GEORGIA: RECENT TRENDS AND DRIVERS OF...

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GEORGIA: RECENT TRENDS AND DRIVERS OF POVERTY REDUCTION (FY16 GEORGIA POVERTY ASSESSMENT) POVERTY AND EQUITY GLOBAL PRACTICE AUGUST 17 2016

Transcript of GEORGIA: RECENT TRENDS AND DRIVERS OF...

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GEORGIA: RECENT TRENDS AND

DRIVERS OF POVERTY REDUCTION(FY16 GEORGIA POVERTY ASSESSMENT)

POVERTY AND EQUITY GLOBAL PRACTICE

AUGUST 17 2016

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Summary

Economic growth translated into improvements in living conditions for everyone in the country, especially for those at the bottom of the income distribution.

Poverty decreased for the fourth consecutive year in 2014, but it still affects close to one third of the country (32 percent of population living at less than US$2.5/day 2005 PPP poverty line).

Between 2010-2014 households’ income from economic activities played a significant role in reducing poverty. This is in contrast to the pre-2010 period when income from economic activities played a limited role and income from social transfers were more important for poverty reduction.

Government’s redistributive policies continue to play a significant role in lifting households out of poverty.

Households with per capita spending above the $5/day line are better integrated into the services sector, especially in high-skilled jobs, than those households living on per capita spending of between $2.5/day and $5/day (“vulnerable households”).

Context play a more important role than endowments (such as, education level) in explaining the inability of the persistently poor to escape poverty.

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Outline

• Recent poverty trends ($2.5/day)

• Drivers of poverty reduction

• Inclusive access to economic opportunities

• A deeper look at the rural economy

• The role of fiscal policy

• Profile of labor market outcomes for those living above the poverty line

• Poverty persistence in Georgia

• Policy discussion

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POVERTY TRENDS 2010-2014

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Robust economic growth of 2010-2014 slowed down in 2015 due to

external factors

5

9.4

12.6

2.4

-3.7

6.27.2

6.4

3.44.6

2.8 3

4.55

-6

-4

-2

0

2

4

6

8

10

12

14

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016f 2017f 2018f

Average

5.0

Source: CPS 2014-2017, Macro Poverty Outlook – Spring 2016 edition

Average

5.6

Note: 2016-2018 are

forecasts produced by

the WB.

Georgia Real GDP growth 2006-2018f

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Economic growth accompanied by sustained poverty reduction...

Source: WB staff calculations based on 2006-2014 IHS.

Note: 2015-2018 poverty rates are forecasts

based on the elasticity of GDP-poverty from the

2010-2014 period. These estimates will be

updated as forecasted GDP is updated and

new IHS rounds are available.

35.7

42.6

45.843.0

45.146.7

44.842.5

36.0

32.3

31.0

29.427.5

25.5

17.2

25.4

42.8

10

15

20

25

30

35

40

45

50

55

60

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015f 2016f 2017f 2018f

Georgia poverty rate, $2.5/day 2005 PPP line

National Tbilisi Rest Urban Rural

WB simulations show that a price

increase of 6 percent (as observed

between 2014Q3-2015Q3) would

have led to poverty increase.

However, positive trends in labor

earnings, agricultural income and

social transfers are expected to

have offset these impacts.

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…and higher living standards across the distribution

-8-4

04

81

2

An

nu

al g

row

th r

ate

%

1 10 20 30 40 50 60 70 80 90 100Consumption percentiles

Growth incidence 95% confidence bounds

Growth in mean Growth at median

Mean growth rate

Georgia (2010-2014)

19.218.1

16.5

13.011.4

10.5 10.08.7

6.55.6

0

5

10

15

20

25

2010 2011 2012 2013 2014

Gap Severity

Source: WB staff calculations based on 2010-2014 IHS.

Note: Poverty gap measures the average distance to the poverty line

for the poor. It is expressed as a percentage of the poverty line. Poverty

severity is the average of squared distance, thus giving more

importance to the extreme poor.

Source: WB staff calculations based on 2010-2014 IHS.

Note: Growth incidence curves measure the change between the initial

and ending period for each percentile of the welfare distribution.

Growth Incidence Curve shows a pro-poor growth

pattern over 2010-2014

Poverty Gap (FGT1) and Poverty Severity (FGT2)

show improvements below the poverty line

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Inspite of the recent decrease, the poverty rate is still high compared to

countries with similar levels of GDP per capita…

Georgia (2014)Kyrgyz Republic

(2014)Armenia (2014)

FYR Macedonia (2013) Romania (2012)

Albania (2012)

Turkey (2013)Moldova (2014)

0

5

10

15

20

25

30

35

0 5,000 10,000 15,000 20,000 25,000

Povert

y headcount

(US

$2.5

/day

2005 P

PP

)

GDP per capita (2005 PPP US$)

Poverty rate and GDP per capita, selected countries ECA (c. 2014)

Source: WB staff calculations based on data from the ECAPOV harmonization.

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…and differences in living standards across regions persist

Source: WB staff calculations based on 2014 IHS.

Poverty Headcount by Regions ($2.5/day 2005 PPP)

Georgia 2014

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Inequality also decreased likely driven by improved welfare among the

less well-off. Shared prosperity indicator shows similar pattern.

6.4

7.76.9

5.3

8.3

9.8

8.77.9

0

2

4

6

8

10

12

National Tbilisi Rest Urban RuralA

nn

ual

ized

gro

wth

201

0-2

014

(P

erce

nta

ge)

Shared Prosperity Indicator

All population Bottom 40 percent

Source: WB staff calculations based on 2010-2014 IHS.

Note: Shared prosperity measures annualized growth of mean per capita consumption

expenditure of the bottom 40 percent of the population. This is compared to annualized

growth of mean consumption of the total population. World Bank standardized

consumption expenditure is used. This differs from Geostat’s consumption expenditure.

42.141.6 41.3

40.0 40.1

2.62.5 2.5

2.5 2.5

2.82.9

2.72.6 2.6

2.0

2.2

2.4

2.6

2.8

3.0

3.2

3.4

3.6

3.8

4.0

35

36

37

38

39

40

41

42

43

44

45

2010 2011 2012 2013 2014

Inequality Indicators

Gini

Ratio 90th/50th percentile

Ratio 50th/10th percentile

Source: WB staff calculations based on 2010-2014 IHS.

Georgia 2010-2014

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Despite improvements, Georgia must pay attention to:

(a) those who remain in poverty for long time (poverty persistence);

(b) potential risk of poverty increase due to macro conditions

31.8

21.5

16.114.2

16.5

Perc

enta

ge o

f popula

tion

(a) Poverty status 2009-2011-2013

2.9

1.50.8

-0.04

-10

0

10

20

30

40

50

Rate Gap Severity Gini

Poverty Inequality

Actual 2014 $2.5/day

Adding 2015 inflation effect

Adding 2015 inflation effect adjusted by consumption bundle

Source: Welfare Monitoring Survey 2009-2011-2013 panel. Nationally

representative household survey (See Annex slides for more information)

Note: Persistent poverty is defined as being poor in 2009, 2011 and 2013. In

and out are households who escape poverty in 2011 and fall back in 2013,

or that fall to poverty in 2011 and escape in 2013.

(b) Welfare effects of 2015 Inflation

Source: WB staff calculations based on 2014 IHS (Q3).

Note: “Inflation effect” estimated deflating consumption by national average price

increases 2014Q3-2015Q3 (estimated at 6 percent) and re-estimating poverty.

“Inflation effects adjusted by consumption bundle” is estimated similarly but using a

household-level price increase which reflects the household consumption basket.

See Cancho et al. (2016) for more details.

WB simulations show that a price

increase of 6 percent (as observed

between 2014Q3-2015Q3) would

have led to poverty increase.

However, positive trends in labor

earnings, agricultural income and

social transfers are expected to

have offset these impacts.

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Share of vulnerable population is also growing

(percentage of those who live just above the poverty line)

47 45 43 36 32

34 35 3537

37

15 16 17 21 24

4 4 5 5 7

0

10

20

30

40

50

60

70

80

90

100

2010 2011 2012 2013 2014

Poverty and Vulnerable groups, 2010-2014 (percentage)

<$2.5 $2.5 - $5 $5 - $10 $10+

Poor

Moderate

Poor

Vulnerable

Middle-class

Source: WB staff calculations based on 2010-2014 IHS.

Note: All measures based on US$ 2005 PPP. $2.5/day is the ECA regional extreme poverty line, $5/day is the ECA

regional moderate poverty line. Above $10/day is considered middle class.

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DRIVERS OF POVERTY REDUCTION

2010-2014

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Real incomes increased across rural and urban areas 2010-2014

174.8

206.6

174.7157.4

242.1

300.9

235.5214.2

8% 10% 8% 8%

0

50

100

150

200

250

300

350

National Tbilisi Rest Urban Rural

Average monthly per capita income (bars, 2010-2014, 2014 GEL) and annualized growth (numbers in bold), by region

2010 2014

Source: WB staff calculations based on 2010-2014 IHS.

Note: Income includes labor earnings, agricultural income, social protection, remittances, inter-household transfers and

other minor sources. Numbers at the column base represent average annual growth 2010-2014.

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4%11%

6%2%

18%16%

21%

13%13%

6%1% 11%

11%

8%

8%

14%

6%

10%

7%

4%

-10%

0%

10%

20%

30%

40%

50%

National Tbilisi Rest Urban Rural2006-2008National*

Drivers of income increases on average, Georgia 2010-2014

Share adults Employment Labor income Agricultural income

Social Protection Private transfers Property income

Total Income Growth

2006-2008

(National)*

Source: WB staff calculations based on 2010-2014 IHS. (*) Based on 2006-2008 IHS, per adult equivalent income.

15

Economic

activities

income

Income increase was driven by income from economic activities

(paid work and agriculture) and social transfers

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Economic activities and transfers also explain most of the

poverty reduction observed between 2010-2014

-0.26

11.11

8.57

-1.71

-3.36

Demographics

Economic activities

Transfers

Other

Cons/Inc.*

Contribution to poverty reduction 2010-2014 (percentage points, positive bars are

drivers that lowered poverty and negative bars are drivers that raised poverty)

Total poverty reduction: 14.4 percentage points

Source: WB staff calculations based on 2010-2014 IHS. Economic activities refer to employment

rate, earnings, agricultural income and agricultural self-consumption. Transfers include income from

social protection, remittances and private transfers. Other refers to miscellaneous income sources.

(*) Cons/Inc. represents the ratio consumption to income at the household level, used to transform

income into consumption levels.

Note: Effects estimated as average change in poverty attributable to

each source of income. Average change estimated over effects

obtained when varying the order in which income sources are added.

See Azevedo et al. (2012) for more details on the methodology.

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Economic activities and transfers also explain most of the

poverty reduction observed between 2010-2014

(with disaggregated income components)

Contribution to poverty reduction 2010-2014 (percentage points)

Total poverty reduction: 14.4 percentage points

Source: WB staff calculations based on 2010-2014 IHS. (*) Cons/Inc. represents the ratio consumption to income at the

household level, used to transform income into consumption levels.

Demographics

Economic activities

Transfers

Other

Cons/Inc.*

Labor Market Agricultural

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This is in contrast to the results before 2010, when government transfers

were by and large the largest driver of poverty reduction

Demographics

Economic Activities

Transfers

Other

0.1

0.80

4.54

0.40

Contribution to poverty reduction 2006-2008 (percentage points)

Source: WB staff calculations based on 2014 Georgia Poverty Assessment analysis of 2006 and 2008 IHS. Poverty measured

based on income and national poverty line, decreases from 24.5 to 18.7 (5.9 percentage points). Actual consumption poverty

in the period fell from 18 to 17.7 percent.

Estimates based on income per adult equivalent, results should be consistent when using per capita scale as in previous slides

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Drivers of poverty reduction are similar across urban and rural areas

-3.7

-0.2

2.3

3.3

3.0

3.0

-0.1

6.5

0.4

1.3

-2.9

Rural

-3.4

-0.2

3.9

6.6

0.2

0.0

0.1

4.9

0.7

2.8

-0.1

Cons./Inc.

Dependency rate

Non-farm employment

Labor income

Agric. sales

Agric. self-cons.

Property income

Social Protection

Remittances

Private transfers

Other income

Tbilisi

Disaggregated Income components and their effects on poverty reduction 2010-2014,

by location

Total poverty reduction 15.8pp 16.6pp 12.9pp

-3.0

-0.3

3.4

5.6

0.5

1.0

0.3

5.5

1.4

2.1

-0.1

Rest Urban

Source: WB staff calculations based on 2010-2014 IHS.

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Labor market status, education and gender of the household head are

among the factors that determine probability of being poor

Marginal effect on probability of being poor

Poverty $2.5/day

National Urban Rural

HH Head Sociodemographic

65+ (elderly less likely to be poor) - -

Female (female heads are more likely to be poor) + + +

Secondary or higher (less likely to be poor) - - -

HH Head Labor Market Status (compared to employed)

Self-employed (more likely to be poor) + +

Unemployed (more likely to be poor) + + +

Inactive (more likely to be poor) + + +

HH Head Status

IDP (more likely to be poor) + +

Disability (more likely to be poor) + +

Household characteristics

Size (larger families more likely to be poor) + + +

Children 0-14 (more likely to be poor) + + +

Rural (more likely to be poor) +

Note: Table reports statistical significance and sign of marginal effect of variable to the probabilities of being poor. Dark yellow indicates

statistical significance at 1%, light yellow at 5%. Includes regional dummies.

Source: WB staff calculations based on 2014 IHS data.

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INCLUSIVE ACCESS TO ECONOMIC OPPORTUNITIES

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All sectors of the economy expanded in 2010-2014

22

6% 3% 6% 1% 9% 3% 4% 6% 14% 3% 3% 3% 8% 0% 4% 9% 6% 4%0

500

1000

1500

2000

2500

3000

3500

4000

20

10

mil.

GE

L

GDP (mil. GEL) and GDP Annual Growth (%) 2010-2014 by Sectors

2010 2014

Numbers at column bases indicate sector annualized GDP growth 2010-2014.

Source: WB staff calculations based on 2010-2014 IHS.

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Manufacturing

Electricity and utilities

Construction

Trade

Hotels and restaurants

Transport and communication

Real estate and …

Education

HealthOther

community

-5%

0%

5%

10%

15%

20%

25%

30%

-5% 0% 5% 10% 15% 20% 25% 30%

An

nu

al g

row

th a

ve

rag

e s

ala

rie

s

Annual growth employment

Manufacturing

Electricity and utilities

Construction

Trade

Hotels and restaurants

Transport and communication

Real estate and business activities

Education

Health

Other community

-5%

0%

5%

10%

15%

20%

25%

30%

-5% 5% 15% 25%A

nn

ua

l gro

wth

ave

rag

e s

ala

rie

s

Annual growth employment

Economic growth was associated with both salary growth and

employment creation, in contrast to the pre-2010 period

23

Average salary growth and employment growth by sectors

2006-2010 2010-2014

Note: Bubble size represents the size of employment in the sector by the ending period.

Source: WB staff calculations based on average salaries from Geostat and employment from 2006, 2010 and 2014 IHS.

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Note: Data include forms in non-service sectors only.

Source: Georgia Country Economic Memorandum (2014). Based on Geostat employment

data

This is consistent with the evidence of a slowdown in job destruction and higher net job creation in more recent years (2010-2012)

Job Creation and Destruction in Georgia 2007-2012 (percent of previous year’s

employment)

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7%

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

2010 2014 Growth in labor income

Em

plo

yment

Agriculture Manufacturing Construction Services

56.6%

50.7%

Between 2010 and 2014, employment rates among the poor increased from 50.7% to

56.6% even though the total number of the poor who are employed declined (this is

due to reduction in number of poor)

This translates into increased access to economic opportunities for the poor

Note: Numbers above the bars represent the employment rate for the poor in 2010 and 2014, respectively.

Source: WB staff calculations based on employment and income information from 2010-2014 IHS.

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Labor Force Status by Poverty and Vulnerability Status, Urban-Rural (2014)

Employment is opportunity to escape poverty in a sustainable manner, as employment indicators for the well-off suggest…

0

10

20

30

40

50

60

Less than$2.5

$2.5 - $5 $5 - $10 $10 + Less than$2.5

$2.5 - $5 $5 - $10 $10 +

Urban Rural

Employed Self-employed Unemployed Inactive

Source: WB staff calculations based on employment information from 2014 IHS.

26

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31.243.7

51.961.7

31.120.7

13.67.0

25.8 21.0 17.3 11.1

11.8 13.7 16.1 18

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Less than $2.5 $2.5 - $5 $5 - $10 $10 +

Share of income by components, by poverty and vulnerability status (Georgia 2014)

Labor Income Social Assistance Agricultural Income Private Transfers Property

27

…and sources of income for the well-off also support this conclusion

Source: WB staff calculations based on 2010-2014 IHS.

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A DEEPER LOOK AT THE RURAL ECONOMY

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Direction and statistical significance of effect

On: Poverty Headcount

From: National Urban Rural

Urban growth - -

Rural growth - -

On: Poverty Gap

From: National Urban Rural

Urban growth -

Rural growth - -

Note: Primary sector includes agriculture, forestry, fishing, mining, and quarrying; the secondary sector includes manufacturing, construction, and

electricity, gas, and water supply; the tertiary sector includes trade, hotels, restaurants, transport, storage, communication, finance, insurance,

real estate, business services, and community, social, and personal services. Results from OLS regression of average consumption on poverty

levels, following Ravallion and Datt (1996). Signs indicate direction of the effect and shadowed cell indicate statistical significance at 0.01.

Source: Sinha et al. (2016)

Rural poverty reduction over 2006-2014 is only associated with rural growth and growth in agricultural sector; it is unaffected by urban growth

Direction and statistical significance of effect

On: Poverty Headcount

From: National Urban Rural

Primary sector - -

Secondary

Tertiary -

On: Poverty Gap

From: National Urban Rural

Primary sector -

Secondary

Tertiary

29

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Employment levels and annualized growth (2010-2014), by sectors and areas

In addition, there has been employment growth in rural areas for non-agricultural sectors in 2010-2014…

Note: Numbers on columns base indicate annualized growth 2010-2014.

Source: WB staff calculations based on employment information from 2010-2014 IHS.

1.1 1.3 0.4 4.8 3.7 6.1 1.3 4.7

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

900,000

Urban Rural Urban Rural Urban Rural Urban Rural

Agriculture Manufacturing Construction Services

Em

plo

ym

en

t

2010 2014

30

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-1.74

-1.81

2.83

0.26

4.42

4.54

0.38

6.02

-2.15

Demographics

Education

Diversification

Sector

Employment

Agric. Income

Residuals

Nonlabor income

Others

Income Components Effects on Rural Poverty Reduction 2010-2014 (Behavioral responses model, Inchauste et al. (2013))

… which can be linked to the emerging role that diversification plays in explaining rural poverty reduction 2010-2014

Bars indicate the contribution, in percentage points, of the factors listed for rural poverty reduction. Non-labor income

includes social protection government transfers and private transfers.

Source: WB staff calculations based on methodology developed by Inchauste et al. (2013) and information from 2010-

2014 IHS.

31

Total rural poverty reduction: 12.9 percentage points

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Distributional Impacts of Fiscal

Policies

32

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72% 14% 117% 22% 88%0

200

400

600

800

1,000

1,200

1,400

Selected social programs introduced or scaled-up 2012-2014 (2012 GEL)

2012 2014

2012-2014 social spending was expanded, leading to a growth of 60 percent in real terms, led by pensions, health and other direct transfer

Note: Numbers on columns base indicate total growth 2012-2014.

Source: Georgia Public Expenditure Review 2015, based on Ministry of Finance information.

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425

1,055

1,822

2,926

6,924

2,631

9651,495

2,061

2,913

6,092

2,706

0

1000

2000

3000

4000

5000

6000

7000

8000

Poorest II III IV Richest

Quintiles All

Average annual household income, before and after fiscal interventions (2013 GEL)

Before taxes and transfers After taxes and transfers

Overall, taxes and transfers redistribute resources from the top to the bottom of the income distribution

Source: Georgia Public Expenditure Review 2015. Based on Commitment to

Equity methodology and information from 2010-2013 IHS.

34

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Labor Market Profile

Above the Poverty Line

35

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36

-0.8

22.3

37.2

13.2

9.5

0.8

38.8

6.9

15.5

-11.1

-32.5

-1.8

20.1

31.4

12.8

13.1

0.5

40.0

5.9

13.8

-12.4

-23.4

Share adults

Employment

Labor income

Agricultural sales

Agricultural self-consumption

Property

Social Protection

Remittances

Private transfers

Other

Cons./Inc.

$5.0

$2.5

Labor markets played a more important role in moving people above the $5/day line than in moving them above the $2.5/day line

Contribution to poverty reduction 2010-2014 (as a percentage of the reduction)

Total poverty reduction: 14.4 pp ($2.5/day) and 11.1 pp ($5.0/day)

Source: WB staff calculations based on 2010-2014 IHS.

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1422

31

42

3929

22

144 6 7

810 9 75

31 32 32 29

0

20

40

60

80

100

Poor(<$2.5)

Moderate Poor($2.5-$5)

Vulnerable($5-$10)

Middle class($10+)

Unknown

Inactive

Discouraged

Unemployed

Self-employed (Non-agric.)

Self-employed (Agric.)

Employed

37

Those above the poverty line have better attachment to labor markets (lower unemployment and less incidence of agric. self-employment)

Labor Force Status by vulnerability and poverty status (15+ years old), Georgia 2014

Source: WB staff calculations based on 2010-2014 IHS.

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71

52

37

22

4

7

7

10

4

4

22

3852

64

0

10

20

30

40

50

60

70

80

90

100

Poor(<$2.5)

Mod. Poor($2.5-$5)

Vulnerable($5-$10)

Middle class($10+)

Agriculture Manufacturing Construction Services

38

Largest sector of employment for the vulnerable is services, but for the moderate poor it is still agriculture. There is roughly similar composition of services sub-sectors across income groups

6.1 11.3 14.8 19.6

6.7 10.211.1 12.3

2.0 4.27.0 10.8

3.1 5.07.3 7.4

1.4 2.5 5.8 7.0

2.0 3.6 4.4 4.7

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Poor(<$2.5)

Mod. Poor($2.5-$5)

Vulnerable($5-$10)

Middle class($10+)

Health & education Wholesale & retail tradePublic administration Transport & communic.Real estate & finance Hotels & restaurantOther

Sector of employment by vulnerability and

poverty status (15+ years old), Georgia 2014

Sub-sector of employment within services by vulnerability

and poverty status (15+ years old), Georgia 2014

Source: WB staff calculations based on 2010-2014 IHS.

Note: Numbers in bars represent share of total employment in each services sub-sector. They add up to total services

sector share.

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39

The vulnerable have better access than the moderate poor to jobs requiring advanced skills

Source: WB staff calculations based on 2014 IHS.

Occupation by vulnerability and poverty status (15+ years old), Georgia 2014

69.4

50.6

36.2

22.1

4.3

9.8

19.8

28.6

6.8

11.79.7

10.1

5.9 12.5

3.67.8 11.4

14

15.2 17.9 16.9 12.7

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Poor (<$2.5) Mod. Poor ($2.5-$5) Vulnerable ($5-$10) Middle class ($10+)

Other Technicians and Associate Professionals

Legislators, Senior Officials and Managers Service Workers, Shop and Market Sales Workers

Professionals Skilled Agricultural and Fishery Workers

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40

POVERTY PERSISTENCE IN GEORGIA

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Source: WMS 2009-2011-2013.

Escaped poor defined as poor in 2009 or 2011 but not in 2013. Downward mobility defined as non-poor in

2009 and poor in 2013.

41

31.839.4

23.9

32.2

31.0

33.6

16.5 14.318.7

19.515.4

23.8

0

10

20

30

40

50

60

70

80

Non-Poor Poor Non-Poor Poor Non-Poor Poor

National Urban Rural

Poverty status by mobility status, Georgia 2013 (Urban and Rural)

Never poor Escaped poverty Persistent poor Downward mobility

Close to half of the poor in 2013 are persistently poor, and overall roughly half of the population in the country has either moved out of poverty or fallen into poverty

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44.0

56.1

4.2

12.6

3.9

12.4

9.9

6.0

25.5

17.0

3.6

5.0

Urban

Rural

Mtskheta-Mtianeti

Samegrelo

Guria

Qvemo Qartli

Kakheti

Sida Qartli

Tbilisi

Imereti*

Samtskhe-Javakheti

Adjara

Distribution of Persistent Poverty, Georgia 2013

42

Persistent poverty is both an urban and rural phenomenon; the highest incidence of persistence tends to coincide with the highest overall poverty rates

*Includes Racha-Lechkhumi and Kvemo-Svaneti

Source: WMS 2009-2011-2013.

Urban

RuralMtskheta-Mtianeti

Samegrelo

Guria

Qvemo Qartli

Kakheti

Sida Qartli

Tbilisi

Imereti*

Samtskhe-JavakhetiAdjara

0

10

20

30

40

50

60

0 10 20 30 40

20

13

Po

ve

rty H

ea

dco

un

t (2

00

5 U

S$

)

2013 persistent Poverty Headcount

Poverty Persistence and Poverty by Urban/Rural and Regions (Georgia, 2013)

*Includes Racha-Lechkhumi and Kvemo-Svaneti

Source: WMS 2009-2011-2013 and 2013 IHS.

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1.51.7

5.9

1.6

3.7

6.3

2.1

6.0

7.7

0

1

2

3

4

5

6

7

8

9

Persistent Escapes poverty Never poor

Ave

rag

e e

xp

en

ditu

re p

er

ca

pita

pe

r d

ay (

20

05

US

$

PP

P)

Average expenditure by category 2009-2011-2013 (US$/day per capita, 2005 PPP)

2009

2011

2013

Source: Welfare Monitoring Survey 2009-2011-2013 rounds

43

The persistent poor have also benefited from the recent growth, but less so than the rest

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44

95.7 96.5 94.3

82.476.4 81.9

-20

0

20

40

60

80

100

120

National Urban Rural National Urban Rural

Household education and demographic composition Adding assets

Pe

rce

nta

ge

po

ints

Endowments Returns to endowments Interaction

Endowments (household head’s age, education, ownership of assets) explain very little of difference in welfare between persistent poor and those escaping poverty. Unobserved factors (returns to endowments) explain most of the difference

Source: Own estimations based on Welfare Monitoring Survey 2013 round.

Note: The figure decomposes consumption differences between the persistent poor and those originally poor who escaped

poverty into the part that can be attributed to endowments, the difference in the returns to these endowments, and the

unexplained portion of the differential. Methodology Oaxaca (1973), following Vakis et al. (2015). Endowments considered are

household head age and education, household demographic composition and asset ownership (e.g. vehicles, appliances).

Differences in welfare explained by endowments and returns to endowments,

Georgia 2013

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0

10

20

30

40

50

60

70

80

90

HH Head Labor ForceStatus

Sector of employment HH Head Labor ForceStatus

Sector of employment

Urban Rural

Labor Market Indicators for Persistent Poor and Escaped Poverty at Initial Period (2009)

Chronic Poor Escaped Poverty

Employment indicators also show differences in spite of similar endowments, especially in urban areas

Note: OLF stands for Out of Labor Force.

Source: WB staff calculations based on employment information from 2009-2013 Welfare Monitoring Survey.

45

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Policy discussion

46

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Implications for a policy agenda

GROW

• Deepen structural transformation + promote efficient relocation of resources

• Raise agricultural productivity

• Develop the tradeable sector

INVEST

• Connectivity (infrastructure + people)

• Improve access to and quality of basic services

• Grow productive assets base (skills, land, credit)

PROTECT

• Safety nets – Continue to strengthen (income) support for the poor, paying attention

to potential work disincentives

• Social insurance – Continue to provide fiscally sustainable support to those unable

to work

47

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Appendix

48

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Feedback from Consultation

Discussion held in Tbilisi on May 19th, 2016.

Comments received:

• Importance of regional poverty dynamics in the country, as some regions have reduced

poverty considerably.

• Social benefits should not create disincentives to work, as anecdotic evidence in the

country may suggest.

• Role of Universal Health Care to reduce poverty should be analyzed.

• Aging should be included in the discussion on poverty, as it will play a more important

role to shape social assistance policies in the future.

• The Ministry of Agriculture expressed interest in disseminating results from analysis to a

wider audience.

49

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Methodological Notes

The poverty line used in this study is $2.5/day 2005 PPP.

• Regional extreme poverty line, average of the national poverty line of the poorest countries in the region

converted into comparable prices using the 2005 Purchasing Power Parity prices.

Consumption aggregate used is a harmonized aggregate, designed to allow comparability across

countries.

• Consumption is used as welfare aggregate in all instances, except when presenting the

microdecomposition 2006-2008. In this case, the welfare aggregate is income.

• The harmonized consumption measure is called Europe and Central Asia Poverty (ECAPOV)

consumption, maintained by the ECA Team for Statistical Development.

• Databases used for Georgia are the 2010-2014 IHS, harmonized versions.

• Consumption aggregate contains Food, Alcohol/Tobacco, Clothing, Housing/Utilities, Furnishings/HH

Equipment, Health, Transport, Communications, Recreation, Education, Hotels/Restaurants and

Miscellaneous. In addition, it contains rent and durables.

• Expressed in per capita terms, deflated spatially and in time.

The shared prosperity indicator is defined as the annualized growth of the mean consumption of

the country, against the annualized growth of the mean consumption of the bottom 40 percent

of the population

• Estimated using the ECAPOV consumption aggregate.

• The shared prosperity indicator should ideally be positive and larger for the bottom 40, as to signal positive

economic growth and inclusion of the less well-off in the growth process.50

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Microdata used for this analysis (Integrated Household Survey) is collected by

Geostat, which also provided support for understanding details of the data.

• The IHS is a nationally representative household budget survey conducted continuously during

the year.

• It is representative at the annual and quarter level (in time) and for urban/rural regions, and 11

administrative conglomerates

• It contains information on employment, income and expenditure.

• The sample size is around 11,000 interviews per year.

Welfare Monitoring Survey (2009-2011-2013) data, shared by UNICEF, is

used for the analysis of poverty dynamics.

• The WMS is a nationally representative household budget survey conducted in 2009, 2011 and

2013 to the same sample of households (panel).

• It is representative at the national level and contains information on income and expenditure,

health and employment.

• The sample size is around 3,000 interviews per round.

• The WMS collects a consumption aggregate similar to the one collected in the IHS. Poverty

persistence analysis is performed using the ranking coming from this consumption aggregate,

applying the poverty rates obtained from the IHS.

Acknowledgments

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Azevedo, Joao Pedro; Viviane Sanfelice and Minh Cong Nguyen (2012) Shapley Decomposition by Components of a

Welfare Aggregate. World Bank. mimeo.

Cancho, Cesar; Natsuko Kiso and Paul Corral (2016) Welfare Impact of Macroeconomic Events: The Case of

Georgia and Azerbaijan in the Aftermath of the 2015-16 Currency Devaluations. Paper prepared for the South

Caucasus Programmatic Poverty Assessment TA FY16.

Inchauste, Gabriela; Joao Pedro Azevedo; B. Essama-Nssah; Sergio Olivieri; Trang Van Nguyen; Jaime Saavedra-

Chanduvi and Hernan Winkler (2013) Understanding Changes in Poverty. The World Bank Group.

Oaxaca, R. (1973) Male-female wage differentials in urban labor markets. International economic review, Vol. 14, No.

3, pp. 693-709.

Ravallion, Martin and Gaurav Datt (1996) How Important to India's Poor Is the Sectoral Composition of Economic

Growth? The World Bank Economic Review 10 (1): 1-25.

Sinha, Nistha; Paul Andres Rodas Corral; Rodrigo Salcedo DuBois and Cesar Cancho (2016) Impact of Structure of

Growth and Income on Rural Poverty in Georgia. Paper Prepared for South Caucasus Programmatic Poverty

Assessment TA FY15-16.

Vakis, Renos; Rigolini, Jamele and Leonardo Lucchetti (2015) Left Behind: Chronic Poverty in Latin America and the

Caribbean - Overview. Washington, DC ; World Bank Group.

References

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Thank you.

53