Poverty Dynamics among Kenyan Refugees During COVID-19: A Heteroscedasticity Consistent Ordered Probit Model

Authors

  • Abayomi Oyekale North-West University

Abstract

COVID-19 remains an income shock of significant economic consequence to many households across the world. The situation among refugees can be pathetic due to their inherent economic deprivations and vulnerability to income shocks. This paper analyzed the dynamics of poverty among refugees in Kenya during the COVID-19 pandemic and determined their correlates.  The data were the first five waves of the were the COVID-19 Rapid Response Phone Surveys that were conducted among refugees. The data were analysed with heteroscedasticity consistent Ordered Probit model. The results showed that with only 8.14% never entering poverty within the survey periods, majority of the refugees were transiently (46.27%) and chronically (45.59%) poor. The error variance differed across household sizes, and heteroscedasticity properly corrected. Movement from never being poor to chronic poverty was significantly promoted by urban residence, household size, educational levels, and camp of residence (Kakuma, Dadaab and Kalobeyei), while asset disposal income, amount of credit, remittance, and other gifts reduced it. It was concluded that efforts to reduce poverty vulnerability among refugees should among others address maternal fertility and promotion of policies to allow formally educated refugees to be gainfully engaged in the Kenyan labour markets.  

References

African Union. List of Countries Which Have Signed, Ratified/Acceded To The African Union Convention for the Protection and Assistance of Internally Displaced Persons in Africa (Kampala Convention). 18 June 2020.

Alkire, S., & Foster, J. (2011). Counting and multidimensional poverty measurement. Journal of Public Economics, 95(7-8), 476-487.

Alkire, S., Santos, M.E. A Multidimensional Approach: Poverty Measurement & Beyond. Soc Indic Res 112, 239–257 (2013). https://doi.org/10.1007/s11205-013-0257-3

Altindag, O., O'Connell, S. D., Sasmaz, A., Balcioglu, Z., Cadoni, P., Jerneck, M., & Foong, A. K. (2020). Targeting humanitarian aid using administrative data: Model design and validation. SSRN Electronic Journal.https://doi.org/10.2139/ssrn.3444974

Alvarez, R. M., and J. Brehm. 1995. American ambivalence towards abortion policy: Development of a heteroskedastic probit model of competing values. American Journal of Political Science 39: 1055–1082. https://doi.org/10.2307/2111669.

Ambani B. Kenyans Choke Under Rising Cost of Basic Goods, Services. 20 July 2021. Available online: https://allafrica.com/stories/202107200672.html (Accessed on 11 July 2022).

Amirthalingam, K., and R. Lakshman. 2012. “Impact of Displacement on Women and Femaleheaded Households: A Mixed Method Analysis with a Microeconomic Touch.” Journal of Refugee Studies 26 (1): 26‐46.

Anonymous (undated). Kenya’s Refugee Act 2021: Opportunities for Refugee Livelihoods and Self-Reliance, Part 1. Available online: https://www.hias.org/sites/default/files/kenyas_refugee_act_2021-_opportunities_for_refugee_livelihoods_and_self-reliance_-final_draft31.pdf (Accessed on 27 October 2022).

Arapi-Gjini, A., Möllers, J. & Herzfeld T. (2020), Measuring Dynamic Effects of Remittances on Poverty and Inequality with Evidence from Kosovo, Eastern European Economics, 58:4, 283-308, DOI: 10.1080/00128775.2020.1720517

Azami H. (2021). Contrasting monetary and non-monetary measures of poverty in developing countries: a survey. Available online: https://doi.org/10.21203/rs.3.rs-537501/v1 (Accessed on 14 July 2022).

Azeem, M. M., Mugera, A. W., & Schilizzi, S. (2018). Vulnerability to Multi-Dimensional Poverty: An Empirical Comparison of Alternative Measurement Approaches. Journal of Development Studies, 54(9), 1612–1636.

Barletta G., Castigo F, Egger E-M, Keller M., Salvucci V, Tarp F. The impact of COVID-19 on consumption povertyin Mozambique. Journal of International Development, 2022;34:771–802.

Barnes, M., Conolly, A. and Tomaszewski, W. (2008). The circumstances of persistently poor families with children: Evidenfrom the Families and Children Study (FACS). Department for Work and Pensions (Working Paper No. 487).

Beltramo T. and Pape U. (2021). After three decades, how are refugees in Kenya’s Kakuma refugee camp faring? Apr 19, 2021. Available online: https://www.unhcr.org/blogs/after-three-decades-how-are-refugees-in-kenyas-kakuma-refugee-camp-faring/ (Accessed 4 July, 2022).

Bogale, A. (2012). Vulnerability of smallholder rural households to food insecurity in Eastern Ethiopia. Food Security, 4(4), 581–591.

Bollinger CR and Hagstrom P. (2004). Poverty Rates of Refugees and Immigrants. UKCPR Discussion Paper Series #2004-06, December 2004. Available online: http://www.ukcpr.org/Publications/DP2004-06.pdf (Accessed on 16 July 2022).

Boza-Kiss, B., Pachauri, S., & Zimm, C. Deprivations and Inequities in Cities Viewed Through a Pandemic Lens. Front. Sustain. Cities, 19 March 2021 Sec. Urban Energy End-Use

https://doi.org/10.3389/frsc.2021.645914

Brown, R. and R. Moffitt (1982), ‘The Effect of Ignoring Heteroscedasticity on Estimates of the Tobit Model’, Mimeo, University of Maryland, Department of Economics, June 1982.

Calvo, C., & Dercon, S. (2013). Vulnerability to individual and aggregate poverty. Social Choice and Welfare, 41(4), 721-740.

Carter, M. R. (2007). Learning from asset-based approaches to poverty. In reducing global poverty: The case of asset accumulation. ed. Caroline O. N. Moses, 51-61. Washington, DC: Brookings Institutions.

Carter, M. R. and Barrett, C. B. (2006). The economics of poverty traps and persistent poverty: An asset-based approach. Journal of Development Studies, 42(2): 178-199.

Chaaban, J., Ghattas, H., Salti, N., Moussa, W., Irani, A., Jamaluddine, Z., & Al Mokdad, R. (2020). MultiPurpose Cash Assistance in Lebanon: Impact Evaluation on the Well-Being of Syrian Refugees. Retrieved from https://www.aub.edu.lb/fafs/agri/aedrg/Pages/Impactevaluation.aspx

Charlier, D.; Legendre, B.; Risch, A. Fuel poverty in residential housing: Providing financial support versus combatting substandard housing. Appl. Econ. 2019, 51, 5369–5387

Chaudhuri, S., Jalan, J., & Suryahadi, A. (2002). Assessing household vulnerability to poverty from cross-sectional data: A methodology and estimates from Indonesia. Columbia University Department of Economics Working Papers Series #0102-52. New York, NY: Columbia University Department of Economics. https://academiccommons.columbia.edu/ doi/10.7916/D85149GF

Chen, K. & Feng, C. (2022). Linking Housing Conditions and Energy Poverty: From a Perspective of Household Energy Self-Restriction. Int. J. Environ. Res. Public Health, 19, 8254. https://doi.org/10.3390/ijerph19148254

Coley RL, Leventhal T, Lynch AD, Kull M. Relations between housing characteristics and the well-being of low-income children and adolescents. Dev Psychol. 2013 Sep;49(9):1775-89. doi: 10.1037/a0031033.

Delloitte. Kenya Tax Alert - Government response to COVID-19. March 2020. Available online: https://www2.deloitte.com/content/dam/Deloitte/ke/Documents/tax/Tax_Alert_COVID19_Government_Measures.pdf (Accessed on 11 July 2022).

Doss, C., Oduro, A.D., Deere, C.D., Swaminathan, H., Baah-Boateng, W. & Suchitra J.Y. (2015). Shocks, Assets and Social Protection: A Gendered Analysis of Ecuador, Ghana and Karnataka, India. Available online: https://www.unwomen.org/sites/default/files/Headquarters/Attachments/Sections/Library/Publications/2015/DiscussionPaper-ShocksAssetsAndSocialProtection-AGenderedAnalysis-en.pdf (accessed 28 October 2022).

Emad Abd Elmessih Shehata, 2011. "TOBITHETM: Stata module to estimate Tobit Multiplicative Heteroscedasticity Regression," Statistical Software Components S457323, Boston College Department of Economics, revised 14 Nov 2011.

Feeny, S., & McDonald, L. (2016). Vulnerability to multidimensional poverty: Findings from households in Melanesia. Journal of Development Studies, 52(3), 447–464.

Gaiha, R., & Imai, K. (2008). Measuring Vulnerability and Poverty Estimates for Rural India. In WIDER Research Paper, No. 2008/40. Helsinki, Finland: The United Nations University (UNU) and World Institute for Development Economics Research (UNU-WIDER). https://www.econstor.eu/bitstream/10419/45160/1/575630159.pdf

Gruenewald PJ, Mair C, Wang-Schweig M (2016) Sources of misspecification bias in assessments of risks related to alcohol use. Journal of Studies on Alcohol and Drugs, 77(5), 802–810

Hanmer L, Arango DJ, Julieth ER. How does poverty differ among refugees? Taking a gender lens to the data on Syrian refugees in Jordan. Policy Research Working Paper 8616. Available online: https://openknowledge.worldbank.org/bitstream/handle/10986/30586/WPS8616.pdf?sequence=1&isAllowed=y (Accessed on 18 July 2022).

Harvey, A. C. 1976. Estimating regression models with multiplicative heteroscedasticity. Econometrica 44: 461–465. https://doi.org/10.2307/1913974.

HM Government. An evidence review of the drivers of child poverty for families in poverty now and for poor children growing up to be poor adults. Available online: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/285389/Cm_8781_Child_Poverty_Evidence_Review_Print.pdf (Accessed 9 July 2022).

International Labour Organization (2021). Towards decent work for young refugees and host communities in the digital platform economy in Africa Kenya, Uganda, Egypt. Available online: https://www.ilo.org/wcmsp5/groups/public/---ed_emp/documents/publication/wcms_816539.pdf (accessed on 26 October 2022).

Irungu I. The Drivers of Inflation During the COVID-19 Pandemic The drivers of inflation during the COVID-19 pandemic period resulted from demand-pull inflation, cost-push inflation and money supply. October 9 2020. Available online: https://www.theelephant.info/data-stories/2020/10/09/the-drivers-of-inflation-during-the-covid-19-pandemic/ (Accessed on 11 July 2022).

Jones, N., Pincock, K., Guglielmi, S., Baird, S., Tapia, I.S., Oakley, E., Seager, J. (2022) Barriers to Refugee Adolescents' Educational Access during COVID-19: Exploring the Roles of Gender, Displacement, and Social Inequalities. Journal on Education in Emergencies 8:2, pages 44.

Lacovou, M. and Berthoud, R. (2006). The economic position of large families. Department for Work and Pensions (Research Report 358).

Ligon, E., & Schechter, L. (2003). Measuring vulnerability. The Economic Journal, 113(486), C95- C102

Lyons, Angela and Kass-Hanna, Josephine and Montoya Castano, Alejandro, A Multidimensional Approach to Measuring Vulnerability to Poverty of Syrian Refugees in Lebanon (April 1, 2021). Economic Research Forum Working Paper No. 1472 , Available at SSRN: https://ssrn.com/abstract=3787795 or http://dx.doi.org/10.2139/ssrn.3787795

McKay, A. (2009). Assets and chronic poverty: Background paper. Working Paper No. 100. Chronic Poverty Research Centre. University of Sussex, Brighton, UK.

McLean M. The Impact of COVID-19 On Poverty in Kenya. 25 June 2021. Available online: https://borgenproject.org/the-impact-of-covid-19-on-poverty-in-kenya/ (Accessed 8 July 2022).

McPeak, J., P. Little and C. Doss. 2012. Risk and Social Change in an African Rural Economy. London: Routledge.

Mekasha, T.J. & Tarp, F. (2021). Poverty, vulnerability andCovid- 19: Introduction and overview. Review of Development Economics, 25, 1838– 1858.

Mixed Migration Centre (2021). The impact of COVID-19 on refugees and migrants on the move in North and West Africa. Available online: www. mixedmigration.org (Accessed on 10 July 2022).

Morrison, C.; Shortt, N. Fuel poverty in Scotland: Refining spatial resolution in the Scottish Fuel Poverty Indicator using a GIS-based multiple risk index. Health Place 2008, 14, 702–717.

Ozughalu, U. M. (2016). Relationship between household food poverty and vulnerability to food poverty: Evidence from Nigeria. Social Indicators Research, 125(2), 567–587.

Prianto Budi Saptono, Gustofan Mahmud, Li-Fen Lei. (2022) Do international remittances promote poverty alleviation? Evidence from low- and middle-income countries. IZA Journal of Development and Migration 13:1.

Reardon, S. F., B. R. Shear, K. E. Castellano, and A. D. Ho. 2017. Using heteroskedastic ordered probit models to recover moments of continuous test score distributions from coarsened data. Journal of Educational and Behavioral Statistics 42: 3–45. https://doi.org/10.3102/1076998616666279.

Santamaria J., Hanmer, L, & Rubiano, L. (2021). The Impact of Protracted Displacement on Syrian Refugees in Jordan: The Evolution of Household Composition and Poverty Rates. Available online: https://doi.org/10.1596/1813-9450-10194

Smith, N. and Middleton, S. (2007). A Review of Poverty Dynamics Research in the UK. York: Joseph Rowntree Foundation.

STATA (undated). hetoprobit — Heteroskedastic ordered probit regression. Available online: https://www.stata.com/manuals/rhetoprobit.pdf (accessed on 16 October 2022).

UNHCR (2021a). Socio-economic impact of COVID-19 on refugees in Kenya - Panel - Anonymized for Licensed Use. Dataset downloaded from https://microdata.unhcr.org on (7th July 2022).

UNHCR (2021b). Microdata Library. Available online: https://microdata.unhcr.org/index.php/access_licensed/track/563 (Accessed 30 August 2021).

UNHCR (2021c). Kenya - Socio-economic impact of COVID-19 on refugees - Round 5, 2021 UNHCR Report generated on: July 27, 2021. Available online: https://microdata.unhcr.org/index.php

UNHCR and World Bank (undated a). Understanding the Socioeconomic Conditions of Refugees in Kakuma Camp, Kenya. Available online: https://www.unhcr.org/603904d14.pdf (Accessed 9 July 2022).

UNHCR and World Bank (Undated b). Understanding the Socioeconomic Conditions of Refugees in Kenya Volume B: Kakuma Camp - Results from the 2019 Kakuma Socioeconomic Survey. 2021. Available online: https://reliefweb.int/attachments/c449f5de-0b31-3f09-a02e-93e8d09dab2f/Understanding-the-Socio-Economic-Conditions-of-Refugees-in-Kenya-Volume-B-Kakuma-Camp-Results-from-the-2019-Kakuma-Socioeconomic-Survey.pdf (Accessed on 11 July 2022).

UNHCR and World Bank (Undated c). Understanding the Socioeconomic Conditions of Refugees in Kenya Volume A: Kalobeyei Settlement Results from the 2018 Kalobeyei Socioeconomic Survey. Available online: https://microdata.unhcr.org/index.php/catalog/232/download/1162 (Accessed 9 July 2022).

UNHCR. Joint statement by the Government of Kenya and the United Nations High Commissioner for Refugees: Dadaab and Kakuma Refugee Camps Roadmap. 29 April, 2021. Available online: https://www.unhcr.org/news/press/2021/4/608af0754/joint-statement-government-kenya-united-nations-high-commissioner-refugees.html (Accessed on 10 July 2022).

United Nations (2020). Policy Brief : COVID-19 in an Urban World. United Nations. Available online at: https://www.un.org/sites/un2.un.org/files/sg_policy_brief_covid_urban_world_july_2020.pdf (accessed December 21, 2020).

United Nations High Commission for Refugees (UNHCR): Global displacement hits another record, capping decade-long rising trend. 16 June 2022. Available online: https://www.unhcr.org/news/press/2022/6/62a9d2b04/unhcr-global-displacement-hits-record-capping-decade-long-rising-trend.html (Accessed on 16 July 2022).

United Nations. A Pandemic of Exclusion The impact of COVID-19 on the human rights of migrants in Libya, August 2021. Available online: https://www.ohchr.org/sites/default/files/Documents/Issues/Migration/A_pandemic_of_exclusion.pdf (Accessed on 10 July 2022).

Vegeris, S. and Perry, J. (2003). Families and Children 2001: Living Standards and the Children. Department for Work and Pensions (Research Report No. 190).

Verme, P., & Gigliarano, C. (2019). Optimal targeting under budget constraints in a humanitarian context. World Development, 119, 224-233.

Verme, P., Gigliarano, C., Wieser, C., Hedlund, K., Petzoldt, M., & Santacroce, M. (2016). The welfare of Syrian refugees: Evidence from Jordan and Lebanon. Washington, D.C.: The World Bank. https://openknowledge.worldbank.org/bitstream/handle/ 10986/23228/9781464807701.pdf?sequeb

Wagstaff, A. and M. Lindelow. 2013. “Are Health Shocks Different? Evidence from a Multishock Survey in Laos.” Health Economics (published online June 2013).

Wang, X. (2022). On the Relationship Between Income Poverty and Multidimensional Poverty in China. In: Multidimensional Poverty Measurement. International Research on Poverty Reduction. Springer, Singapore. https://doi.org/10.1007/978-981-19-1189-7_5.

Wang, X., Feng, H., Xia, Q., and Alkire, S. (2016). “On the relationship between Income Poverty and Multidimensional Poverty in China.” OPHI Working Paper 101, University of Oxford.

Warah R. COVID-19 only heightened Kenya’s existing economic problem. 10 February 2022. Available online: https://www.one.org/africa/blog/covid19-kenya-economy-inflation/ (Accessed on 11 July 2022).

Williams, R. 2010. Fitting heterogeneous choice models with oglm. Stata Journal 10: 540–567.

World Bank (2017). Forcibly displaced: towards a development approach supporting refugees, the internally displaced and their hosts. Washington DC: World Bank.

World Bank (2021). Kenya’s Economy is Showing Resilience as Output Rises Above Pre-Pandemic Levels Driven by a Rebound in the Services Sector. December 14, 2021. Available online: https://www.worldbank.org/en/news/press-release/2021/12/14/kenya-s-economy-is-showing-resilience-as-output-rises-above-pre-pandemic-levels-driven-by-a-rebound-in-the-services-sect (Accessed on 11 July 2022).

World Bank (2022). Monitoring COVID-19 Impact on Households in Kenya. June 9, 2022. Available online: https://www.worldbank.org/en/country/kenya/brief/monitoring-covid-19-impact-on-households-and-firms-in-kenya (Accessed 7 July 2022).

World Bank (undated) Kenya. Poverty & Equity Brief, 2020. Available online: https://databank.worldbank.org/data/download/poverty/33EF03BB-9722-4AE2-ABC7-AA2972D68AFE/Global_POVEQ_KEN.pdf (Accessed 22 June, 2022).

World Bank. (2020). Poverty and shared prosperity 2020: Reversals of fortune. World Bank. https://www.worldbank.org/en/publication/poverty-and-shared-prosperity (accessed April 2021), https://doi.org/10.1596/978-1-4648-1602-4

Yonzan N, Cojocaru A, Lakner C, Mahler DG, Narayan A. The impact of COVID-19 on poverty and inequality: Evidence from phone surveys. January 18, 2022. Available online: https://blogs.worldbank.org/opendata/impact-covid-19-poverty-and-inequality-evidence-phone-surveys (Accessed 9 July 2022).

Downloads

Published

2022-12-30

How to Cite

Oyekale, A. (2022). Poverty Dynamics among Kenyan Refugees During COVID-19: A Heteroscedasticity Consistent Ordered Probit Model . Acta Universitatis Danubius. Œconomica, 18(6). Retrieved from https://dj.univ-danubius.ro/index.php/AUDOE/article/view/2024

Issue

Section

Economic Development, Technological Change, and Growth