metadata: authors: 0: author: Atamanov,Aziz
1: author: Azevedo,Joao Pedro Wagner De
2: author: Rajabov,Alisher
count: Tajikistan
docna: 0: docna: Poverty reduction and shared prosperity in
            Tajikistan : a diagnostic
docty: Policy Research Working Paper
subtopic: Economic Theory & Research,Industrial Economics,Labor Markets,Educational Sciences,Gender and Development,Economic Growth,Inequality
teratopic: Poverty Reduction,Health, Nutrition and Population,Macroeconomics and Economic Growth
abstracts: cdata!: Tajikistan was one of the fastest
            growing countries in the Europe and Central Asia region
            during the last decade. The economic growth was widely
            shared by the population and as a result poverty (measured
            by the national poverty line) declined from 73 percent in
            2003 to 47 percent in 2009 accompanied by falling
            inequality. Consumption growth of the bottom 40 percent of
            the population -- a measure of shared prosperity proposed by
            the World Bank- was positive, pointing out that the growth
            was shared among the less well off. This work presents a
            diagnostic of shared prosperity and poverty reduction in
            Tajikistan during 2003-2009. The paper also focuses on
            quantifying the main drivers of poverty reduction, shared
            prosperity, and intra-generational mobility (class
            transitions). Some of the mechanisms of poverty reduction
            are explored in detail. Finally, main impediments to
            inter-generational mobility are discussed.
geo_reg_key: 517208,517198,545134,82689,517191
repnme: repnme: Poverty reduction and shared prosperity in
            Tajikistan : a diagnostic
display_title: Poverty reduction and shared
            prosperity in Tajikistan : a diagnostic
listing_relative_url: /research/2014/06/19680393/poverty-reduction-shared-prosperity-tajikistan-diagnostic
topicv3: Economic Growth m1326241 471,Poverty m1326687 695,Education m1327048 470,Gender m1327621 615,Labor Earnings m1504041 2738
publishtoextweb_dt: 2014-06-01T00:00:00Z
historic_topic: Poverty Reduction,Health, Nutrition and Population,Macroeconomics and Economic Growth
no_of_pages: 36
author_keys: 0: author_key: 1182029
1: author_key: 675142
2: author_key: 1140301
model_extractions: WPS6923 Policy Research Working Paper 6923 Poverty Reduction and Shared Prosperity in Tajikistan

# A Diagnostic

_Joao Pedro Azevedo Aziz Atamanov Alisher Rajabov_ The World Bank Europe and Central Asia Region Poverty Reduction and Economic Management Team June 2014
Policy Research Working Paper 6923

# **Abstract**

Tajikistan was one of the fastest growing countries in the Europe and Central Asia region during the last decade. The economic growth was widely shared by the population and as a result poverty (measured by the national poverty line) declined from 73 percent in 2003 to 47 percent in 2009 accompanied by falling inequality. Consumption growth of the bottom 40 percent of the population—a measure of shared prosperity proposed by the World Bank- was positive, pointing out that the growth was shared among the less well off. This work presents a diagnostic of shared prosperity and poverty reduction in Tajikistan during 2003–2009. The paper also focuses on quantifying the main drivers of poverty reduction, shared prosperity, and intra-generational mobility (class transitions). Some of the mechanisms of poverty reduction are explored in detail. Finally, main impediments to inter-generational mobility are discussed.

This paper is a product of the Poverty Reduction and Economic Management Team, Europe and Central Asia Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank. org. The authors may be contacted at jazevedo@worldbank.org, aatamanov@worldbank.org, and arajabov@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Poverty Reduction and Shared Prosperity in Tajikistan: A Diagnostic

Joao Pedro Azevedo, Aziz Atamanov and Alisher Rajabov JEL: D6; I3; J11; J3; J6 Keywords: Middle Class; Poverty; Inequality: Shared Prosperity; Economic Mobility; Decompositions; Tajikistan; Central Asia
# Acknowledgement and Disclaimer

Authors are thankful to all participants of the joint seminar organized by the World Bank and the Ministry of Economic Development and Trade of the Republic of Tajikistan in Dushanbe in June 2013 as well as participants of the seminar in Washington, DC in October 2013. We are particularly thankful to Marsha McGraw Olive, Ambar Narayan, Carolina Sanchez-Paramo and Luis-Felipe Lopez-Calva for their useful comments and suggestions. The authors also thank Kimberly Bolch for editing the report. The first draft of paper was circulated in December, 2013.

All PPP figures used in this paper is based in the 2008 ICP round. All Poverty rates based on the dollarper-day measures are also based on the PPP conversations factors from the 2008 ICP round. As ICP estimates are revised, they are of five data sources that are used to compute the incidence of poverty using the “dollar a day” poverty line methodology. The use of the 2011 PPPs in the calculation of global or regional poverty estimates requires additional analysis. One issue that warrants consideration is that people who live at or below the poverty line likely have different patterns of consumption than the total population (which is the basis for the PPPs). The representation of price data in rural areas (where many of the poor live), from local markets (where the poor shop) and of poorer quality goods also warrants closer examination. DEC economists engaged in the global poverty calculations will obtain detailed data and metadata from the ICP _Global Office_ , regional coordinating agencies, and participating economies in order to assess whether the new PPP estimates can be used for poverty measurement purposes, or whether adjustments will be needed. These data will take some time to acquire and assess and so DEC will not incorporate the new PPPs into the poverty measure calculations immediately. This is consistent with past practice: when the 2005 PPPs were released in 2007, DEC analyzed the PPPs in detail and made additional adjustments before incorporating them into the poverty measures two years later.” The support of UK-DFID is gratefully acknowledged.

2
# **Table of Contents**

|1.<br>Introduction and analytical framework ................................................................................................. 5|
|---|
|2.<br>Growth, shared prosperity, poverty and inequality ............................................................................... 7|
|3.<br>Intra-generational (class) mobility ...................................................................................................... 10|
|4.<br>Determinants of poverty reduction, inequality and intra-generational mobility ................................. 13|
|4.1<br>Drivers of poverty reduction ....................................................................................................... 13|
|4.2<br>Mechanisms of poverty reduction in the labor market ................................................................ 16|
|4.3<br>Prospects for poverty reduction after 2009 ................................................................................. 19|
|5.<br>Going forward ..................................................................................................................................... 21|
|6.<br>References ........................................................................................................................................... 26|
|7.<br>Annex .................................................................................................................................................. 28|
|**Figures**|
|Figure 1.1: The assets approach to assess income generation capacity ........................................................ 6|
|Figure 2.1: GDP per capita in 2012 and GDP per capita, PPP 2005 annualized growth rates between<br>2000-2012 in selected countries and group of countries ............................................................................... 7|
|Figure 2.2: Shared Prosperity Indicator for selected ECA countries ............................................................ 8|
|Figure 2.3: Poverty rates by residence, 2003, 2007 and 2009 ...................................................................... 9|
|Figure 2.4: Regional poverty rate in 2003, 2007 and 2009 ........................................................................... 9|
|Figure 2.5: Regional structure of poor population, 2003 and 2009 .............................................................. 9|
|Figure 2.6: Inequality in selected ECA countries measured by Gini .......................................................... 10|
|Figure 3.1: Average consumption per capita in different groups in the bottom 40 percent of the<br>population, upper bound ............................................................................................................................. 13|
|Figure 4.1: Income poverty decomposition, 2003-2009 ............................................................................. 14|
|Figure 4.2: Income Gini decomposition, 2003-2009 .................................................................................. 14|
|Figure 4.3: Income poverty decomposition by classes, 2003-2009 ............................................................ 15|
|Figure 4.4: Source of income growth for the bottom 40, 2003-2009 ........................................................ 15|
|Figure 4.5: Income poverty decomposition across residence, 2003-2009 .................................................. 15|
|Figure 4.6: Income poverty decomposition by gender, 2003-2009 ............................................................ 16|
|Figure 4.7: Gini decomposition by gender .................................................................................................. 16|
|Figure 4.8: Employment creation and economic growth by sectors ........................................................... 16|
|Figure 4.9: Conditional and unconditional gender wage gaps .................................................................... 17|
|Figure 4.10: Labor force status in %, population, 16+................................................................................ 17|
|Figure 4.11: Returns to education in 2003, 2007 and 2009 across gender ................................................. 18|

3
|Figure 4.12: Returns to experience in 2003, 2007 and 2009 across gender ................................................ 18|
|---|
|Figure 4.13: Monthly real wage index (2009=1) by economic sectors during 2009-2013 ......................... 19|
|Figure 4.14: Monthly real wages by economic sectors and real minimum wage during 2009-2013 ......... 19|
|Figure 4.15: Monthly real wages in agricultural sector and real minimum wage during 2009-2013 ......... 20|
|Figure 4.16: Remittances received in mln. USD and % of GDP during 2009-2013 .................................. 20|
|Figure 4.17: Estimates and projections of total dependency ratios, 1950-2065 ........................................ 21|
|Figure 5.1: Quality of electricity services in Tajikistan, 2011 .................................................................... 22|
|Figure 5.2: Access to financial institutions in Tajikistan, ECA and low-income countries, % of population<br>+15 .............................................................................................................................................................. 23|
|Figure 5.3: Access to financial services in Tajikistan across urban and rural areas, % of population +15 23|
|Figure 5.4: Governance indicators in selected ECA countries, 2011.......................................................... 24|
|Figure A1: Consumption and income poverty, % ....................................................................................... 30|
|Figure A2: Education of male workers across years,% .............................................................................. 30|
|Figure A3: Education of female workers across years, % .......................................................................... 30|
|Figure A4: Churning in the bottom 40 percent of the population ............................................................... 31|
|Figure A5: Synthetic panel approach .......................................................................................................... 32|
|**Tables**|
|Table 3.1: The middle class over time in Tajikistan, % .............................................................................. 10|
|Table 3.2: Mobility matrix, 2003-2009, upper bound ................................................................................ 11|
|Table 3.3a: Mobility matrix for urban areas, 2003-2009, lower bound ..................................................... 11|
|Table 3.3b: Mobility matrix for rural areas, 2003-2009, upper bound ...................................................... 11|
|Table 3.4: Mobility matrix for the bottom 40 and top 60 percent of the population ................................. 12|
|Table 4.1: Employment in 2009 and 2012 by economic sectors ................................................................ 20|
|Table A.1: Shares of different income components in total income across years, % ................................ 28|
|Table A.2: Growth rate of different income components, share of adults and share of employed across<br>quartiles during 2003-2009, % .................................................................................................................... 28|
|Table A.3: Profile of population in the bottom 40 percent for selected years ........................................... 28|
|Table A.4: Profile of households in the bottom 40 percent for selected years ......................................... 29|
|Table A.5: Construction of income aggregates .......................................................................................... 34|

|**Boxes**|
|---|
|Box 1. Churning in the bottom 40 percent of the population ...................................................................... 31|
|Box 2. Synthetic panel methodology .......................................................................................................... 32|

4
# **1. Introduction and analytical framework**

1. **Tajikistan is the poorest country in the Europe and Central Asian region with GDP per capita of US$ 2,247 in PPP terms in 2012.** The country has grown very fast during the 2000s and due to effective mitigating measures, the social impacts of  the 2008-2009 world financial crisis were minimized. Poverty rates dropped from 73 percent in 2003 to 47 in 2009 using the national poverty line.<sup>1</sup> Tajikistan’s achievement in poverty reduction during 2007-2009 (using the World Bank’s Europe and Central Asia (ECA) regional daily poverty line of US$2.5 PPP 2005) positions it in the top decile of the world performers.<sup>2</sup> Nevertheless, the level of poverty is still very high. Further poverty reduction along with improvement of living standards are priority goals for the Government of Tajikistan. There is also a growing interest in expanding the middle class in the country (Heleniak, Sulla and Rajabov, 2012). Therefore, the Government needs to understand the analytical underpinnings of poverty reduction and intra-generational mobility in Tajikistan in order to inform the future policy making agenda and sustain the path to poverty reduction.

2. **The World Bank Group has established twin goals to end extreme poverty and to promote shared prosperity.** In particular, the goals consist of the following: (i) to ensure the percentage of people living with less than $1.25 a day to fall to no more than 3 percent globally by 2030; (ii) to foster income growth of the bottom 40 percent of the population in every country. These goals should be achieved in such a way as to be sustainable over time and across generations. While both goals focus on monetary measures of well-being, they unequivocally imply progress in non-monetary dimensions of welfare, such as education, health, nutrition, and access to essential infrastructure, as well as in enhancing voice and participation of all segments of society in economic, social, and political spheres (World Bank Group, 2013).

3. **Economic growth is a necessary, but not a sufficient condition for poverty reduction and shared prosperity.** The metaphorical pie should be growing and the most effective way to translate growth into higher incomes is through the generation of more and better jobs based on private sector investment. However, a growing economy is not a sufficient condition for shared prosperity and the incidence of growth is critical as well **.** One easy way to conceptualize the relationship between growth and equity is by using assets approach as discussed in Attanasio and Szekely (1999). According to the authors, inequality reflects skewed distribution of income earnings assets with human capital being the most important. Expanding this approach, growth incidence can be shown to depend on: (i) distribution of assets (human, capital, land); (ii) intensity of use of these assets; (iii) returns to assets; (iv) public and private transfers (figure 1.1).

> 1 2009 is the last year for official poverty estimates based on microdata. The World Bank currently works closely with the Statistical Agency of Tajikistan (TajStat) and the Ministry of Economic Development and Trade to update the poverty numbers using Household Budget Survey collected and administered by TajStat.

> 2 See Figure A6 for further details. Benchmarking methodology is described in Newman and Azevedo (2013). Computation using Stata Ado benchmark by Minh Cong Nguen and Joao Pedro Azevedo. Source: WDI (2013) downloaded using wbopendata.

5
# -——_1+—+— i eeeoe0
<!-- Start of picture text --> — l14 — - 25,000<br>in GOP per capita in 2012, PPP M&GOP per capita growth, PPP 2005<br>a<br>~ 12<br>a. a<br>fc 10 a<br>ae :<br>a ds 15,000 g<br>oa<br>s $6 .<br>oo 10,000 8<br>= oa 5<br>= «(Ct rr<br>wm<br>~ 5,000<br>bawmi] 2<br>a<br>a oO 0<br>=) mow’ oO = Ur tom = Unnoannhthuree = rps<br>i] = = Pd<br>“@BSSLESES2ELESF2SS255<br><!-- End of picture text -->
<!-- Start of picture text --> 18<br>16 m@ Consumption growth of bottom 40%<br>14 ®@ Consumption growth of total population<br>i ee© |<br>iee 2p8 nr?1 i||<br>ad<br>pf ———C“(‘<br>g 6 ll TT<br>eC<br>og SET<br>LEELA<br>|e<br>rr<br>-2<br>ERS>ooosesssvz22FNSSSSEKSeAeez22%¢8eozyrze eatin xewvrxe<br><!-- End of picture text -->
<!-- Start of picture text --> 80<br>75 SN —erural —TM—urban —#—country<br>a oN<br>t./& 6S<br>= 60<br>S|<br>a 55 =<br>Sg) ee.<br>i<br>& 45<br>40<br>35<br>30<br>2003 2007 2009<br><!-- End of picture text -->

<!-- Start of picture text --> 90 100<br>80 m 2003 90 GBAO<br>80<br>@ © Khatlon<br>B 60 so<br>= 40 sod<br>vu 50 =<br>-—mEkin<br>240 20 § Dushanbe<br>"2 &EeE ie<br>20 BEE E | 2008 2009<br>Dushanbe Sogd Khatlon RRP GBAO<br><!-- End of picture text -->
<!-- Start of picture text --> 0.43<br>0.41<br>0.39 :<br>0.37<br>0.35<br>433 i _$—<$<$<$<_—_—<br>ie,<br>0.27<br>0.25<br>circa 2003 circa 2007 circa 2009 circa 2011<br><!-- End of picture text --> —Tajikistan ———Moldova ———Georgia ———Armenia ———Kyrgyzstan
12. **The growing middle class, however, is the most unstable group and the people who comprise it have non-negligible chances of moving to the vulnerable or poor groups.** Table 3.2 shows a mobility matrix between different classes during 2003-2009 (upper bound). In particular, 39 percent of the poor in 2003 moved to the vulnerable and 13 percent moved to the middle class in 2009. About 24 percent of the vulnerable in 2003 moved to the middle class in 2009. About 16 percent of the middle class fell in to poverty and about 55 percent moved to the vulnerable group. This makes the middle class very unstable contrary to expectations that it comprises the most stable strata of society.

**Table** **<u>3.2:  Mobility matrix, 2003-2009, upper bound</u>**

||Origin<br>||Percentage<br>|movingto 2009<br>||
|---|---|---|---|---|---|
||(In 2003)|Poor|Vulnerable|Middle Class|Total|
|Poor|72|48|39|13|100|
|Vulnerable|22|29|47|24|100|
|Middle class|6|16|55|30|100|
|Total|100|44|41|16|100|

Source: Authors’ calculations based on ECAPOV data. Notes: transition matrix is based on synthetic panel for 2003-2009.<sup>5</sup> Threshold for poor is 162 somoni and for middle class 294 somoni per month. Explanatory variables include year of birth cohort, number of children, education of the head of household, rural/urban and regional dummies, and different interactions between these variables and means are the regional level. Sample: heads of household 25-55 years of age. Welfare aggregate is as used to calculate national poverty rates.

13. **Upward mobility is much stronger in urban areas, while volatility of class transitions is more pronounced in rural areas.** Tables 3.3ab contain mobility matrixes for urban and rural areas. Consistent with higher poverty in rural areas, there are lower chances to be in the middle class for rural residents. Moreover, rural areas are characterized by much higher volatility than urban areas. For example, in urban areas only 7 percent of the middle class fell into poverty in 2009, while in rural areas this ratio is more than 3 times higher. This is consistent with - higher volatility of earnings in rural areas that are strongly dependent on seasonal and climate-dependent agricultural activities.

**Table 3.3a:  Mobility matrix for urban areas, 2003-2009, lower bound**

||Origin<br>||Percentage<br>|movingto 2011<br>||
|---|---|---|---|---|---|
||(In 2002)|Poor|Vulnerable|MiddleClass|Total|
|Poor|66|43|41|16|100|
|Vulnerable|25|25|43|32|100|
|Middle class|9|7|48|46|100|
|Total|100|37|42|21|100|

**Table 3.3b:  Mobility matrix for rural areas, 2003-2009, upper bound**

||Origin||Percentage|movingto 2011||
|---|---|---|---|---|---|
||(In 2002)|Poor|Vulnerable|Middle Class|Total|
|Poor|74|51|38|11|100|
|Vulnerable|21|32|49|19|100|
|Middle class|5|25|62|13|100|

> 5 Brief non-technical explanation of the synthetic panel methodology is provided in box 2 in annex.

11
<mark>Total 100 47 40 13 100</mark>

# Source: Authors’ calculations based on ECAPOV data.

Notes: transition matrix is based on synthetic panel for 2003-2009. Threshold for poor is 162 somoni and for middle class 294 somoni per month. Explanatory variables include year of birth cohort, number of children, education of the head of household, rural/urban and regional dummies, and different interactions between these variables and means are the regional level. Sample: heads of household 25-55 years of age. Welfare aggregate is as used to calculate national poverty rates.

14. **Consistent welfare improvement is observed across the whole population in spite of the churning in the bottom 40 percent**<sup>**6**</sup> **.** From 8 to 49 percent of the population (depending on lower or upper bound) in the bottom 40 shifted upwards to the top 60 in 2009.<sup>7</sup> From 5 to 33 percent of the top 60 shifted down to bottom 40 in 2009 (tables 3.4ab). In spite of a churning, overall positive mobility prevails as can be clearly seen from figure 3.1. Average consumption of graduates from the top 60 percent of the population in 2003 was still higher than the average consumption of entrants to the top 60 in 2009. Coupled with a very high growth of consumption per capita in households staying in the bottom 40 percent in two years, overall mobility was strongly upward moving.

|**Table 3.4: Mobility matrix for the bottom 40 and top 60 percent of the population**|
|---|

|a) Uppe|r bound|||b) Lowe|r bound|||
|---|---|---|---|---|---|---|---|
|||2009||||2009||
|2003|Top60|Bottom 40|Total|2003|Top60|Bottom 40|Total|
|Top60|41|20|60|Top60|57|3|60|
|Bottom 40|19|20|40|Bottom 40|3|37|40|
|Total|60|40|100|Total|60|40|100|

Source: Authors’ calculations based on ECAPOV data.

Notes: transition matrix is based on synthetic panel for 2003-2009. Explanatory variables include year of birth cohort, number of children, education of the head of household, rural/urban and regional dummies, and different interactions between these variables and means are the regional level. Sample: heads of household 25-55 years of age. Welfare aggregate is as used to calculate national poverty rates.

> 6 Detailed explanation of churning in the bottom 40 percent is provided in box 1 in annex.

> 7 48 percent were obtained by dividing 19 by 40 in table 3.4a, 8 percent were obtained by dividing 3 by 40 in table 3.4b.

12
<!-- Start of picture text --> 120<br>o 100<br>#a<br>G 380<br>i<br>a<br>ER 60<br>E 6 40<br>aE<br>eo<br>8 * 320<br>e<br>y 0<br>a 2003 2009 2003 2009<br>Bottom 40 (persistent group) B40 to T60 T60 to B40<br>(graduates) {entrants}<br><!-- End of picture text -->
during 2003-2009. Labor market gains, namely labor earnings, accounted for 21 percentage points of this total, while creation of new employment opportunities contributed minimally to poverty reduction=. Among other income sources, remittances played a crucial role accounting for 8 percentage points of poverty reduction. These results are not surprising given importance of labor earnings in total income of households and the real growth of labor earnings, pensions and remittances during 2003-2009 (tables A1 and A2). Other factors such as the demographic dividend<sup>8</sup> , pensions and social assistance were also poverty decreasing, but their role was rather minor.

18. **Remittances and labor earnings are more important for the welfare improvement of the middle class, while employment and pensions are more important for the poor/vulnerable and the bottom 40 percent of the population.** Figures 4.3 and 4.4 demonstrate the role each factor plays in welfare changes across different classes and the bottom 40 percent of the population. The middle class benefited more from the labor earnings and remittances in relative terms than the poor/vulnerable and the bottom 40. In contrast, employment and pensions were more important for the poor and the vulnerable as well as for the bottom 40 percent of the population.

19. **Employment played the most important role for inequality reduction, while remittances had a neutral or even a dis-equalizing effect.** Decomposing changes in income per capita Gini shows that all factors, except remittances, were associated with lower inequality (figure 4.2). Interestingly, employment played a minimal role in poverty reduction, but had the strongest equalizing impact which is in line with the higher role of employment in improving the wellbeing of the poor and vulnerable. Remittances had a dis-equalizing effect and this is consistent with their high role in welfare improvement of the middle class. This may be a result of costs international migrants have to incur and which make international migration a difficult option for the poorest households.

**Figure 4.1: Income poverty decomposition, Figure 4.2: Income Gini decomposition, 20032003-2009 2009**

<!-- Start of picture text --> 0<br>0.01<br>-4<br>-0.01<br>-8<br>-0.02<br>-12<br>-0.03<br>-16<br>-20 -0.04<br>-24 -0.05<br>Gini<br>share of adults share of employed labor earnings pensions social assistance remittances other income<br>points<br>drop in poverty, percentage share of pensions<br>share of adults employed labor earnings social assistance remittances other income<br><!-- End of picture text --> Source: Authors’ calculation based on ECAPOV data. Notes: Poverty line is 2.5 USD/PPP per day. Welfare aggregate is income per capita.

Source: Authors’ calculation based on ECAPOV data. Notes: Poverty line is 2.5 USD/PPP per day. Welfare aggregate is income per capita.

> 8 Demographic dividend is reflected by the share of adults in income decomposition.

14
<!-- Start of picture text --> 100<br>0<br>60<br>40<br>So<br>0<br>-20<br>Poor vulnerable — middle income<br>class<br>mw<br>m@ share of adults m share of employed<br>§ sociallabor earningsassistance TM@@ p r e mittancesnsions<br><!-- End of picture text --> <!-- Start of picture text --> 100<br>80<br>60<br>40<br>&<br>20<br>0 :<br>total population bottom 40<br>m share of adults m share of employed<br>wlab : - :<br>Ssheaae2 ea SERERSON S<br><!-- End of picture text --> <!-- Start of picture text --> 100<br>80<br>60<br>&<br>40<br>20<br>0)<br>rural urban<br>@ share of adults mMshare ofemployed __@ labor earnings<br>@ pensions @ social assistance @ remittances<br>® other income<br><!-- End of picture text -->
<!-- Start of picture text --> % female mmale mnogender disaggregation<br>i] fa)<br>e<br>- -4<br>7)Q<br>ra 8<br>> ‘e112<br>comae16<br>%<br>a<br>oO§ xe}2wn« 38© od —B®c2) ro)Vv—€8 xe}&a)<br>S a = ra o<br>vo= SeLF) os rmv rs)wv<br>oC o £ —<br>iw 2—a© o iocw<br><!-- End of picture text --> <!-- Start of picture text --> 0.01 -mfemale_mmale no gender disaggregation<br>‘<br>0.00<br>-0.01<br>-0.02<br>-0.03<br>-0.04<br>-0.05<br>5 & 6 —g &<br>2== 8Q €&G =§c cisSs8<br>° = © fe °<br>vo oft° 25 £ wvo<br>om wo o ° a<br>“ ao=a ore wv<br>w<br><!-- End of picture text -->
<!-- Start of picture text --> Middle class +)<br>Poor and the vulnerable<br>- Industry agriculture<br>8 i) .<br>} Q construction<br>8<br>i]<br>=<br>S Services-<br>fe}<br>=<br>Cy)<br>u<br>3 6<br>B<br>o size of the buble<br>3<br>g # of employed<br>rT]<br>o<br>=<br>-6 -4 -2 0 2 4 6 8 10 12<br>Employment growth, 2000-2010<br><!-- End of picture text --> <!-- Start of picture text --> 2003 2007 2009 Ww 109<br>7cw 0 ¥cc go<br>SE s<br>oS -0.2 3 60<br>Go =<br>oS a 40<br># = 70.4 3<br>> 2 ny<br>E= 0.6 o 20<br>Esoo Ry<br>TB YW -08<br>< “3 male female male female male female<br>§s 7 2003 2007 2009<br>-1.2 Hiotalemployed unemployed S retired<br>mstudent @ OLF<br>munconditional conditional<br><!-- End of picture text --> <!-- Start of picture text --> Ww 109<br>¥cc go<br>s<br>3 60<br>=<br>a 40<br>3<br>ny<br>o 20<br>Ry<br>male female male female male female<br>2003 2007 2009<br>Hiotalemployed unemployed S retired<br>mstudent @ OLF<br><!-- End of picture text -->
<!-- Start of picture text -->
1.60<br>1.40 m 2003 = 2007 m 2009<br>1.20<br>1.00<br>0.80<br>0.60<br>0.40<br>0.20<br>0.00 . . . .<br>basic general specialized tertiary<br>education secondary secondary<br><!-- End of picture text -->

<!-- Start of picture text -->
1.60<br>1.40 m 2003 = 2007 m 2009<br>1.20<br>1.00<br>0.80<br>0.60<br>0.40<br>0.20<br>0.00<br>bash: general specialized tertiary<br>education secondary secondary<br><!-- End of picture text -->

<!-- Start of picture text --> m 2003 2007 = 2009<br>1.6<br>1.4<br>1:2<br>1.0<br>0.8<br>0.6<br>0.4<br>0.2<br>0.0<br>5 : 3 2<br>= A<br><!-- End of picture text --> <!-- Start of picture text --> = 2003 = 2007 = 2009<br>16<br>:<br>1.4<br>1.2<br>1.0<br>0.8<br>0.6<br>0.4<br>0.2<br>0.0<br>0.2<br>6 7 F YF w<br>wo wo ae<br><!-- End of picture text -->
<!-- Start of picture text --> 2.2<br>.<br>1.8<br>1.6<br>1.2<br>1<br>vr Jan, Jan, Jan, Jan, Jan,<br>8o 2009 2010 2011 2012 2013<br>N<br>—total —— industry ——agriculture<br>——=construction -—— services<br><!-- End of picture text --> <!-- Start of picture text --> 1200<br>& 1000<br>£8<br>w 800<br>SD<br>3 600<br>2<br>= 400<br>Pe<br>c<br>2 200<br>0<br>Jan, Jan, Jan, Jan, Jan,<br>oe 7BI0 ae) 2012 2013<br>——— industry —— agriculture = construction<br>—— services —l— min real wage<br><!-- End of picture text -->
<!-- Start of picture text --> 200<br>fil<br>150<br>100<br>a<br>so<br>0<br>Jan, Jan, Jan, Jan, Jan,<br>_ 2009 2010 2011 2012 2013<br>6<br>~ —— agriculture @ minreal wage<br>=<br><!-- End of picture text --> <!-- Start of picture text --> 4000 60<br>3500 50<br>3000<br>ay 40<br>2500 ss<br>£5 2000 1 30 ba<br>Sea 20 *<br>1000<br>500 10<br>0 0<br>2009 2010, 2011-2012<br>Gum remittances recevied, min USD<br>—— remittances recevied, % GDP<br><!-- End of picture text -->
<!-- Start of picture text --> 110<br>105<br>100<br>95 _— Tajikistan<br>= 90<br>o<br>oO<br>@ 85<br>S<br>2 80<br>> _ Kyrgyzstan<br>o 75 i—_-<br>© A =<br>2 AS ~— World<br>x 8 a 7<br>F 60 —¥ ” aad a ———<br>Kazakhstan I cic<br>= Sa _ a =<br>50 wee<br>45<br>40<br>1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065<br><!-- End of picture text -->
<!-- Start of picture text --> 100<br>390<br>80<br>4 70<br>2 60<br>a<br>s 50<br>re)<br>= 40<br>°<br>se «30<br>20<br>0 ia<br>° a ig i<br>Nationwide Dushanbe GBAO Sogd Khatlon RRS<br>@ Experienced unscheduled electricity interruptions<br>@ Satisfied with the quality of electrical service<br><!-- End of picture text -->
<!-- Start of picture text --> 50 12<br>=<br>p e 40 4 10<br>fe = rural murban<br>S ye<br>sm 30 S 8<br>Zz ie<br>o 20 a<br>Qwo 2. 6<br>£ 10 fom<br>sGax 0 P=) ini i B ra::co)°::co)°co)°°<br>Tajikistan Europe & Central Low income Fi 2<br>Asia (developing =<br>only) 0<br>Account at a a formal Loan fromaa financial<br>@ Account at a formal financial institution financial institution, institution in the the past year year<br>m@ Loan from a financial institution in the past year ee,, Caaeeay).. Ss<br><!-- End of picture text --> <!-- Start of picture text --> 12<br>4 10<br>= rural murban<br>ye<br>S 8<br>ie<br>a<br>2. 6<br>fom<br>ra::co)°::co)°co)°°<br>Fi 2<br>=<br>0<br>Account at a a formal Loan fromaa financial<br>financial institution, institution in the the past year year<br>ee,, Caaeeay).. Ss<br><!-- End of picture text -->
<!-- Start of picture text --> @ Tajikistan @ECA<br>80<br>70<br>60<br>uv<br>wv 50<br>€ 40<br>o<br>: 30<br>a 20<br>10<br>Qe<br>eec 5 Ooe =£ vn6Es8 =< az Ss5c<br>ow off Vv =] 4<br>s 26 2 c > Co ° 3<br>Ve = = -— Pa} ro<br>Ms$§oo aoa556 £252° a> =& 5Oo5<br>x wo FP S 2<br>vt G Fe rs)<br>Be ee oP Hes<br>= ° faa vad<br>=: 2 :<br>2 Oo<br><!-- End of picture text -->
increasing returns to experience was the key factor behind the poverty reducing effect of labor earnings. In terms of inequality, however, employment was the most equalizing factor, while remittances were inequality enhancing. Looking forward, sustaining inclusive growth will require Tajikistan to address the following challenges: (i) high vulnerability to macroeconomic shocks and climate change, (ii) poor quality of public services and unequal access to them, (iii) lack of well-functioning and easily accessible markets.

25
# **6. References**

Abras, Anna., Cuesta, Joce and Sailesh, Tiwari. (forthcoming). How equal are opportunities among children in Tajikistan. World Bank.

Attanasio, Orazio and Szekely, Miguel eds. 2001. Portrait of the Poor: An Assets-based Approach, Inter-American Development Bank. Washington, DC.

- Azevedo, Joao Pedro, Minh Cong Nguyen & Viviane Sanfelice, (2012). "ADECOMP: Stata module to estimate Shapley Decomposition by Components of a Welfare Measure," Statistical Software Components S457562, Boston College Department of Economics.

- Basu, Kaushik. 2013. Shared Prosperity and the Mitigation of Poverty in Practice and in Precept. Policy Research Working Paper 6700. World Bank. Washington, DC.

Development Coordination Council (2012). Tajikistan: 2012 Development Forum.

FINDEX. Global Financial Inclusion Database. Available from: http://datatopics.worldbank.org/financialinclusion/

- Kaufmann, Daniel and Kraay, Aart and Mastruzzi, Massimo, The Worldwide Governance Indicators: Methodology and Analytical Issues (2010). World Bank Policy Research Working Paper No. 5430.

- Heleniuk, Е., Sulla, V. and Rajabov, A. (2012). Sustainable Poverty Reduction and Emerging Middle Class in Tajikistan.

- Lanjouw, Peter, Jill Louto, and David McKenzie. 2011. “Using Repeated Cross-Sections to Explore Movements in and out of Poverty.” World Bank Policy Research Working Paper 5550.

Newman, John, L., Joao Pedro Azevedo (2013) “Setting reasonable performance targets for public service delivery”, Policy research Working Paper Series 6385.

National Statistical Committee of the Republic of Tajikistan. www.stat.tj Sattar, S., Bierbaum, M., Barfieva, S., Flanaga, J., Lakhani, S. and Swinkels, R. (2013). Tajikistan Gender Diagnostics Note. Report No: ACS5015.

World Bank (2009). Republic of Tajikistan poverty assessment. Report No. 51341-TJ.

World Bank (2013a). When Prosperity is not Shared: On the Weak Links between Growth and Equity in Dominican Republic. Washington, DC: World Bank.

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World Bank (2013b). Tajikistan. Policy notes of public expenditures. Report No. 77607-TJ.

World Development Indicators. http://data.worldbank.org/data-catalog/world-developmentindicators World Governance Indicators. http://info.worldbank.org/governance/wgi/index.aspx#home 27
# **7. Annex**

**<u>Table A.1:  Shares of different income components in total income across years, %</u>**

||2003|2007|2009|
|---|---|---|---|
|Labor earnings|65.1|74.6|61.2|
|Pensions|12.7|11.8|8.1|
|Social assistance|3.1|1.0|2.5|
|Remittances|11.0|8.7|17.0|
|Other income|8.0|3.9|11.1|
|Source: Authors’ calculations based on ECAPOV data.||||

**Table A.2:  Growth rate of different income components, share of adults and share of employed -** **<u>across quartiles during 2003 2009, %</u>**

|Quart<br>iles|Share of<br>adults|Share of employed (non-zero<br>labor earnings)|Labor<br>earnings|Pensi<br>ons|Social<br>assistance|Remitta<br>nces|Other<br>income|
|---|---|---|---|---|---|---|---|
|botto||||||||
|m|11|90|1277|381|857|1244|1463|
|II|10|3|522|451|491|898|906|
|III|12|-1|439|428|322|848|715|
|top|9|0|332|221|170|951|415|

Source: Authors’ calculations based on ECAPOV data. Notes: Quartiles are constructed based on income per capita. Income components are USD/PPP 2005 prices.

**<u>Table A.3:  Profile of population in the bottom 40 percent for selected years</u>**

|||Bottom 40||Top60||
|---|---|---|---|---|---|
||2003|2007<br>2009|2003|2007|2009|
|||**Residence**||||
|urban|26.5|27.8<br>23.6|31.6|25.3|28.2|
|rural|73.5|72.2<br>76.5|68.4|74.7|71.8|
|||**Oblast**||||
|Dushanbe|5.2|10.4<br>6.5|12.3|8.7|11.4|
|Sogd|32.4|44.4<br>26.7|31.4|19.9|31.3|
|Khatlon|44.8|21.9<br>44.3|24.4|44.9|30.2|
|RRP|13.7|21.3<br>19.6|29.7|22.8|24.2|
|GBAO|4.0|2.0<br>2.9|2.9|0.0|0.0|
|||**Education (16+)**||||
|none/<1-4|6.6|6.7<br>7.8|6.0|6.6|5.3|
|incomplete 5-12|18.6|23.0<br>21.3|16.5|19.9|17.6|
|gen sec|55.0|50.6<br>52.3|49.3|48.3|52.0|
|spec sec|6.9|9.1<br>8.6|11.2|12.3|11.2|
|tertiary|4.5|6.4<br>6.1|10.5|10.4|11.6|
|missing|8.4|4.2<br>3.8|6.4|2.5|2.4|
|||**Labor force status (16+)**||||
|employee|31.8|19.6<br>17.2|30.4|25.0|18.3|

28
|self-employed|19.0|21.4|22.7|22.9|21.1|22.6|
|---|---|---|---|---|---|---|
|unemployed|2.5|1.8|5.4|2.3|2.0|4.2|
|retired|7.2|10.1|8.5|7.6|8.1|8.9|
|student|4.1|8.1|8.6|6.2|10.9|10.1|
|OLF|35.4|39.1|37.6|30.5|32.8|35.9|

Source: Authors’ calculations based on ECAPOV data.

**<u>Table A.4:  Profile of households  in the bottom 40 percent for selected years</u>**

|||Bottom 40|||Top 60||
|---|---|---|---|---|---|---|
||2003|2007|2009|2003|2007|2009|
|||**Number of ch**<br>|**ildren in HH**<br>||||
|0-1|12.5|17.9|14.1|26.0|30.6|32.7|
|2|18.7|19.8|18.6|21.9|22.3|26.7|
|3|20.1|23.4|21.2|20.7|21.5|17.6|
|4|19.5|19.0|21.3|14.3|13.0|11.9|
|5+|29.3|19.8|24.9|17.2|12.6|11.2|
|Dependency ratio|0.45|0.43|0.41|0.41|0.37|0.35|
|||**Size of the**|**household**||||
|1|0.2|0.1|0.0|0.8|0.6|0.6|
|2|0.4|0.6|0.2|2.2|1.6|1.7|
|3|1.2|1.8|0.6|4.3|4.2|4.2|
|4|3.2|4.6|2.2|9.1|8.4|7.4|
|5+|95.0|92.9|97.0|83.7|85.3|86.1|
|||**HH ed**<br>|**ucation**<br>||||
|incomplete 5-12|14.2|16.3|16.2|10.1|11.3|11.3|
|gen sec|48.9|42.6|40.0|37.0|33.9|34.6|
|spec sec|14.2|19.6|20.4|20.3|26.9|25.0|
|tertiary|11.6|13.8|12.6|22.1|20.4|22.5|
|none/<1-4|11.1|7.8|10.8|10.6|7.6|6.6|
|||**HH labor f**<br>|**orce status**<br>||||
|employee|44.0|29.3|28.2|45.3|37.9|29.6|
|self-employed|17.4|27.8|27.2|19.9|29.5|32.4|
|unemployed|2.7|1.7|3.1|2.3|2.0|4.5|
|retired|18.4|24.7|28.7|16.9|18.5|21.7|
|student|0.3|0.6|0.0|0.3|0.6|0.0|
|OLF<br>Source: Authors’ calculation|17.2<br>s based on ECAP|15.9<br>OV data.|12.9|15.3|11.6|11.9|

29
<!-- Start of picture text --> 2.5 USD/PPP 2005<br>100<br>£ c 80 ——<br>= 60<br>a<br>a<br>°<br>=<br>° 40<br>&<br>20<br>0<br>consumption income<br>@ 2003 @ 2007 @ 2009<br><!-- End of picture text --> <!-- Start of picture text --> w 100<br>a B80<br>= =60<br>Zon<br>wig wm510<br>=~ 4<br>¢ Ba<br>7003 7007 7009<br>B primaryand less § basic education<br>lB general secondary § specialized secondary<br>SM tertiary<br><!-- End of picture text --> <!-- Start of picture text --> 2 100<br># 80<br>= =60<br>=n<br>uiB50om<br>=a<br>g 230<br>2005 2007 2009<br>@ primaryand less § basic education<br>@ general secondary B§ specialized secondary<br>M@ tertiary<br><!-- End of picture text -->
Box 1. Churning in the bottom 40 percent of the population The shared prosperity indicator, which measures consumption per capita growth of the bottom 40 percent of the population, is an anonymous indicator. In other words, there is no guarantee to observe the same individuals in the bottom 40 percent of the population across years. In particular, several potential scenarios may occur. First, individuals can be the same in the bottom 40 percent in two periods _[(1) in Figure A.4]_ . Second, individuals from the bottom 40 percent in the first period can move to the top 60 percent in the second period (graduates) _[(2) in Figure A.4]_ . Third, individuals from the top 60 percent of the population in period one can move to the bottom 40 percent in the period two (entrants) _[(3) in Figure A.4]_ . The forth scenario, in which the population in the top 60 percent is the same across periods, is not relevant to this analysis of the bottom 40 percent [ _(4) in Figure A.4]_ . The overall impact of churning will depend on the magnitude of these movements.

There are several options to see the described scenarios. The first option is to track the mobility of people using panel data. This will allow tracking the same people over a particular period. The second option is to use a synthetic panel approach based on repeated cross-sectional data. This provides an opportunity to predict the consumption of households in the first period using information about their consumption in the second period and permanent household characteristics. In this paper, the second approach is used.

**Figure A4: Churning in the bottom 40 percent of the population**

<!-- Start of picture text --> 4<br>Top Top<br>60 60<br>2<br>3<br>Bottom Bottom<br>1<br>40 40<br>Period T Period T+1<br><!-- End of picture text --> <!-- Start of picture text --> Source : Authors’ drawing.<br><!-- End of picture text --> 31
Box 2. Synthetic panel methodology The issue of economic mobility has gained relevance in academic and wider policy discussion over the last years. Data requirements to analyze this issue are not trivial, though. A proper study requires householdlevel information for at least two periods, not only for income or consumption, but also for other variables that can affect changes in income or consumption. Unfortunately, the availability of panel surveys that contain this type of information is quite limited, and even when existent, many times they suffer from high attrition rates and relatively short survey periods.

The synthetic panel methodology overcomes these shortcomings and builds on an imputation methodology to predict consumption in the second period using two different rounds of data. It relies on time-invariant individual and household characteristics (Figure A5). Consumption in each period is modeled as the sum of two components: a first one associated with time-invariant characteristics (F(X)), and a second one capturing non-observable factors (e). To create the predicted consumption in the first round for the households from the second round, we generate a new component based on how their time-invariant characteristics are associated with consumption, but in the first round. Adding up this new component to the non-observable factors we obtain the predicted consumption in round one. With these two welfare aggregates we construct transition matrices to analyze economic mobility between rounds.

<!-- Start of picture text --> Figure A5: Synthetic panel approach<br>Round one Round two<br>Observed consumption Predicted consumption Observed consumption<br>C1 C1 Ĉ2 Ĉ2 C2 C2<br>C1 Ĉ2 C2<br>C1 Ĉ2 C2<br>C1 X1 Ĉ2 C2<br>C1=F1(X1)+e1<br>C – consumption<br>Ĉ – predicted consumption<br>X – time invariant household and individual characteristics<br><!-- End of picture text --> Depending on the assumptions made about the non-observable characteristics, the method generates a high and a low mobility scenario. For the low mobility scenario, non-observable characteristics do not change in time, whereas for the high mobility scenario they change between rounds. In intuitive terms, low mobility implies that if a shock affects consumption in the first period, it continues to do so in the second one, and in the same direction. High mobility implies that there is no relationship between shocks in time. True mobility should be found within these two boundaries.

The quality of the imputation improves as time-invariant characteristics capture more variation in consumption. Notwithstanding this limitation, synthetic panels allow the use of existing data in a novel way to better understand economic mobility and its determinants.

Source: Adopted by Atamanov, A., Cancho, C. and Meyer, M. from Lanjouw, Louto and McKenzie (2011) 32
<!-- Start of picture text --> All (5 years inte a)<br>sample: Gl ~ |<br>1.25 USD-PPPper day 2.50 USD-PPP per day 5.00 USD-PPPper day<br>3iii<br>2: i i<br>=iHHe<br>3N i EF- i Es i ga<br>zi:i zu=a i:i zua i:i =w7<br>i — i — i<br>Oth 20th 40th 60th 80th 100th Oth 20th 40th 60th 80th 100th Oth 20th 40th 60th 80th 100th<br>Percentile of countries performance (Unconditional distribution) | Percentile of countries performance (Unconditional distribution) | Percentile of countries performance (Unconditional distribution)<br>Benchmarking: Tajikistan Betas:<br>Betas: Global; Poverty line: All; Model Model ; 5 years(s) years(s) interval | Global bd<br><!-- End of picture text -->

Benchmarking: Tajikistan Betas: Global; Poverty line: All; Model Model ; 5 years(s) years(s) interval <!-- Start of picture text --> Europe & Central Asia (all income levels), Tajikistan<br>1.25 USD-PPP per day 2.50 USD-PPP per day 5.00 USD-PPP per day<br>2004-2009 2004-2009 2004-2009<br>100 90th 90th 96th S2th<br>81th<br>74th<br>®Ss<br>-0 - -<br>Unconditional percentile Conditional Percentile Unconditional percentile Conditional Percentile Unconditional percentile Conditional Percentile<br><!-- End of picture text -->
**Table A.5:** **<u>Construction of income aggregates</u>** ECAPOV harmonized data is use as a basis for construction income aggregates used in this paper. The main difference between income aggregate in this paper and the ECAPOV data stems from the definition of remittances. Remittances in this paper are defined differently between 2003 and 2007/2009 years given the changes in questionnaires.

In 2003 remittances include the transfers households received from donors residing outside of Tajikistan both in cash and in-kind forms (module 7a, questions 8 and 11). In 2007 and 2009 years migration module was expanded and remittances are defined as a sum of transfers from donors living outside of Tajikistan both in cash and in-kind (module 8a, questions 8 and 12), remittances from family members living abroad (module 2c, question 19), and finally as 70 percent of returned migrant net income while he/she was being abroad (module 2b, question 12).

Other income components include labor earnings, pensions, social assistance, and other income.

Labor earnings include wages and self-employment income. Pensions include old age, disability, social and survivor pensions.

Social assistance includes allowances, benefits to Chernobyl victims and Afghan war participants, illness benefits etc.

Other income include child benefits, unemployment benefits, property income (income from renting <u>property, income from selling assets and property), income from gambling, and interest rates.</u> 34