metals and machinery
0.25
M
Electronics
0.25
M
Chemicals and pharmaceuticals
0.22
M
Wood and furniture
0.31
M
Non-metallic and plastic materials
0.28
M
Auto and auto components
0.20
M
Other manufacturing
0.25
S
Retail and wholesale trade
0.26
S
Hotels and restaurants
0.29
S
Construction, Transportation
0.39
S
Other services
0.26
Temporary employees and country income
.3
Correlation: -0.137
Timor Leste2009
Tanzania2013
Liberia2009
Togo2009
Uganda2013
.2
Kenya2013
Mongolia2009
Chad2009
Congo2009
Mongolia2013
Afghanistan2008
Peru2006
Bolivia2006
Benin2009
Vietnam2009
Philippines2009
Rwanda2011
DRC2010
Kenya2007
Ukraine2013
Tanzania2006 Peru2010
Kyrgyz
Republic2013
Honduras2006
Iraq2011
Panama2006
Colombia2010
Kosovo2013
Micronesia2009
BurkinaFaso2009
Mauritania2006
Bolivia2010
Mali2010
Paraguay2006
Niger2009
Vanuatu2009
Colombia2006
Nicaragua2006
Guyana2010
Gabon2009
Centralafricanrepublic2011
Elsalvador2010
Kosovo2009
ElSalvador2006
Rwanda2006
Kyrgyz
Republic2009
Tajikistan2013
Samoa2009
Gambia2006
Yemen2010
Mali2007
SriLanka2011
Uganda2006
Nepal2013
Ecuador2006 Venezuela2010
Paraguay2010
Venezuela2006
TrinidadandTobago2010
CapeVerde2009
Nicaragua2010
Djibouti2013 Montenegro2009
Georgia2008
Botswana2006
Bangladesh2007
Ethiopia2011
Armenia2009
Guatemala2006
Malawi2009
Madagascar2009
Tajikistan2008
Côte
d'Ivoire2009 Chile2006 Pakistan2007
Poland2009
Zambia2013
LaoPDR2012
StKittsandNevis2010
Grenada2010
Costarica2010
Nepal2009
Angola2006
Guatemala2010
Honduras2010
Cameroon2009
Bahamas2010
DRC2006
Georgia2013
Chile2010
Montenegro2013
Namibia2006
DRC2013
Nigeria2007
Moldova2009
Albania2007
Fiji2009
Barbados2010
Senegal2007
Ghana2007
SouthAfrica2007
StVincentandGrenadines2010
Botswana2010
Mauritius2009
Swaziland2006
Indonesia2009
Guinea2006
Mexico2010
Uruguay2006
Azerbaijan2009
Zambia2007
Burundi2006 Mozambique2007
Croatia2007
Bosnia
and
Herzegovina2009
DominicanRepublic2010
Croatia2013
Serbia2009
GuineaBissau2006
Angola2010
Eritrea2009
CzechBangladesh2013
Republic2009
Fyr
Macedonia2009
China2012
Uruguay2010
Estonia2009
Latvia2009
Russia2012
Brazil2009
Tonga2009
Albania2013
Lithuania2013
Kazakhstan2013
Russia2009
Azerbaijan2013
Lithuania2009
Serbia2013
Jamaica2010
Suriname2010
Ukraine2008 Mexico2006
Kazakhstan2009
Romania2009
Belarus2013
Latvia2013 Belarus2008
Belize2010
Bosnia and Herzegovina2013
Turkey2008
Armenia2013
Fyr Macedonia2013
Panama2010
Antiguaandbarbuda2010
Bulgaria2013
Hungary2009
Moldova2013
LaoPDR2009
Bulgaria2007 Romania2013
StLucia2010
Bulgaria2009
Dominica2010
Sierra Leone2009
0
.1
Lesotho2009
Bhutan2009
20
22
24
26
GDP PPP, in logs
28
30
0
1
2
3
Distribution of temporary employees, as per cent of firm’s
workforce, by legal regulations governing fixed-term work
0
.2
.4
.6
.8
x
FTCs prohibited for permanent tasks
FTCs authorized for permanent tasks
1
Temporary employees and EPL
.3
Correlation: 0.029
Tanzania2013
Uganda2013
Vietnam2009
Philippines2009
Afghanistan2014
DRC2010
Lesotho2009
Tanzania2006
Peru2010
Panama2006
BurkinaFaso2009
Niger2009
Centralafricanrepublic2011
Gabon2009
Elsalvador2010
Yemen2010
SriLanka2011
Venezuela2010
Georgia2008
Bangladesh2007
Armenia2009Ethiopia2011
Madagascar2009
Côte d'Ivoire2009
Zambia2013 Malawi2009Angola2006
Cameroon2009
Honduras2010
DRC2006
Georgia2013
Chile2010
Montenegro2013
DRC2013
Moldova2009
Senegal2007
SouthAfrica2007
Indonesia2009
Azerbaijan2009
Argentina2010Mexico2010
China2012 Angola2010
Fyr Macedonia2009 Czech Republic2009
Bangladesh2013
Russia2012
Serbia2013
Mexico2006
Romania2009
Antiguaandbarbuda2010
Bulgaria2013Panama2010
Hungary2009 Fyr Macedonia2013
Moldova2013
Romania2013
StLucia2010
Rwanda2011
Nigeria2007
0
.1
.2
Mongolia2009
Afghanistan2008
Mongolia2013
.2
.4
.6
Level of employment protection, regular contracts
.8
V. Empirical framework
Temp_share_all ijkt = αijk + β1i Xi + β2iYi + jj + kk + tt+ εijkt
Temp_share_all ij - share of temporary labour in firm i operating in sector j
country k and year t
Xi - the set of individual baseline firm characteristics
Yi - set of additional individual firm characteristics :
flexibility, cost, and technology factors
jj, kk , tt - sector, country, and year, by including the corresponding dummies
εijkt - error term
Estimations Step 1: Internal Factors
VARIABLES
(1)
VARIABLES
Flexibility
National market
0.00657***
(0.00192)
International market
0.0175***
(0.00368)
Informal competition
0.0107***
(0.00160)
Sales volatility
Training
Regulation
obstacle
2.11e-14***
-4.14E-15
Employment ratio
Total labour cost
0.0136***
0.000143***
0.00392***
(0.000569)
Constant
0.274***
(0.0211)
Observations
57,033
R-squared
0.184
0.00562***
(0.000578)
0.0117***
Certification
(0.000912)
-0.0108***
(0.00184)
Borrowed
technology
0.00535*
Constant
(0.00308)
0.397***
0.00286***
(0.00285)
0.00471***
0.00283***
Constant
(0.000734)
0.373***
(0.0220)
Observations
R-squared
(3)
Technology
Telecoms
problem
Education
obstacle
(3.67e-05)
Finance is an obstacle
VARIABLES
(0.000849)
(0.00220)
Employment ratio
(start)
(2)
Cost
48,752
0.125
(0.0654)
Observations
R-squared
27,336
0.121
Estimations Step 2: External Factors
Low-middle income
Upper-middle income
High-income
GDPgrowth
GDPgrowth_3y_lag
Unemployed
Macro
Macro, EPL
MACRO,
EPL, FTC
MACRO, EPL,
FTC, coverage
-0.00134
(0.0154)
-0.0503***
(0.0165)
-0.0512***
(0.0155)
0.000910
(0.00130)
-0.000388
0.00213
(0.0216)
-0.0517**
(0.0196)
-0.0463**
(0.0213)
0.000280
(0.00183)
0.000811
-0.00683
(0.0229)
-0.0503**
(0.0200)
-0.0555**
(0.0248)
0.000323
(0.00154)
-0.000832
-0.0573***
(0.0131)
-0.0766***
(0.0186)
-0.142***
(0.0212)
0.00128
(0.00139)
0.000984
(0.000720)
0.00101
(0.000743)
(0.000900)
0.000458
(0.000929)
0.0161
(0.0724)
(0.00117)
-0.000362
(0.00107)
0.0914
(0.0581)
0.148***
(0.0278)
0.112**
(0.0519)
-0.0359**
(0.0163)
0.00361
(0.0143)
0.116**
(0.0552)
(0.00205)
-0.00186
(0.00112)
0.175
(1.156)
0.106
(0.493)
-0.0572
(1.227)
-0.0819***
(0.0139)
0.00812
(0.0165)
0.0942
(0.472)
39,126
0.137
19,940
0.139
19,940
0.144
14,803
0.158
EPLEX
EPL Coverage
EPLEX*Coverage
FTC prohib perm
FTC dur unlim
Constant
Observations
R-squared
Estimations Step 3:
Disagregations by Sector and Country Income,
selected results
VARIABLES
(1)
(2)
(3)
(4)
Manuf
Services
Lower income
Upper income
International market
0.0215***
0.00690
0.0225***
0.0117**
Sales volatility
(0.00445)
2.11e-14***
(0.0119)
-3.54e-14
(0.00672)
2.29e-14**
(0.00487)
2.07e-14***
-4.14E-15
(2.86e-14)
(9.74e-15)
(5.79e-15)
0.000137***
8.07e-05
0.000240**
0.000100**
(4.28e-05)
(0.000107)
(0.000112)
(4.52e-05)
0.00483***
0.00160
0.00431***
0.00340***
(0.00106)
(0.00171)
(0.00157)
(0.00105)
Education
obstacle
0.00337***
0.00161
0.00421***
0.00175*
Observations
R-squared
(0.000940)
27,978
0.171
(0.00139)
12,698
0.245
(0.00131)
18,337
0.185
(0.000920)
22,339
0.174
Employment ratio
(start)
Regulation
obstacle
Key message: relevance of micro-factors varies across
sectors rather than across levels of development
Estimations Step 3:
Disagregations by Sector and Country Income,
selected results
(1)
Manuf
Valid grounds
Prohibited grounds
Trial period
Procedural requirements
Notice period
Severance / redundnacy pay
Redress
FTC prohib perm
FTC dur unlim
Constant
Observations
R-squared Key
(2)
Services
(3)
Lower income
(4)
Upper income
0.0695***
(0.0257)
0.0303
(0.0245)
-0.0119
(0.0217)
0.0213
(0.0303)
0.106
(0.0919)
-0.0782
(0.0474)
0.0288
(0.0271)
-0.0524***
(0.0185)
0.00756
(0.0219)
0.134*
(0.0693)
0.0676***
(0.0247)
0.00604
(0.0208)
-0.0390
(0.0215)
0.00627
(0.0201)
0.0189
(0.0663)
-0.0103
(0.0343)
0.0554
(0.0277)
-0.0506***
(0.0159)
-0.0177
(0.0179)
0.298***
(0.0600)
0.148***
(0.0315)
0.0387
(0.0261)
-0.108***
(0.0288)
-0.0401
(0.0415)
-0.00941
(0.0833)
-0.0474
(0.0267)
0.0839**
(0.0313)
-0.0909***
(0.0226)
-0.0157
(0.0213)
0.197*
(0.0993)
0.255***
(0.0482)
0.0782***
(0.0236)
0.0472***
(0.0116)
-0.00673
(0.0146)
0.152**
(0.0700)
-0.0714
(0.0471)
-0.0248
(0.0239)
-0.0416***
(0.0125)
0.0191
(0.0117)
-0.0436
(0.0542)
13,409
10,314
11,126
12,597
message: relevance
of 0.219
macro-factors
0.131
0.180varies across
0.168
levels of development rather than across sectors of activity
Final remarks
 We tested the relevance of flexibility, cost, and technology factors for




the firm use of temporary labour in developing countries
We confirmed that these factors, when measured at the micro level, are
at work, similarly to developed countries
At the macro level, the relevance is only partial: regulations governing
FTC matter, but regulations governing termination of regular contracts
have only a limited relevance; macroeconomic fluctuations have
limited relevance
Relevance of micro factors varies across sectors rather than across
levels of development
Relevance of macro factors varies across levels of development rather
than across sectors of activity, perhaps suggesting that compliance and
enforcement issues are at stake
Thank You
[email protected]