AGGREGATE LABOR MARKET IMPACTS OF THE FINANCIAL
CRISIS
IN SELECTED MIDDLE-INCOME COUNTRIES
OVERVIEWAims and objectivesData and indicatorsQuestions addressedPreliminary results When were they hit? Who was hit the most?
How were they hit?
2
AIMS AND OBJECTIVESThe main objective is to collect empirical
evidence on: The impact of the 2008 crisis on labor markets
in terms of 1. Intensity and 2. Timing
The main adjustment mechanisms and transmission channels:
1. The relative importance of employment and earnings in the adjustment process.
2. The extent and direction of sectoral shifts.
3
AIMS AND OBJECTIVES
The task also aims at Identifying any emerging patterns across
(a) geographical regions and (b) income groups.
Monitoring the results closely, and update them at regular intervals
4
THE DATA AND INDICATORS Data Source: ◦ CEIC and EMED databases, ◦ The Haver Analytics database ◦ supplemented by ILO Laborsta dataset
Frequency: Quarterly Coverage: 36 middle income countries across
the world. Largely LAC (Latin America), ECA (East Europe and Central Asia) and East Asia.
Period: March 2006 to September 2009 (where available).
5
THE DATA AND INDICATORS
6
Indicator Coverage/Source Percentage of countries
EmploymentWhole country 73.0
Only urban 16.2Unclear/Largely urban 10.8
EmploymentOnly formal 8.1All persons 75.7
Unclear/May exclude self-employed 16.2
EmploymentLFS/HHS 64.9
Establishment survey 16.2
Combination of two/Unclear 18.9
EarningsIndustry/Non agriculture 29.0
All sectors 61.3Unclear 9.7
EarningsLFS 9.7
Establishment survey 61.3
Combination/Unclear 29.0
THE DATA AND INDICATORSINDICATOR DEFINITION
Percentage point difference in Pre and Post Crisis Average of:
SOURCES
Change in Employment Growth
Growth in total persons employed
Country Statistical Offices Labour Force Surveys
Change in Earnings Growth
Growth in average monthly earnings
Country Statistical OfficesAnd ILO LaborSta, (usually Establishment Surveys.)
Change in Unemployment Rate
Ratio of unemployed to those in the labor force
Country Statistical Offices Labour Force Surveys
Change in Hours Worked Growth
Growth in hours worked Country Statistical Offices Labour Force Surveys
Change in SectoralEmployment Shares(Agriculture, Industry and Services)
Percentage of Employed in Sector to Total Employment
Country Statistical Offices Labour Force Surveys
7
Data Caveats:◦ The employment data is from Labor Force Surveys,
while the earnings data is from Establishment Surveys. Compiling the two together is problematic if the earnings levels for self-employed are different from salaried. Hence, we use the ‘change in the growth’ of earnings as our indicator, as that requires less harsh an assumption.◦ Very small sample of countries: 36 MICs Highlights need for data capacity-building and timely data
acquisition ◦ Inconsistency in data: 16% of the countries have data only on urban centers. 8% enumerate employment for only formal employees 29% of earnings do not include the agricultural sector
8
THE DATA AND INDICATORS
9
EmploymentAlbania Argentina Armenia Belarus Brazil BulgariaChile China Colombia Dom. Rep. Ecuador EgyptGeorgia Jamaica Kazakhstan Kyrgyz Rep. Latvia LithuaniaMacedonia Malaysia Mauritius Mexico Moldova MoroccoPeru Phillipines Poland Romania Russia SerbiaSouth Africa Sri Lanka Thailand Turkey Ukraine Venezuela
EarningsArgentina Armenia Belarus Brazil Bulgaria Chile ChinaColombia Ecuador Kazakhstan Latvia Lithuania Macedonia MexicoMoldova Paraguay Peru Phillipines Poland Romania SerbiaSouth Africa Sri Lanka Thailand Ukraine Uruguay Venezuela West Bank
Hours WorkedArgentina Brazil Bulgaria Colombia Latvia Mexico PeruPoland Romania Serbia Uruguay West Bank and Gaza Strip
THE DATA AND INDICATORS
Change in the GDP growth: used as indicator of severity of the crisis on the economy as a whole.
Change in the rate of growth of wage bill: used as summary indicator of the labor market impact.
10
Indicators for ‘severity of impact’
THE DATA AND INDICATORS Why do we use the % point ‘change in growth rates’
instead of the % ‘growth rates’?◦ We are more interested in countries that had a fall in growth rates
from 10% to 1%, than in countries that had a fall in growth from 1% to -1%. Countries that had a positive GDP growth in the 3rd quarter of 2009, on
an average had a growth rate that was 6.4 % points below their growth rate pre-crisis.
Example: Argentina grew at 1.7% in the 3rd quarter of 2009, but this was 6.7% points below it’s pre-crisis growth.
◦ Since our establishment surveys don’t enumerate self employed workers, our assumption is that ‘change in the growth rates in earnings’ for the salaried workers are similar to those for the self-employed. This assumption is less harsh than assuming that the growth rates in earnings for the two groups are the same.
◦ The ‘change in growth’ deseasonalises any seasonal shifts.
11
Questions Addressed
1. When were they hit?
2. Who was hit the most?
3. How were they hit?
12
1. When were they hit?
The crisis struck in the last quarter of 2008
Decline in earnings growth preceded the other indicators ◦ Real earnings began their descent in early
2008, possibly due to the price rises in the food crisis.
ECA’s wage bill hit first ◦ No consistent decline in East Asian wage bill
13
MAIN MESSAGES:
1. When were they hit?
Only for the common sample of countries for which data exists across all indicators in the graph
-5
-3
-1
1
3
5
7
9
11Employment GrowthGDP GrowthWage Bill Growth
1a. Which indicators were affected first?
-7
-5
-3
-1
1
3
5
7
9
11
Dec
-06
Mar
-07
Jun-
07
Sep-
07
Dec
-07
Mar
-08
Jun-
08
Sep-
08
Dec
-08
Mar
-09
Jun-
09
Sep-
09
Hours Growth
Earnings Growth
Employment Growth
1. When were they hit?
-10
-5
0
5
10
15
Mar
-07
Jun-
07
Sep-
07
Dec
-07
Mar
-08
Jun-
08
Sep-
08
Dec
-08
Mar
-09
Jun-
09
Sep-
09
Lower Middle Income
Middle Income
Higher Middle Income
-10
-5
0
5
10
15
Mar
-07
Jun-
07
Sep-
07
Dec
-07
Mar
-08
Jun-
08
Sep-
08
Dec
-08
Mar
-09
Jun-
09
Sep-
09
Lower Middle Income
Middle Income
Higher Middle Income
1b. Which income groups were hit first?
GDP growth
Growth of wage bill
15
1. When were they hit?
-6
-1
4
9
14
ECA
LAC
EAP
-6
-1
4
9
14
ECA
LAC
EAP
MEA
1c. Which regions were hit first?
GDP growth
Growth of wage bill
16
2. Who was hit the most?
Higher middle-income and ECA countries experienced largest reduction in total wage bill growth. ◦ LAC and low-income MICs also affected
The overall wage bill slowdown is closely related to GDP slowdown, controlling for region and income levels.◦ Effect of growth slowdown is greater when
growth is low
17
MAIN MESSAGES:
2a. Similarities across regions and income groups
-15.0
-10.0
-5.0
0.0
EAP (4)ECA (12) LAC (8)
South Africa All (25)
-8.1
-12.9
-6.3 -5.8
-9.8
-3.5
-10.7
-5.6-6.5
-7.7
Change in GDP Growth
Change in Wage Bill Growth
-15.0
-10.0
-5.0
0.0
Lower Middle
Income (8)
Middle Income
(10)
Higher Middle
Income (7) All (25)
-11.1
-7.9
-10.9-9.8-9.0
-3.4
-12.4
-7.7
Change in GDP Growth
Change in Wage Bill Growth
Severity of Impact By Region
Severity of Impact By Income
Number of countries in parenthesis.
2. Who was hit the most?
18
2. Who was hit the most?
19
-5.0
-3.0
-1.0
1.0
3.0
5.0
EAP (4) ECA (12)
LAC (8)
South Africa
(1)
All (25)
GDP growth
Wage bill growth
-5.0
-3.0
-1.0
1.0
3.0
5.0
Lower Middle Income
(8)
Middle Income
(10)
Higher Middle Income
(7)
All (25)
GDP growth
Wage bill growth
2a. Similarities across regions and income groups
These graphs have ‘growth rates’ and not the ‘change in growth rates’
2. Who was hit the most?
20
Argentina
Armenia
Belarus
Brazil
BulgariaChile
China
ColombiaEcuador
Kazakhstan
Latvia
Lithuania
Macedonia
Mexico
Moldova
PeruPhillipinesPoland
Romania
SerbiaSouth Africa
Sri Lanka
Thailand
Ukraine
Venezuela
-20
-10
01
02
0G
DP
gro
wth
-20 -10 0 10 20Wage bill growth
2b. Which countries were worst hit?(by growth rates)
Correlation Coefficient =0.52; 25 Countries
Wage bill adjustment smaller than GDP adjustment
Wage bill adjustment larger than GDP adjustment
2b. Which countries were worst hit?(by change in growth rates)
UkraineLatvia ArmeniaLithuania
KazakhstanChina
Romania ThailandMexicoBulgariaPeruMoldovaSerbia ColombiaEcuador ArgentinaChileVenezuela MacedoniaBelarusSouth AfricaPoland PhillipinesSri Lanka
Brazil-3
0-2
0-1
00
10
Cha
ng
e in
GD
P G
row
th
-30 -20 -10 0 10Change in Wage Bill Growth
Wage bill adjustment smaller than GDP adjustment
Wage bill adjustment larger than GDP adjustment
Correlation Coefficient =0.69; 25 Countries
2. Who was hit the most?
21
Kazakhstan
China
RomaniaThailand
Mexico
Bulgaria PeruMoldova RepublicSerbia ColombiaEcuadorArgentinaChileVenezuela Belarus
South AfricaPoland
PhilippinesSri Lanka
-20
-15
-10
-50
Cha
nge
in G
DP
gro
wth
-20 -15 -10 -5 0Change in Wage bill growth
Correlation coefficient: 0.0437Not significant19 countries
Bulgaria PeruMoldova Republic
ColombiaEcuadorArgentinaChileVenezuela Belarus
South Africa
Poland
PhilippinesSri Lanka
-10
-50
Cha
nge
in G
DP
gro
wth
-10 -5 0Change in Wage bill growth
Correlation coefficient: -0.2871Not significant13 countries
2c. Determinants of Impact Severity
Percentage point change in total wage bill growth
Specification 1 Specification 2
East Asia (base region)Europe and Central Asia -1.78 -1.49
Latin America -2.18 -2.05South Africa -3.93 -6.98*
Log Per Capita GDP -1.64 -1.32Change in GDP growth rate 0.99*** 0.16
Negative GDP growth (dummy) 11.54*
Change in GDP growth X negative GDP growth 1.26***
Constant 16.62 8Adjusted R2 0.39 0.50
Number of Observations 25 25
Regression of percentage point change in total wage bill growth on country characteristics
2. Who was hit the most?
23
3. How were they hit?
The labor market can adjust via…
Sectoralreallocation of employment
Total wage bill change
Employment Earnings
Wage rates
Hours24
Labor force participation
Unemployment rate
Most adjustment occurred through earnings rather than employment, and hours rather than wage rates.
Much smaller employment slowdowns in East Asia and Lower middle-income countries
Industrial employment fell in severely hit and high income countries ◦ Service sector expanded in most affected
countries
25
3. How were they hit?MAIN MESSAGES:
3. How were they hit?
26
Number of countries
2 Year Pre Crisis Average
Post-crisis Difference between Post and Pre Crisis
Change in total wage bill 25 8.9 1.2 -7.7
Percent change in employment 36 1.7 0.3 -1.5
Percent change in earnings . 28 5.7 0.9 -4.8
Percent change in wages 11 4.8 4.6 -0.2
Percent change in hours. 12 0.7 -3.2 -3.8
Sectoral shares
Change in industry share 18 -0.1 -0.6 -0.5
Change in agricultural share 18 -0.6 -0.2 0.3
Change in service share 18 0.6 0.7 0.1
3. How were they hit?
96%
4%
Change in average growth of earnings (-3.6 % points)
% Due to Hours
% Due to Wages
25%
75%
Change in growth of average total wage bill (-5.9 % points)
% Due to Employment
% Due to Earnings
3a. Decomposition of total wage bill and earnings for the “Average Country”
27
3. How were they hit?
28
-6
-5
-4
-3
-2
-1
0
LAC
ECA
Change in growth of hours worked.The change is the difference between ‘the post-crisis average growth in hours’ and ‘the pre-crisis average growth in hours.’
Serbia was the worst hit among the 5 ECA countries with data on hours worked. The other ECA countries had an average decline of 1% point only.
Argentina, Mexico and Brazil had the largest reduction in hours growth among the 6 LAC countries.
3. How were they hit?
-12 -10 -8 -6 -4 -2 0
All
Low
Medium
High
-1.536
-0.684
-1.472
-2.618
-4.864
-5.016
-0.828
-9.282
% Due to Employmen% Due to Earnings
-12 -10 -8 -6 -4 -2 0 2
All
EAP
ECA
LAC
South Africa
-1.536
1.44
-2.73
-1.386
-0.774
-4.864
-5.04
-4.27
-4.914
-7.826
% Due to Employment% Due to Earnings
-12 -10 -8 -6 -4 -2 0
All
Mild
Moderate
Severe
-1.536
0.228
-0.966
-3.51
-4.864
-7.828
-3.634
-4.29
% Due to Employment
% Due to Earnings
3b. Decomposition of the total wage bill by region, income and severity
By Region
By Income Group
By Severity of impact
29
3. How were they hit?3b. How does employment growth vary across
regions and income groups?
-2
-1
0
1
2
3
All (36) Mildly Hit (9)
Moderately Hit (15)
Severely Hit (12)
2 Year Pre Crisis Average
Post-crisis
-2
-1
0
1
2
3
All (36) EAP (5) ECA (17)
LAC (10)
MNA and
SSA (4)
2 Year Pre Crisis Average
Post-crisis
-2
-1
0
1
2
3
All (36) Lower Middle Income
(12)
Middle Income
(14)
Higher Middle Income
(10)
2 Year Pre Crisis Average
Post-crisis
By Region
By Income
By Severity of impact on GDP
3b. Were there similarities in employment growth across regions and income groups?
Explanatory variables Specification 1 Specification 2
EAP (base region) ECA -2.89*** -2.98***LAC -2.98*** -2.95***
MENA and SSA -3.61*** -3.63***Log Per Capita GDP -1.47** -1.48**
Change in GDP growth rate 0.25*** 0.29***Negative GDP growth (dummy) -0.8
Change in GDP growth X negative GDP growth (dummy) -0.08
Constant 14.89*** 15.30**Adjusted R
20.435 0.4
Number of Observations 35 35
Regression of the change in employment growth on country characteristics
3. How were they hit?
31
3. How were they hit?
32
0.0
0.5
1.0
1.5
2.0
2.5
All (36)
EAP (5)
ECA (18)
LAC (9)
MEA (4)
Pre Crisis
Post Crisis
0.0
0.5
1.0
1.5
2.0
2.5
All (36) Mild (12) Moderate (13)
Severe (11)
Pre Crisis
Post Crisis
0.0
0.5
1.0
1.5
2.0
2.5
All (36) Lower Middle Income
(11)
Middle Income
(14)
Higher Middle Income
(11)
Pre Crisis
Post Crisis
By Region
By Income
By Severity of impact on GDP
3b. How does labor force participation growth vary across regions and income groups?
3. How were they hit?
33
3b. How does change in labor force participation growth vary across regions and income groups?
Explanatory variablesSpecification 1 Specification 2
EAP (base region) ECA LAC -0.49 -0.60
MENA and SSA -2.06*** -2.00***Log Per Capita GDP -2.57*** -2.61***
Change in GDP growth rate 0.22 0.23Negative GDP growth (dummy) 0.08 0.12***
Change in GDP growth X negative GDP growth (dummy) -1.21
Constant -0.10Adjusted R
2 -0.09 0.20Number of Observations 0.024 -0.024
3b. Were there similarities in earnings growth across region, income and severity?
-5
-3
-1
1
3
5
All (28) Lower Middle Income
(9)
Middle Income
(10)
Higher Middle Income
(9)
2 Year Pre Crisis Average
Post-crisis
-5
-3
-1
1
3
5
All (28)
EAP (4)
ECA (12)
LAC (10)
MNA and SSA (2)
2 Year Pre Crisis Average
Post-crisis
-5
-3
-1
1
3
5
All (28) Mildly Hit (7)
Moderately Hit (12)
Severely Hit (9)
2 Year Pre Crisis Average
Post-crisis
By Region
By Severity of impact on GDP
By Income
3. How were they hit?
3b. Were there similarities in change in earnings growth across region, income and severity?
Explanatory variables Specification 1 Specification 2
EAP (base region) ECA -1.18 -0.67LAC -0.56 -0.39
MENA and SSA -0.71 -1.97Log Per Capita GDP -1.13 -0.73
Change in GDP growth rate 0.67** 0.01Negative GDP growth (dummy) 7.14
Change in GDP growth X negative GDP growth (dummy) 0.93**
Constant 10.96 3.3Adjusted R
20.192 0.25
Number of Observations 25 25
Regression of the change in earnings growth on country characteristics
3. How were they hit?
35
3. How were they hit?3b. Were there similarities in change in unemployment
rates across region, income and severity?
By Region
By Income
By Severity of impact on GDP
-0.5
0
0.5
1
1.5
2
2.5
All (32) EAP (5) ECA (14)
LAC (9) MNA and SSA
(4)
2 Year Pre Crisis Average
Post-crisis
-0.5
0
0.5
1
1.5
2
2.5
All (32) Lower Middle Income
(9)
Middle Income
(12)
Higher Middle Income
(11)
2 Year Pre Crisis Average
Post-crisis
-0.5
0
0.5
1
1.5
2
2.5
All (32) Mildly Hit (10)
Moderately Hit (11)
Severely Hit (11)
2 Year Pre Crisis Average
Post-crisis
3. How were they hit?
Percentage point change in Unemployment rates
Specification 1 Specification 2
EAP (base region) ECA 1.15 0.82LAC -0.29 -0.1
MENA and SSA 0.23 -0.1Log Per Capita GDP 1.34** 1.31**
Change in GDP growth rate -0.12** -0Negative GDP growth (dummy) -2.23**
Change in GDP growth X negative GDP growth (dummy) -0.21*
Constant -10.72** -9.67**Adjusted R
20.426 0.49
Number of Observations 30 30
Regression of the percentage point change in unemployment rates on country characteristics
3b. Were there similarities in change in unemployment rates across region, income and severity?
37
3. How were they hit?
38
3d. Shifts in employed persons across sectors
-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0
All (21)
Mild (6)
Moderate (6)
Severe (9)
-0.3
-0.1
-0.4
-0.5
0.6
0.2
0.6
0.9
-0.2
-0.0
-0.3
-0.3
-0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8
All (21)
EAP (6)
ECA (11)
LAC (4)
-0.3
-0.4
-0.3
-0.4
0.6
0.5
0.7
0.6
-0.2
-0.1
-0.3
-0.2
-0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8
All (21)
Lower Middle Income (7)
Middle Income (8)
Higher Middle Income (6)
-0.3
-0.2
-0.4
-0.4
0.6
0.7
0.5
0.7
-0.2
-0.5
-0.1
-0.1
Change in industrial shareChange in services shareChange in agriculture shareBy Income group
By Severity of impact
Change in the sectoral shares of employment
3. How were they hit?
-0.4 -0.2 0 0.2 0.4
All
EAP
ECA
LAC
-0.2
-0.2
-0.2
-0.4
0.1
0.1
-0.1
0.4
0.2
0.1
0.3
0
-0.6 -0.4 -0.2 -1E-15 0.2 0.4
All
Low
Medium
High
-0.2
-0.2
-0.1
-0.6
0.1
0.2
-0.1
0.1
0.2
-0.1
0.2
0.5
Change in the Change in Industrial Share of Employment (% point)
Change in the Change in Services Share (% point)
Change in the Change in Agricultural Share of Employment (% points)
-0.6 -0.4 -0.2 -1E-15 0.2 0.4
All
Mild
Moderate
Severe
-0.2
0
-0.1
-0.6
0.1
-0.2
0
0.3
0.2
0.1
0.1
0.3
3d. Shifts in employed persons across sectors
By Region
By Income group
By Severity of impact39
Change in the change in the sectoral shares of employment
3. How were they hit?
40
3e . Microsimulation results for Mexico, Philippines and Bangladesh
-4
-3.5
-3
-2.5
-2
-1.5
-1
-0.5
0
Mexico Bangladesh Phillipines
% Change in employment between benchmark and crisis
3. How were they hit?
41
3e . Microsimulation results for Mexico, Philippines and Bangladesh
-3.7
-4.8
-2.3
-5.5
-7.3
-8.8
-2.4
-1.6
-8.8
-10
-9
-8
-7
-6
-5
-4
-3
-2
-1
0
Total HH IncomeHH Labor Income HH Remittances
Philippines
Mexico
Bangladesh
3. How were they hit?
42
3e . Microsimulation results for Mexico, Philippines and Bangladesh
-2.3
-1
-0.2
-3.5
-1.9
-0.2
-1.2
-0.3
1.2
-4
-3
-2
-1
0
1
2
Poverty Headcount Poverty Gap Gini
Philippines
Mexico
Bangladesh
3. How were they hit?
Mexico and Brazil experienced a large reduction in hours worked (7.3%) and a fall in the growth of hours worked (7.9%points)
Russia and Mexico witnesses a sharp fall in employment (1.5 %), and a fall in the growth of employment (3.6 % points)
Russia also experienced a sharp rise in unemployment rates (2.1 % points)
Mexico and Russia had a negative GDP growth of 6.5%, and this was 12.3%points below their pre-crisis GDP growth.
Mexico witnessed a fall in wage rate growth, hours growth and employment growth, pulling down it’s wage bill growth.
43
What happened to the large economies?
Next steps:
◦Continue to track methodology and update results every quarter.
◦ Study the micro-data to get a disaggregated picture and to get a better idea about where the macro-data is coming from.
44