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Yes, Africa can end poverty…but will we know when it happens?

Waly Wane's picture

Today poverty data are available for almost all countries in the world1.  Because a country’s success is measured by the number of people it lifts out of poverty, identifying best performers is a fair exercise only if poverty indicators are fully comparable. One indicator used is the share of the population whose consumption (or income) level is below a nationally defined poverty line or the US 1.25 dollar PPP per day. But even if policy makers and other stakeholders can count on readily available statistics, the poverty numbers should not be taken at face value.

Data are useful if they give us a sense of reality

Poverty data are based on a set of arbitrary assumptions that may lead to erroneous conclusions. In the graph, Tanzania ranks among the poorest countries in Sub-Saharan Africa when poverty is defined by the US$1.25 per day threshold, but among the least poor when the national poverty line is the yardstick.

Click on the graph to see it bigger

Each of these indicators is constructed differently. For example, to update its national poverty line in 2007, had Tanzania used its official Consumer Price Index - as Uganda did – instead of a survey-based price index, its poverty headcount would have been 18 percent rather than 33 percent. To compute its poverty line, Uganda assumes that a person needs 3000 kilo calories per day, which is 40 percent higher than the threshold used in Angola or Mozambique. This mechanically leads to higher poverty rates in the first country, keeping everything else constant.

When it comes to the international $1.25 a day poverty headcount, countries measure consumption differently some including durables which others totally exclude2.  Those differences arise from technical decisions that may be driven by data limitations but could also reflect political interference to influence the results.

The heart of the matter

Over the last two decades, most developing countries have launched household surveys to better understand households’ consumption patterns and measure poverty3.  This quest for data suffers from the lack of a recent population census (e.g., Madagascar’s latest 2010 household survey’s sample is based on the 1993 census). Often questionnaires are imported from other contexts without specific context in mind, such as the large fraction of illiterate households who may have difficulties in responding to a lengthy and complex questionnaire (illiteracy rates are as high as 74 percent in Mali or 64 percent in Ethiopia). And if one questionnaire yields poor results, it is often changed substantially in the next survey, with no regard for comparability.

Assuming the collected data are reliable, we still have a problem because measuring poverty involves the construction of (1) a consumption aggregate that captures a household’s total consumption, and (2) a poverty line that is the consumption level below which a household is deemed poor.

To be meaningful, a consumption aggregate should include the major spending categories of each household. Yet, in Tanzania, it excludes important expenditure such as health, education and utilities. Some surveys include housing (Angola, Uganda); others don’t (Sudan). Related to the measurement of consumption is the adjustment for cost of living differences. Because prices vary across time and locations, consumption has to be normalized using a price index. Here, again practices differ with some countries using prices collected through the survey (unit values or community level prices) and others using national indices, based on prices collected through different surveys of rural and urban markets4.  There is still no consistent methodology to measure consumption across countries and within countries over time.

The second calculation is to define the national poverty line. Again, the methodologies differ widely across countries. The kilo calorie threshold adequate for human functioning on which the food poverty line is anchored varies from 2100 in Angola to 2400 in Malawi and 3000 in Uganda. The reference group used to derive the consumption basket of the poor ranges from the bottom 28% of the population in Sierra Leone to 70% in Angola, while other countries like Malawi choose households in the middle of the consumption distribution. The international poverty lines makes this issue very simple, by just assuming that everyone in the country needs the same amount of money per capita to live on.

In short, there are no two countries in Sub-Saharan Africa whose poverty headcounts can be considered comparable and very few where the headcounts can even be considered comparable over time within the country5
 
Africa’s poverty statistics tragedy calls for action

First, consumption and poverty measurement should be harmonized across countries. As with National Accounts, one single approach has to be defined, under the auspices of international institutions, to iron out technical differences6.  This will make comparisons across countries more meaningful and at the same time help minimize political interferences because technical options would be pre-determined to a large extent.

Second, the frequency of data collection for poverty measurement should be increased. One should be able to distinguish between transitory and structural poverty. The financial situation of many households varies significantly from one year to the next. The 2010 household survey in Madagascar was rightly influenced by the unstable political conditions and indicated an increase of 9 percentage points in the poverty rate compared to 20057.  Similarly, climatic conditions can shift poverty levels. Poverty has certainly temporarily risen in the Horn of Africa because of the major drought suffered by these countries. It is frequently argued that periodic surveys are impossible because of their costs (US$1-2 millions). But this figure represents such a marginal share of official aid toward developing countries that they could be funded easily.

Wouldn't it be more persuasively powerful to have reliable, frequent and comparable poverty statistics that properly capture the reality on the ground and would rightly inform policy makers on the impact of the full range of their poverty alleviation policies? Ending the statistical tragedy could go a long way to ending the human tragedy.

“The issue of poverty is not a statistical issue. It is a human issue.”
James Wolfensohn

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Notes:
1. See for example, the World Development indicators, www.worldbank.org

2. This indicator also assumes no difference between rural and urban needs and the national CPI is always used as deflator without taking account regional variations.
3. For the layman, the concept of poverty is simple -- a household is poor if it does not have enough income to make ends meet. This simple idea could however not be applied in reality because income data are very difficult to collect in the developing world. For this reason, economists have developed an alternative approach based on consumption needs: a household who is able to fill its basic needs is therefore out of poverty. This approach is now well accepted worldwide.
4. Consumer Price indexes are usually urban while survey prices also include prices faced by the rural population which, in most countries in Sub-Saharan Africa, represents the majority.
5. This annex shows for few countries the various decisions made for the construction of the consumption aggregate and poverty line.
6. The SHIP initiative of the World Bank Chief Economist for the Africa region is one step towards the right direction.
7. The Government was not recognized by the International community and aid was temporally suspended by most donors.

Bonus file: Differences among african countries when measuring poverty (excel file)

Comments

Submitted by Thomas on
Great blog and thank you for adding to the debate about quality of statistics in developing countries. It is important to keep this topic on the front burner. With regards to national income and growth aggregates, the system of national accounts is only a data compilation framework. In theory, the system enables statisticians to compare, contrast and reconcile data from different sources, but any problem of poor primary data is likely to be compounded and aggregated in the national aggregates. Fortunately, many developing countries are aware of this and are working hard to improve primary data sources, methodologies and compilation frameworks. The World Bank and the rest of the donor community should continue to support this and scale up where needed

Submitted by Rachel Kasumba on
First of all, given the global economic slow down of the last decade and continuing into this one, the universal USD 1.25 PPP metric to ascertain who is living below or above the poverty line needs to be adjusted upward to reflect the reality in most countries, whether in the West or South. Next, most of us know that a lot of countries manipulate data (even where it is easily available) for all sorts of reasons. So, for us to have reliable and meaningful information, we need to address the root causes of why those that are this charged with crucial responsibility choose to mislead the general public. In addition to your discussion above, poor countries sometimes lack data availability due to the informal nature of many of the activities that would be used as source data or adequate training and awareness to collect whatever data is available on a timely basis. With the increase in technology, media, globalization, etc many people in poor countries have developed a distrust of those they perceive as being in power (politicians, donors, the elite) such that when they are approached for anything, especially information, they are not forthcoming or in some cases you will be outright attacked since they conclude that you want to sell this information for personal gain. So educating the public as to why this excise is for their benefit prior to carrying it out is very important.

Submitted by Leonora on
The same applies to various aspects of transport data collected worldwide. Definitions of parameters (e.g. accident fatalities) vary from country to country or region to region, hence it is difficult to present global statistics without extensive disclaimers. In research, there are no straightforward conclusions because of all the assumptions one makes regarding other researchers' methodologies. It is good that this blog highlights the challenges faced in trying to obtain data when records are incomplete or non-existent, and also when definitions of parameters differ across the board.

Submitted by Louise Fox on
Jacques, Waly- I have no problem with the diagnosis - it has been made before. Among others, Angus Deaton made it 10 years ago, but, it is great for you to raise it again. We need to keep saying this. It is a tough thing to say, but we have to say it. our excellent research department has developed the tools, but they are not being applied. So we have confusion. Several points. (1) There are several texts and books which are considered the "bibles" on the subject.. However, what is considered good practice in middle and low income countries is often not applied in SSA because we don't have the data, or the quality is poor. For example, the rental value of owner occupied housing. We probably need more survey research to figure out exactly how to apply the good practice techniques in poorly monetized economies. (2) I also think you overestimate the degree of harmonization and quality of the national accounts. As with poverty, few low income countries in SSA use the agreed methods - most are stuck in SNA of the 80s or worse. And have you seen the agricultural statistics in Africa? These are often produced with very primitive methods, despite the fact that it is actually quite difficult to estimate production when you have so much intercropping, fragmented land plots, and home consumption or barter. (3) Finally, one of the main differences between the $1.25/day and the national poverty lines is the poor quality of countries' CPI. Many of these have weights that are 20 years old. So we need to work on that as well. In other words, it is all related. it is not just poverty numbers. So I would say - overall, the quality of data produced by most low income country AFR stats office is at best iffy. We need to start being a lot more cautious about the "trends" we find. And then we come back to the basic problems of leadership and financing. What is going to be done and who is going to do it? Who will the lead this effort, and who will pay for it? In Latin America, they had a 10 year effort involving The World Bank, The IDB, and the UNECLA, called MECOVI. In those days, there was more money for this type of effort. We should have done the same thing for SSA at that time. We didn't, and we lost time. Who would pay for such an effort now? Do we have the capacity to lead such a multi-year capacity building effort any more at the World Bank? Does management have the desire, and the vision? or are we just happy when the numbers go up, and then when they go done we complain about quality of data?

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