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Yıl 2025, Cilt: 75 Sayı: 2, 475 - 497, 15.01.2026
https://doi.org/10.26650/ISTJECON2025-1736468
https://izlik.org/JA94SW37WA

Öz

Kaynakça

  • Agyemang, F. S. K., Memon, R., Wolf, L. J., & Fox, S. (2023). High-resolution rural poverty mapping in Pakistan with ensemble deep learning. PLOS ONE, 18(4), e0283938. https://doi.org/10.1371/journal.pone.0283938 google scholar 
  • Ahmed, S. (2025). Some new strategies for estimating area-level parameters using information from successive surveys. Quality & Quantity, 59(1), 411–455. https://doi.org/10.1007/s11135-024-01942-6 google scholar 
  • Allen, B., Bourke, M., Datt, G., Gibson, J., Hwang, V., Parajuli, D. (2005). Mapping Poverty in Rural Papua New Guinea. Pacific Economic Bulletin, 20(1), 1–26. doi: 10.1111/j.1467-8373.2005.00274.x google scholar 
  • Arif G. M., Nazli H., & Haq R. (2000). Rural non-agriculture employment and poverty in Pakistan. The Pakistan Development Review, 39(4), 1089–1110. [suspicious link removed] google scholar 
  • Arouri, M., Ben Youssef, A., & Nguyen, C. (2017). Does urbanisation reduce rural poverty? Evidence from Vietnam. Economic Modelling, 60, 253–270. https://doi.org/10.1016/j.econmod.2016.09.022. google scholar 
  • Asian Development Bank. (2020). Introduction to Small Area Estimation Techniques: A Practical Guide for National Statistics Offices (0 ed.). Asian Development Bank. doi: 10.22617/TIM200160-2 google scholar 
  • Awan, M. S., & Iqbal, N. (2010). Determinants of Urban Poverty: The Case of Medium Sized City in Pakistan. PIDE-Working Papers, 2010:60. https://ideas.repec.org//p/pid/wpaper/201060.html google scholar 
  • Awan, S., M., Waqas, M., & Aslam, M. (2015). Multidimensional measurement of poverty in Pakistan: Provincial analysis. Nóesis. Revista de Ciencias Sociales y Humanidades, 24(48), 55–72. https://doi.org/10.20983/noesis.2015.2.2 google scholar 
  • Awan, M. S., Waqas, M., & Aslam, M. A. (2011). Multidimensional Poverty in Pakistan: The Case of Punjab Province [MPRA Paper]. google scholar 
  • Balamurali, A., Janflone, J., & Zhu, E. (2015, November 1). Impact of Education on Poverty. google scholar 
  • Banerjee, A. V., & Duflo, E. (2012). Poor economics: A radical rethinking of the way to fight global poverty (Paperback ed.). PublicAffairs. google scholar 
  • Bartram, L., Roe, B. (2005). Dependency ratios: Useful policy‐making tools? Geriatrics & Gerontology International, 5(4), 224–228. https://doi.org/10.1111/j.1447-0594.2005.00311.x google scholar 
  • Bata T., & Sinnathurai V. (2013). An Empirical Study on the Nexus of Poverty, GDP Growth, Dependency Ratio, and Employment in Developing Countries. Journal of Competitiveness, 5(2), 67–82. https://doi.org/10.7441/joc.2013.02.05 google scholar 
  • Briones, K. J., Lopez, J., Elumbre, R. J., & Angangco, T. M. (2021). Income, consumption, and poverty measurement in the Philippines. MPRA Paper, Article 106025. google scholar 
  • Cheema, A., Khalid, L., Patnam, M. (2008). The geography of poverty: Evidence from Punjab. Lahore Journal of Economics, 13(Special Edition), 163–188. https://doi.org/10.35536/lje.2008.v13.isp.a10 google scholar 
  • Christiaensen, L., & Shorrocks, A. (2012). Measure poverty over time. The Journal of Economic Inequality, 10(2), 137–143. https://doi.org/10.1007/s10888-012-9225-4 google scholar 
  • Corral, P., Molina, I., Cojocaru, A., & Segovia, S. (2022). Guidelines for Small Area Estimation for Poverty Mapping. World Bank. google scholar 
  • Crull, S. R. (1996). Housing Inadequacy and Satisfaction of Black and White Households in Poverty. Housing and Society, 23(2), 1–14. doi: 10.1080/08882746.1996.11430238 google scholar 
  • Denny, K. (2002). New Methods for Comparing Literacy Across Populations: Insights from Measurement of Poverty. Journal of the Royal Statistical Society Series A: Statistics in Society, 165(3), 481–493. https://doi.org/10.1111/1467-985X.00249 google scholar 
  • Deo, S., Sane, A., Sharma, S., & Tabar, S. (2024). Economic dependency ratio as a dimension of poverty and vulnerability. In R. Goel, T. Singh, Md. M. Rahman, Q. T. Islam, & S. K. Baral (Eds.), Understanding the Multi-Dimensional Nature of Poverty (pp. 109–130). Emerald Publishing Limited. https://doi.org/10.1108/978-1-83753-292-620241006 google scholar 
  • Dodge, Y. (2010). The concise encyclopaedia of statistics (Updated ed.). Springer. google scholar 
  • European Commission. (2017). Statistical matching of European Union statistics on income and living conditions (EU-SILC) and the household budget survey. Publications Office. google scholar 
  • Farooq, H. U., Nazar, M. J., Hanif, M. S., & Faisal, A. (2024, July 27). Using Satellite Imagery to Map Poverty-Struck Areas in Pakistan Using Neural Networks. EasyChair Preprint. google scholar 
  • Fiadzo, E., Houston, J., & Godwin, D. (2001). Estimating housing quality for poverty and development policy analysis: CWIQ in Ghana. Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 53(2), 137–162. https://doi.org/10.1023/A:1026764711406 google scholar 
  • Gine-Garriga, R., Perez-Foguet, A. (2018). Measuring Sanitation Poverty: A Multidimensional Measure to Assess the Delivery of Sanitation and Hygiene Services at the Household Level. OPHI Working Papers, Article 116. google scholar 
  • Gine‐Garriga, R., & Pérez‐Foguet, A. (2019). Monitoring and targeting the sanitation poor: A multidimensional approach. Natural Resources Forum, 43(2), 82–94. https://doi.org/10.1111/1477-8947.12171 google scholar 
  • Glaeser, E. L., Kahn, M. E., & Rappaport, J. (2000). Why Do the Poor Live in Cities? (SSRN Scholarly Paper No. 228112). Social Science Research Network. google scholar 
  • Hameed, A., Padda, I. U. H., Karim, S. (2016). Multidimensional Poverty Mapping for Rural Pakistan. SSRN Electronic Journal. doi: 10.2139/ssrn.3149119 google scholar 
  • Haughton, J., Khandker, S. R. (2012). Handbook on Poverty and Inequality. World Bank. google scholar 
  • Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic regression (2. ed., [Nachdr.]). Wiley. google scholar 
  • Jamal, H. (2007). Income Poverty at the District Level: Application of the Small Area Estimation Technique (No. 70). Social Policy and Development Centre. google scholar 
  • Javed, Z., Asif, A. (2011). Female households and poverty: A case study of Faisalabad District. google scholar 
  • Khan, A. U., Saboor, A., Hussain, A., Sadiq, S., Mohsin, A. Q. (2014). Investigating Multidimensional Poverty across Regions in the Sindh Province of Pakistan. Social Indicators Research, 119(2), 515–532. https://doi.org/10.1007/s11205-013-0511-8 google scholar 
  • Khan, M., Saboor, A., Rizwan, M., & Ahmad, T. (2020). An empirical analysis of monetary and multidimensional poverty: Evidence from a household survey in Pakistan. Asia Pacific Journal of Social Work and Development, 30(2), 106–121. https://doi.org/10.1080/02185385.2020.1712663 google scholar 
  • Lanjouw, P., & Ravallion, M. (1995). Poverty and household size. The Economic Journal, 105(433), 1415. https://doi.org/10.2307/2235108 google scholar 
  • Lemanski, C. (2011). Moving up the ladder or stuck on the bottom row? Homeownership as a solution to poverty in urban South Africa: Homeownership as a solution to poverty in South Africa? International Journal of Urban and Regional Research, 35(1), 57–77. https://doi.org/10.1111/j.1468-2427.2010.00945.x google scholar 
  • Lipton, M. (1984). Demography and poverty (Working Paper No. 623; World Bank Staff Working Papers). google scholar 
  • Majoka, Z., Wieser, C., Qazi, M., Fonseca, D. G., Sohnesen, T. P., & Khan, I. (2024). Mind the Gap: Assessing Pakistan’s National Socioeconomic Registry (Report No. 194522). World Bank. google scholar 
  • Meenakshi, J. V., Ray, R. (2002). Impact of household size and family composition on poverty in rural India. Journal of Policy Modelling, 24(6), 539–559. https://doi.org/10.1016/S0161-8938(02)00129-1 google scholar 
  • Meyer, B. D., & Sullivan, J. X. (2003). Measuring the Well-Being of the Poor Using Income and Consumption. The Journal of Human Resources, 38, 1180. doi: 10.2307/3558985 google scholar 
  • Mihai, M., Ţiţan, E., Manea, D. (2015). Education and Poverty Procedia Economics and Finance, 32, 855–860. https://doi.org/10.1016/S2212-5671(15)01532-4 google scholar 
  • Najam, Z. (2021). The sensitivity of poverty trends to dimensionality and distribution sensitivity in poverty measures—District level analysis for Pakistan. Poverty and Public Policy, 13(4), 368–411. https://doi.org/10.1002/pop4.323 google scholar 
  • Naveed, A., Ghaus, M. U. (2018). Geography ofPoverty Update: Multidimensional poverty in Pakistan at the national, provincial and district levels—2014-15. Pakistan Poverty Alleviation Fund. google scholar 
  • Naveed, A., & Islam, T. (2010). Estimating Multidimensional Poverty and Identifying the Poor in Pakistan: An Alternative Approach (Working Paper No. Recoup Working Paper 28; Research Consortium on Education Outcomes and Poverty). University of Cambridge. google scholar 
  • Orbeta, A. J. C. (2005). Poverty, vulnerability, and family size: Evidence from the Philippines. Discussion Papers, Article DP 2005-19. google scholar 
  • Padda, I. U. H., Hameed, A. (2018). Estimating multidimensional poverty levels in rural Pakistan: A contribution to sustainable development policies. Journal of Cleaner Production, 197, 435–442. https://doi.org/10.1016/j.jclepro.2018.05.224 google scholar 
  • PBS. (2021). Pakistan Social and Living Standards Measurement Survey 2019-2020. Pakistan Bureau of Statistics, Statistics Division, Government of Pakistan. google scholar 
  • Prasad, N. G. N., & Rao, J. N. K. (1990). Estimation of the Mean Squared Error of Small Area Estimators. Journal of the American Statistical Association, 85(409), 163–171. https://doi.org/10.1080/01621459.1990.10475320 google scholar 
  • Qureshi, S., & Arif, G. (2001). Profile of Poverty in Pakistan, 1998-99 (Working Paper No. 2001:05; MIMAP Technical Paper Series). Pakistan Institute of Development Economics. google scholar 
  • Said, F., Musaddiq, T., Mahmud, M. (2011). Macrolevel Determinants of Poverty: Investigation Through Poverty Mapping of Districts of Pakistan. Pakistan Development Review, 50(4 Part II), 895–911. google scholar 
  • Salahuddin, T., Zaman, A. (2012). Multidimensional Poverty Measurement in Pakistan: Time Series Trends and Breakdown. The Pakistan Development Review, 51(4), 493–504. google scholar 
  • Sandhu, R. S. (2000). Housing poverty in urban India. Social Change, 30(1–2), 114–129. doi: 10.1177/004908570003000208 google scholar 
  • Shabnam, N., Ameer, W., Aurangzeb, N., Ashraf, M. A., & Shah, S. H. (2023). Estimation of poverty bounds for Pakistan using synthetic panel data. PLOS ONE, 18(3), e0276673. doi: 10.1371/journal.pone.0276673 google scholar 
  • Shifat, Z. F., Alam, M. J., Begum, I. A., Iqbal, M. A., Sarma, P. K., & McKenzie, A. M. (2025). The association between household asset ownership and food security: Panel data evidence from Bangladesh. Frontiers in Sustainable Food Systems, 8, 1479410. https://doi.org/10.3389/fsufs.2024.1479410 google scholar 
  • Sial, M. H., Noreen, A., & Awan, R. U. (2015). Measuring Multidimensional Poverty and Inequality in Pakistan. The Pakistan Development Review, 54(4), 685–698. google scholar 
  • Sinha, A. (2017). Assessing latrine use in low-income countries: A field study in rural India. doi: 10.17037/PUBS.03449896. google scholar 
  • Subbaraman, R., Nolan, L., Sawant, K., Shitole, S., Shitole, T., Nanarkar, M., Patil-Deshmukh, A., & Bloom, D. E. (2015). Multidimensional measurement of household water poverty in a Mumbai Slum: Looking Beyond Water Quality. PLOS ONE, 10(7), e0133241. https://doi.org/10.1371/journal.pone.0133241 google scholar 
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Estimating Tehsil’s Poverty Ranking in the Province of Punjab from District-Level Survey Data Using Regression Synthetic Estimation

Yıl 2025, Cilt: 75 Sayı: 2, 475 - 497, 15.01.2026
https://doi.org/10.26650/ISTJECON2025-1736468
https://izlik.org/JA94SW37WA

Öz

Limited number of observations hamper poverty estimation in smaller areas, rendering national surveys nonrepresentative. National surveys in Pakistan lack adequate sample sizes to generate statistically valid estimates at levels beyond the division and district (i.e., tehsil). This research employs regression synthetic estimation, a small area estimation technique. Poverty in Punjab’s tehsils is estimated using per-adult-equivalent consumption, auxiliary variables derived from national surveys, and census data. Econometric model generates best linear unbiased estimates of per-adult-equivalent consumption at the Tehsil level, providing a spatial view of poverty through the rankings of Tehsils. Empirical results of this research indicate significant inter- and intra-district disparities. This research lifts the veil on the district and shows that peripheral Tehsils are highly impoverished. Findings from this research provide a basis for spatially balanced regional development and support investments in areas outside district headquarters and rural economic development.

Kaynakça

  • Agyemang, F. S. K., Memon, R., Wolf, L. J., & Fox, S. (2023). High-resolution rural poverty mapping in Pakistan with ensemble deep learning. PLOS ONE, 18(4), e0283938. https://doi.org/10.1371/journal.pone.0283938 google scholar 
  • Ahmed, S. (2025). Some new strategies for estimating area-level parameters using information from successive surveys. Quality & Quantity, 59(1), 411–455. https://doi.org/10.1007/s11135-024-01942-6 google scholar 
  • Allen, B., Bourke, M., Datt, G., Gibson, J., Hwang, V., Parajuli, D. (2005). Mapping Poverty in Rural Papua New Guinea. Pacific Economic Bulletin, 20(1), 1–26. doi: 10.1111/j.1467-8373.2005.00274.x google scholar 
  • Arif G. M., Nazli H., & Haq R. (2000). Rural non-agriculture employment and poverty in Pakistan. The Pakistan Development Review, 39(4), 1089–1110. [suspicious link removed] google scholar 
  • Arouri, M., Ben Youssef, A., & Nguyen, C. (2017). Does urbanisation reduce rural poverty? Evidence from Vietnam. Economic Modelling, 60, 253–270. https://doi.org/10.1016/j.econmod.2016.09.022. google scholar 
  • Asian Development Bank. (2020). Introduction to Small Area Estimation Techniques: A Practical Guide for National Statistics Offices (0 ed.). Asian Development Bank. doi: 10.22617/TIM200160-2 google scholar 
  • Awan, M. S., & Iqbal, N. (2010). Determinants of Urban Poverty: The Case of Medium Sized City in Pakistan. PIDE-Working Papers, 2010:60. https://ideas.repec.org//p/pid/wpaper/201060.html google scholar 
  • Awan, S., M., Waqas, M., & Aslam, M. (2015). Multidimensional measurement of poverty in Pakistan: Provincial analysis. Nóesis. Revista de Ciencias Sociales y Humanidades, 24(48), 55–72. https://doi.org/10.20983/noesis.2015.2.2 google scholar 
  • Awan, M. S., Waqas, M., & Aslam, M. A. (2011). Multidimensional Poverty in Pakistan: The Case of Punjab Province [MPRA Paper]. google scholar 
  • Balamurali, A., Janflone, J., & Zhu, E. (2015, November 1). Impact of Education on Poverty. google scholar 
  • Banerjee, A. V., & Duflo, E. (2012). Poor economics: A radical rethinking of the way to fight global poverty (Paperback ed.). PublicAffairs. google scholar 
  • Bartram, L., Roe, B. (2005). Dependency ratios: Useful policy‐making tools? Geriatrics & Gerontology International, 5(4), 224–228. https://doi.org/10.1111/j.1447-0594.2005.00311.x google scholar 
  • Bata T., & Sinnathurai V. (2013). An Empirical Study on the Nexus of Poverty, GDP Growth, Dependency Ratio, and Employment in Developing Countries. Journal of Competitiveness, 5(2), 67–82. https://doi.org/10.7441/joc.2013.02.05 google scholar 
  • Briones, K. J., Lopez, J., Elumbre, R. J., & Angangco, T. M. (2021). Income, consumption, and poverty measurement in the Philippines. MPRA Paper, Article 106025. google scholar 
  • Cheema, A., Khalid, L., Patnam, M. (2008). The geography of poverty: Evidence from Punjab. Lahore Journal of Economics, 13(Special Edition), 163–188. https://doi.org/10.35536/lje.2008.v13.isp.a10 google scholar 
  • Christiaensen, L., & Shorrocks, A. (2012). Measure poverty over time. The Journal of Economic Inequality, 10(2), 137–143. https://doi.org/10.1007/s10888-012-9225-4 google scholar 
  • Corral, P., Molina, I., Cojocaru, A., & Segovia, S. (2022). Guidelines for Small Area Estimation for Poverty Mapping. World Bank. google scholar 
  • Crull, S. R. (1996). Housing Inadequacy and Satisfaction of Black and White Households in Poverty. Housing and Society, 23(2), 1–14. doi: 10.1080/08882746.1996.11430238 google scholar 
  • Denny, K. (2002). New Methods for Comparing Literacy Across Populations: Insights from Measurement of Poverty. Journal of the Royal Statistical Society Series A: Statistics in Society, 165(3), 481–493. https://doi.org/10.1111/1467-985X.00249 google scholar 
  • Deo, S., Sane, A., Sharma, S., & Tabar, S. (2024). Economic dependency ratio as a dimension of poverty and vulnerability. In R. Goel, T. Singh, Md. M. Rahman, Q. T. Islam, & S. K. Baral (Eds.), Understanding the Multi-Dimensional Nature of Poverty (pp. 109–130). Emerald Publishing Limited. https://doi.org/10.1108/978-1-83753-292-620241006 google scholar 
  • Dodge, Y. (2010). The concise encyclopaedia of statistics (Updated ed.). Springer. google scholar 
  • European Commission. (2017). Statistical matching of European Union statistics on income and living conditions (EU-SILC) and the household budget survey. Publications Office. google scholar 
  • Farooq, H. U., Nazar, M. J., Hanif, M. S., & Faisal, A. (2024, July 27). Using Satellite Imagery to Map Poverty-Struck Areas in Pakistan Using Neural Networks. EasyChair Preprint. google scholar 
  • Fiadzo, E., Houston, J., & Godwin, D. (2001). Estimating housing quality for poverty and development policy analysis: CWIQ in Ghana. Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, 53(2), 137–162. https://doi.org/10.1023/A:1026764711406 google scholar 
  • Gine-Garriga, R., Perez-Foguet, A. (2018). Measuring Sanitation Poverty: A Multidimensional Measure to Assess the Delivery of Sanitation and Hygiene Services at the Household Level. OPHI Working Papers, Article 116. google scholar 
  • Gine‐Garriga, R., & Pérez‐Foguet, A. (2019). Monitoring and targeting the sanitation poor: A multidimensional approach. Natural Resources Forum, 43(2), 82–94. https://doi.org/10.1111/1477-8947.12171 google scholar 
  • Glaeser, E. L., Kahn, M. E., & Rappaport, J. (2000). Why Do the Poor Live in Cities? (SSRN Scholarly Paper No. 228112). Social Science Research Network. google scholar 
  • Hameed, A., Padda, I. U. H., Karim, S. (2016). Multidimensional Poverty Mapping for Rural Pakistan. SSRN Electronic Journal. doi: 10.2139/ssrn.3149119 google scholar 
  • Haughton, J., Khandker, S. R. (2012). Handbook on Poverty and Inequality. World Bank. google scholar 
  • Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic regression (2. ed., [Nachdr.]). Wiley. google scholar 
  • Jamal, H. (2007). Income Poverty at the District Level: Application of the Small Area Estimation Technique (No. 70). Social Policy and Development Centre. google scholar 
  • Javed, Z., Asif, A. (2011). Female households and poverty: A case study of Faisalabad District. google scholar 
  • Khan, A. U., Saboor, A., Hussain, A., Sadiq, S., Mohsin, A. Q. (2014). Investigating Multidimensional Poverty across Regions in the Sindh Province of Pakistan. Social Indicators Research, 119(2), 515–532. https://doi.org/10.1007/s11205-013-0511-8 google scholar 
  • Khan, M., Saboor, A., Rizwan, M., & Ahmad, T. (2020). An empirical analysis of monetary and multidimensional poverty: Evidence from a household survey in Pakistan. Asia Pacific Journal of Social Work and Development, 30(2), 106–121. https://doi.org/10.1080/02185385.2020.1712663 google scholar 
  • Lanjouw, P., & Ravallion, M. (1995). Poverty and household size. The Economic Journal, 105(433), 1415. https://doi.org/10.2307/2235108 google scholar 
  • Lemanski, C. (2011). Moving up the ladder or stuck on the bottom row? Homeownership as a solution to poverty in urban South Africa: Homeownership as a solution to poverty in South Africa? International Journal of Urban and Regional Research, 35(1), 57–77. https://doi.org/10.1111/j.1468-2427.2010.00945.x google scholar 
  • Lipton, M. (1984). Demography and poverty (Working Paper No. 623; World Bank Staff Working Papers). google scholar 
  • Majoka, Z., Wieser, C., Qazi, M., Fonseca, D. G., Sohnesen, T. P., & Khan, I. (2024). Mind the Gap: Assessing Pakistan’s National Socioeconomic Registry (Report No. 194522). World Bank. google scholar 
  • Meenakshi, J. V., Ray, R. (2002). Impact of household size and family composition on poverty in rural India. Journal of Policy Modelling, 24(6), 539–559. https://doi.org/10.1016/S0161-8938(02)00129-1 google scholar 
  • Meyer, B. D., & Sullivan, J. X. (2003). Measuring the Well-Being of the Poor Using Income and Consumption. The Journal of Human Resources, 38, 1180. doi: 10.2307/3558985 google scholar 
  • Mihai, M., Ţiţan, E., Manea, D. (2015). Education and Poverty Procedia Economics and Finance, 32, 855–860. https://doi.org/10.1016/S2212-5671(15)01532-4 google scholar 
  • Najam, Z. (2021). The sensitivity of poverty trends to dimensionality and distribution sensitivity in poverty measures—District level analysis for Pakistan. Poverty and Public Policy, 13(4), 368–411. https://doi.org/10.1002/pop4.323 google scholar 
  • Naveed, A., Ghaus, M. U. (2018). Geography ofPoverty Update: Multidimensional poverty in Pakistan at the national, provincial and district levels—2014-15. Pakistan Poverty Alleviation Fund. google scholar 
  • Naveed, A., & Islam, T. (2010). Estimating Multidimensional Poverty and Identifying the Poor in Pakistan: An Alternative Approach (Working Paper No. Recoup Working Paper 28; Research Consortium on Education Outcomes and Poverty). University of Cambridge. google scholar 
  • Orbeta, A. J. C. (2005). Poverty, vulnerability, and family size: Evidence from the Philippines. Discussion Papers, Article DP 2005-19. google scholar 
  • Padda, I. U. H., Hameed, A. (2018). Estimating multidimensional poverty levels in rural Pakistan: A contribution to sustainable development policies. Journal of Cleaner Production, 197, 435–442. https://doi.org/10.1016/j.jclepro.2018.05.224 google scholar 
  • PBS. (2021). Pakistan Social and Living Standards Measurement Survey 2019-2020. Pakistan Bureau of Statistics, Statistics Division, Government of Pakistan. google scholar 
  • Prasad, N. G. N., & Rao, J. N. K. (1990). Estimation of the Mean Squared Error of Small Area Estimators. Journal of the American Statistical Association, 85(409), 163–171. https://doi.org/10.1080/01621459.1990.10475320 google scholar 
  • Qureshi, S., & Arif, G. (2001). Profile of Poverty in Pakistan, 1998-99 (Working Paper No. 2001:05; MIMAP Technical Paper Series). Pakistan Institute of Development Economics. google scholar 
  • Said, F., Musaddiq, T., Mahmud, M. (2011). Macrolevel Determinants of Poverty: Investigation Through Poverty Mapping of Districts of Pakistan. Pakistan Development Review, 50(4 Part II), 895–911. google scholar 
  • Salahuddin, T., Zaman, A. (2012). Multidimensional Poverty Measurement in Pakistan: Time Series Trends and Breakdown. The Pakistan Development Review, 51(4), 493–504. google scholar 
  • Sandhu, R. S. (2000). Housing poverty in urban India. Social Change, 30(1–2), 114–129. doi: 10.1177/004908570003000208 google scholar 
  • Shabnam, N., Ameer, W., Aurangzeb, N., Ashraf, M. A., & Shah, S. H. (2023). Estimation of poverty bounds for Pakistan using synthetic panel data. PLOS ONE, 18(3), e0276673. doi: 10.1371/journal.pone.0276673 google scholar 
  • Shifat, Z. F., Alam, M. J., Begum, I. A., Iqbal, M. A., Sarma, P. K., & McKenzie, A. M. (2025). The association between household asset ownership and food security: Panel data evidence from Bangladesh. Frontiers in Sustainable Food Systems, 8, 1479410. https://doi.org/10.3389/fsufs.2024.1479410 google scholar 
  • Sial, M. H., Noreen, A., & Awan, R. U. (2015). Measuring Multidimensional Poverty and Inequality in Pakistan. The Pakistan Development Review, 54(4), 685–698. google scholar 
  • Sinha, A. (2017). Assessing latrine use in low-income countries: A field study in rural India. doi: 10.17037/PUBS.03449896. google scholar 
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Toplam 63 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Ekonomi Teorisi (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Khurram Afzal Malik 0009-0007-5175-9120

Farrukh Mahmood 0000-0002-9100-2786

Gönderilme Tarihi 7 Temmuz 2025
Kabul Tarihi 12 Aralık 2025
Yayımlanma Tarihi 15 Ocak 2026
DOI https://doi.org/10.26650/ISTJECON2025-1736468
IZ https://izlik.org/JA94SW37WA
Yayımlandığı Sayı Yıl 2025 Cilt: 75 Sayı: 2

Kaynak Göster

APA Afzal Malik, K., & Mahmood, F. (2026). Estimating Tehsil’s Poverty Ranking in the Province of Punjab from District-Level Survey Data Using Regression Synthetic Estimation. İstanbul İktisat Dergisi, 75(2), 475-497. https://doi.org/10.26650/ISTJECON2025-1736468
AMA 1.Afzal Malik K, Mahmood F. Estimating Tehsil’s Poverty Ranking in the Province of Punjab from District-Level Survey Data Using Regression Synthetic Estimation. İstanbul İktisat Dergisi. 2026;75(2):475-497. doi:10.26650/ISTJECON2025-1736468
Chicago Afzal Malik, Khurram, ve Farrukh Mahmood. 2026. “Estimating Tehsil’s Poverty Ranking in the Province of Punjab from District-Level Survey Data Using Regression Synthetic Estimation”. İstanbul İktisat Dergisi 75 (2): 475-97. https://doi.org/10.26650/ISTJECON2025-1736468.
EndNote Afzal Malik K, Mahmood F (01 Ocak 2026) Estimating Tehsil’s Poverty Ranking in the Province of Punjab from District-Level Survey Data Using Regression Synthetic Estimation. İstanbul İktisat Dergisi 75 2 475–497.
IEEE [1]K. Afzal Malik ve F. Mahmood, “Estimating Tehsil’s Poverty Ranking in the Province of Punjab from District-Level Survey Data Using Regression Synthetic Estimation”, İstanbul İktisat Dergisi, c. 75, sy 2, ss. 475–497, Oca. 2026, doi: 10.26650/ISTJECON2025-1736468.
ISNAD Afzal Malik, Khurram - Mahmood, Farrukh. “Estimating Tehsil’s Poverty Ranking in the Province of Punjab from District-Level Survey Data Using Regression Synthetic Estimation”. İstanbul İktisat Dergisi 75/2 (01 Ocak 2026): 475-497. https://doi.org/10.26650/ISTJECON2025-1736468.
JAMA 1.Afzal Malik K, Mahmood F. Estimating Tehsil’s Poverty Ranking in the Province of Punjab from District-Level Survey Data Using Regression Synthetic Estimation. İstanbul İktisat Dergisi. 2026;75:475–497.
MLA Afzal Malik, Khurram, ve Farrukh Mahmood. “Estimating Tehsil’s Poverty Ranking in the Province of Punjab from District-Level Survey Data Using Regression Synthetic Estimation”. İstanbul İktisat Dergisi, c. 75, sy 2, Ocak 2026, ss. 475-97, doi:10.26650/ISTJECON2025-1736468.
Vancouver 1.Afzal Malik K, Mahmood F. Estimating Tehsil’s Poverty Ranking in the Province of Punjab from District-Level Survey Data Using Regression Synthetic Estimation. İstanbul İktisat Dergisi [Internet]. 01 Ocak 2026;75(2):475-97. Erişim adresi: https://izlik.org/JA94SW37WA