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Zonder onderwerpscode: wereldeconomie, ontwikkelingsproblematiek

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Existing empirical studies on the relation between inequality and growth have been criticized for their focus on income inequality and their use of cross-country data sets. Schipper and Hoogeveen use two sets of small area welfare estimates-often referred to as poverty maps-to estimate a model of rural per capita expenditure growth for Uganda between 1992 and 1999. They estimate the growth effects of expenditure and education inequality while controlling for other factors, such as initial levels of expenditure and human capital, family characteristics, and unobserved spatial heterogeneity. The authors correct standard errors to reflect the uncertainty due to the fact that they use estimates rather than observations. They find that per capita expenditure growth in rural Uganda is affected positively by the level of education as well as by the degree of education inequality. Expenditure inequality does not have a significant impact on growth.

Cross-Country Data --- Data Sets --- Developing Countries --- Economic Growth --- Empirical Evidence --- Empirical Research --- Empirical Studies --- Equity and Development --- Growth Regression --- Growth Regressions --- Health, Nutrition and Population --- Human Capital --- Income --- Income Inequality --- Inequality --- Inequality Measure --- Macroeconomics and Economic Growth --- Policy Research --- Population Policies --- Poverty Impact Evaluation --- Poverty Incidence --- Poverty Reduction --- Poverty Reduction Strategies --- Pro-Poor Growth --- Regional Dummies --- Rural Development --- Rural Poverty Reduction --- Services and Transfers to Poor --- Significant Effect --- Significant Impact

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Household survey data are very useful for monitoring living conditions of citizens of any country. In developing countries, a lot of this data are collected through "traditional" face-to-face household surveys. Due to the remote and dispersed nature of many populations in developing countries, but also because of the complex nature of many survey questionnaires, collection of timely welfare data has often proved expensive and logistically challenging. Yet, there is a need for faster, cheaper to collect, lighter, more nimble data collection methods to address data gaps between big household surveys. The recent proliferation of mobile phone networks has opened new possibilities. By combining baseline data from a traditional household survey with subsequent interviews of selected respondents using mobile phones, this facilitates welfare monitoring and opinion polling almost real time. The purpose of this handbook is to contribute to the development of the new field of mobile phone data collection in developing countries. The handbook documents how this innovative approach to data collection works, its advantages and challenges. The handbook draws primarily from the authors' first-hand experiences with mobile phone surveys in Africa and also benefits from experiences elsewhere. It is intended to serve a diverse audience including those involved in collecting (representative) data using mobile phones, and those using data collected through this approach. For those who will be implementing a mobile phone panel survey, the different chapters guide them through every stage of the implementation process. For potential users of the data collected via mobile phone technology, the handbook presents a new approach to data collection which they can use for monitoring programs and facilitate almost real time decision-making. A further purpose of this book is to contribute to the debate regarding the advantages of the method as well as the challenges associated with it.

Telephone surveys --- Methodology. --- Developing countries.

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We present results from a large-scale randomized experiment across 350 schools in Tanzania that studied the impact of providing schools with (a) unconditional grants, (b) teacher incentives based on student performance, and (c) both of the above. After two years, we find (a) no impact on student test scores from providing school grants, (b) some evidence of positive effects from teacher incentives, and (c) significant positive effects from providing both programs. Most importantly, we find strong evidence of complementarities between the two programs, with the effect of joint provision being significantly greater than the sum of the individual effects. Our results suggest that combining spending on school inputs (which is the default policy) with improved teacher incentives could substantially increase the cost-effectiveness of public spending on education.