Operational Poverty Targeting In Peru ? Proxy Means Testing With Non-Income Indicators

he measurement of per capita daily expenditures relative to a monetary poverty line, also known as ?sophisticated means testing?, is the most widely used approach to poverty assessment. However, it is reliant on the implementation of time- and cost-intensive household surveys. Hence, for operational purposes, it is not an effective method for targeting poor households with development services. This paper shows how to identify an alternative poverty assessment tool for Peru. The tool consists of a maximum of 15 indicators that are powerful predictors of per capita household expenditures. The indicators were selected out of a wide range of indicators used to gauge different poverty dimensions. The resultant poverty classification of households is based on the ?percent point function? of the predicted expenditures and validated by various accuracy measures and their confidence intervals. The results reveal that the 15 indicators correctly identify over 81 per cent of poor households when the national poverty line is employed as the benchmark. Thus, this tool might be considered, under certain conditions, as an alternative to the collection of detailed expenditure data. It offers an operational instrument for fairly accurate ex-ante poverty targeting and ex-post impact assessments.Poverty targeting, Targeting accuracy, Expenditure predictions, Percent point function, Latin America, Peru

The capability dilemma in operational poverty assessment

This paper compares the standard economic welfare approach to poverty measurement to the empirical approaches proposed in the capability literature under the special focus of their suitability for operational poverty assessment, i.e. targeting and outreach evaluation. We question whether the measurement of per capita daily expenditures compared with a monetary poverty line justifiably remains the most widely used approach regarding poverty assessment. Its underlying value judgments and unsatisfactory assumptions differ considerably from those of the capability concept of poverty but the two approaches can be linked and critically compared with respect to the role of income, the conceptualisation of absolute poverty and the development of operational tools. We argue that despite the progress made in operationalizing the capability approach, there remain serious challenges when focussing on targeting and outreach evaluation and propose three alternative solutions for dealing with this capability dilemma in practice.

Proxy Means Tests for Targeting the Poorest Households -- Applications to Uganda

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 power and hence the robustness of the identified set of regressors. Moreover, the confidence intervals are approximated out-of sample using the bootstrap algorithm and the percentile method. The main conclusion that emerges from this research is that measures of absolute poverty estimated with Quantile regression can yield fairly accurate in-sample predictions of absolute poverty in a nationally representative sample. On the other hand, the OLS and Probit perform better out-of sample. Besides it complexity, the Quantile regression is less robust. The Probit may be the best alternative for optimizing both accuracy and robustness of a poverty assessment tool. The best regressor sets and their derived weights can be used in a range of applications, including the identification of the poorest households in the country, the assessment of poverty outreach of Microfinance Institutions (MFIs), and the measurement of poverty and welfare impacts of agricultural development projects. To confirm or reject the conclusions in this paper, future research using datasets from other countries is needed.Uganda, poverty assessment, targeting, proxy means test, out-of-sample test, bootstrap, Consumer/Household Economics, Food Security and Poverty,

How Best to Target the Poor? An operational targeting of the poor using indicator-based proxy means tests

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 indicator being perfectly correlated with poverty, the models developed achieve fairly accurate out-of-sample predictions of absolute poverty. Furthermore, findings suggest that the estimation method is not relevant for developing a fairly accurate model for targeting the poor. The models developed are potentially useful tools for the development community in Uganda. This research can also be applied in other developing countries.Uganda, poverty assessment, targeting, proxy means tests, validations, bootstrap, Food Security and Poverty,

Developing Poverty Assessment Tools Based on Principal Component Analysis: Results from Bangladesh, Kazakhstan, Uganda, and Peru

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 method is the second best technique for two of the countries. In comparison with regression techniques, PCA models accurately predict a large percentage of households. With regard to out-of sample validations, there is no clear trend; neither the PCA method nor the Quantile regression consistently yields the most robust results. The results highlight the need to assess the out-of-sample performance and thereby the robustness of a poverty assessment tool in estimating the poverty status of a new sample. We conclude that measures of relative poverty estimated with PCA method can yield fairly accurate, but not so robust predictions of absolute poverty as compared to more complex regression models.poverty assessment, targeting, principal component analysis, Bangladesh, Peru, Kazakhstan, Uganda, Food Security and Poverty, H5, Q14, I3,

Perfil de desarrollo infantil temprano en la población elegible para visitas domiciliarias en Bolivia

La literatura en desarrollo infantil temprano y las experiencias de la región proveen evidencia creciente sobre la efectividad de diferentes modalidades de atención, considerando servicios institucionalizados (como aquellos provistos en centros infantiles y centros de salud como los no institucionalizados. Entre los últimos se destaca la atención profesional en hogares mediante visitas domiciliarias. Ante los desafíos de la situación de desarrollo físico, cognitivo y emocional de los niños y niñas en Bolivia, el gobierno está implementando el Programa de Desarrollo Infantil Temprano “Crecer Bien para Vivir Bien” con especial foco en un componente de atención en hogares por vía de visitas domiciliarias. Esta nota técnica analiza los datos de línea de base de la evaluación de impacto para el componente de visitas domiciliarias del programa que incluye variaciones de atención en frecuencia y perfiles profesionales a fin de informar sobre mecanismos costo efectivos de implementación de este tipo de intervenciones. El estudio representa la continuación de iniciativas de levantamiento de información sobre pruebas estandarizadas de dimensiones de desarrollo infantil temprano en el país con el fin de generar evidencia para los tomadores de decisión dentro del sector

Centros infantiles en Bolivia : atención, infraestructura y calidad de servicios de desarrollo infantil

En una serie de trabajos publicados en 2008 en la revista científica The Lancet, se señala que los daños provocados por la desnutrición en los primeros años de vida no solamente llevan a rezagos permanentes, sino que además pueden afectar a las generaciones futuras. Los primeros 1000 días de vida (desde el embarazo hasta aproximadamente los 2 años de edad) de niños y niñas constituyen una ventana única de intervención en desarrollo infantil temprano para la estimulación y para orientar a padres en prácticas de paternidad. Como respuesta a los retos persistentes de la situación del desarrollo físico, cognitivo y socioemocional de la niñez en Bolivia, el gobierno está implementando el Programa de Desarrollo Infantil Temprano “Crecer Bien para Vivir Bien”. La información presentada en esta nota técnica analiza los datos de línea de base de la evaluación de impacto para el componente de fortalecimiento de centros infantiles del programa. El estudio representa un primer esfuerzo de levantar datos estandarizados sobre la calidad de centros infantiles en Bolivia, en particular en los departamentos de Chuquisaca y Potosí

Bed-Sharing in Couples Is Associated With Increased and Stabilized REM Sleep and Sleep-Stage Synchronization

Methods Young healthy heterosexual couples underwent sleep-lab-based polysomnography of two sleeping arrangements: individual sleep and co-sleep. Individual and dyadic sleep parameters (i.e., synchronization of sleep stages) were collected. The latter were assessed using cross-recurrence quantification analysis. Additionally, subjective sleep quality, relationship characteristics, and chronotype were monitored. Data were analyzed comparing co-sleep vs. individual sleep. Interaction effects of the sleeping arrangement with gender, chronotype, or relationship characteristics were moreover tested. Results As compared to sleeping individually, co-sleeping was associated with about 10% more REM sleep, less fragmented REM sleep (p = 0.008), longer undisturbed REM fragments (p = 0.0006), and more limb movements (p = 0.007). None of the other sleep stages was significantly altered. Social support interacted with sleeping arrangement in a way that individuals with suboptimal social support showed the biggest impact of the sleeping arrangement on REM sleep. Sleep architectures were more synchronized between partners during co-sleep (p = 0.005) even if wake phases were excluded (p = 0.022). Moreover, sleep architectures are significantly coupled across a lag of ± 5min. Depth of relationship represented an additional significant main effect regarding synchronization, reflecting a positive association between the two. Neither REM sleep nor synchronization was influenced by gender, chronotype, or other relationship characteristics. Conclusion Depending on the sleeping arrangement, couple's sleep architecture and synchronization show alterations that are modified by relationship characteristics. We discuss that these alterations could be part of a self-enhancing feedback loop of REM sleep and sociality and a mechanism through which sociality prevents mental illness