GEORGIA: RECENT TRENDS AND DRIVERS OF POVERTY REDUCTION (FY16 - - PowerPoint PPT Presentation

GEORGIA: RECENT TRENDS AND DRIVERS OF POVERTY REDUCTION

(FY16 GEORGIA POVERTY ASSESSMENT) POVERTY AND EQUITY GLOBAL PRACTICE

AUGUST 17 2016

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

• f 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

• f 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.

2

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

3

POVERTY TRENDS 2010-2014

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

5

9.4 12.6 2.4

• 3.7

6.2 7.2 6.4 3.4 4.6 2.8 3 4.5 5

• 6
• 4
• 2

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

6

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 45.8 43.0 45.1 46.7 44.8 42.5 36.0 32.3 31.0 29.4 27.5 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.

7

…and higher living standards across the distribution

• 8
• 4

4 8 12 1 10 20 30 40 50 60 70 80 90 100 Consumption percentiles

Growth incidence 95% confidence bounds Growth in mean Growth at median Mean growth rate

Georgia (2010-2014)

19.2 18.1 16.5 13.0 11.4 10.5 10.0 8.7 6.5 5.6 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

8

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) 5 10 15 20 25 30 35 5,000 10,000 15,000 20,000 25,000 Poverty headcount (US$2.5/day 2005 PPP) GDP per capita (2005 PPP US$) Poverty rate and GDP per capita, selected countries ECA (c. 2014)

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

9

…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

10

Inequality also decreased likely driven by improved welfare among the less well-off. Shared prosperity indicator shows similar pattern.

6.4 7.7 6.9 5.3 8.3 9.8 8.7 7.9 2 4 6 8 10 12 National Tbilisi Rest Urban Rural

Annualized growth 2010-2014 (Percentage) 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.

42.1 41.6 41.3 40.0 40.1 2.6 2.5 2.5 2.5 2.5 2.8 2.9 2.7 2.6 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

11

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 16.1 14.2 16.5 Percentage of population (a) Poverty status 2009-2011-2013 2.9 1.5 0.8

• 0.04
• 10

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,

• r 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.

12

Share of vulnerable population is also growing (percentage of those who live just above the poverty line)

47 45 43 36 32 34 35 35 37 37 15 16 17 21 24 4 4 5 5 7 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.

13

DRIVERS OF POVERTY REDUCTION 2010-2014

14

Real incomes increased across rural and urban areas 2010-2014

174.8 206.6 174.7 157.4 242.1 300.9 235.5 214.2

8% 10% 8% 8%

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

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

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 Rural 2006-2008 National*

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

16

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

• btained when varying the order in which income sources are added.

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

17

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

18

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

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.

20

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.

21

INCLUSIVE ACCESS TO ECONOMIC OPPORTUNITIES

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%

500 1000 1500 2000 2500 3000 3500 4000 2010 mil. GEL

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.

Manufacturing Electricity and utilities Construction Trade Hotels and restaurants Transport and communication Real estate and … Education Health Other community

• 5%

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

• 5%

0% 5% 10% 15% 20% 25% 30% Annual growth average salaries 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% Annual growth average salaries 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.

24

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)

7%

0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 100,000 200,000 300,000 400,000 500,000 600,000 700,000 2010 2014 Growth in labor income Employment 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.

25

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…

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

31.2 43.7 51.9 61.7 31.1 20.7 13.6 7.0 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.

28

A DEEPER LOOK AT THE RURAL ECONOMY

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

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

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 Employment

2010 2014

30

• 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

Distributional Impacts of Fiscal Policies

32

72% 14% 117% 22% 88% 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.

425 1,055 1,822 2,926 6,924 2,631 965 1,495 2,061 2,913 6,092 2,706 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

Labor Market Profile Above the Poverty Line

35

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.

14 22 31 42 39 29 22 14 4 6 7 8 10 9 7 5 31 32 32 29 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.

71 52 37 22 4 7 7 10 4 4 22 38 52 64

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

• f services sub-sectors across income groups

6.1 11.3 14.8 19.6 6.7 10.2 11.1 12.3 2.0 4.2 7.0 10.8 3.1 5.0 7.3 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 trade Public administration Transport & communic. Real estate & finance Hotels & restaurant Other

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.

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 11.7 9.7 10.1 5.9 12.5 3.6 7.8 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

40

POVERTY PERSISTENCE IN GEORGIA

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

31.8 39.4 23.9 32.2 31.0 33.6 16.5 14.3 18.7 19.5 15.4 23.8 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

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

• verall poverty rates

*Includes Racha-Lechkhumi and Kvemo-Svaneti Source: WMS 2009-2011-2013. Urban Rural Mtskheta- Mtianeti Samegrelo Guria Qvemo Qartli Kakheti Sida Qartli Tbilisi Imereti* Samtskhe-Javakheti Adjara 10 20 30 40 50 60 10 20 30 40 2013 Poverty Headcount (2005 US$) 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.

1.5 1.7 5.9 1.6 3.7 6.3 2.1 6.0 7.7 1 2 3 4 5 6 7 8 9 Persistent Escapes poverty Never poor

Average expenditure per capita per day (2005 US$ PPP)

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

44

95.7 96.5 94.3 82.4 76.4 81.9

• 20

20 40 60 80 100 120 National Urban Rural National Urban Rural Household education and demographic composition Adding assets Percentage points 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

10 20 30 40 50 60 70 80 90 HH Head Labor Force Status Sector of employment HH Head Labor Force Status 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

Policy discussion

46

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

Appendix

48

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

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

• f 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

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

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

Thank you.

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