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Is Poverty increasing in Bangladesh? Reconciling national and global monitoring estimates

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*Except for the MDG monitor site listed first in Table C.1, both Table C.2 and C.3 are taken directly from the “links” page of the official UNSD MDG Indicators site (see (http://mdgs.un.org). Inter-agency and Expert Group (IAEG) on MDG IndicatorsIs Poverty increasing in Bangladesh? Reconciling national and global monitoring estimates* Final report to UNDP-BDP Poverty Group, New York Darryl McLeod** Draft submitted July 26th 2007 Revised August 17th 2007 Final draft October 24th 2007 _______________________________________ *This is Part I of a two part report evaluating the sources of inconsistency among poverty rates used in national MDG Reports and those reported as “global monitoring” estimates by the UN and World Bank. Part II of this report focuses on middle income and transition economies (Bulgaria, Chile, Costa Rica, El Salvador, Mexico, plus Honduras and Trinidad and Tobago). Both reports benefitted greatly from numerous meetings of the Poverty Group’s MDG Data Quality project, especially Nuzhat Ahmad, Nora Lustig, Selim Jahan, Craig Fagan, Emmanuel Letouze, Rosendo Ramirez. Nuzhat Ahmad commissioned this report and ably directed its preparation. Maria Davalos and Elitza Mileva provided excellent research assistance in preparing the Latin America and Eastern Europe tables. The views expressed in this report are, of course, solely those of the author, and should not be attributed to Poverty Group or other participants in the MDG data quality project. **Consultant to UNDP-BDP Poverty Group and the UNDP BCPR, Summer 2007, and Associate Professor of Economics, Fordham University, Rosehill Campus, comments, corrections welcome: please contact [email protected] or [email protected] I. Bangladesh in the 1990s, Pro-poor growth, or not? Is poverty increasing in Bangladesh? If it is, the chances of achieving Millennium Development Goal 1 in the seventy-one least developed countries (LDCs) are slim if only because nearly 20% of this LDC population resides Bangladesh. Yet these are precisely the nations and groups the MDGs are designed to focus resources on. The various international MDG Monitoring sites (see Box 1) report that between 1991 and 2000 Bangladesh’s $1/day poverty rate rose from 36% to 41%. But Bangladesh’s own 2005 National MDG Report claims $1/day poverty fell between 1991 and 2000 and the Bangladesh Bureau of Statistics claims poverty fell even faster between 2000 and 2005. National poverty estimates have Bangladesh on track to achieve MDG 1, but global monitoring agencies say poverty and inequality are rising. Who is correct? Raising the stakes in this debate, a consortium of respected development agencies recently singled out Bangladesh as a model of “pro-poor growth in the 1990s.” But how can growth be pro-poor if poverty and inequality rose during this period? This report explores the available evidence on poverty trends in Bangladesh. How can poverty estimates derived from the same survey yield disparate estimates of poverty trends? This is important not only because MDG 1 focuses on absolute poverty measures, but because multiple and disparate poverty estimates are found in many countries, not just Bangladesh. Some countries have no poverty data, others have more than one “official” poverty rate – both can frustrate policy maker’s efforts to tie interventions to poverty outcomes. How can the quality of alternative poverty estimates be assessed? What are the procedures for reconciling conflicting estimates? How should national and international users of poverty data deal with inconsistent poverty rates? This is not a statistical detail: if Bangladesh’s current growth boom excludes the poorest, new growth initiatives may be needed or targeted transfers may be necessary to make growth more inclusive. If on the other hand, its current growth trajectory is “pro-poor” as a recent World Bank-DFID case study claims,1 Bangladesh should stay the course and other $1/day poverty countries can learn from its success. To preview our key findings, severe poverty does appear to be falling in Bangladesh through the 1990s and even faster after 2000 as economic growth accelerates. National poverty estimates use income estimates and living costs that more accurately reflect the purchasing power of Bangladesh’s rural poor, which is where about 85% of Bangladesh’s very poor population live. To value home food production to determine quantities (calories) of food consumed, household surveys collect data on both the quantity and prices of goods consumed by the poor. Food is a large share of poor household spending so survey price data cover most of the spending of the rural poor, the largest share of very poor population. The national Bangladesh Bureau of Statistics (BBS) poverty estimates use both prices and quantities derived from survey data. The Global Monitoring poverty estimates use survey expenditures but adjust them for inflation using the national Consumer Price Index (CPI), not because the CPI is superior to a survey based price index, but because it is available for all countries, where household survey prices data is not. The World Bank groups strives to use the same approach to estimating poverty in every country and the CPI is their standard price information. In Bangladesh urban consumer prices rose faster than prices in rural areas, so using the national CPI underestimates rural income growth, thereby reporting rising poverty in Bangladesh. However, even poverty estimates based on better methods and more accurate data need to be validated ex post. It is relevant to note for example, that Bangladesh is on track in most of its education 1 DFID-World Bank (2005) Pro-Poor Growth in the 1990s: Lessons and Insights from 14 Countries, World Bank, June, Washington D.C. (DFID is the United Kingdom’s Department of International Development). Darryl McLeod Page 9/2/2008 23and health related MDGs as well (child mortality for example, is sensitive to increases in poverty). Poverty estimates can also be corroborated with changes in food spending patterns and other indicators such as the number of families living in brick houses. If falling poverty rates are not a statistical illusion, they should be reflected in a host of related changes in consumption patterns and living conditions (for cross country tests of this ex post evaluation approach, see McLeod, 2006).


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