UNIVERSITY OF ECONOMICS INSTITUTE OF SOCIAL STUDIES HOCHIMINH CITY THE HAGUE VIETNAM THE NETHERLANDS VIETNAM – NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS AN ASSET-BASED GEOGRAPHIC TARGETING: EVIDENCE FROM RURAL VIETNAM A thesis submitted in partial fulfillment of the requirement for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By PHAM THI NGOC AI Academic Supervisor: Dr. PHAM KHANH NAM HO CHI MINH CITY, MAY 2014 TIEU LUAN MOI download : skknchat@gmail.com ACKNOWLEDGEMENT The thesis would not have been finished without the kind assistance and fruitful guidance of many people who have the contributions of different aspects for accomplishing the thesis. First of all, I am specially grateful to Dr. Pham Khanh Nam who encourages me at the beginning of title and help my deep understanding on literature theory as well as thesis writing.
In addition, I would like to express the sincere gratitude to Dr. Truong Dang Thuy for sharing his knowledge for the technique of the model and some valuable advices for the methodology. I would like to give special thank for my boss and colleagues who create conditions and assist working in order that I have more time for the research. Finally, my most gratitude is for my family, especially my parents and husband who have been always side by side with me during learning this program and researching process.
TIEU LUAN MOI download : skknchat@gmail.com ABSTRACT The purpose of this paper is to find out which asset is the most suitable for a particular region through calculating marginal return to a range of assets and then creating a serial of maps. The data are taken from Vietnam Living Standard Survey in 2006. The Weighted Least Squares is used for running the regression and combining with technique bootstrap and stepwise iterative deletion with the threshold of 5%. All targetable assets are focused on calculating marginal benefit.
It gives the reasonable findings that have very heterogeneous average marginal benefit across areas. The results give suggestion for choosing which assets are suitable for a particular region, thus it makes increases their efficacy. However, the governors and donors should consider the existence of trade-off equity and efficacy. TIEU LUAN MOI download : skknchat@gmail.com TABLE OF CONTENTS CHAPTER I: INTRODUCTION .5 Organization of the paper.
3 CHAPTER II: LITERATURE REVIEW .1 Geographic targeting theory .2 Household welfare function .3 The small estimation method.4 Transfer in-kind .5 The linkage between household welfare and return to assets .6 Review of empirical studies. 12 CHAPTER III: OVERVIEW OF HOUSEHOLD WELFARE IN VIETNAM AND METHODOLOGY .1 Overview of household welfare in Vietnam. 28 TIEU LUAN MOI download : skknchat@gmail.com CHAPTER IV: EMPIRICAL RESULTS .1 Statistics and value of marginal return of assets at national level .2 Analysis for average of mean marginal return of assets at provincial level .3 Kinds of maps for Vietnam. 42 CHAPTER V:CONCLUSION, POLICY IMPLICATION, LIMITATION AND FURTHER RESEARCH .3 Limitation of this study .4 Direction for Further research.
53 TIEU LUAN MOI download : skknchat@gmail.com LIST OF CHARTS Graph 3.1:The quintiles of income in urban and rural of Vietnam .2: The quintiles of expenditure in urban and rural of Vietnam .3: The Quintiles of income in the eight regions of Vietnam.4: The quintiles of expenditure in the eight regions of Vietnam .5: Poverty rate at different level of region in Vietnam (Unit: %) .1: Proportion of literate for each region .2: Distribution of educational level for each region .3: Distribution of expenditure for each educational level and each region 30 Graph 4.4: Distribution of ethnic minorities across regions .5: Expenditure of some ethnics .6: Distribution of livestock for each region .7: Distribution of other assets across regions. 33 TIEU LUAN MOI download : skknchat@gmail.com LIST OF FIGURES Figure 4.1: Maps of AMB that is significantly greater than zero .2: Maps of proportion of positive AMB .3: Maps of maximum significant AMB.4: Maps of maximum proportion of positive .5: Example of choosing cattle transferred to provinces which meet three conditions: the magnitude of AMB at 0.035, 95% households have positive AMB and poverty rate 30%. 48 TIEU LUAN MOI download : skknchat@gmail.com LIST OF TABLES Table 3.1: Average standard deviation of mean marginal return for national, regional and provincial level .2: Mean of AMB and proportion of provinces with positive AMB at national level .3: Values of AMB that are significantly greater than zero .4: Data for proportion (%) of positive AMB of households in provinces .5: Correlating between asset holdings and poverty with significant and proportion of positive AMB. 47 TIEU LUAN MOI download : skknchat@gmail.com TIEU LUAN MOI download : skknchat@gmail.com CHAPTER I: INTRODUCTION 1.
Problem statement Alleviating poverty is always the major targeting interested in by policy-makers in the developing countries. There are many transfer programs made around the world from years to years. However, increasing transfer program efficacy under the condition of scarce resources is the extremely important issue which governors and donors consider. One of the methods used widely and popularly for researching and practicing is geographic targeting.
As it gives a visual and useful tool and performance with low cost and easy administration. Thus, the important rule of the geographic targeting for poverty reduction is emphasized by Baker and Grosh(1994), Bigman and Foback (2000). Moreover, many papers have proven that the efficacy of transfer programs is higher when geographic units are smaller (Elbers et al. 2007, Minot 2000, Bigman and Foback 2000).
Poverty map is a tool of geographic targeting. It displays poverty indicator across Commented [PKN1]: I’ve made a new paragraph here. geography and answer the question where the poor people reside and who the poor people are (Elbers et al. 2003, Minot and Baulch 2005) as well as why the area has high incidence poverty which is driven by natural resources (Szonyi et al.
However, the greatly advanced step of geographic targeting is targeting map with asset-based approach. It answers the extremely important question that governors and donors should use in-kind transfer for a particular region to bring the highest benefit for the poor and might create motivation for them out of poverty. Besides, it gives a visual and practical tool for policy-makers and donors to manage their transfer programs with budget limitation. Benefit of transferring whether in-kind or cash is better, always consider by the researchers, donors and governors.
However, in many places in the world, they prefer transferring in-kind and in some cases, transfer in-kind is better (Hoffmann, Barrett and Just, 2009). 1 TIEU LUAN MOI download : skknchat@gmail.com For Vietnamese case, poverty alleviation is one of the most national goals. After many programs have been applied, the poverty reduction has been gained some remarkable achievement. The poverty rate felt from 58% in 1993 to 14,23% in 2010 (GSO).
The efficacy of these programs stems from the approximately exact determination who is poor or where the region is poor so that the transfer can go right address (Minot 2000, Minot and Baulch 2005, Cuong et al. These researchers have generated poverty and inequality map showing poverty and inequality at disaggregated level. The policy-makers always wonder which transfer program will bring the best benefit for a particular region and how to measure it. Thus, determining scope and magnitude Commented [PKN2]: Here you should add a paragraph explaining why estimating marginal benefit of an asset could help transfer programs and therefore help poverty alleviation.
of marginal benefit to assets at various regional level is very necessary. They may help the governors to identify which asset brings the most benefit for a particular region. Based on that it makes the transfer programs increase efficacy. This is also the aim of my paper.
The way that I study, is to determine the expected marginal return of a given asset to vary households across geography. Then, we can identify expected marginal benefit of a given asset for a particular area and map the results. It gives a visual map for rapid detection of which assets are the best for that region. This thing has extremely necessary meaning for poverty alleviation intervention.
Research objective The goal of this paper is to create a map which shows the expected average marginal benefit to assets of household across space. Thus, the research has three particular objectives as follows: 1. To determine the mean marginal returns to each asset at household level. To determine the average expected marginal benefit of assets for a specific region.
To create a visual map that illustrates marginal returns to household’s assets in Vietnam. 2 TIEU LUAN MOI download : skknchat@gmail. Research questions In this paper, we are going to answer following specific research questions: (1) How much is marginal gross benefit of an asset in the studied area? (2) How does a map of marginal return to asset in Vietnam look like? 1. Research contributions This research estimates average marginal return for varying assets across household and across geographic levels.
Based on that, we know the magnitude and scope of marginal benefit of asset for a particular region. Combing with the map software and other poverty indicators, it is a powerfully visual and practical tool for the policy- makers or donors to consult about the in-kind transfer scheme. Moreover, the large advantage of this method is the cost for implementing and administering lowly and easy for performance though it still exists some shortcomings unavoidably. Organization of the paper The study consists of the five chapters which show theoretical and empirical study to estimate average marginal return to a range of asset across space.
The first chapter gives the overview of the study. It shows the problem statement that explained importance of research this matter, Based on that, we give the research objectives and research questions for finding out the result. The research contribution and organization of the paper also present at the first chapter. At the second part, it consists of the main theories related to the linkage between household welfare and asset return, household welfare function, the small estimation method, geographic targeting and transfer –in.
Overview of household welfare in Vietnam, data and methodology are presented in Chapter 4 in which thedata from Vietnam Household Living Standard Surveys (VHLSS) and the Rural Agriculture and Fishery Cencus (RAFC) in 2006 is 3 TIEU LUAN MOI download : skknchat@gmail.com used and the model regression is the Weighted Least Square combined bootstrap technique and stepwise repeated deletion with threshold at 5% to calculate marginal return of asset. At the final chapter, it discusses the main results and gives policy implication and limitation of study as well as direction for further research. 4 TIEU LUAN MOI download : skknchat@gmail.com CHAPTER II: LITERATURE REVIEW 2.1 Geographic targeting theory For poverty reduction policy, determining the people who are eligible to receive the transfer is very important because of the budget constraints and avoiding waste of resources. If no targeting, the program is not effective as many people need the help but not receiving and vice versa.
According to Coady et al. (1993), “Targeting is a means of increasing program efficiency by increasing the benefit that the poor can get within a fixed program budget.” There are some kinds of targeting method including community targeting, categorical targeting, self-selection targeting, indicator targeting. While geographic targeting is applied broadly and commonly as it is applied easily and less cost for administering and monitoring. As well, it overcomes the limitation on information of individuals and households in developing countries (Bigman and Foback 2000).
Geographic targeting is a part of allocating budget to geographic region. It is a method to refer all individuals in a particular region in which they are determined to be eligible for receiving benefit. So, this method always is suitable for public works and social funds. The popular approach of geographic targeting is “poverty map” where the poverty indictor as well as variables used for calculating, reflect the basic needs or capabilities (Skoufas and others 2001).