Nutrition mapping in Tanzania: an exploratory analysis

"For effective decisionmaking, policymakers and program managers often need detailed information about the welfare of the population, including knowledge about which specific areas are most affected by poverty and undernutrition. Household sample surveys are an important source of information, yet because the typical sample size is only a few thousand observations, the information is only useful for inferences at high levels of aggregation, such as the nation or large regional units. In contrast, data sources with wider coverage, such as national censuses, rarely capture detailed information on welfare levels. Recently small-area estimation techniques have been applied to the study of poverty to produce estimates of poverty, or poverty maps, for small geographic units. This paper uses household survey and unit record census data from Tanzania to explore the possibility of applying small-area estimation methods to the study of children's nutritional status as measured by anthropometry. Overall, undernutrition models have had lower explanatory power than poverty models, which has important implications for the precision of the small-area estimates. The analysis finds that applying small-area estimation techniques to anthropometric data is feasible, although the relatively low explanatory power of the regressions does limit both the degree of disaggregation possible and the power to detect significant differences in undernutrition prevalence between districts and subdistricts. In the case of Tanzania, the nutrition mapping approach reveals considerable heterogeneity in nutritional status within regions and within districts. The most striking finding is the much lower levels of undernutrition in areas classified as urban, including relatively small district centers." Authors' AbstractNutrition mapping, malnutrition, Anthropometry, Small area estimation, Tanzania,

The short-term impact of higher food prices on poverty in Uganda

World prices for staple foods increased between 2006 and 2008, and accelerated sharply in 2008. Initial analysis indicated that the adverse effects of higher food prices in Uganda were likely to be small because of the diversity of its staple foods, high level of food self-sufficiency, and weak links with world markets. This paper extends the previous analyses, disaggregating by regions and individual food items, using more recent price data, and estimating the impact on consumption poverty. The analysis finds that poor households in Uganda tend to be net buyers of food staples, and therefore suffer welfare losses when food prices increase. This is most pronounced in urban areas, but holds true for most rural households as well. The diversity of staple foods has not been an effective buffer because of price increases across a range of staple foods. The paper estimates that both the incidence and depth of poverty have increased -- at least in the short run -- as a result of higher food prices in 2008, increasing by 2.6 and 2.2 percentage points, respectively. The increase in poverty is highest in the Northern region, which is already the poorest in Uganda. The need for mitigating social protection measures appears to be greater than previously recognized. Not only are the negative impacts larger, but they are also much more widespread geographically. This suggests the need for continued close monitoring of the situation, including monitoring the adequacy of existing safety nets and feeding programs.Food&Beverage Industry,Rural Poverty Reduction,Regional Economic Development,Markets and Market Access

Quality or quantity?

The role of school quality in determining educational outcomes has received much research attention in the United States. However, in developing countries, where a significant part of the school age population never attends school, policymakers must consider both quality and quantity when deciding how to maximize the impact of scarce investments. Acknowledging this difference in the policy environment in developing countries, this paper provides comparative estimates of the impact of quality versus quantity investments in school supply in rural Mozambique, one of the world's poorest countries. Policy simulations show that improving school quality (through the pupil-teacher ratio) increases grade attainment and efficiency by approximately 9 percent with no impact on overall enrollment rates. However, these same results can be generated by increasing starting enrollment probabilities through the establishment of new schools in all rural villages that currently do not have schools. Furthermore, similar rates of increase in school achievement indicators can be achieved by building schools in only 56 percent of all villages currently without schools, provided these schools are placed in those villages that also do not have a school nearby. When cost information is considered, the main policy implication is that the expansion of school quantity through well targeted placement of new schools will provide the greatest increase in educational outcomes for Mozambique at this time.FCND ,School children. ,Education Economic aspects. ,Mozambique. ,

Quality or quantity?

The role of school quality in determining educational outcomes has received much research attention in the United States. However, in developing countries, where a significant part of the school age population never attends school, policymakers must consider both quality and quantity when deciding how to maximize the impact of scarce investments. Acknowledging this difference in the policy environment in developing countries, this paper provides comparative estimates of the impact of quality versus quantity investments in school supply in rural Mozambique, one of the world's poorest countries. Policy simulations show that improving school quality (through the pupil-teacher ratio) increases grade attainment and efficiency by approximately 9 percent with no impact on overall enrollment rates. However, these same results can be generated by increasing starting enrollment probabilities through the establishment of new schools in all rural villages that currently do not have schools. Furthermore, similar rates of increase in school achievement indicators can be achieved by building schools in only 56 percent of all villages currently without schools, provided these schools are placed in those villages that also do not have a school nearby. When cost information is considered, the main policy implication is that the expansion of school quantity through well targeted placement of new schools will provide the greatest increase in educational outcomes for Mozambique at this time.FCND ,School children. ,Education Economic aspects. ,Mozambique. ,

Poverty, inequality, and geographic targeting

"This paper applies small area estimation techniques to Mozambican data to develop high resolution (subdistrictlevel) poverty and inequality maps...The picture that emerges is one of considerable local-level economic heterogeneity, with the poor living alongside the nonpoor. Rather than finding stark pockets of intense poverty traps in one part of the country and a relative absence of poverty in other parts, the situation is much more nuanced. This suggests that targeting antipoverty efforts on purely geographic criteria is almost certain to be inefficient, with leakages to the nonpoor and under-coverage of the significant numbers of poor households in areas that are “less poor.”" From TextInequality ,Geographic targeting ,Small area estimation ,Poverty mapping ,

Poverty Comparisons with Endogenous Absolute Poverty Lines

The objective of measuring poverty is usually to make comparisons over time or between two or more groups. Comm on statistical inference methods are used to determine whether an apparent difference in measured poverty is statistically significant. Studies of relative poverty have long recognized that when the poverty line is calculated from sample survey data, both the variance of the poverty line and the variance of the welfare metric contribute to the variance of the poverty estimate. In contrast, studies using absolute poverty lines have ignored the poverty line variance, even when the poverty lines are estimated from sample survey data. Including the poverty line variance could either reduce or increase the precision of poverty estimates, depending on the s pecific characteristics of the data. This paper presents a general procedure for estimating the standard error of poverty measures when th e poverty line is estimated from survey data. Based on bootstrap methods, the approach can be used for a wide range of poverty measures and methods for estimating poverty lines. The method is applied to recent household survey data from Mozambique. When the sampling variance of the poverty line is taken into account, the estimated standard errors of the headcount and the poverty gap at the national level increase by 27 and 29 percent respectively.poverty measurement, bootstrap, Mozambique, Food Security and Poverty, I32, C13, 012,

Poverty, inequality, and geographic targeting: Evidence from Small-Area Estimates in Mozambique

"Typical living standards surveys can provide a wealth of information about welfare levels, poverty, and other household and individual characteristics. However, these estimates are necessarily at a high level of aggregation, because such surveys usually include only a few thousand households, with coarse spatial stratification. Larger databases, such as national censuses, provide sufficient observations for more disaggregated analysis, but typically collect very little socioeconomic information. This paper combines data from the 1996–97 Mozambique National Household Survey of Living Conditions with the 1997 National Population and Housing Census to generate small-area (subdistrict) estimates of welfare, poverty, and inequality, with the associated standard errors. These small-area estimates are then used to explore several dimensions of poverty and inequality in Mozambique, particularly with regard to geographical targeting of antipoverty efforts. Reliably identifying and targeting the poor can be administratively costly, especially in rural Africa, where low population density and weak administrative capacity are common. Geographical targeting, or targeting poor areas, is sometimes proposed as a feasible alternative to targeting poor people, and poverty maps may serve as a valuable tool in this regard. Unfortunately, the notion of poor areas might not always be especially useful, as appears to be the case in Mozambique. The poverty maps do not reveal a particularly strong spatial concentration of poverty; the differences in poverty levels between areas tend to be subtle. This pattern is also observed in the decomposition of small-area inequality estimates, which shows that only about 20 percent of consumption inequality is accounted for by inequality between districts or between administrative posts. The picture that emerges of the poor living alongside the nonpoor indicates that targeting poor areas is likely to result in leakage to the nonpoor in that area, and considerable under-coverage of the significant numbers of poor households in areas that are less poor.”" Authors' AbstractInequality ,Geographic targeting ,Small area estimation ,Poverty mapping ,

Poverty comparisons with absolute poverty lines estimated from survey data

"The objective of measuring poverty is usually to make comparisons over time or between two or more groups. Common statistical inference methods are used to determine whether an apparent difference in measured poverty is statistically significant. Studies of relative poverty have long recognized that when the poverty line is calculated from sample survey data, both the variance of the poverty line and the variance of the welfare metric contribute to the variance of the poverty estimate. In contrast, studies using absolute poverty lines have ignored the poverty line variance, even when the poverty lines are estimated from sample survey data. Including the poverty line variance could either reduce or increase the precision of poverty estimates, depending on the specific characteristics of the data. This paper presents a general procedure for estimating the standard error of poverty measures when the poverty line is estimated from survey data. Based on bootstrap methods, the approach can be used for a wide range of poverty measures and methods for estimating poverty lines. The method is applied to recent household survey data from Mozambique. When the sampling variance of the poverty line is taken into account, the estimated standard errors of Foster-Greer- Thorbecke and Watts poverty measures increase by 15 to 30 percent at the national level, with considerable variability at lower levels of aggregation." -- Authors' AbstractPoverty measurement, Surveys -- Statistical methods, Household surveys, Poverty lines

Estimating utility-consistent poverty lines

"With the focus of international development resources increasingly turned toward poverty reduction, the demand for reliable empirical estimates of poverty levels has grown dramatically... This paper contributes to the poverty measurement literature by introducing an information theoretic approach to assuring the utility consistency of poverty lines. Even though the philosophical roots of information theory and the links between information theory and other estimation criteria fill volumes, the actual practical application of the approach is quite straightforward." From TextPoverty lines ,Poverty alleviation ,Development projects Evaluation ,measurement ,Entropy estimation ,

Public Spending and Poverty in Mozambique

Government expenditure, Poverty and inequality, Mozambique