AGGREGATE LABOR MARKET MPI ACTS OF THE …siteresources.worldbank.org/INTLM/Resources/390041...Aims...

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


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


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


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


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


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:


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


-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


1b. Which income groups were hit first?

GDP growth

Growth of wage bill

15


-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


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.


18


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)


(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’


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


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


23


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:


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


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


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.


-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)


Post-crisis

-2

-1

0

1

2

3

All (36) EAP (5) ECA (17)

LAC (10)

MNA and

SSA (4)


Post-crisis

-2

-1

0

1

2

3

All (36) Lower Middle Income

(12)

Middle Income

(14)


(10)


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


Regression of the change in employment growth on country characteristics


31


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


(11)

Middle Income

(14)


(11)

Pre Crisis

Post Crisis

By Region

By Income


3b. How does labor force participation growth vary across regions and income groups?


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


(9)

Middle Income

(10)


(9)


Post-crisis

-5

-3

-1

1

3

5

All (28)

EAP (4)

ECA (12)

LAC (10)

MNA and SSA (2)


Post-crisis

-5

-3

-1

1

3

5


Moderately Hit (12)

Severely Hit (9)


Post-crisis

By Region


By Income


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


Regression of the change in earnings growth on country characteristics


35

3. How were they hit?3b. Were there similarities in change in unemployment

rates across region, income and severity?

By Region

By Income


-0.5

0

0.5

1

1.5

2

2.5

All (32) EAP (5) ECA (14)

LAC (9) MNA and SSA

(4)


Post-crisis

-0.5

0

0.5

1

1.5

2

2.5


(9)

Middle Income

(12)


(11)


Post-crisis

-0.5

0

0.5

1

1.5

2

2.5


Moderately Hit (11)

Severely Hit (11)


Post-crisis


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


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


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


-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


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


41


-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


42


-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


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

AGGREGATE LABOR MARKET MPI ACTS OF THE …siteresources.worldbank.org/INTLM/Resources/390041...Aims...

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