1.2.2 Geographical Targeting of Poverty Alleviation Programs 1 MEASUREMENT AND POVERTY MAPPING UPA Package 1, Module 2.

Slides:



Advertisements
Similar presentations
1.2.3 Background of Poverty Mapping 1 MEASUREMENT AND POVERTY MAPPING UPA Package 1, Module 2.
Advertisements

Medicaid Update 2013 John J. Wernert, MD President, Professional Development Associates, LLC Medical Director, Medical Management Wishard Health System.
Introduction to Medicaid Roger Auerbach Rutgers Center for State Health Policy Regional Housing Conference September 10, 2003.
This research is funded in part through a U.S. Health Resources and Services Administration, State Planning Grant to the Hawaii State Department of Health,
1.2.1 Measurement of Poverty 1 MEASUREMENT AND POVERTY MAPPING UPA Package 1, Module 2.
Theoretical Structure of Financial Accounting
Overview of Income Redistribution Programs
Can we predict how enrollment may change if eligibility floor is raised to 200% of FPL? Test health insurance policy option Determine typical characteristics.
Further Inference in the Multiple Regression Model Prepared by Vera Tabakova, East Carolina University.
© 2003 By Default!Slide 1 Poverty Mapping Celia M. Reyes Introduction to Poverty Analysis NAI, Beijing, China Nov. 1-8, 2005.
Improving Social Policy through Spatial Information: Application of Small Area Estimation and Spatial Microsimulation Methods in Geographical Targeting.
Palestinian Central Bureau of Statistics (PCBS) Palestine Poverty Maps 2009 March
Mexico’s Oportunidades: Self- Selection in Targeted Social Programs César Martinelli Professor of Economics, ITAM, Mexico City and Wilson Center/Comexi.
Ethiopia Productive Social Safety Net. Program description This program aims to provide –Predictable, multi-year assistance to –chronically the food insecure.
Constructing the Welfare Aggregate Part 2: Adjusting for Differences Across Individuals Bosnia and Herzegovina Poverty Analysis Workshop September 17-21,
Environmental Science Ch
THE EFFECT OF INCOME SHOCKS ON CHILD LABOR AND CCTs AS AN INSURANCE MECHANISM FOR SCHOOLING Monica Ospina Universidad EAFIT, Medellin Colombia.
5110 Zeller Guidelines for research proposal
Producer Demand and Welfare Benefits of Price and Weather Insurance in Rural Tanzania Alexander Sarris (FAO), Panayiotis Karfakis (Univ. of Athens and.
Adjustment of benefit Size and composition of transfer in Kenya’s CT-OVC program Carlo Azzarri & Ana Paula de la O Food and Agriculture Organization.
Designing a Random Assignment Social Experiment In the U.K.; The Employment Retention and Advancement Demonstration (ERA)
Integrating Quantitative and Qualitative Methods for Understanding Poverty Principles and Country Case Study.
Comparing SPI and SSI Data Formats The case of Sri Lanka Ruwanthi Elwalagedara Joint ADB / ILO / OECD Korea Policy Centre Technical Workshop on Social.
1 Targeting and Calibrating Educational Grants: Focus on Poverty or on Risk of Non-Enrollment? Elisabeth Sadoulet and Alain de Janvry University of California.
Module 6: Quantifying gaps and measuring coverage ILO, 2013.
Social Assistance Pilots Program SA Pilots Seminar Ways for improving housing subsidies system Liudmyla Kotusenko CASE Ukraine March 2010.
Poverty Targeting in Asia Country surveys on India, Indonesia, the Philippines, PRC and Thailand.
Assessing the Distributional Impact of Social Programs The World Bank Public Expenditure Analysis and Manage Core Course Presented by: Dominique van de.
Targeted Interventions in Health Care: The case of PROMIN Sebastian Galiani Mercedes Fernandez Ernesto Schargrodsky.
Introduction A GENERAL MODEL OF SYSTEM OPTIMIZATION.
Strengthening existing information systems to provide improved analysis to support the design of cash transfer programmes John Seaman Evidence for Development.
ICP Workshop, Tunis Nov. 03 Overview of the Sample Framework.
Presented by: Edoardo Pizzoli - HANDBOOK ON RURAL HOUSEHOLD, LIVELIHOOD AND WELL-BEING: STATISTICS ON RURAL DEVELOPMENT AND AGRICULTURE HOUSEHOLD INCOME.
LONG TERM CARE Financing Long Term Care. THE NEED FOR LONG-TERM CARE SERVICES IN THIS COUNTRY IS EXPECTED TO INCREASE DRAMATICALLY.
Efficiency, equity and feasibility of strategies to identify the poor: an application to premium exemptions under national health insurance in Ghana Caroline.
Y X 0 X and Y are not perfectly correlated. However, there is on average a positive relationship between Y and X X1X1 X2X2.
MDG data at the sub-national level: relevance, challenges and IAEG recommendations Workshop on MDG Monitoring United Nations Statistics Division Kampala,
Poverty Maps: Uses and Caveats Tara Vishwanath Lead Economist World Bank.
1 Ministry of Finance and Ministry of Samurdhi Welfare Benefits Board The Targeting Formula: Analysis Using Pilot Data Welfare Workshop Colombo,
Social Welfare Policymaking
Indirect Measures: a scorecard (objective) and perception (subjective) based poverty Sajjad Zohir Lecture # 5 GED-ERG Training Workshop on Measuring Poverty.
Targeting of Public Spending Menno Pradhan Senior Poverty Economist The World Bank office, Jakarta.
1 When Support for the Poor is Poor Support: Income-tested social assistance programs in Russia Emil Daniel Tesliuc HNDSP World Bank.
Social Welfare Policymaking. What is Social Policy and Why is it so Controversial? Social welfare policies provide benefits to individuals, either through.
WHAT IS PUBLIC POLICY? Social and Economic Policy.
CHAPTER 11 Planning and Budgeting the Marketing Mix Part 1: Pages
Caterina Ruggeri Laderchi, Ramya Sundaram, Natsuko Kiso and Alexandru Cojocaru World Bank International Conference “Poverty and Social Inclusion in the.
1 Who benefits from utility subsidies? Caroline van den Berg K. Komives, V. Foster, J. Halpern, Q. Wodon and R. Abdullah September 13, 2006.
1 Efficiency of Targeting of Social Transfers in Bosnia and Herzegovina Edin Šabanović, Agency for Statistics of Bosnia and Herzegovina Fahrudin Memić,
GOVERNMENT OF THE KINGDOM OF LESOTHO Water and Sewerage Company (WASCO) Greater Maseru Water Supply Feasibility Study & Preliminary Design Results of Socio-Economics.
A STUDY ON PRO-POOR TARGETING OF STUDENTS AND SCHOLARSHIP DISTRIBUTION IN NEPAL BY Tara Chouhan Monitoring and Evaluation Officer Student Financial Assistance.
“Neighborhood Social Planning and Development” NEBSOC WORK PACKAGES (DATA COLLECTION STRATEGY) & 3.2 (DEEPENING AND IDENTIFICATION OF THE SOCIAL.
Keep Kansas Dollars in Kansas with a Kansas Solution: The Bridge to a Healthy Kansas Insert Meeting Name Your Name Date.
Best practices related to procurement within a project (for part of the expenditure) implemented by the beneficiary itself (art. 67, par. 4 of Regulation.
1 TARGETING HEALTH INSURANCE TO THE POOR IN COLOMBIA By Tarsicio Castañeda Reaching the Poor Conference The World Bank, February 18-20, 2004.
PROVIDING INTERNATIONAL COMPARABILITY OF POVERTY ASSESSMENTS
Social Welfare Policymaking
Overview of Income Redistribution Programs
International Labour Office
Disability and Social Safety Nets in Developing Countries
Training course to enhance collection of fisheries and aquaculture statistics Module 5 – Obtaining SSF and aquaculture statistics through a household.
Social Welfare Policymaking
Social Welfare Policymaking
Evaluating Impacts: An Overview of Quantitative Methods
Social Welfare Policymaking
Social Welfare Policymaking
Social Welfare Policymaking
Social Welfare Policymaking
Presentation transcript:

1.2.2 Geographical Targeting of Poverty Alleviation Programs 1 MEASUREMENT AND POVERTY MAPPING UPA Package 1, Module 2

1.2.2 Geographical Targeting of Poverty Alleviation Programs 2 POVERTY: Theory, Measurement, Policy and Administration - Geographical Targeting of Poverty Alleviation Programs -

1.2.2 Geographical Targeting of Poverty Alleviation Programs 3 Background Geographical targeting of welfare programs is common in developing countries and is often used in conjunction with additional targeting criteria to narrow the beneficiary population and thus reduce costs The challenge for policymakers is to use the available resources to provide the greatest possible assistance to those who need it most In the absence of reliable information on personal income, the first best solution of identifying the poor and directing all benefits only to them is not feasible

1.2.2 Geographical Targeting of Poverty Alleviation Programs 4 Background Even in industrial countries that have the necessary data, it is not possible to ascertain whether targeted programs do indeed reach all of the poor and do not leak to the nonpoor In the past, since most developing countries did not have reliable information on individual income, many chose programs with universal coverage However, governments had to drastically reduce or even terminate these programs due to growing budget constraints Some countries replaced universal coverage with means testing

1.2.2 Geographical Targeting of Poverty Alleviation Programs 5 Background Targeting by the use of indirect indicators The absence of reliable information for identifying the poor, on the one hand, and the mounting constraints on public resources, on the other, made targeting by means of indirect indicators the only viable alternative for most developing countries The indicators used to determine eligibility could include the household’s size, the number of children in the household, the size of the household’s landholdings or other assets, and the region in which the household was located

1.2.2 Geographical Targeting of Poverty Alleviation Programs 6 Geographical Targeting The optimum solution in welfare programs, from a theoretical point of view, is to identify the target population and design the most effective program for this group In most cases, however, it is not possible to identify the target population since this requires information that is not observable and thus difficult to verify In poverty alleviation programs, the target population is the group of households with incomes below a certain minimum level necessary to provide basic needs. Household income is often difficult to observe, however, and efforts to assess its value and thus identify the target group may involve prohibitive costs

1.2.2 Geographical Targeting of Poverty Alleviation Programs 7 Geographical Targeting These costs consist not only of direct administrative expenses for collecting the necessary information on income, but also of indirect costs due to incentives that the program may give individuals either to modify their behavior or to falsify information on their income in order to qualify for the program’s benefits Poverty alleviation programs such as income transfers or food subsidies to the poor, for example, may provide incentives to work less, cut earnings, or underreport income in order to qualify

1.2.2 Geographical Targeting of Poverty Alleviation Programs 8 Geographical Targeting Even in countries that have an accurate income reporting system, frequent means testing is necessary to verify that only households that meet the criteria remain on the eligibility lists The difficulties and expenses involved in identifying eligible households leave two options: either to implement universal programs that cover the entire population, or to use observable indicators that are highly correlated with the relevant unobserved variables, such as income, in order to determine eligibility

1.2.2 Geographical Targeting of Poverty Alleviation Programs 9 Geographical Targeting Universal programs are too expensive for most developing countries, and even many industrial countries find the rising welfare costs daunting The only viable option, therefore, is to use some form of targeting This, however, requires a careful choice of the targeting criteria, the observable indicators that will determine eligibility, and the programs that be fit the specific conditions of the country or locality

1.2.2 Geographical Targeting of Poverty Alleviation Programs 10 Geographical Targeting Aside from geographic targeting, there are other targeting options available to developing countries These options fall into three categories, namely, self-targeted programs, programs targeted on the basis of household characteristics and programs targeted on the household’s place of residence

1.2.2 Geographical Targeting of Poverty Alleviation Programs 11 Effectiveness of Targeted Programs The effectiveness of a targeted program depends on the share of the target population – that is, the percentage of the total poor population – that is actually covered by the program This, in turn, depends on the accuracy with which the observable indicators predict the unobserved variables that are the basis for determining eligibility For poverty alleviation programs, the desired indicators are those that are highly correlated with income

1.2.2 Geographical Targeting of Poverty Alleviation Programs 12 Effectiveness of Targeted Programs The effectiveness of the set of indicators depends on the probability expressed as where is the household’s level of the k th indicator (for example, the number of children) and is the critical value of the indicator that determines eligibility, y i is the unobservable income the i th household, and z is the poverty-line income, below which the household is considered poor and therefore eligible for the program

1.2.2 Geographical Targeting of Poverty Alleviation Programs 13 Effectiveness of Targeted Programs In practice, a data set containing complete information on both income and the indicators that are highly correlated with income is used and the reduced form of the analysis is where P i is either the level of consumption expenditures or a dummy variable which indicates whether the household is considered poor or not, are household or personal indicators and are dummies that identify the place of residence

1.2.2 Geographical Targeting of Poverty Alleviation Programs 14 Effectiveness of Targeted Programs When the dependent variable is itself a dummy variable, the econometric analysis is transformed into a logit analysis, and the equation then estimates the probability of a person being poor, assuming his personal indicators are within a given range and his place of residence is in a given area

1.2.2 Geographical Targeting of Poverty Alleviation Programs 15 Costs of Targeted Programs The overall costs of the program have the following there components: (1) the direct (administrative) costs of obtaining the information on these indicators; (2) the indirect costs dues to incentives that eligibility for the program may provide; and (3) the costs of providing the benefits to the population covered by the program