SAMOD

SAMOD is a tax-benefit microsimulation model for South Africa and was developed primarily for use by Government.

History:

SAMOD was the first developing country model to use the EUROMOD software. Development of SAMOD started in 2007.

Current team members:

Southern African Social Policy Research Insights (UK) and Southern African Social Policy Research Institute (South Africa)

Former team members:

Centre for the Analysis of South African Social Policy, University of Oxford, UK

Status:

Maintained

Content accessibility:

• Private, access restricted
Notes: Apply for access to Dr Gemma Wright (email: info@saspri.org)

Data accessibility:

• Freely available for download
Notes: Living Conditions Survey (via Statistics South Africa); National Income Dynamics Study (via https://www.datafirst.uct.ac.za

Input data sources:

• Currently: Living Conditions Survey (LCS) 2014/15 and National Income Dynamics Study (NIDS) Wave 5

Model outputs:

• K. Wilkinson (2009) Adapting EUROMOD for use in a developing country - the case of South Africa and SAMOD. EUROMOD Working Paper No. EM5/09, Essex: University of Essex.
• Wright, G., Noble, M., Barnes, H., McLennan, D. and Mpike, M. (2016) SAMOD, a South African tax-benefit microsimulation model: recent developments. WIDER Working Paper No. 2016/115. UNU-WIDER: Helsinki, Finland.
• Wright, G., Barnes, H., Noble, M., McLennan, D. and Masekesa, F. (2018) Assessing the quality of the income data used in SAMOD, a South African tax-benefit microsimulation model. WIDER Working Paper No. 2018/173. UNU-WIDER: Helsinki, Finland.
• Income Distribution and the Potential of Redistributive Systems in Africa: A Decomposition Approach
• The effect of fiscal drag on income distribution and work incentives: A microsimulation analysis on selected African countries
• Barnes, H., G. Espi-Sanchis, M. Leibbrandt, D. McLennan, M. Noble, J. Pirttilä, W. Steyn, B. van Vrede, and G. Wright (2021). ‘Analysis of the distributional effects of COVID-19 and state-led remedial measures in South Africa’. International Journal of Microsimulation, 14(2): 2-31. DOI: 10.34196/IJM.00234
• Wright, G. and Mpike, M. (2021) ‘A South African Tax and Benefit Microsimulation Model’ in Department of Social Development Social Security Review 2021: Evolution of Social Security in South Africa – An Agenda for Action. Pretoria: Department of Social Development. Pages 92-97. ISBN:978-0-621-44817-7.
• Van den Heever, A., Chitiga-Mabugu, M., Devereux, S., Leibbrandt, M., Sachs, M., van Heerden, J. and Wright, G. (2021). Expert Panel on Basic Income Support Final Report: Report into the appropriateness and feasibility of a system of Basic Income Support for South Africa, Pretoria: Department of Social Development, Republic of South Africa.
• Van den Heever, A., Chitiga-Mabugu, M., Devereux, S., Leibbrandt, M., Sachs, M., van Heerden, J. and Wright, G. (2021). Expert Panel on Basic Income Support Executive Summary, Pretoria: Department of Social Development, Republic of South Africa.
• Steyn, W., A. Sithole, W. Ngobeni, E. Muwanga-Zake, H. Barnes, M. Noble, D. McLennan, G. Wright and K. Gasior (2021). ‘Simulating Personal Income Tax In South Africa Using Administrative Data And Survey Data: A Comparison Of Pitmod And Samod For Tax Year 2018’. WIDER Working Paper 2021/120. Helsinki: UNU-WIDER.
•  Barnes, H., G. Espi-Sanchis, M. Leibbrandt, D. McLennan, M. Noble, J. Pirttilä, W. Steyn, B. van Vrede, and G. Wright (2021). ‘Analysis of the distributional effects of COVID-19 and state-led remedial measures in South Africa’, WIDER Working Paper 2021/68. Helsinki: UNU-WIDER.
• Gcabo, R., Moche, B., Steyn, W., Moahlodi, B., Pirttila, J., Noble, M., Wright, G., Barnes, H. and Masekesa, F. (2019) Modelling value-added tax (VAT) in South Africa: Assessing the distributional impact of the recent increase in the VAT rate and options for redress through the benefits system.  WIDER Working Paper No. 2019/13. UNU-WIDER: Helsinki, Finland.
• Altman, M., Mokomane, Z. and Wright, G. (2014) ‘Social security for young people amidst high poverty and unemployment: some policy options for South Africa’, Development Southern Africa, 31(2), pp.347-362.

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