Taking poverty monitoring serious Improving poverty data and statistics. Isis Gaddis University of Göttingen
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1 Taking poverty monitoring serious Improving poverty data and statistics Isis Gaddis University of Göttingen 1
2 Introduction Poverty reduction is a core objective of development assistance, and a policy priority in developing countries: o MDG 1: Eradicate poverty and hunger o DFID/ukaid: Leading the British Government s fight against world poverty o World Bank: The World Bank s Mission is to reduce poverty and improve living standards through sustainable growth and investments in people. o AusAID: Our purpose is to help people overcome poverty. o Zambia SNDP : Sustained economic growth and poverty reduction o But do we really know about the state of affairs in this fight against poverty? 2
3 This presentation argues that: Introduction 1. We know much more than a few decades ago Much greater availability of household survey data in developing countries Poverty estimates are nowadays routinely published by statistical agencies (this what I call here national poverty estimates ) 2. We don t know enough Huge comparability problems of national poverty estimates across and within countries Gaps between surveys are still often too long (esp. in SSA) International (1.25 $ a day) poverty estimates don t solve the problems 3. That we could know much more. if we were to Take steps towards international harmonization of poverty measures Scale up funding to statistics to improve data availability 3
4 Outlines of today s talk: Introduction National poverty estimates what is behind those estimates What are the problems? Comparability across countries Comparability over time Data gaps Why the international $1.25 USD a day poverty estimates are not a credible solution A roadmap for improving poverty statistics 4
5 National Poverty Estimates Over the past two decades, the availability of micro data in developing countries has greatly increased yearint agricultural censuses and surveys expenditure/multi-purpose surveys population censuses labor force surveys demographic surveys * Trends smoothed using 5-year averages. Surveys per year. ** Source: International Household Survey Network (2012). 5
6 National Poverty Estimates Nowadays routinely published by statistical agencies Typically used for country-level development planning Traditionally using a monetary poverty concept (but multidimensional poverty indices are gaining ground) Input data: household income/expenditure surveys, sometime together with price surveys How do we compute poverty? We need an indicator of welfare to rank all households (i.e. consumption or income) Cut-off (to distinguish the poor from the non poor) $ $ $ $ $ $ $ welfare indicator: per capita income poverty line 6
7 National Poverty Estimates In practice it boils down to the following steps: 1) Computing the welfare indicator Measure of total household consumption (or income) (aggregate over different consumption items/income sources) Normalize consumption for spatial price differences (deflators) and household composition (e.g. real consumption per capita or per adult) Continuous ranking of households 7
8 National Poverty Estimates 2) Generate a poverty line to separate the poor from the nonpoor - often (but not always) based on cost of basic needs method Anchored in nutrition (pre-defined calorie norm) The food poverty line is given by the cost of a food basket that delivers exactly the pre-defined calorie norm and that mirrors consumption patterns of households close to the poverty line The total poverty line adds an allowance for basic non-food needs (e.g. based on the average spending on non-food items of households close to the poverty line) Cut-off to distinguish the poor from the non-poor 8
9 What are the Problems? Following through these steps requires a number of (normative) assumptions/judgement calls Lack of international harmonization comparability problems arise both across countries and within countries over time Differences in the household survey to collect consumption data Seasonality Recall periods Length of the questionnaire, number of items Computing the consumption aggregate and the poverty line requires several (to some degree arbitrary) assumptions Items to include in the consumption aggregate (education, health, consumer durables, rental equivalent for home owners) Calorie anchor of the food poverty line Updating the poverty line over time (Prices only or prices and basket? Which deflator?) 9
10 Comparability across countries Country: Kenya (KIHBS 2005/06) Consumption aggregate includes: Education Health Housing yes only frequent items yes (urban only) (1) actual or (2) statistically imputed rent Malawi (IHS2 2004/05) yes yes yes (1) actual, (2) household estimate or (3) statistically imputed rent Rwanda (EICV2 2005/06) yes only frequent items yes (1) actual or (2) household estimate Sierra Leone (SLIHS 2003/04) Tanzania (HBS 2007) Uganda (UNHS 2005/06) yes yes yes (1) actual or (2) household estimate no no no n.a. yes yes yes (1) actual, (2) household estimate or (3) statistically imputed rent 10
11 Comparability across countries Ethiopia (CSA 2004/05) Kenya (KIHBS 2005/06) Malawi (IHS2 2004/05) Mozambique (IAF 2002/03) Namibia (NHIES 2003/04) Rwanda (EICV2 2005/06) Sierra Leone (SLIHS 2003/04) Tanzania (HBS 2007) Uganda (UNHS 2005/06) Approach for setting the poverty line Daily calorie norm (if applicable) national or regional poverty lines? CBN 2,200 calories per adult national CBN 2,250 calories per adult urban/rural CBN 2,400 calories per person national CBN 2,150 calories per person regional (13) CBN 2,100 calories per person national CBN 2,500 calories per adult national CBN 2,700 calories per adult national CBN 2,200 calories per adult national** CBN 3,000 calories per adult regional (8) 11
12 Comparability over time Updating the Poverty Line - Zambia cost of food basket food basket - Food CPI updated cost of food basket - CPI updated prices matter!!! 12
13 Data Gaps Remain 1,00 0,90 0,80 0,70 Number of Surveys per Year and Country, agricultural censuses and surveys labor force surveys 0,60 0,50 0,40 expenditure/multipurpose surveys 0,30 demographic surveys 0,20 0,10 0,00 East Asia & Pacific Europe & Central Asia Latin America Middle East & & Caribbean North Africa South Asia Sub-Saharan Africa population censuses Source: International Household Survey Network (2012). 13
14 International Poverty Estimates So what about international poverty estimates? World Bank s 1.25 $ a day poverty estimates (formerly dollar-a-day) Used for comparisons across countries and global poverty monitoring (such as MDGs) Absolute poverty concept seeks to apply a fixed poverty line (fixed in some real value) to all developing countries But does this ensure comparability across countries? First thing to note: The 1.25 $ a day poverty estimates DON T harmonize the measure of aggregate household consumption (or income) but rely on survey estimates as reported by the statistical office problems related to the survey instrument and comprehensiveness of the consumption measure remain All that is harmonized is the poverty line 14
15 International Poverty Estimates How is the international day poverty line derived? Based on a sample of national poverty lines (74 in the latest revision) Updated back / forth to a reference year (e.g. 2005) using national CPI (remember the problems with the CPI!) Use international purchasing power parities (PPP) to convert all national poverty lines to a common currency (US $) The (absolute) international poverty line is then based on the notion that the national poverty lines of the poorest countries have a similar purchasing power parity (in US $), only when countries get richer we observe an income gradient The value of the international poverty line (currently 1.25 $ a day) is then the average over the poverty lines of a reference group of poor countries (15 countries in the latest revision) 15
16 International Poverty Estimates Source: Ravallion, Chen and Sangraula (2009) 16
17 International Poverty Estimates Problems with the 1.25 $ a day poverty line: Little policy relevance in the countries themselves Applies a harmonized poverty line to an un-harmonized measure of consumption can make matters worse, because poverty lines are in fact tailored to a specific survey Statistical difficulties in separating the flat proportion of the curve (Greb, Klasen, Hidayat Pasaribu and Wiesenfarth 2011) Reliance on PPP constant revisions of entire time series with each ICP round (2012 ICP round will lead to yet another revision) Changes in the reference group of poor countries have large effects Deaton (2009): Paradoxically, one of the main reasons that India (and the rest of the world) became poorer was because India had grown less poor. Main reason why the 2008 update increased the global number of poor people from 900 million to 1.4 billion 17
18 International Poverty Estimates Source: Deaton (2010) 18
19 International vs. National Poverty Estimates Source: Morisset and Wane (2011) Huge divergence, neither national nor international poverty estimates are fully comparable across and within countries We don t have the database to assess whether we made progress in poverty reduction 19
20 A Roadmap Forward 1. Major coordination effort to harmonize poverty estimates internationally and intertemporally (similar in scale to the International Comparison of Prices Project or the UN System of National Accounts) Most promising seems to an internationally coordinated cost of basic needs approach (e.g. Reddy et al. 2006) This leaves room for a dual approach, where countries implement a national approach alongside a standardized international approach Will involve trade-offs and compromises (esp. with respect to data collection) and further conceptual work but we should start this process as soon as possible What lessons can we learn from previous efforts to harmonize statistical systems internationally (e.g. national accounts, labor statistics)? 20
21 A Roadmap Forward 2. Funding to statistical systems and statistical development More frequent collection of poverty data (esp. in countries where the gaps are currently large) Faster turn around of the data (including public use files) Offer further support to countries where statistical capacity is weak 3. Greater emphasis on developing multidimensional approaches to poverty measurement (e.g. the Multidimensional Poverty Index developed by Alkire and Santos 2010) Focus directly on poverty relevant attributes Fewer comparability problems 21
22 A Roadmap Forward Thank you for your attention! 22
23 References Alkire, S. and Santos, E. (2010): Acute multidimensional poverty: A New Index for Developing Countries, OPHI Working Papers 38, Oxford Poverty and Human Development Initiative (OPHI). Deaton, A. (2010): Price indexes, inequality, and the measurement of world poverty, American Economic Review, 100(1): Greb, F., Klasen, S., Hidayat Pasaribu, S. and Wiesenfarth, M. (2011): Dollar a day re-revisited, Courant Research Centre Discussion Papers 91, University of Goettingen. Klasen, S., Lange, S. and M. Lo Bue (2012): New Developments in National and International Poverty Measurement: Promise, Limits, and Applicability for different Development Actors, Paper prepared for KfW. Morisset, J. and Wane W. (2011): Yes, Africa can end poverty but will we know when it happens?, Blog, URL: Ravallion, M., Chen, S. and Sangraula, P. (2008): Dollar a day revisited, World Bank Policy Research Working Paper 4620, World Bank. Reddy, S., Visaria, S. and Asali, M. (2006): Inter-country comparisons of income poverty based on a capability approach, UNDP International Poverty Centre Working Paper 27, UNDP. 23
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