Estimating Rates of Return of Social Protection
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1 Estimating Rates of Return of Social Protection A business case for non-contributory social transfers Franziska Gassmann Andrés Mideros Pierre Mohnen Bangkok, 14 September 2012
2 Acknowledgments UNICEF Cambodia Royal Government of Cambodia CARD/SPCU, SNEC, NIS
3 Agenda Introduction Analytical framework Modelling framework Results Conclusions and recommendations
4 Agenda Introduction Analytical framework Modelling framework Results Conclusions and recommendations
5 Introduction Research objective: Contribute to the evidence on the links between social protection investments and socio-economic development in Cambodia Estimate rates of return of investments in social protection Definition: Rate of return is the relation between net benefits (between baseline and policy scenario x) and the costs of the investment
6 Introduction Call for proposals: Fall 2011 Start project: January 2012 Final report: September 2012 Literature review on international evidence Stakeholder interviews Government agencies, local and international organizations and NGOs Quantitative analysis 2 rounds of peer reviews EPRI (South Africa), IDS (UK), NATSEM (Australia), TEAGSAC (Ireland), IRC (Florence), UNICEF-New York, and other independent researchers.
7 Agenda Introduction Analytical framework Modelling framework Results Conclusions and recommendations
8 Analytical framework Social protection Public and private interventions aimed at preventing, reducing and eliminating socio economic vulnerabilities. In-kind and cash transfers (contributory and non-contributory) Reduce poverty and redistribute, and help households to manage risks Socio-economic development Enhance and sustain productive capacity Promote human development
9 Analytical framework Social protection Direct effects Poverty and inequality Various instruments Behavioural effects Education Health Human capital Household consumption Child wellbeing Livelihoods and productive investments Physical capital Spillovers and local multiplier Labour Labour productivity Return Financing Economic performance
10 International Evidence Direct effects (distribution) Poverty reduction (headcount): 12% (South Africa), 18% (Brazil) Poverty reduction (gap): 20% (Mexico), 47% (South Africa) Inequality decline (Gini): 1% (Brazil), 3% (South Africa) References: Barrientos (2005), Arnold et al (2011), Samson et al (2004) [...] people who have access to a basic set of goods, services, and transfers are lifted out of poverty or vulnerability and can become more productive contributors to the economy (Cichon et al, 2011: 5).
11 International Evidence Behavioural effects (human capital) Health: health visits (18% increment in Mexico), child immunisation (more than 45% increment in Bangladesh), nutrition (0.17 Kg. Gain in children weight in Bangladesh). Education: school enrolment (5%, 10%, 11% increase in Malawi, Pakistan and Ecuador, respectively), attendance (63% reduction in drop out in Brazil). References: Barrientos and Scott (2008), Arnold et al (2011), Schady and Araujo (2006) Child wellbeing Child poverty (25%, 40% reduction in Poland and Hungary, respectively), cognitive development (0.25 standard deviations improvement in Ecuador) References: Barrientos and DeJong (2006), Paxson and Schady (2008)
12 International Evidence Behavioural effects (livelihoods) Productive investments (6%, 8% increment in livestock in Paraguay and Ethiopia, respectively). Household income multiplier ( , 2 in Mexico and Bolivia, respectively). References: Arnold et al (2011), Barrientos and Sabatés-Wheeler (2009) Behavioural effects (labour) Labour participation (2.6 percentage points, 11% increment in Brazil and South Africa, respectively). Child work (11%, 17%, 26% reduction in Cambodia, Ecuador and Brazil, respectively). References: Arnold et al (2011), Schady and Araujo (2006)
13 International Evidence Spillovers and local multipliers Demonstration effects (increasing school enrolment of children from non-beneficiaries households in Mexico). Third party investment (local business increase their sales in Malawi and Brazil) Non-beneficiaries household income (12% difference in Mexico) Regional multiplier (2.2, 2.4, 2.6 in Ecuador, Malawi and Zimbawe, respectively). References: Barrientos and Sabatés-Wheeler (2009), Miller (2011), Hanlon et al (2010), Staunton (2011), Davies and Davey (2007), Woller and Parsons (2002),
14 Economic returns (mechanisms) Institutional changes: Poverty reduction and inequality decline Social cohesion and peace Human capital Higher investments on health and education Child wellbeing Productive capacity Fostering productive investments, and protect assets Reducing liquidity constrains and covers transportation costs Consumption Enhancing local demand
15 Financial Affordability Basic social protection: 4% - 10% of GDP (ILO) Cambodia (NSPS): 4% - 7% (excluding health sector) of GDP in 2012 (Costing study) Fiscal space (*), political will (NSPS) and policy priorities (human capital and productive capacity) Affordability is at the end an issue of political choice. Social protection is an investment in both social/human and economic development. Economic growth is the easiest way to finance social protection.
16 Agenda Introduction Analytical framework Modelling framework Results Conclusions and recommendations
17 Modelling framework RoR: relation between net benefits and costs Data: CSES (2004 and 2009) 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 (linear and probabilistic regressions) School attendance (education) Nutrition (health) Labour (participation and supply) Dynamic: 20 periods
18 Modelling framework Social protection Direct (distributional) effects Poverty and inequality Various instruments Behavioural (income) effects Education (school attendance) Human capital Household consumption Health (underweight) Return Labour Labour productivity Economic performance
19 Policy options (scenarios)
20 Static microsimulation Total costs is between 1.5% and 1.7% of GDP Costs by SPI and policy option (scenario) Transfer Total Cost Beneficiaries KHR billion % of GDP KHR billion % of GDP Persons Households Scenario , ,118 Cash transfer Scenario , ,341 Scenario , ,341 Scenario , ,491 Social pension Scenario , ,988 Scenario , ,231 Scholarship Scenario , ,146 Scenario ,113 12,113 Public works Scenario ,563 64,563
21 Static microsimulation Cash transfers for poor children generate the highest reduction on poverty Poverty headcount Phnom Penh Other Urban Other Rural Total Poverty variation (%, head count) Base line Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario
22 Cost-effectiveness Cash transfers are the most cost-effective to reduce poverty gap and severity (Effect (change, %) / Cost (% of GDP)) SP over the life-cycle: - Cash transfers (Scenario 3) - Social pensions (Scenario 5) - Scholarships (Scenario 7) - PWP (Scenario 9) Poverty Poverty Inequality Poverty (gap) (head count) (severity) (Gini) Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario Scenario
23 Household consumption per capita Income proxy Cambodian Socio Economic Survey 2004 and2009 Triple role in the model: Define poverty and inequality Economic returns of human capital at the household level Generate behavioural effects: changes due to social transfers
24 Returns of human capital An additional year of education is related with a 4.1% higher wage. Returns of human capital (log wages) National Men Women Urban Rural Heckman Selection Model Schooling *** *** *** *** *** (0.003) (0.004) (0.005) (0.005) (0.004) Female= ** *** (0.018) (0.027) (0.022) Other Urban= *** *** *** (0.057) (0.109) (0.109) Other Rural= *** *** *** (0.056) (0.105) (0.110)
25 Returns of human capital On average, an additional year of education (maximum level) is related with a 1.8% higher household consumption for a poor rural household. Returns of human capital (household) Urban (Non-poor) Urban (Poor) Rural (Non-poor) Rural (Poor) Schooling (max) *** ** *** *** (0.005) (0.007) (0.003) (0.002)
26 Behavioural (income) effects School attendance (X axis = grade) CSES 2009 School attendance(%) School attendance(%) Total Boys Girls 20.0
27 Behavioural (income) effects School attendance (individuals between 6 and 25 years old) Pr(School attendance = 1) Primary Lower Upper Education Secondary Secondary Rural Poor ln(hh_consumption) (q) ** ** (0.089) (0.262) (0.516) ln(hh_consumption) (q) Rural Non-Poor *** (0.036) (0.066) (0.115) Urban Poor ln(hh_consumption) (q) (0.118) (0.276) (0.625) A 10% increase in the level of consumption is related with a 5.6 percentage points higher probability to attend lower secondary school for a poor rural person
28 Behavioural (income) effects Under-five underweight by consumption quintile CSES 2009 Underweight (%) Under-five Quintile 1 Quintile 5 Total Age
29 Behavioural (income) effects 10% increase in consumption is related with 0.4 percentage points lower probability of being underweighted. Nutrition (children under 5 years old) Pr(Underweight = 1) National National (Poor) Urban (Poor) Rural (Poor) Rural (Poor) ln(consumption) (q) *** (0.015) (0.038) (0.127) (0.041) (0.036) No toilet= ** *** (0.016) (0.030) (0.072) (0.029) ln(consumption) *(toilet=1) *** (0.009)
30 Behavioural (income) effects Higher household consumption reduces unpaid labour participation, but it increases or does not change paid work. Labour participation (not working, unpaid work, paid work) (5-14) (15-17) (18-30) (31-45) (46-64) (65+) Unpaid work Urban (Poor) * *** * *** (0.815) (1.004) (0.832) (0.544) (0.806) (0.000) Rural (Poor) *** ** *** (0.440) (0.568) (0.395) (0.344) (0.349) (0.554) Paid work Urban (Poor) *** *** (0.338) (0.745) (0.803) (0.674) (0.916) (0.000) Rural (Poor) ** ** (0.192) (0.448) (0.395) (0.388) (0.452) (1.100)
31 Behavioural (income) effects Labour supply (paid work) increases for individuals with household consumption per capita below USD 100 per month. However, it may decline in the case of rural poor individuals. log (work hours) (15-17) (18-30) (31-45) (46-64) (18-64) ln(consumption) (q) Urban (Poor) (1.719) (0.496) (0.448) (0.708) (0.325) Rural (Poor) ln(consumption) (q) ** * * (0.889) (0.452) (0.415) (0.697) (0.305) National ln(consumption) (q) *** (0.015) ln(consumption>100) (q) (0.163) ln(consumption<=100) (q) *** (0.015)
32 Behavioural (income) effects A 10% increase in household consumption is related with a 7.8 percentage points higher probability of formal work for poor persons between 18 and 64 years old in rural areas. Formal labour Pr(Formal labour = 1) (18-30) (31-45) (18-45) (18-64) Urban (Poor) ln(consumption) (q) *** ** *** (0.743) (1.597) (0.596) (0.446) Rural (Poor) ln(consumption) (q) ** *** ** *** (0.365) (0.360) (0.277) (0.230)
33 Dynamic microsimulation model Joint policy scenario (life-cycle): Cash transfers (poor children in rural areas, up to 2 per household) Social pensions (poor elderly in rural areas) Scholarships (poor children in rural areas, lower secondary) PWP (poor households in rural areas) Benefits: difference between policy and base line scenarios. Three modules (sub-models): demography, human capital accumulation and household consumption.
34 Agenda Introduction Analytical framework Modelling framework Results Conclusions and recommendations
35 Results: benefit (human capital) Labour force s median education level increases faster due to social transfers. Labour force median education level (schooling) Years of education Difference (Bs) Without SPI With SPI Bs (schooling - years)
36 Results: Benefit (hh consumption) Total household consumption grows faster if SPI are implemented. Total household consumption average growth rate Household Consumption average growth rate Difference (Bc) 0.04 Without SPI With SPI Bc (hh consumption growth rate)
37 Results: Benefit (poverty reduction) Poverty headcount decreases faster because of SPI Head count Poverty (head count) Difference (Bp) Without SPI With SPI Bp (poverty head count)
38 Results Total cost of SPI decreases over time. KHR (billion) 1.6 % of GDP Total cost (KHR billion) Total cost (% of GDP)
39 Results Rate of return Effect on total household consumption (%) Period RoRC (d=2%) RoRC (d=4%) RoRC (d=6%)
40 Agenda Introduction Analytical framework Modelling framework Results Conclusions and recommendations
41 Conclusions and recommendations 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.
42 Conclusions and recommendations 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.
43 Conclusions and recommendations Investing in social protection promotes equitable economic growth. In the case of Cambodia: Enhance human development solving human capital constraints Foster 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). Poverty and inequality are immediately reduced (poverty headcount is reduced by 6 percentage points after introducing the SPI)
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