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How robust are indicator based poverty assessment tools over time? Empirical evidence from Central Sulawesi, Indonesia AgEcon
van Edig, Xenia; Schwarze, Stefan; Zeller, Manfred.
Eradicating poverty is one of the most urgent concerns of development policies. Organisations aiming at reducing poverty need simple and stable tools to detect poor households. Using data from Central Sulawesi, Indonesia, this study aims to test first whether two indicators sets for poverty assessment found in 2005 are still capable in predicting absolute poverty and second, if the indicator composition remains robust over time. Data from two household surveys were used: In 2005 we surveyed 264 households in the vicinity of the Lore Lindu National Park in Central Sulawesi to obtain indicators of poverty and to derive the daily per capita consumption expenditures. In total 280 indicators were sampled. Two different multivariate regression models were fit to...
Tipo: Conference Paper or Presentation Palavras-chave: Poverty assessment; Poverty indicators; Robustness over time; Indonesia; Food Security and Poverty; Research Methods/ Statistical Methods; I32; R15.
Ano: 2009 URL: http://purl.umn.edu/51674
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Developing Poverty Assessment Tools Based on Principal Component Analysis: Results from Bangladesh, Kazakhstan, Uganda, and Peru AgEcon
Zeller, Manfred; Houssou, Nazaire; Alcaraz V., Gabriela; Schwarze, Stefan; Johannsen, Julia.
Developing accurate, yet operational poverty assessment tools to target the poorest households remains a challenge for applied policy research. This paper aims to develop poverty assessment tools for four countries: Bangladesh, Peru, Uganda, and Kazakhstan. The research applies the Principal Component Analysis (PCA) to seek the best set of variables that predict the household poverty status using easily measurable socio-economic indicators. Out of sample validations tests are performed to assess the prediction power of a tool. Finally, the PCA results are compared with those obtained from regressions models. In-sample estimation results suggest that the Quantile regression technique is the first best method in all four countries, except Kazakhstan. The PCA...
Tipo: Conference Paper or Presentation Palavras-chave: Poverty assessment; Targeting; Principal component analysis; Bangladesh; Peru; Kazakhstan; Uganda; Food Security and Poverty; H5; Q14; I3.
Ano: 2006 URL: http://purl.umn.edu/25396
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How Best to Target the Poor? An operational targeting of the poor using indicator-based proxy means tests AgEcon
Houssou, Nazaire; Zeller, Manfred; Alcaraz V., Gabriela; Johannsen, Julia; Schwarze, Stefan.
This paper seeks to answer an operational development question: how best to target the poor? In their endeavor, policy makers, program managers, and development practitioners face the daily challenge of targeting policies, projects, and services at the poorer strata of the population. This is also the case for microfinance institutions that seek to estimate the poverty outreach among their clients. This paper addresses these challenges. Using household survey data from Uganda, we estimate four alternative models for improving the identification of the poor in the country. Furthermore, we analyze the model sensitivity to different poverty lines and test their validity using bootstrapped simulation methods. While there is bound to be some errors, no...
Tipo: Journal Article Palavras-chave: Uganda; Poverty assessment; Targeting; Proxy means tests; Validations; Bootstrap; Food Security and Poverty.
Ano: 2010 URL: http://purl.umn.edu/95780
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Proxy Means Tests for Targeting the Poorest Households -- Applications to Uganda AgEcon
Houssou, Nazaire; Zeller, Manfred; Alcaraz V., Gabriela; Schwarze, Stefan; Johannsen, Julia.
The motivation for this research stems from increasing interest showed for the issue of targeting. The paper explores the use of proxy means tests to identify the poorest households in Uganda. The set of indicators used in our model includes variables usually available in Living Standard Measurement Surveys (LSMS). Previous researches seeking to develop proxy means tests for poverty most often use Ordinary Least Squares (OLS) as regression method. In addition to the OLS, the paper explores the use of Linear Probability Model, Probit, and Quantile regressions for correctly predicting the household poverty status. A further innovation of this research compared to the existing literature is the use of out-of sample validation tests to assess the predictive...
Tipo: Conference Paper or Presentation Palavras-chave: Uganda; Poverty assessment; Targeting; Proxy means test; Out-of-sample test; Bootstrap; Consumer/Household Economics; Food Security and Poverty.
Ano: 2007 URL: http://purl.umn.edu/7946
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