PROXY MEANS TESTING: AN ALTERNATIVE METHOD FOR POVERTY ASSESSMENT

Transcription

1 PROXY MEANS TESTING: AN ALTERNATIVE METHOD FOR POVERTY ASSESSMENT SURAPONE PTANAWANIT Faculty of Social Administration, Thammasat University, Bangkok, Thailand Abstract- This article discusses the experiment of a proxy means test for assessing poverty levels in Thailand. It explains why a proxy means test instead of a conventional income or assets test is more applicable to a developing country like Thailand where income data are rather inaccurate. The main point of the article is its discussion in details on how the study develops the proxy means test. Apart from suggesting a way by which poverty can be measured by the proxy means test, the article also explains how this instrument can assess clients eligibility for social assistance benefit. Keywords- Poverty Assessment, Eligibility Assessment, Proxy Means Test, Social Assistance. I. INTRODUCTION Direct poverty assessment such as a means test and an assets test has been a common tool for evaluating the right to social assistance benefit in welfare states. Although this direct poverty assessment has become a useful instrument for social assistance arrangements, its applications in many occasions bring about negative consequences. As direct poverty testing is concerned with financial status, eligible clients are labeled as people with poverty. This labeling problem is sometimes believed to be the main cause of a low takeup rate. van Oorschot and Schell (1989) indicate in their study that the decline in the social assistance take-up rate might be the result of social labeling in Western European countries such as the UK, the Netherlands, and Germany. Their study also showed that the nontake-up rate for the family income supplement in the UK was as high as 46%. Developing countries encounter different problems of direct poverty assessment. A lot of people in these countries particularly those in poverty do not declare their incomes and wealth to the authorities. This results in inadequate data on poverty incomes and inaccurate poverty lines. Professional workers; therefore, are unable to construct a direct poverty test or to base their decisions to provide or to withhold welfare benefit on clients financial status. Inapplicability of direct poverty assessment also arises because social welfare in developing countries is independent from taxation. As a consequence, use of income or assets data as criteria for providing social assistance benefit is not possible. Literature has showed that direct poverty measurement like means testing has been a tool for determining the entitled amounts of social assistance benefit in most of the welfare states for a long time. Arguments in favor of the means test system are efficiency and adaptability. Despite these advantages, means testing is not above criticism. Legros (2009) points out the complexity and unfairness of the means tested system in France. He also mentions that the means tested benefit makes people dependent on the system in the long-term. Stigmatization caused by means testing seems to be another problem with which we are most familiar. Stigma discourages the target people to exercise their rights and results in a waste of welfare resources due to a low take-up rate of means tested benefit (see Moffitt 1983; Pudney, Hancock, & Sutherland 2006) In developing countries, limited application of means tests is not because of its complexity and cause of stigmatization; but unreliable income data and inaccurate poverty lines are the main reason. Kidd & Wyld (2011) argue that targeting the poor, especially, in developing countries is complicate because their large informal economies make it difficult to accurately assess people s incomes. Other authors including Johannsen (2006) mention similar limitations of using proxy means tests for targeting the poor and for providing welfare in these countries. Instead of encouraging use of means testing, some international organizations tend to support application of a proxy means test in developing countries. A paper published by FAO (see Tiba 2011), for example, suggests that means testing works best only in settings where declared income is verifiable; but in developing countries where income information is notoriously difficult, proxy means testing becomes an alternative way to assess the wealth status of an individual or a household. According to a UN s publication (Ortiz 2007), proxy means testing is cheaper than means tests and allows wider participation opportunities for community groups and local governments. One of the World Bank s publications (Grosh & Baker 1995) indicates that, in targeting the poor, social workers gather many aspects of information, thus, systematic use of collected data may improve targeting outcomes and increase the fairness and transparency of social programmes. Chile is known as the first country where the proxy means test was originated (Kidd & Wyld 2011; Grosh & Baker 1995). The Chile model employed a form filled out by a social worker to collect information on household characteristics such as location, housing quality, household composition, and the works done by the household members. Answers to these questions are prescribed with scores which will help predict the poverty or income level of each household. Other 4

2 developing countries such as Bangladesh (Sharif 2009), the Philippines (Mapa & Albis 2013), Uganda (Housson, Zeller, Alcaraz, Schwarze, & Johannsen 2007), and Peru (Johannsen 2006), then, adopted the proxy means testing as the method of eligibility assessment. II. OBJECTIVES This article aims to show how an indirect method for poverty assessment or the so called proxy means testing was developed. In conjunction with the first objective, the article will suggest to welfare agencies that this proxy means testing can be a valid testing method for social assistance eligibility. III. METHODOLOGY The research was designed as a survey research which collected data from people in communities and from persons who came for social assistance benefits throughout the country. The main aim of the survey was to test whether the indicators contained in the research instrument were valid enough to predict or to determine poverty levels. To achieve thid aim, the research launched the following procedure Research Instrument Design The research began with a review of literature concerning proxy means testing and group discussions with social workers, welfare administrators, and welfare recipients. The researcher expected that the literature review and group discussions would suggest a number of indicators that could predict a poverty level. After the literature review and group discussions, the researcher decided to select 10 indicators for measuring poverty levels. These 10 indicators consisted of educational levels, personal illness, age, marital status, the burden of caring, employment, debts, home ownership, housing conditions, and property owned. The researcher, then, formed these 10 indicators into a proxy means test which would become the instrument for the field survey. The proxy means test prescribed a score to each answer of each question (see Box 1). The score was, actually, the number of the answer choice. If the respondent had no personal illness, for example, he/she would tick option three under the question about current personal illness and would obtain a score of three. The total sum score of all items was a hint of the financial status of the respondent Populations and Sampling The country-wide survey covered people residing in communities and potential clients who came to the Social Development and Human Security Provincial Offices for social assistance benefits during the time of data collection. As the study was unable to construct a sampling frame, a non-probability sampling namely Proxy Means Testing: An Alternative Method For Poverty Assessment 5 judgmental sampling with a sample size of approximately 3000 respondents in each population was applied Data Collection Social workers and welfare officers who worked with the Social Development and Human Security Provincial Offices around the county were responsible for purposively choosing respondents in communities and social assistance clients to respond to the proxy means tests. The study intended to draw representative samples from the two populations by trying to cover respondents from various socio-economic statuses in terms of gender, age, education, employment, income etc Data Analysis Validation of the Proxy Means Test The validation took into account the capability to differentiate social assistance clients who were presupposed to be persons in poverty from people in communities who were believed to be more financially secure. The differentiation analysis compared the proxy means test data between the two sample groups. Only the indicator that showed a difference of at least 10% in terms of either an average value or a proportion between the two samples would be kept as a question item in the final version of the proxy means test Proxy Means Test Criteria As the indirect poverty assessment by the proxy means test must classify people according to their financial security, the data analysis needed to set up criteria for assessing people s financial status, To achieve this purpose, the analysis compared the average proxy means test scores between the samples and related them to the poverty ratios among Thai people. IV. RESULTS AND DISCUSSION 4.1. Validity of the Proxy Means Test Indicators All the 10 proxy means test indicators exhibited apparent contrast between the two sample groups above the predetermined 10% criterion set up prior to the data analysis. This means that each proxy means test indicator is, to a large extent, able to differential social assistance clients from people in communities. In other words, the ten proxy means test indicators are capable of differentiating people in poverty from those who are more financially secure. Consequently, we can identify people in poverty without paying attention to their incomes but by using the 10 proxy means test indicators to assess their socioeconomic status instead. In sum, people in poverty are likely to have the 10 following characteristics in common: Have a health problem Are below 20 years of age or older than 60 years old Have a lower educational background Tend to be divorced or be a widow/ widower

3 Proxy Means Testing: An Alternative Method For Poverty Assessment Box 1 The Proxy Means Test 6

4 Have insecure home ownership Live in poor housing conditions Own limited property Have insecure employment status Have the burden of caring Are in debt 3.5. Proxy Means Test Criteria Table 1 shows mean scores and standard deviations of the social assistance client group, the people in community group, and the whole sample group. The mean score of the social assistance clients is approximately with a standard deviation of This mean score is almost equal to the average value of the whole sample minus ½ of its standard deviation ( /2). The people in community group who are most economically secure retains the highest average proxy means test score of with the most dispersive standard deviation of If we take the proxy means test scores of the social assistance client group (the mean score of and its standard deviation of 10.93) as criteria for determining the national or whole country poverty levels, we will find a few interesting findings in relation to income poverty in Thailand. First, the World Bank (2015) reports that 12.60% of the Thai population earned income below the national official poverty line. This poverty ratio is almost equal to the figure of 13.6% of those who score lower than 25 in the whole sample group. The score of 25 is actually the average proxy means test score in the social assistance client group minus ½ of its standard deviation ( /2). Therefore, the score of 25 can be comparable with the Thai official poverty line. The same World Bank Report also mentions that the income poverty headcount ratio at $4 a day (PPP) in Thailand is approximately 30.97%. This ratio is very close to 32.2% of the whole sample who score lower than which is the average proxy means test score of the social assistance client group. As a consequence, the proxy means test score of or approximately 35 can be comparable with the Thai poverty at the international poverty line (PPP). Table 1. Average Proxy Means Test Scores and Their Standard Deviations CONCLUSION AND RECOMMENDATIONS In Thailand where information about incomes is inaccurate, the conventional methods of poverty measurement such as poverty lines, an income test, and an assets test are rather impractical. This study, Proxy Means Testing: An Alternative Method For Poverty Assessment 7 therefore, intended to introduce proxy means testing by which poverty levels are indirectly measured as an alternative method for poverty assessment. By basing its initial analysis on literature and focus groups, the study developed the so called proxy means test which consisted of 10 socio-economic indicators for assessing people s financial status. The study, then, conducted a nation-wide survey to validate the proxy means test. The findings indicated a number of conclusions. Indirect measurement by the proxy means test comprising socio-economic indicators can be an alternative to direct poverty measurement by income or assets testing. The ten indicators proved to be able to measure poverty levels or to differentiate people in poverty from those with economic security comprises employment status, health status, age, education, marital status, the burden of caring, debt burdens, property owned, home ownership, and housing conditions. The analysis of the national survey data in relation to the World Bank statistics indicated that the proxy means test scores from the social assistance clients could be baselines for measuring poverty levels. The value of 25 derived from the average proxy means test level scored by the social assistance clients minus ½ of its standard deviation, for example, could be used as the Thai national poverty threshold. This threshold can be compared with the national income poverty line which is the conventional direct poverty measurement. Measurement of poverty by the proxy means test shows more than economic status because it reveals socio-economic aspects of deprivation. Proxy means test scores, therefore, represent depth of poverty which is useful for both social and economic development. Apart from using the proxy means testing for indirect assessment of poverty, this paper would suggest another application of this indirect poverty measurement in judging social assistance eligibility. From the above findings particularly that of the social assistance client group, the study can derive a proxy means test scale for allocating general social assistance benefit. Box 2 shows how the scale functions to determine an eligible amount of social assistance benefit based on client s proxy means test score. Clients, whose proxy means test scores are in the Free Area or below the threshold of 35, are entitled to a full allowance. The score of 46 is the cut-out point at which the provision of an allowance stops as persons who score 46 or higher will be considered financially secure, thus, ineligible for any amount of benefit. Clients with scores from 36 to 46 are entitled to an allowance determined either by a rigorous or a lenient eligibility formula. The rigorous formula gives a smaller amount of benefit than that computed by the lenient eligibility one. The rigorous formula is appropriate for the situation where welfare agencies have limited budgets or want clients to rely more on market incomes than on social assistance benefit. Welfare agencies may also choose to provide eligible clients with benefit larger

5 Proxy Means Testing: An Alternative Method For Poverty Assessment Box 2 Application of the Proxy Means Test than nominal amounts by applying the lenient formula in determining social assistance allowances. The welfare agency needs to declare a full or a maximum allowance (FA) before applying the proxymeans-test formulas. The threshold (Th) and cut-out (CS) scores are the static terms of 36 and 46. However, the threshold and cut-out scores change corresponding to national socio-economic circumstances. This implies that the proxy means test scale and formulas must be adjusted from time to time. A social worker obtains the client s proxy-means-test score or the PMTS after interviewing him/her according to the proxy-means-test questions. The eligible amount of benefit (EA) is, then, derived by substituting these terms in either the rigorous or the lenient formula. If the current full allowance is 5,000 baht/month (33 Thai baht = 1US$) and the client scores 38 from the proxy means test, for example, his/her rigorous and lenient allowances will be 4,000 and 4,782 baht/month respectively. REFERENCES [1]. Grosh, M., & Baker, J. (1995). Proxy Means Tests for Targeting Social Programs: Simulations and Speculation, LSMS working paper no.118. Washington D.C.: the World Bank. [2]. Houssou, N., Zeller, M., Alcaraz, V.G., Schwarze, S., & Johannsen, J. (2007). Proxy Means Tests for Targeting the Poorest Households Applications to Uganda. Paper presented at 8

6 the 106th seminar of the EAAE pro-poor development in low income countries: Food, agriculture, trade, and environment, Montpellier, France. [3]. Johannsen, J. (2006). Operational Poverty Targeting in Peru- Proxy Mean Testing with Non-income Indicators. Brasilia (Brazil): International Poverty Centre (the United Nations Development Programme). [4]. Kidd, S.W., & Wylde, E. (2011). Targeting the Poorest: An Assessment of the Proxy Means Test Methodology. Canberra: Agency for International Development. [5]. Legros, M. (2009). France: Minimum Income Schemes: From Crisis to Another, The French Experience of Means Tested Benefits. Retrieved from file:///c:/users /Get/ Downloads /France_1_ 2009_EN%20(3).pdf [6]. Mapa, D.S., & Albis, M.L.F. (2013). New Proxy Means Test (PMT) Models: Improving Targeting of the Poor for Social Protection. Paper presented at the 12th National Convention on Statistics (NCS), Mandaluyong City, The Philippines. [7]. Moffitt, R. (1983). An Economic Model of Welfare Stigma. American Economic Review, 73(5), [8]. Ortiz, I. (2007). Social Policy. New York: Department for Economic and Social Affairs of the United Nation. Proxy Means Testing: An Alternative Method For Poverty Assessment [9]. Pudney, S., Hancock, R., & Sutherland, H. (2006). Simulating the Reform of Means-tested Benefits with Endogenous Takeup and Claim Costs. Oxford Bulletin of Economics and Statistics, 68(2), doi: /j x [10]. Sharif, I.A. (2009). Building a Targeting System for Bangladesh Based on Proxy Means Testing. Washington D.C: the World Bank. [11]. Tiba, Z. (2011). Targeting the Most Vulnerable: Implementing Social Safety Nets. In A. Prakash (Ed.). Safeguarding Food Security in Volatile Global Markets ( ). Rome: Food and Agriculture Organization of the United Nations. [12]. van Oorschot, W.J.H., & Schell, J. (1991). Means Testing in Europe: A Growing Concern. In M. Adler, C. Bell, J. Clasen, & A. Sinfield (Eds.), The Sociology of Social Security ( ). (Edinburgh education and society series). Edinburgh: Edinburgh University Press. [13]. World Bank. (2016). Poverty and Equity Database. Retrieved from = poverty-and-equity-database 9