Author

Abstract

In this paper I develop a Proxy Means Tests (PMT) model and examine several targeting lines based on 2008 household survey data to identify beneficiaries for a targeting subsidy scheme in Iran. Based on the findings of this study, setting a cut-off percentile of 40% is expected to provide compensation for almost 70 percent of the poorest households. This will result in the highest accuracy mainly in rural areas where poverty is much more severe than elsewhere in the country. Substituting the current scheme which covers almost all households in Iran with a targeting scheme based on the results of the PMT model will allow for either transferring larger amount of money to the extreme poor at the current budget, or reducing the government expenditure in the form of repayment after removing subsidies on fuel and energy.

Keywords

Article Title [Persian]

آزمون تقریب وسع برای برنامه هدفمندی یارانه‌ها در ایران

Author [Persian]

  • محمد بخشوده

Abstract [Persian]

هدف این مقاله شناسایی افراد مشمول برنامه هدفمندی یارانه‌ها در ایران با استفاده از الگوی «آزمون تقریب وسع» و «آزمون چندین خط هدف» بر مبنای داده‌های خانوار سال 1387 می‌باشد. بر مبنای یافته‏های به‌دست آمده، خط هدف 40%، بالاترین میزان دقت را دارد و براساس آن، با جدا کردن 40 درصد جمعیت با درآمد بالا، می‏توان از طریق پرداخت نقدی برای حدود 70 درصد از فقیرترین خانوارها به خصوص در مناطق روستایی که فقر در آنها شدیدتر از سایر مناطق است، جبران خسارت کرد. با جایگزین کردن برنامه فعلی، که تقریباً همه خانوارها را تحت پوشش پرداخت نقدی قرار داده، با برنامه پیشنهادی فوق می‌توان با بودجه اختصاصی فعلی، مبلغ بیشتری به افراد فقیر پرداخت نمود و یا مخارج دولت برای این برنامه را از طریق حذف 40 درصد خانوارها کاهش داد.

Keywords [Persian]

  • برنامه هدفمندی یارانه ها
  • آزمون تقریب وسع (آزمون جایگزین درآمد)
  • ایران
Ahmed, A. U., & Bouis, H. E. (2002). Weighing what’s practical: Proxy Means Tests for targeting food subsidies in Egypt. Food Policy, 27 (5–6), 519–40.
Araujo, C. & Carraro, L. (2011). A proxy-means test exercise for the selection of beneficiaries of poverty targeted programs in Mongolia. Technical Report prepared for the Ministry of Social Welfare, Mongolia.
AusAID, (2011). Targeting the Poorest: An assessment of the proxy means test methodology, Published by the Australian Agency for International Development (AusAID). Retrieved from:
www.ausaid.gov.au/Publications/Documents/targeting-poorest.pdf.
Baulch, B. (2002). Poverty monitoring and targeting using ROC curves: Examples from Vietnam. Working Paper no. 161, Institute of Development Studies, University of Sussex, England.
Burchardt, T. (2005). Incomes, functionings and capabilities: The well-being of disabled people in Britain. PhD in Social Policy, London School of Economics.
Coady, D., Grosh, M. & Hoddinott, J. (2002). Targeting outcomes redux. FCND Discussion Paper no. 144.
Coady, D., & Parker, S. (2009). Targeting social transfers to the poor in Mexico, IMF Working Paper WP/09/60.
Coady, D., & Skoufias, E. (2004). On the targeting and redistributive efficiencies of alternative transfer instruments, Review of Income and Wealth, 50 (1), 11–27.
Castañeda, T.  (2005). Targeting social spending to the poor with proxy-means testing: Colombia’s SISBEN System. Social Protection Discussion Paper Series no. 0529. Social Protection Unit, Human Development Network, The World Bank.
Dutrey, A. P. (2007). Successful targeting? Reporting efficiency and costs in targeted poverty alleviation programmes. Social Policy and Development Programme Paper no. 35, United Nations Research Institute for Social Development.
Grosh, M., & Baker, J. (1995). Proxy Means Tests for targeting social programs: Simulations and speculations. Living Standards Measurement SurveyWorking Paper no. 118. Washington DC: The World Bank.
Grosh, M., & Glinskaya, E. (1997). Proxy means testing and social assistance in Armenia. Draft Report. Washington DC: The World Bank.
Grosh, M. (1994). Administering targeted social programs in Latin America: From platitudes to practice. World Bank Regional and Sectoral Studies, the International Bank for Reconstruction and Development / The World Bank, 188pp.
Glewwe, P., & Kanaan, O. (1989). Targeting assistance to the poor: A multivariate approach using household survey data. Policy, Planning and Research Working Paper no. 225. Washington DC: The World Bank.
Haddad, L., Sullivan, J., & Kennedy, E. (1992). Identification and evaluation of alternative indicators of food and nutrition security: Some conceptual issues and an analysis of extant data, International Food Policy Research Institute Final Report. Retrieved from: http://pdf.usaid.gov/pdf_docs/XNABL423A.pdf
Houssou, N. (2010). Operational poverty targeting by proxy means tests, models and policy simulations for Malawi. PhD Dissertation, Faculty of Agricultural Sciences, Department of Agricultural Economics and Social Sciences in the Tropics and Subtropics University of Hohenheim.
Houssou, N., Zeller, M., Alcaraz, V., Schwarze, S., & Johannsen, J. (2007). Proxy means tests for targeting the poorest households applications to Uganda. Paper Prepared for Presentation at the 106th Seminar of the EAAE, Pro-poor Development in Low Income Countries: Food, Agriculture, Trade, and Environment, 25-27 October 2007, Montpellier, France.
Instituto Nacional De Estadistica (INE). (Undated). Poverty and its measurement: The presentation of a range of methods to obtain measures of poverty. Retrieved from: http://www.ine.es/en/daco/ daco42/sociales/pobreza_en.pdf.
IRIS. (2005). Note on assessment and improvement of tool accuracy. Mimeograph, IRIS Center, University of Maryland, USA.
Johannsen, J. (2006). Operational poverty targeting in Peru - Proxy means testing with non-income indicators. International Poverty Centre Working Paper no. 30, United Nations Development Programme International Poverty Centre.
Kingdon, G. G. & Knight, J. (2004). Subjective well-being poverty versus income poverty and capabilities poverty?, the ESRC Global Poverty Research Group, GPRG-WPS-003.
Kraay, A. (2004). When Is Growth Pro-Poor? Cross-Country Evidence, IMF Working Paper, WP/04/47.
Mapa, D. S. & Albis, M. L. F. (2013). New Proxy means test (PMT) models: improving targeting of the poor for social protection, 12th National Convention on Statistics (NCS) EDSA Shangri-La Hotel October 1-2, 2013.
Narayan, A., & Yoshida, N. (2005). Proxy means test for targeting welfare benefits in Sri Lanka, South Asia Poverty Reduction and Economic Management, World Bank, Washington D.C., Report No. SASPR-7.
 Persaud, A. (2005). Constructing a proxy mean test using survey data - an exposition of the methodology. Presented at the 30th Meeting of the Standing Committee of Caribbean Statisticians, 26–28 October 2005, Kingston, Jamaica.
Ravallion, M. (1998). Poverty lines in theory and practice. Living standards measurement study (LSM). Working Paper no. 133. Washington DC: The World Bank.
Ravallion, M. (2002). How can qualitative methods help in measuring poverty? Workshop on Poverty Measurement, Monitoring and Evaluation, January 11–12, 2002, India.
Ravallion, M. (2003). Measuring aggregate welfare in developing countries: How well do national accounts and surveys agree? Review of Economics and Statistics, 8, 645–52.
Ravallion, M. (2004). Pro-poor growth: A primer, Development Research Group, World Bank. Retrieved from:
http://web.usal.es/~bustillo/RavallionPPGPrimer.pdf
Ravallion, M., & Chen, S. (2003). Measuring pro-poor growth, Economics Letters, 78, (2003) 93–99.
Samson, M., van Niekerk, I., & Mac Quene, K. (2010). Designing and implementing social transfer programmes, 2nd ed., Economic Policy Research Institute, pp. 289.
Sen, A. (1993). Capability and Well-being. In M. Nussbaum & A. Sen (Eds.), The Quality of Life. Oxford: Clarendon Press.
Sharif, I. A. (2009). Building a targeting system for Bangladesh based on proxy means testing. Discussion Paper no. 0914. The World Bank.
Schreiner, M. (2006). A simple poverty scorecard for India. Microfinance Risk Management, Center for Social development, Washington University in Saint Louis, USA.
Sumarto, S., & Suryahadi, A. (2001). Principles and approaches to targeting: With reference to the Indonesian social safety net programs, a paper from the SMERU Research Institute, with supported from AusAID and the Ford Foundation. Retrieved from:
http://www.smeru.or.id/report/workpaper/principapproach/principleapproach.pdf.
Van Edig, X., Schwarze, S., & Zeller, M. (2013). Poverty Assessment by Proxy-Means Tests: Are Indicator-Based Estimations Robust over Time? A Study from Central Sulawesi, Indonesia, Quarterly Journal of International Agriculture, 52 (1), 27-49.
Zeller, M., & Alcaraz, V. G. (2005). Developing and testing poverty assessment tools: Results from accuracy tests in Uganda. IRIS Center, University of Maryland, College Park. Retrieved from:
http://www.povertytools.org/other_documents/Uganda%20Accuracy%20Report.pdf.
Zeller, M., Houssou, N., Alcaraz, V. G., Johansen, J., & Schwarze, S. (2006). Developing poverty assessment tool based on principal component analysis: Results from Bangladesh, Kazakhstan, Uganda, and Peru. Paper Presented at the 26th International Association of Agricultural Economists (IAAE) Conference, Gold Coast, Australia, 12–19 August 2006.
Zuhr, N. B. (2009). Proxy inference methods: Survey of literature. Economic Research Group. Retrieved from:
http://www.ergonline.org/youthforum/proxy%20inference%20nahim.pdf