Simulating Distributional and Poverty Outcomes of the New Law on Social Welfare in Serbia Sonja Avlijaš (FREN, Belgrade) with Mihail Arandarenko, Saša.

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Presentation transcript:

Simulating Distributional and Poverty Outcomes of the New Law on Social Welfare in Serbia Sonja Avlijaš (FREN, Belgrade) with Mihail Arandarenko, Saša Ranđelović, Marko Vladisavljević and Jelena Žarković Rakić Brussels, December 2010

Presentation Outline Social welfare reform in Serbia Building SRMOD Results of microsimulations Concluding remarks

Social Welfare Reform in Serbia Poverty in Serbia increases during crisis New Draft Social Welfare Law intends to increase coverage and improve design of MOP Changes in MOP eligibility criteria and equivalence scale MOP eligibility criteria relaxed for large families, HHs from rural areas, single parents and HHs with all incapable of work Ex ante policy input on distributional and poverty effects of the Draft Law needed

SRMOD: Serbian tax-benefit microsimulation model Construction of SRMOD initiated in October 2009 by FREN Training provided by University of Essex (EUROMOD platform) Initiative came due to growing need for ex ante public policy analysis Relevant for current reform of social assistance and announced PIT reform Improving capacity to assess budgetary effects of tax and benefit policy options and their effects on distribution, inequality and poverty

Building SRMOD  2007 Living Standards Measurement Survey (LSMS) conducted by SORS and WB  2007 chosen as baseline policy year Simulated taxes and benefits: Personal Income Tax Social Security Contributions Unemployment benefit Social Assistance (MOP) Child Allowance Birth grant Maternity and child care salary compensation Caregiver allowance

SRMOD validation Formal and informal workers distinguished in LSMS Thus, simulated values for PIT and SSC not overestimated while informal earnings are included into disposable income 1,000 RSD take-up threshold Micro validation case-by-case Macro validation based on fiscal data and administrative records on benefit take up

Simulating changes to MOP rules New equivalence scale Increase in the max. number of eligible HH members from 5 to 6 Increased MOP payments for single parent HHs with one or two underage children Increased MOP payments for HHs in which all members are incapable to work Raising the ceiling on land ownership for HHs where all members are incapable to work from 0.5 to 1ha Accounting those in education from and those on maternity leave into incapable to work

Results: distributional impact of changes Simulation results suggest improved coverage and targeting of social assistance Theoretical increase in coverage: 22.1% or 12,000 HHs Fiscal exp. increase by 34.6% (0.05% of GDP) New HHs receive low social assistance MOP coverage of 1st income decile increases by 3.3 pp Average amount of MOP received per a.e. in the 1st decile increases by 10.6% (from low base, 15% of avg. wage in 2008)

Results: income and poverty impact of changes 3.5% increase in avg. HH income per a.e. within 1 st decile (5.4% within 1 st ventile) Decrease in the number of poor by 2.1% when poverty line at 10th percentile (3.4% when line at 5 th percentile) Results were also disaggregated by number of children in HH, HH size and age of members

Non-take-up and overpayment issues We don’t fully account for non-take-up Number of eligible HHs much greater than those receiving MOP in administrative records In our simulation non-take-up ratio is 76.9% Potential explanations: time inconsistency, information and transaction costs, stigma 62.5% of HHs who receive MOP in database do not meet at least one criterion

Concluding remarks Coverage remains low (increase from 18 to 21.3%) New criteria complement existing recipients by the “better off” poor Income of the most needy boosted Reasons for ineligibility beyond income Administrative barriers remain

Thank you for your attention! Questions?