What if growth had been as good for the poor as everyone else? Research reports and studies

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1 May 2015 Report What if growth had been as good for the poor as everyone else? Chris Hoy and Emma Samman Over the last three decades, acr  or income growth of oss 100 countries, consumption the bottom 40% of the population roughly equalled average growt h. In just over half of countries (55%) that accounted for nearly 80% of the global population, average growth exceeded tha t of the bottom 40%. If growth of the bottom 40% had eq ualled national averages in a ll countries, the  world would be on track to reac h zero poverty by 2030 and China would have no es would have higher poverty. poverty today – but some countri If growth had been more equal, abo ut two hundred million fewer people would be  ay’s low-income come countries. In most of tod poor in many of today’s middle-in countries, growth was relatively pro-poor on average. Proposals that the growth of the  ght to exceed the bottom 40% within countries ou national average must be sensitiv s – taking to account e to diverse potential outcome ce poverty, to w hat extent, and h whether a growth gap will redu ow best to redistribute.

2 Acknowledgements We are very grateful to Ricardo Fuentes-Nieva who gave us the i dea for this paper, and for reviewing an earlier draft. Claire Melamed and Elizabeth Stuart also provided helpfu l comments and suggestions. Kofo Sanusi and Ben Tritton managed layout and production. 1 Effective international development action beyond 2015 This paper is an output of the following project: ‘ ’. Details of current funders of the project can be found online. 1 http://www.odi.org/projects/2531- post-2015-millennium-sustaina ble-development-goals-poverty

3 Table of contents ii Acknowledgements Executive summary iii 5 1 Introduction 2 Methodology 10 10 2.1 Dataset h incidence curves 11 2.2 Application of growt 2.3 Making global poverty estim 14 ates using the country sample er the last 30 years 2.4 Country experience ov 14 17 2.5 Equal growth scenario 2.6 Extreme poverty headcount r atio in equal growth scenario 18 2.7 Pro-poor growth scenarios 22 3 Conclusion 31 Figures unt ratio in the developing wor ld, 1990-2011 6 Figure 1: Extreme poverty headco in extreme poverty (millions) , 1990-2011 6 Figure 2: Number of people living Figure 3: Projections of extreme poverty headcount ratio in 203 0 (%) 7 Figure 4: Projections of the extr ) in 2030 under different eme poverty headcount ratio (% inequality scenarios 8 Figure 5: World Bank (2014) sce narios for extreme poverty 8 Figure 6: Initial consum ption distribution 11 12 Figure 7: Actual consumption growth Figure 8: Scenario 1: Equal gro wth across distribution 12 13 buted from the top 60% Figure 9: Growth redistri Figure 10: Growth redistributed from top 10% 13 distribution was different 14 nario 2 for China if share of Figure 11: Growth rates under sce owth of mean and bottom 40% Figure 12: Difference between gr 15 Figure 13: Distribution of countri th and growth of the es’ gaps between average grow 17 bottom 40% t experienced different levels of pro-poor growth Figure 14: Share of countries tha 17 Figure 15: Equal growth scenario 20 Figure 16: Total poverty by income category 22 Figure 17: Extreme poverty headco unt ratio in pro-poor growth ( 1pp) scenario 23 Figure 18: Pro-poor (1pp) scenario 24 unt ratio in pro-poor growth ( 2pp) scenario Figure 19: Extreme poverty headco 24 Figure 20: Pro-poor growth (2pp) scenario 26 Figure 21: Extreme poverty headco unt ratio in pro-poor growth ( 3pp) scenario 27 Figure 22: Pro-poor growth (3pp) scenario 29 Figure 23: Extreme poverty under d ifferent redistribution scena rios 30 Tables Table 1: Summary of findings on poverty impact of the different scenarios iv and gap between 16 Table 2: Basic statistics concerning growth of mean, bottom 40% i

4 growth compared with observed patterns over last 30 Table 3: Poverty effects of equal years 19 Table 4: Extreme poverty headcoun t ratios in selected UMICs bas ed upon equal growth scenario 21 t ratios in selected LICs base d upon Equal Growth Table 5: Extreme poverty headcoun Scenario 21 Table 6: Pro-poor growth (1pp) c ompared with observed patterns over last 30 years 23 ompared with observed patterns Table 7: Pro-poor growth (2pp) c over last 30 years 25 ed upon pro-poor unt ratios in selected LMICs bas Table 8: Extreme poverty headco growth (2pp) scenario 25 over last 30 years 28 Table 9: Pro-poor growth (3pp) c ompared with observed patterns Table 10: Extreme poverty headco unt ratios in selected LICs bas ed upon pro-poor growth scenarios 29 Table 11: Summary of findings o n poverty impact of the differen t scenarios 31 ii

5 Executive summary World leaders are set to endorse an ambitious set of Sustainabl e Development Goals (SDGs) in September 2015. Proposed targets aim to, among other things, eliminate extreme income poverty ($1.25 a day) by 2030 and ensure that the bottom 40% of the distribution rowth. Although extreme povert y has fallen considerably experiences higher than average g persists at unacceptably high le vels and inequality within many over the last thirty years, it countries has risen. More equally distributed growth could redu ce poverty further, in addition to having other positive spill-over effects. Numerous projections have suggested that the world could come c lose to eliminating extreme poverty by 2030. However they tend to assume that growt h will be shared equally by all people, regardless of where they are located in the inco me distribution. This report interrogates this assumption. It considers the implications of growth in which the bottom 40% of the population shares equally or more, taking a retrospe ctive view. First, we consider the range of country experience over the las t three decades, in terms of the growth of the bottom 40% of the population relative to the societal average. On average, growth was equal for the bottom 40% and the average, but with a wide range of country experiences. The mean grew faster than the bottom 40 percent i n just over half of countries (55%). Around two hundred million more pe ople would have escaped pover ty in many of today’s middle-income countries (MICs), if growth had not been so unequ al. In contrast, in most of today’s low-income countries (LICs), there would be relative li ttle difference in the number of people in extreme poverty because growth was already relativ ely pro-poor on average. Country experiences over the last thirty years tend to fall in two distinct categories: those that have grown considerably, on average, and now are MICs, but where the poor did not benefit as much as the average person from growth, or those tha t have not grown significantly and have stayed LI Cs, but where the poor did not miss out disproportionally from the growth that did occur. Second, the report asks what would have happened to poverty if the growth of the bottom 40% of the population had been equal to or higher than that of the average over the past thirty years for those countries that have reliable data. The a nalysis is based on the admittedly crude assumption that redistribution of the benefits of growth would not have affected overall levels; nonetheless, this may in fact result i n an understatement of growth given considerable evidence that greater equality can enhance g rowth. We explore two types of scenarios: 1. Equal Growth. All parts of the population experience average na tional growth. 2. Pro-poor Growth. Bottom 40 percent experiences higher than aver age growth – we select three plausible growth gaps (1, 2 and 3 percentage points) draw ing on actual country performance over the las t 30 years (Table 1). We show that global poverty could have been significantly lower today had growth over rld would be on track to the last 30 years been more equally distributed and that the wo iii

6 y poverty in some eliminate extreme poverty completely by 2030. Indeed, 1.25 a da countries – including China – would disappear. Table 1: Summary of findings on poverty impact of the different scenarios Actual Equal 3ppt/10% 3ppt/60% 1ppt 2ppt growth b40% 2010 20.6 16.8 10.0 7.1 7.7 4.4 Had growth had been ‘pro-poor’, in particular if the bottom 40% had grown just 1 percentage point faster than the mean for those years for which we have data, global poverty would be half of what it is today. With a growth gap of 3 perce ntage points, which is towards verty would depend on the upper bounds of country experience, the effect on global po where in the distribution growth would be reduced to compensate . In other words, there may be a perverse effect on poverty when growth stays constant if reductions in income from the upper part of the distribution push people into povert y. We illustrate this point by comparing the implications of a 3 p ercentage point gap in growth alongside redistribution from the top 60% of the population and top 10%, respectively. In the case of the former, global poverty would increase relative to the 2 percentage point scenario while in the latter, it would drop markedly – to one-f ifth of the actual 2010 poverty level. The range of country experiences is diverse, suggesting that national policies need to account for whether a growth gap will be poverty reducing, the appropriate size, and how redistribution should be accomplished. iv

7 1 Introduction e Development Goals (SDGs) World leaders are set to endorse an ambitious set of Sustainabl 2 in September 2015. Proposed targets aim to, among other things, eliminate extreme poverty on experiences at least by 2030 and ensure that the bottom 40% of the income distributi 3 average growth. Although extreme poverty has fallen considerably over the last twenty-five 4 y high levels, and inequality within many countries has risen. years, it persists at unacceptabl duced poverty further, in It is argued that more equally distributed growth could have re 5 addition to having other positive spill-over effects. For example, Hildebrand and Van Kerm (2009, p. 7) assert that globally, between 1981 and 2005, while the impact of economic growth was to lift hundreds of millions of people out of povert y, increases in inequality meant that nearly 600 million people who would have escaped pov erty had inequality 6 remained static were denied that chance. 7 The available data t five suggests that the MDG target of halving extreme poverty was me years ahead of schedule but with considerable regional variatio n (Figure 1). According to ping world (43%) were poor the $1.25 a day measure, more than 4 in 10 people in the develo in 1990, while the most recent estimates suggest less than half that number (17%) remained 8 poor in 2011. East Asia and the Pacific (EAP) and Sub-Saharan Africa (SSA) h ad similar poverty rates (around 55%) in 1990; by 2011, the poverty rate h ad dropped to less than 10% in EAP, but it remained just below 50% in SSA. The poverty rate declined steadily in South Asia (SoA). Elsewhere in the developing world, the poverty rate was low already in 1990 9 (less than 7%) and it declined to about 2.5% by 2011. 2 All reference in this paper ar on the $1.25 a day metric as this was the focus of MDG e to income poverty and we focus t. target 1.1 and is likely to be the focus on a SDG poverty targe 3 lopment Goals (2014) Open Working Open Working Group of the General Assembly on Sustainable Deve Group proposal for Sustainable Dev Sustainable Development Knowledge elopment Goals. New York: UN Platform. (http://sustainabledeve lopment.un.org/content/documen ts/1579SDGs%20Proposal.pdf) 4 The regional picture is diver 1990 shows that inequality increas ed more in Eastern Europe se. Data for 141 countries since and the Former Soviet Union as w ell as Asia, that it declined s ignificantly in Latin America after 2000, and while Sub- Saharan Africa remains highly une qual, its Gini has fallen almo st 5 points on average since 1990 (Ortiz and Cummins 2001). Ortiz, I. & M. Cummins, 2011. " Global Inequality: Beyond the Bo ttom Billion – A Rapid Review of Income Distribution in 141 Countries," Working papers 1102, UNICEF, Division of Policy and Practice. 5 See Samman, E. and C. Melame d (2014), “Equity, inequality and human development”, in Jespersen, E. et al. (Eds), st . Century: Conceptualizing and measuring progress Human Development for the 21 6 (2009), “Income inequality and Hildebrand, V. and P. Van Kerm self-rated health status: evidence from the European Community Household Panel”, Demography, Nov; 46(4):805-25 . 7 Data are available for 100 of 188 official IBRD countries – bu t these cover 91% of the population of the developing world. The specific time period varies depending on the country – see Appendix for more details. 8 Poverty figures are from the World Bank’s PovCal Net, availabl e at: http://iresearch.worldbank.or g/PovcalNet/index.htm?3 9 The ‘Rest of Developing World’ category includes low- and midd le-income countries in Latin America and the Caribbean, . Middle East and North Africa as well as Europe and Central Asia 5

8 dcount ratio in the developing wor Figure 1: Extreme poverty hea ld, 1990-2011 70% 60% 50% Sub-Saharan 40% Africa South Asia 30% 20% East Asia and Pacific 10% Rest of the Developing World 0% t: http://iresearch.worldbank.org/PovcalNet/index.htm?3 Source: World Bank’s PovCal Net, available a A focus on the share of people in poverty hides population chan ge over the period, and therefore the number of people who are poor at any time. Almost 2 billion people were in andscape changed extreme poverty in 1990, around half of whom were in EAP. The l people remained poor. Over es – as of 2011, about 1 billion dramatically over the two decad 80% of these poor people lived in SoA and SSA (Figure 2). The n umber of people living in by about 125 million. extreme poverty declined slightly in SoA, but increased in SSA , 1990- in extreme poverty (millions) Figure 2: Number of people living 2011 2000 1800 1600 1400 1200 1000 800 600 400 200 0 1990 1993 1996 1999 2002 2005 2008 2010 2011 South Asia Sub-Saharan Africa Rest of the world East Asia and Pacific h.worldbank.org/PovcalNet/index.htm?3 Source: World Bank’s PovCal Net, available at: http://iresearc 6

9 monstrate that the world Numerous studies have projected trends in extreme poverty to de 10 could come close to eliminating extreme poverty by 2030. Most of these studies include a ‘business as usual’ approach – they attempt to estimate future poverty by projecting past 11 growth rates forward, holding inequality constant. Estimates of extreme poverty based on this method vary only slightly: estimates for 2030 tend to be i n the range of around 3-7% of the world’s population (Figure 3). This means that approximatel y 200-550 million people would be in extreme poverty, c ompared with 1 billion today. Figure 3: Projections of extreme 0 (%) poverty headcount ratio in 203 50 45 40 35 Actual 30 Ravallion Karver 25 Chandy 20 Edward 15 WB (2014) 10 5 0 2030 2020 2010 2000 1990 Sources: Please see footnote 10. in both growth and Most of these authors also pr esent scenarios based upon changes inequality and these illustrate t hat any poverty rate between 2010 levels and zero is possible in 2030 (Figure 4). For example, Ravallion (2013) provides opti mistic and pessimistic etween them in the timeline scenarios, highlighting a potential gap of more than 30 years b to end extreme poverty. Along similar lines, Chandy et al (2013 ) show that changes in 10 Ravallion, M. (2013). How long w ill it take to lift one billio n people out of poverty? World Bank policy research working paper 6325 . Washington, DC: World Bank. Karver, J., Ke . nny, C., and Sumner, A. (2012). MDGs 2.0: What go Working paper 297 als, targets, and timeframe? Washington, DC: Center for Global Development. The Final Countdown: Prospects for Ending Extreme Poverty by 2030 . Chandy, L., Ledlie, N., and Penciakova, V. (2013). Brookings Institution. Global Vi ews. Policy Paper 2013-04. . Overseas Development Institute, Horizon 2025: Creative Destruction in the Aid Industry Kharas, H., Rogerson, A. (2012). London. and in the Future: How raphy of Global Poverty Now stimating the Scale and Geog Edward, P., and Sumner, A. (2014).E Vol. 58, pp. 67-82. much Difference Do Method and Assumptions Make?: World Development Concepts, Data, and the oosting Shared Prosperity: World Bank (2015), ‘A Measured Approach to Ending Poverty and B Twin Goals.’ Policy Research Re port, World Bank: Washington D.C . Lakner, C., Negre, M., and Beer Prydz, E. (2014). Twinning the Goals: How Can Promoting Sh ared Prosperity Help to Reduce Global Poverty?: World Ba nk policy research working pape r 7106. Washington, DC: World Bank. 11 ost commonly cited studies is t A main difference between the m he data used to project growth into the future. Chandy et al (2012) adjust (2013) rely on growth forecasts until 2030 from the Economist I s and Rogerson ntelligence Unit, while Khara and project IMF forecasts forwa rd to 2030 based upon assumption s about capital accumulation and labour force productivity. recasts of economic growth a Karver, Kenny and Sumner (2012) use pre-financial crisis IMF fo nd project the se until 2030. ore recent data. Ravallion ( Edward and Sumner (2014) follow the same methodology, but use m 2013) uses historical growth m the 1980s and 1990s as the basis for his pessimistic rates for the developing world as a whole (excluding China) fro nario. In contrast, a projecti on in World Bank (2014) relies on scenario and growth rates from the 2000s for his optimistic sce country specific growth rates based upon the last 10 years. 7

10 inequality can matter just as much as changes in growth, and th at extreme poverty could be almost twice as high in 2030 as their business as usual scenari o if inequality worsens. Figure 4: Projections of the ex ) in treme poverty headcount ratio (% 2030 under different inequality scenarios 50 45 40 35 30 25 20 15 10 5 0 2010 2030 2020 2000 1990 Source: Please see footnote 9. The World Bank (2014) projections look not just at the effects of inequality on poverty, but focus on income growth among the bottom 40% of the population, in line with the Bank’s hat a 2030 global poverty ty’. Their modelling suggests t new emphasis on ‘shared prosperi on whether the bottom rate of anywhere between 3% and 9% appears plausible depending s faster or slower than the 40% of the distribution were to grow by 1 to 2 percentage point average growth rate (Figure 5). Figure 5: World Bank (2014) scen arios for extreme poverty 20% 15% 15% 10% 9% 6% 5% 5% 4% 3% 0% Percentage of World Population 2030 2010 2015 2020 2025 Actual Bottom 40% grow 2% s lower than average Bottom 40% grow 1% s lower than average Baseline Projection Bottom 40% grow 1% faster than average Bottom 40% grow 2% faster than average 8

11 Source: Lakner, C., Negre, M., and Beer Prydz, E. (2014) 12 In this paper, we take a different tack. We frame what is likely to be possible over the next e decades. In particular we 15 years in the light of country experiences over the last thre ach country, relative to its assess how the bottom 40% of the income distribution fared in e average growth. We then ask what difference it would have made to poverty if the growth of the bottom 40% had been equal to or greater than the country average (holding growth constant). We believe it is a useful exercise to think about th e counterfactual that might have resulted today, alongside the projections that others have made of what we can expect in the future. To ground the analysis solidly in country experience, we identi fy pro-poor scenarios drawn from the experiences of the better performing countries in term s of the rate of growth for the bottom 40% relative to their national averages. We use this ana lysis to revisit the Open Working Group proposal that countries adopt a target specifying that the bottom 40% should grow faster than the mean, and consider the potential implicati ons. The analysis is based on s of growth would not have the admittedly crude assumption that redistributing the benefit affected levels. None h given considerable evidence theless, this may in fact understate growt 13 that greater equality can enhance growth. We explore two possible implications – first that the increase in the growth of the bottom 40% is subtracted equa lly from the top 60%; and t of the distribution – a scenario second, that the reduction is made just from the top ten percen 14 that past experiences suggests is more fitting. 12 We are grateful to Ricardo Fuen is idea– of taking a retroactive view of the situation of the tes-Nieva who shared with us th bottom 40% relative to the mean and its likely implications for poverty. 13 See, for example, the review contained in Stewart, F. (2013). http://www.unicef- irc.org/publications/pdf/stewa rt%20inequality_i nequity_layout_f in.pdf. 14 Middles vs. Heterogeneous Tai Palma, J. G. (2011), Homogeneous ls, and the End of the ‘Inverted-U’: It's All About the Share of the Rich. Development and Change, 42: 87–153. 9

12 2 Methodology 15 ner et al. (2014), The methodology of this report is similar to that taken in Lack who model poverty in 2030 using various rowth and inequality on global the likely impact of changes in g 16 growth incidence curves that reflect plausible consumption distributions for a country . A to assist in operationalising th number of assumptions are made is modelling, which they discuss in detail. An important assumption is that when applyin g growth rates to a section of nstant rate across each the distribution (for example, the bottom 40%) they assume a co percentile, i.e. all percentiles grow at the same rate. Our most significant point of departure from this methodology i s in modelling what would have happened if growth had been distributed more equally over the past three decades as opposed to what may happen in the future if certain assumptions hold. The retrospective nature of this paper is valuable for at least one important met hodological reason. The scenarios we present can be directly compared to the actual his torical change in poverty. In xtent to which various scenarios other words, a realistic counterfactual exists to measure the e d looking projections would have altered reality. This overcomes a weakness of forwar leap of faith that the because comparing projections to one another require a greater r, considering what could projections have estimated a reasonable counterfactual. Moreove be the case for poverty today rath er than projecting into the f uture may carry greater resonance for those concerned about who has benefited from grow th. 2.1 Dataset The data used in this analysis is from PovcalNET, which is the World Bank’s publicly available database of all internationally comparable household surveys. The data was retrieved prior to the latest update of the database at the end of 2014. This means that the scenarios presented in this paper are likely to overestimate cu rrent world poverty levels tween 2010 and 2011 the because they are based on data for 2010, as opposed to 2011. Be developing world headcount ratio is reported to have fallen fro m 21% to 17% (a difference pronounced in China and of around 200 million people). These differences are especially India; the poverty headcount in these countries is reported as being 6% and 25% respectively is data, however, is that in 2011, compared to 12% and 33% in 2010. A benefit of using th most of the well-known projections of extreme poverty in 2030 ( see footnote 9) use the same dataset, so the figures can be compared. A major strength of this analysis is that all the data are sour ced from PovcalNET alone, even the growth rates, which is uncommon for poverty projections. So me authors choose to use national account growth rate data instead (including Lackner et al. 2014), citing the lack of availability of survey data. However by doing so they mix data sources that are not directly 17 comparable. Some authors attempt to adjust for the observed discrepancies, e.g. Chandy et 15 . Twinning the Lakner, C., Negre, M., and Beer Prydz, E. (2014) Shared Prosperity Help to Goals: How Can Promoting Reduce Global Poverty? World Ba nk policy research working paper 7106. Washington, DC: World Bank. 16 Growth Incidence Curves give “the rate of growth over the rele vant time period at each per centile of the distribution (2004), Pro-Poor Growth: A Primer . Development (ranked by income or consumption per person)” See Ravallion, M. Research Group, World Bank. 17 It is well known in the litera ture that national account growt h rates tend to be substantially faster than survey growth rate s, especially in India and China. See Chandy, L., Ledlie, N., and Penciakova, V. (2013). The Final Countdown: Prospects for Ending Extreme Poverty by 2030 . Brookings Institution. Global Views. Policy Paper 2013-04. Al so Edward, P., and Sumner, A. (2014).Estimating the Scale a nd Geography of Global Poverty Now and in the Future: How much Difference Do Method Vol. 58, pp. 67-82. World Development and Assumptions Make? 10

13 al (2013). However, given the large amount of survey data that are available, it does not , particularly for analysing seem necessary to use national accounts data in the first place er data are available from poverty, which is measured through survey data alone. While few surveys than national accounts, adjustments can made to enable reasonable estimates of global poverty, as discussed below. included in this analysis All countries that had data on the World Bank’s PovcalNET were as long as there were at least two surveys available. On averag e there were 17 years between surveys. We had to rely on different time periods for different countries, depending on data availability – the minimum gap is 4 years (Trinidad and Tobago) while the maximum is 32 18 years (India). The exercise is clearly illustrative rather than indicative. T he PovcalNET dataset gives the most comprehensive insight possible into how poverty has changed over time (notwithstanding the most recent updates to the data menti oned above). As more data becomes available, especially fol lowing the release of the much anticipated 2011 PPP poverty estimates from the World Bank, we highly recommend that this analysis be repeated. 2.2 Application of gro wth incidence curves Various growth incidence curves were applied to the earliest su rveys’ consumption levels to ave been in the most recent determine what the consumption level of each percentile would h survey if it had grown at a give narios through the example of n rate. We illustrate these sce China. The initial consumption distribution for China is based upon the 1981 household survey available on PovcalNET (Figure 6). sumption distribution Figure 6: Initial con 90 80 70 60 50 40 30 20 10 Monthly consumption (2005 PPP) 0 0 20406080100 Percentile of the Consumption Distribution in 2009, we can determine ls from the most recent survey Using the actual consumption leve each percentiles’ average annualised growth rate (Figure 7). Cl early the growth is distributed ercentiles higher up the in favour of the top of the distribution. In other words, the p distribution tended to grow faster. 18 ithin the 30 year period. analyse distinct sub-periods w Equally because the data was so patchy, we did not attempt to 11

14 Figure 7: Actual cons umption growth 12% 10% 8% 6% 4% Annualised growth rate 2% 0% 0 20406080100 Consumption distribution by percentile ad grown at the average growth In our first scenario, we assume that the entire distribution h rate of the country (6.5%) (Figure 8). This is clearly more pro -poor than the actual consumption growth experienced by China over the period. stribution rowth across di Figure 8: Scenario 1: Equal g 7% 6% 5% 4% 3% 2% Annualised growth rate 1% 0% 0 20406080100 Consumption distribution by percentile The pro-poor scenarios illustrate the potential impact of the b ottom 40% growing faster than f the bottom 40% and the the average. We explore the impact of gaps between the growth o from experiences of better mean of 1, 2 and 3 percentage points respectively, which derive performing countries over the last 30 years – as discussed belo w. The average growth rate f the upper part of the remains constant. It is possible to calculate the growth rate o distribution by using a weighted average formula. ሿ ሾ ሻ ሺ ݁ݎ݄ܽܵܿ݊ܫሺ1െ/ ߤൈ െ ሻ ߤ ݁ݎ݄ܽܵܿ݊ܫ ൌ ߤ ்଺଴% ሺଵ଴%ሻ ஺௅௅ ஻ସ଴% ஻ସ଴% ஻ସ଴% 12

15 top 60% of the distribution In one variant, we assume the growth subtracts evenly from the (Figure 9), while in another, it reduces the incomes of the top 10% of the income distribution only (Figure 10). Figure 9: Growth redistri buted from the top 60% 9% 8% 7% 6% 5% 4% 3% 2% Annualised growth rate 1% 0% 0 20406080100 bution by Percentile Consumption Distri ributed from top 10% Figure 10: Growth redist 9% 8% 7% 6% 5% 4% 3% 2% Annualised growth rate 1% 0% 0 20406080100 Consumption distribution by percentile ibution to allow the bottom The reduction in growth experien ced by the top 60% of the distr 40% of the distribution to grow 1, 2 and 3 percentage points hi gher than the mean tends to be quite small because they hold a large share of total income. Take the case of China. The share of the consumption distribution held by the top 60% was a round 80% in 1981, and .5% per year. To enable the average growth for the country over the next thirty years was 6 ge (8.5%), growth would bottom 40% to grow at 2 percentage points higher than the avera need to fall only to 6% per year for the upper 60%. However, even if the share of the distribution accruing to the upper 60% differed significantly from this, the growth rate would remain relativel y similar (Figure 11). For wealth in place of 80%, then example, under the same scenario, if this group had 70% of the fall to about 5.5% annually, to their consumption growth would enable 2 percentage point 13

16 higher growth among the bottom 40%. Where reductions in growth come from the top 10%, 6.5% to around 4.5%. the growth rate for the top decile would only need to fall from ario 2 for China if share of Figure 11: Growth rates under scen distribution was different 8.5% 8.0% 7.5% 7.0% 6.5% 6.0% Annualised growth rate 5.5% 73% 84% 82% 85% 80% 79% 78% 77% 76% 75% 74% 83% 72% 71% 70% 86% 87% 88% 89% 90% 81% Share of consumption distribution Average Bottom 40% Top 60% op 60% (and even the top 10%) Note it is of course possible that lowering the growth of the t of the distribution could push some people situated there into poverty, particularly where overty line is relatively high . We take this into account in reductions are sizeable and the p the analysis that follows. 2.3 Making global poverty estim ates using the country sample To estimate the global extreme poverty rate, a subset of all co untries on PovcalNET was used (which again, included only those countries with at least two surveys available). In addition, no income surveys (when consumption surveys were also available) nor surveys broken into rural and urban dimensions were included in the glo bal poverty headcount estimate to avoid double countin g. Our analysis of country-spe cific poverty trends is based 19 on this set of 100 countries. For these remaining 100 countries, we determined a revised coun try specific poverty by the poverty headcount headcount ratio. The population of each country was multiplied ratio to calculate the total number of poor people living in ea ch country. The sum of these estimates provided a total number of poor people in the subset of countries. The global total number of people in poverty was determined by scaling up the to tal for the subset of countries by a factor of the fraction of poor people covered. T he global poverty rate was determined by dividing the global total number of people in pov erty by the total developing world population. 2.4 Country experience over the last 30 years On average, in our sample of 100 countries, the mean and the bo ttom 40% of the distribution grew at on average, there was effect at 1.8% (Table 1). This means th ively no difference between the average growth was 4.8 growth of the mean and the bottom 40%. At one extreme, in Fiji, percentage points lower than that of the bottom 40% each year; at the other extreme, in Bosnia and 19 We exclude 6 countries (Maldives, Sierra Leone, Namibia, West Bank and Gaza, Angol a and Guinea-Bissau) because the difference in annual growth rates between the bottom 40% and data appears to be unreliable. In each of these countries, the the average was over five percentage points (almost 20 percenta ge points in the case of the Maldives). 14

17 mean grew faster than the bottom Herzegovina, it was 4 percentage points higher (Figure 12). The 40 percent in just over half of countries (55%), which together accounted for 79% of the world’s population. We also examine in itial levels of inequality for t hose countries where the bottom 40% grew at a higher rate than the mean, and those where it did not . The average Palma for those countries that enjoyed pro-poor growth was 3.0, twice that of t he average for those countries that or in those countr were less pro-poor. In other words, growth was much more pro-po ies where initial hat we will revisit. ngly counter-intuitive finding t inequality was higher – a seemi Figure 12: Difference between g rowth of mean and bottom 40% 0.05 0.04 0.03 0.02 0.01 0 Fiji Togo Niger -0.01 Tunisia Estonia Ethiopia Senegal Vietnam Armenia Ecuador Panama Jamaica Hungary Slovenia Thailand Pakistan Tanzania Colombia Sri Lanka Indonesia Botswana Nicaragua Mauritania Cameroon Costa Rica Kazakhstan South Africa Yemen, Rep Côte d'Ivoire -0.02 Venezuela, RB Czech Republic Growth difference in percentage points Russian Federation -0.03 Central African Republic Bosnia and Herzegovina -0.04 -0.05 15

18 tics concerning growth of mean, bottom 40% Table 2: Basic statis and gap between them Growth of mean Growth of bottom 40% Gap mean and bottom 40% 1.78% 1.82% -0.03% Average Median 1.73% 1.48% 0.17% Minimum -8.58% -7.11% -4.79% Maximum 17.28% 4.16% 14.21% Countries where 55 mean>40% Share in global 79% population Initial Palma 1.5 Countries where 45 mean<40% 3.0 Initial Palma Share in global 21% population Total number of 100 countries There was a moderate standard dev iation equivalent to 1.6 perce ntage points. The distribution is concentrated around zero with a slight left han d tail. This implies that in some countries, the bottom 40% grew faster than the average, but gen erally the mean and bottom 40% growth rates did not differ much (Figure 13). 16

19 th and Figure 13: Distribution of count ries’ gaps between average grow growth of the bottom 40% 40 37 30 20 18 18 Percent Number of countries 10 6 6 4 4 33 1 0 -.04 -.02 0 .02 .04 diff_mean_40P t difference from the mean Average annual percentage poin t: http://iresearch.worldbank.org/PovcalNet/index.htm Source: World Bank’s PovCal Net, available a On the basis of this data, we identify a range of pro-poor grow th rates that are plausible with varying degree of ambition (Table 3). Figure 14: Share of countries that of pro- experienced different levels poor growth 2pp Pro-poor Growth Scenario 3pp 1pp 12% 16% 34% Share of countries We pinpoint three gaps in growth between the mean and the botto m 40% to explore – 1, 2 s roughly corresponds with the expe rience of the top third, 15% and 3 percentage points. Thi and 10%, respectively, of countries that experienced pro-poor g rowth. 2.5 Equal growth scenario Global poverty today would have nts lower if growth in all been around four percentage poi countries was equal across the distribution (Figure 14). At fir st glance a four percentage y might seem relatively small. point reduction in global povert However, this could have been enough for the world to reach zero poverty by 2030, if we assum e that global poverty 17

20 ast twenty years, a view supported continues to fall in a linear fashion as it has done over the l 20 by former World Bank economist Martin Ravallion among others. atio in equal growth scenario 2.6 Extreme poverty headcount r 60% 50% 40% 30% 20% 10% 0% 1980 1990 2010 2000 Actual Equal Growth The range of country experiences is ne hand, poverty could have diverse (Table 3). On the o and China, had the bottom been at least 10 percentage points lower in Bolivia, Bangladesh hand, poverty would be at 40% of these countries grown at national average; on the other ragua, Senegal and Armenia least fifteen percentage points higher in three countries: Nica (Figure 15). 20 people out of poverty? World Ravallion, M. (2013). How long w ill it take to lift one billion Bank policy research working pap er 6325. Washingt on, DC: World Bank. Karver, J., C. 2.0: What Goals, Targets and Timeframe?” CGD Kenny and A. Sumner (2012), “MDGs Development, Washington, DC. R odriguez and Samman Working Paper, Center for Global s for target setting post- (Forthcoming), Patterns of progr ess on the MDGs and implication 2015. 18

21 al growth compared with observed Table 3: Poverty effects of equ patterns over last 30 years Actual Equal Growth Gap Mean poverty level among countries 17.56 17.55 0.01 7 Median poverty 7 0 0 -17 0 Minimum poverty 82 81 20 Maximum poverty Count 100 18 Number of countries where poverty with equal growth b40%> actual poverty Number of countries where actual 62 poverty > poverty with equal growth b40% Number of countries where actual 20 poverty = poverty with equal growth 19

22 Figure 15: Equal growth scenario 0.2 0.15 0.1 0.05 0 Mali Chile Togo Niger -0.05 Malawi Mexico Bhutan Estonia Ukraine Guyana Vietnam Bulgaria Slovenia Lao PDR Guatemala Costa Rica Kazakhstan South Africa Yemen, Rep Turkmenistan -0.1 Venezuela, RB Czech Republic Iran, Islamic Rep Difference in percentage points Russian Federation Trinidad and Tobago -0.15 -0.2 -0.25 20

23 A particularly interesting pattern concerns MICs and LICs. In p articular, equal growth would Poverty would have been have had a dramatic effect on poverty reduction in most UMICs. be history in China, Mexico lower in all UMICs outside Latin America and would effectively and Peru (Table 3). Table 4: Extreme poverty headcount ratios in selected UMICs bas ed upon equal growth scenario Earliest Country Most Recent HC If all grew at mean growth HC HC Initial Actual Survey rate Survey Mexico 1984 2010 13 5 0 Peru 2010 11 5 2 1986 China 1981 2009 84 12 1 the distribution grew faster In many countries (45% of our total sample), the bottom 40% of than the national averages, including in around half of LICs (6 0% of LICs in Sub-Saharan Africa). Poverty would have been higher in these countries if g rowth had been equal across the distribution (Table 4). For example, in Burkina Faso, pover ty fell from 71% to 45%, but if growth had been equal across the distribution, it would have only fallen to 54%. In this case, these countries actually counteract the overall reduction in global poverty rates discussed above. However in aggregate, this impact is limited b ecause these countries tend to have relatively small populations and the poor tend to have only experienced slightly better growth rates than the average. Table 5: Extreme poverty headcount ratios in selected LICs base d upon Equal Growth Scenario Country Min If mean Max Actual Initial year year Burkina Faso 1994 2009 71 45 54 2007 Guinea 1991 93 47 43 Mauritania 1987 41 23 28 2008 This analysis highlights how, crudely, the world’s poor tend to live in two distinct types of countries that are either less equal MICs or more equal LICs. W hile the vast majority of poverty reduction over the last couple of decades occurred in c ountries that are now MICs, this was generally not due to equitable growth. If growth had b een equal in all countries, the lower global rate of poverty would have been almost entirely du e to further poverty reduction in MICs (Figure 16). There would have been effectively no furth er gains in poverty reduction in LICs from equal growth across the distribution because on av erage, this is what already occurred. 21

24 Figure 16: Total poverty by income category 2500 2000 1500 1000 500 0 Millions of people in extreme poverty Equal Growth Actual Initial LIC total MIC total 2.7 Pro-poor growth scenarios potential effects for poverty if This section outlines three pro-poor scenarios: we explore the ercentage points higher than t 1, 2 and 3 p n were to grow a the bottom 40% of the distributio tively. In these scenarios the o their national averages, respec verall growth rate for countries is kept constant, which means the higher growth rates for the b ottom 40% are offset by lower growth within the upper 60% (or 10%) of the distribution. Pro-poor growth scenario 1 lf what it is now, if the bott om 40% of the distribution Global Poverty would be around ha ile keeping the overall nt higher than the average, wh had grown just one percentage poi growth rate constant (Figure 17). 22

25 1pp) ount ratio in pro-poor growth ( Figure 17: Extreme poverty headc scenario 60% 50% 40% 30% 20% 10% 0% 1990 2000 2010 1980 Actual Pro-Poor Growth (1pp) This relatively slight change in the distribution of growth to make it pro-poor would have had significant effects on poverty reduction in some countries, but not others (Table 6, Figure 18). Poverty would have halved in Cambodia, Ghana and South Afr ica, reduced by two- However there would have thirds in Nepal and would have b een eliminated in Turkmenistan. low-income countries, such been little difference in the levels of extreme poverty in many as in Tanzania, Niger and Mozambique. Table 6: Pro-poor growth (1pp) c ompared with observed patterns over last 30 years Scenario 2 Actual Gap 15.28 Mean 17.56 -2.8 -1 Median 7 5 Min 0 0 -15 Max 81 83 28 100 Count 23 Number of countries where 1pp > actual 51 Number of countries where actual > 1pp Number of countries where actual = 1pp 26 23

26 Figure 18: Pro-poor (1pp) scenario 0.2 0.15 0.1 0.05 0 -0.05 Togo Brazil Belize Turkey Croatia Zambia Estonia Uganda -0.1 Georgia Morocco Thailand Lao PDR Paraguay Indonesia Mauritania Seychelles El Salvador Kazakhstan Bangladesh Montenegro -0.15 Madagascar Burkina Faso Central African... Venezuela, RB -0.2 Iran, Islamic Rep Difference in percentage points -0.25 -0.3 -0.35 Pro-poor growth scenario 2 Global poverty would be less than half its current level had th e bottom 40% of the onal average, keeping the distribution grown two percentage points faster than their nati overall growth rate of the country the same (Figure 18). This i s the equivalent degree of pro- poor growth presented by Lackner et al. (2014) though, as noted , they use this to project into the future rather than to revisit the past. 2pp) ount ratio in pro-poor growth ( Figure 19: Extreme poverty headc scenario 60% 50% 40% 30% 20% 10% 0% 1980 1990 2000 2010 Actual Pro-Poor Growth (2pp) 24

27 We see a diverse range of country experiences (Table 6). In 201 0, across our 100 countries, he actual level. At one poverty would be on average four percentage points lower than t ld be over 25 percentage extreme, poverty in Bangladesh, Ethiopia, India and Lao PDR wou points lower; at the other, it would be over 15 points higher i n Mali (Figure 19). ompared with observed patterns over Table 7: Pro-poor growth (2pp) c last 30 years Actual Scenario 2 Gap Mean 17.56 13.37 -4.2 Median 7 2.5 -1 Min 0 -16 0 Max 81 84 31 Count 100 Number of countries where pp2>actual 18 Number of countries where actual

28 Figure 20: Pro-poor growth (2pp) scenario 0.2 0.1 0 Fiji Peru Chile China Latvia Albania Belarus Ukraine Guyana -0.1 Jamaica Pakistan Tanzania Tajikistan Paraguay Honduras Indonesia Nicaragua Swaziland Seychelles El Salvador Bangladesh Montenegro Turkmenistan Moldova, Rep Egypt, Arab Rep -0.2 Difference in percentage points -0.3 -0.4 Pro-poor growth scenario 3 If the bottom 40% had experienced growth that was three percent age points higher than the global poverty rate than under average, this would have actually resulted in a slightly higher the pro-poor growth scenario 2 (7.7% as opposed to 7.1% of the developing world population) (Figure 20). However, this assumes an equal reducti on in the growth of the upper because growth of the bottom 4 0% that is 3 percentage points 60% of the distribution. This is faster than the average requir es a significant reduction in gro wth for the upper 60%. 26

29 3pp) ount ratio in pro-poor growth ( Figure 21: Extreme poverty headc scenario 60% 50% 40% 30% 20% 10% 0% 1990 2000 2010 1980 Actual Pro-Poor Growth (3pp) This very pro-poor growth scenario illustrates some important p oints. Firstly, increasing ivotal in making significant growth for the bottom 40% of the distribution is likely to be p to eliminate extreme poverty, but will not be enough headway toward reducing global rowth rates are higher in poverty in many poorer countries. Furthermore, unless overall g would actually keep many focusing on just the bottom 40% these very poor countries, then if the reduction is r longer people in the top 60% of the distribution in extreme poverty fo . taken equally from that part of the distribution e for the world as a whole, Once more, country experiences vary greatly (Table 8), but whil poverty would be higher under th is scenario than under a 2 perc entage point gap, the same is scenario, poverty would be does not hold for the simple average across countries. Under th d around 1 percentage point 5.3 percentage points lower than the status quo, on average, an ge is very wide – poverty lower than under the 2 percentage point scenario. Again the ran would be 10 percentage points higher than it is presently in Ma li but over 25 percentage points lower in Lao and Bangladesh (Figure 21). 27

30 ompared with observed patterns over Table 9: Pro-poor growth (3pp) c last 30 years Most recent Scenario 3 Gap Mean 17.56 12.27 -5.29 Median 7 1 -1.5 Min 0 0 -17 Max 31 86 81 100 Count Number of countries where 12 pp3>actual Number of countries where 61 actual>pp3 23 Number of countries where pp3=actual 28

31 Figure 22: Pro-poor growth (3pp) scenario 0.2 0.1 0 Mali Brazil Latvia Turkey Algeria Croatia Albania Uganda Ethiopia Vietnam Rwanda Senegal Ecuador Uruguay Thailand Morocco Pakistan -0.1 Lao PDR Tajikistan Paraguay Honduras Indonesia Botswana Swaziland Timor-Leste Montenegro Burkina Faso Moldova, Rep Slovak Republic Kyrgyz Republic Iran, Islamic Rep -0.2 Russian Federation Dominican Republic Difference in percentage points Bosnia and Herzegovina -0.3 -0.4 ot have been lower under In around 10% of countries, the poverty headcount ratio would n etween average growth and this scenario than what actually occurred. A trade-off arises b lly lift more people out growth for the bottom 40% as some very poor countries may actua or example, in the case of of poverty by focusing on growth for the entire distribution. F have occurred under this Mali or Central African Republic, less poverty reduction would scenario than in reality or in any of the other scenarios (Tabl e 10). However even in these cases, if policies are intended for the poorest of the poor, th en targeting the bottom 40% would always be better than focusing on the entire distribution . ount ratios in selected LICs bas Table 10: Extreme poverty headc ed upon pro-poor growth scenarios Equal Country Initial Pro-Poor Earliest Pro-Poor Actual Pro-Poor Most Growth Survey Recent Growth Growth Growth Survey (1pp) (2pp) (3pp) Scenari Scenario o Scenario Scenario 0.67 0.5 0.66 0.65 0.64 0.86 Mali 2010 1994 0.69 0.63 0.83 0.7 0.7 0.69 1992 2008 Central African Republic These scenarios illustrate that the greatest gains in terms of poverty reduction would have while in many LICs this been made by changing the distribution of growth in most MICs, efforts to eliminate would have done very little towards (even harmed in some cases) extreme poverty. 29

32 Redistributing growth from the top 10% vs 60% In the analysis to date, we have assumed that the loss in growt h is redistributed equally away from the upper 60% of the distribution. In reality, countr ies have a range of redistributive strategies open to them and the evidence suggest s that redistribution often occurs between the top 10% and the bottom 40% of societies (see footnote 13). Consequently, we consider the implications of a redistributive scenario in which the growth that is gained by the bottom 40% within countries is redistribu ted from the upper 10 percent only. global extreme poverty rate The impact of these different pro -poor growth scenarios on the is noticeably different (Figure 22). If growth is redistributed away from top 60%, then global poverty starts to increase after a certain point (less t han 3 percentage points higher growth for bottom 40%). In contrast, if growth is redistributed away from top 10% the global poverty rate continues to decline (until a gap of more t han 3 percentage points higher growth for the bottom 40%). Figure 23: Extreme poverty under different redistribution scena rios 25% 20% 15% If redistribute growth from top 60% 10% If redistribute growth from top 10% 5% Global extreme poverty rate 0% 0123 Additonal Growth for Bottom 40% (Percentage Points) At the same time, even with the threshold for redistribution se t extremely high, the amount nd Bangladesh, where the of redistribution could still make people poor – as in Rwanda a % would be sufficient to push reduction in incomes of the top 10 3 percent of people into poverty in each country if the bottom 40% grew 3 percentage poi nts above the average. In short, changing whether to redistribute growth way from the top 60% or top 10% matters in high poverty countries (headcount ratios>35) but it makes no difference in lower poverty countries (headcount ratios<35). 30

33 3 Conclusion eliminated if growth had been Our key finding is that global poverty could be on track to be as good for the poor as it was for everyone else. Global povert y could have been considerably lower had growth been more equal in MICs, however unequal growth was not a major constraint to poverty reduction in LICs. We have shown this by examining retrospectively four key scenarios – in which all incomes withi n each society grew at the average rate and the bottom 40% grew at 1, 2 and 3 percentage p oints higher than the mean (Table 11). poverty impact of the differen t Table 11: Summary of findings on scenarios 3ppt/10% Equal gr 3ppt/60% 1ppt 2ppt Actual b40% 16.8 4.4 2010 20.6 7.7 10.0 7.1 In these scenarios, we sought to hold growth constant. In the p ro-poor scenarios, we looked ncomes that would take place at the impact of two types of redistribution – a reduction in i equally across the top 60% of the distribution, and a reduction that would take place equally across the top 10%. The emphasis on redistributing away from th e upper part of the distribution highlights the potentially perverse impact of high er growth among the bottom 40% of the population in pushing people into poverty in some ci rcumstances. When growth is subtracted instead from just the top 10% of the distribution , this problem is effectively eliminated in nearly all countries. This finding, alongside the diverse array of country experiences, suggests that the potential benefits of a pro-poor growth strategy are vast, but that attention needs to be paid t o country-specific circumstanc es in deciding what type of growth to aim for and how to redistribute its gains. 31

34 ODI is the UK’s leading independent think tank on international development and humanitarian issues. Our mission is to inspire and inform policy and practice which lead to the reduction of poverty, the alleviation of suffering and the achievement of sustainable livelihoods. We do this by locking together high-quality applied research, practical policy advice and policy- focused dissemination and debate. We work with partners in the public and private sectors, in both developing and developed countries. Readers are encouraged to reproduce material from ODI Reports for their own publications, as long as they are not being sold commercially. As copyright holder, ODI requests due acknowledgement and a copy of the publication. For online use, we ask readers to link to the original resource on the ODI website. The views per are those of the presented in this pa author(s) and do not necessarily represent the views of ODI. © Overseas Development Institute 2015. Thi s work is licensed under a Creative Commons A ttribution-NonCommercial Licence (CC BY-NC 3.0). ISSN: 2052-7209 Overseas Development Institute 203 Blackfriars Road London SE1 8NJ Tel +44 (0)20 7922 0300 Fax +44 (0)20 7922 0399

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