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The Investment Case For Social Protection – Methodological Challenges and Lessons Learnt Franziska Gassmann Andrés Mideros Cécile Cherrier Pierre Mohnen.

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Presentation on theme: "The Investment Case For Social Protection – Methodological Challenges and Lessons Learnt Franziska Gassmann Andrés Mideros Cécile Cherrier Pierre Mohnen."— Presentation transcript:

1 The Investment Case For Social Protection – Methodological Challenges and Lessons Learnt Franziska Gassmann Andrés Mideros Cécile Cherrier Pierre Mohnen UNICEF Office of Research, Florence, 18 March 2013

2 Maastricht Graduate School of Governance Outline Why focusing on returns of SP investments? Understanding social protection as economic investment Methodological options and challenges An example: RoR study for Cambodia Are there lessons to be learnt? Conclusions

3 Maastricht Graduate School of Governance The usual arguments for extending social protection rely on… Human rights Empirical evidence on impacts Pilot projects Affordability studies

4 Maastricht Graduate School of Governance ‘Social protection is a human right’ Art.22 and 25 of Universal Declaration of Human Rights (UN 1948) Social Protection Floor: “a set of basic social rights, services and facilities that the global citizen should enjoy” (ILO&WHO, 2009:4) Social assistance as entitlement – state obligation (Cichon et al., 2011) But: –Insufficient domestic resources to ensure all basic human rights at once –Governments set priorities, but not necessarily SP

5 Maastricht Graduate School of Governance ‘We know it works’ Large international evidence base on positive impacts of social transfers on poverty, inequality and access to basic sercives (e.g., EPRI, 2010; Barrientos & Nino-Zarazua, 2010; Arnold et al., 2011) But: –In the absence of a national social transfer program, evidence needs to be drawn from other countries –Effects depend on program design and implementation – no blue print

6 Maastricht Graduate School of Governance ‘Let’s try and prove it’ Social transfer pilot projects to generate country- specific evidence But: –Frequently donor-driven and not aligned with national policy priorities/policy-making process –Weakly evaluated –Questions about scalability and financial sustainability

7 Maastricht Graduate School of Governance ‘We know it’s affordable’ Cost-feasibility studies have been mushrooming (e.g. ILO, HelpAge, Unicef) ‘Prove’ that the provision of a basic package of social protection is affordable But: –Does not take into account output, outcome or impact measures

8 Maastricht Graduate School of Governance Rationale for investment case Prejudices frequently prevail, difficult to fight Additional arguments are needed to move SP up the national development agendas –Demonstrate value for money –Analyze fiscal sustainability –Prove cost-effectiveness, capture multidimensional effects –Compare with alternative investments Develop economic argument for social protection –Costs AND benefits –Short term AND long term –Direct AND indirect

9 Maastricht Graduate School of Governance Non-contributory social protection as economic investment Paradigm shift: SP not just as a cost for the economy –Source of resilience in tough times –Support for growth and productivity in good times –Mechanism for social inclusion SP and economic growth (Alderman&Yemtsov, 2012) –Building and protection human capital, productive assets –Enhancing community assets, infrastructure –Stabilizer of aggregate demand, improving social cohesion, making reforms feasible Supported by international evidence (Barrientos, 2012)

10 Households’ disposable income Health, education, livelihoods Consumption Socio Economic Development Poverty alleviation Cash transfers In-kind transfers Non-contributory Social Protection Institutional framework, social cohesion and structural conditions Long run Equity Environment Public goods and services Savings Labour supply Insurance Taxes Human capital Production Labour productivity Economic growth Demand Investment Physical capital

11 Maastricht Graduate School of Governance Methodological challenges

12 Maastricht Graduate School of Governance Quantifying costs – the easy part? Assumptions: –Number of beneficiaries –Transfer value –Administrative costs (hypothetical) Tools: –Pension Calculator (HelpAge) (online, many countries) –Basic Social Protection Costing Tool (ILO) –Basic Social Protection Floor Costing Tool (ILO&UNICEF) Used in Argentina, Madagascar, Senegal –Rapid Assessment Protocol (+) (ILO) Used in El Salvador, Indonesia, Burkina Faso Outputs: –Costs as % of GDP –Hypothetical impact on poverty headcount and gap (RAP+)

13 Maastricht Graduate School of Governance Quantifying benefits (1) Frequently focus on one specific impact dictated by policy objective, data availability, modeling skills Mathematical models: –Use international evidence on impact to estimate potential country-specific impact given specific program characteristics –Examples: DFID business case: Nigeria, Pakistan, Gaza MBB (WB and UNICEF): Ghana (edu), Nigeria (health) AusAID: Bangladesh, Cambodia, PICs Hodges: Mauritania –Limitations: Impact of social protection programs cannot be generalized; depend on economic, social cultural context and capacity Findings sensitive to underlying assumptions if context differs

14 Maastricht Graduate School of Governance Quantifying benefits (2) Microsimulation models: –Ex-ante analysis of potential impact at micro-level –Based on national household survey data –Examples: Many single country studies ADePT: e.g., Senegal –Limitations: Static simulation (only few dynamic models) Focus on distributional effects (poverty, inequality) Strong assumptions, such as perfect targeting Exclude second-round effects Other models: –Macro models Focus at aggregate level Cross-country analysis –Comupatble General Equilibrium (CGE) models

15 Maastricht Graduate School of Governance Comparing costs with benefits Challenge: assign monetary value to benefits, impacts Express benefits in terms of impact on economic growth –Neglects distributional issues Economic rate of return: –Benefits: sum of distributional and behavioral income effects –Costs: costs of proposed SP package –Dynamic: aggregate effects over time to estimate long-term impact

16 Maastricht Graduate School of Governance RoR study Cambodia What are the economic returns of social protection in the mid- and long-term? Partial approaches: Cross country analysis. Computable general equilibrium model. Cost-(effectiveness/benefit) analysis. Treatment effects. Microsimulation (can be extended).

17 Maastricht Graduate School of Governance RoR study Cambodia – Model RoR: relation between net benefits and costs Data: CSES (2004 and 2009)  Cambodia Microsimulation (steps): Static (cost-effectiveness): changes on poverty and inequality (direct distributional effect) Returns of human capital (education) at the household level Behavioural (income) effects (probabilistic models) School attendance (education) Nutrition (health) Labour (participation and supply) Dynamic: 20 periods

18 Maastricht Graduate School of Governance RoR study Cambodia – Model Household consumption Poverty and inequality Education (school attendance) Health (underweight) Labour participation Human capital Labour productivity Social protection Economic performance Return Direct (distributional) effects Behavioural (income) effects

19 Maastricht Graduate School of Governance RoR study Cambodia – Policy Social Protection Instrument Target PopulationBenefit TransferTotal Cost KHR billion % of GDP KHR billion % of GDP Cash transfer Poor children 0-6 years old in rural areas, up to two per household USD 12 per month (60% rural food poverty line) 3910.94301.0 Social pension Poor persons 65+ in rural areas USD 20 per month (100% rural food poverty line) 1390.31530.4 Scholarship Poor children at lower secondary in rural areas USD 50 per year (20% rural food poverty line) 250.1280.1 Public works Poor persons 18-64 years old in rural areas, up to 1 per household (80 days per year) USD 2.3 per day500.1750.2 Total costs is around 1.6% of GDP (USD 166 million, 2009).

20 Maastricht Graduate School of Governance RoR study Cambodia – Behavioural effects I Model: 2SLS for all households Dependent variable (independent variable) Urban (non-poor) Urban (poor) Rural (non-poor) Rural (poor) log of household consumption per capita (maximum level of education within the household) 0.042***0.016**0.026***0.018*** (0.005) (0.007) (0.003) (0.002) Model: Probit model for individuals 6-25 years old Dependent variable (independent variable) Education level (rural-poor) Primary Lower secondary Upper secondary School attendance (log of household consumption per capita) 0.226**0.560**0.373 (0.089) (0.262) (0.516) Model: Probit model for children under 5 years old Dependent variable (independent variable)National National (poor) Rural (poor) Underweight (log of household consumption per capita) -0.043***-0.048-0.038 (0.015)(0.038)(0.041) Underweight (no toilet facility in the house = 1) 0.0260.062**0.081*** (0.016) (0.029)

21 Maastricht Graduate School of Governance RoR study Cambodia – Behavioural effects II (5-14)(15-17)(18-30)(31-45)(46-64) Unpaid work Urban (Poor) -1.533*-4.076***-1.605*-0.499 -0.369 (0.815)(1.004)(0.832)(0.544)(0.806) N7853811,011639369 Log Pseudo Likelihood-483 -296 -844 -382 -231 Rural (Poor) -1.520***-1.442**-1.236***-0.547 -0.119 (0.440)(0.568)(0.395)(0.344)(0.349) N6,9973,0917,4744,8962,519 Log Pseudo Likelihood-5,400 -2,807 -6,580 -2,942 -1,617 Paid work Urban (Poor) -0.353 1.940***0.936 -0.921 -0.025 (0.338) (0.745) (0.803) (0.674) (0.916) Rural (Poor) -0.042-0.2561.004**0.374-0.605 (0.192) (0.448) (0.395) (0.388) (0.452) Labour participation – Multinomial probit

22 Maastricht Graduate School of Governance RoR study Cambodia – Results BenefitScenarioPeriod 1Period 5Period 10Period 15Period 20 Average years of education (18-64 years old) With social protection6.527.679.0010.4011.62 Without social protection6.527.658.8910.2211.41 Benefit (difference)0.000.020.110.190.21 Total household consumption average annual growth rate (%) With social protection1.552.542.772.822.71 Without social protection0.002.292.652.742.67 Benefit (difference)1.550.260.120.070.04 Poverty headcount (%) With social protection23.7420.715.610.97.8 Without social protection29.7126.719.814.710.4 Benefit (difference)-6.0 -4.2-3.8-2.6 Inequality (Gini of consumption) With social protection0.3130.314 0.3080.302 Without social protection0.3290.3280.3270.3200.312 Benefit (difference)-0.016-0.014-0.013-0.012-0.010 CostPolicyPeriod 1Period 5Period 10Period 15Period 20 Cost (% of GDP)Social protection package1.61.41.20.90.8 RoRDiscount ratePeriod 1Period 5Period 10Period 15Period 20 Rate of Return (Absolute benefit on total household consumption / absolute cost) (%) 2%-11.6-10.0-4.15.814.7 3%-11.6-10.1-4.35.013.3 4%-11.6-10.1-4.64.311.9

23 Maastricht Graduate School of Governance RoR study Cambodia – Results Rate of return Effect on total household consumption through human capital accumulation, due to higher school attendance thanks to social transfers.

24 Maastricht Graduate School of Governance RoR study Cambodia – Final remarks Any model is always a simplification of real life. Effects, benefits and returns may be higher if complementary policies are also implemented. Improving health and education coverage and quality. Enhancing sanitation conditions. Fostering economic productivity, formal labour market, industrialization, innovation and technical change.

25 Maastricht Graduate School of Governance RoR study Cambodia – Final remarks Additional effects may increase benefits and RoR. Behavioural (non-economic) effects due to SPI design. Spillover effects and regional multiplier. Institutional change and social cohesion. Health status improvements (e.g. nutrition). Financing aspects (taxation), administrative issues (inefficiency) and targeting errors may reduce RoR. Specific SPI design (e.g. targeting, conditionality, payment mechanism) may affect RoR.

26 Maastricht Graduate School of Governance RoR study Cambodia – Final remarks Investing in social protection promotes equitable economic growth. Solving human capital constraints, and fostering economic development at the micro level. A basic package of SPI for poor rural individuals in Cambodia has a RoR of between 12% and 15%, after 20 periods (years). It becomes positive after 12 periods (years). Dynamic microsimulation provides a novel approach to analyse economic returns of social protection. Modelling options depends on data constrains. Costs and specific impacts has been estimated. The model can be used to study a gap regarding economic returns in the mid- and long- term.

27 Maastricht Graduate School of Governance The role of CBA in policy making Instrument to support evidence-based policy making and mobilize financial resources Enable dialogue with ‘money keepers’ –Speek the language they speek –Build confidence of social ministries –Examples: Mozambique, Senegal

28 Maastricht Graduate School of Governance Conditions for success Analysis as integral part of policy dialogue Needs to be followed up with in-country support Timing: a crisis may trigger interest Policy options to be defined in consultation with national stakeholders Robust and transparent methodology

29 Maastricht Graduate School of Governance But… Evidence on costs versus benefits or rates of return alone does not do the trick –Policy makers are often prejudiced and myopic –Extending social protection is path dependent, depends on local preferences and capacities –Political will and strong leadership remain pivotal (South Africa, Lesotho, Brazil) –Strong impact evidence is crucial to build political support (Latin America in general) CBA needs to be used with caution, aware of the inherent risks –Narrow focus on poverty reduction –Fragmented approach to social protection –Less attention to development process –Distraction from political economy

30 Maastricht Graduate School of Governance Conclusions Despite compelling evidence on the positive impacts of social protection, many governments are yet to be convinced Treating social protection as investment helps establishing the link between costs and benefits, taking into account the time needed to earn the money back Economic analyses such as CBA/RoR are only one component of policy decision-making –Positive social outcomes and human rights remain valid arguments Political will remains decisive for the expansion of social protection  It all comes down to politics! –More research needed on the underlying motives/incentives/processes of countries that successfully introduced/expanded social protection


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