The World Bank Social Protection and Jobs Global Practice A Quantitative Evaluation of the Greek Social Solidarity Income January 2019 Disclaimer The contents of this document are the sole responsibility of its author and should in no way be taken to reflect the official views of the World Bank and its Board of Directors, the governments they represent or the European Commission. Acknowledgments This report was prepared by a team led by Alessandra Marini (Senior Economist, World Bank) and Michele Zini (Senior Economist, World Bank). The team included Eleni Kanavitsa, Natalia Millan, Chrysa Leventi and Nithin Umapathi. The team would like to thank Dimitris Karellas, George Planiteros, Tasos Tagaris, Stathis Marinos, George Karkalis, Babis Iliades, Irini Andriopoulou, and Alexandros Karakitsios for useful inputs and feedback, and Renata Gukovas for the international comparisons. The team would also like to thank Panos Tsakloglou, Kathy Lindert, Emil Tesliuc and Cem Mete, and Christian Bodewig for their useful comments and feedback. Finally, the team would like to thank Geraldine Mahieu, Theodora Giouroukou and Simone Marino, and acknowledge the technical and financial support of the European Commission’s Structural Reform Support Services in this endeavour. The team would also like to thank the Ministry of Labor, Social Insurance and Social Solidarity for permission to use the image in the cover of this report. 1 Executive Summary This note presents the results of the evaluation of the Greek Social Solidarity Income (SSI) program, a last resort safety net program targeted to extremely poor households with the objective of alleviating poverty in Greece. At the time of finalizing this report, the SSI program absorbed slightly less than half a percentage point of GDP, in line with the program’s budgetary allocation. The SSI reached about 320,000 households in Greece, or approximately 650,000 people. Nationally, this translates to about 6.5 percent of the population, remarkably close to the program’s original target of reaching about 7 percent of the country’s population. The program extended about 220 euros on average on a monthly basis to household meeting three criteria at the same time (income, assets, and residency, as described in the Annex). The objective of this evaluation is to assess the effectiveness of the SSI program’s targeting methodology as well as its impact on poverty indicators . The findings presented are based on data collected through a tailor-made nationally representative survey run for the purposes of evaluating the SSI. Main findings The SSI program is very effective in identifying poor households. Almost 60 percent of all SSI beneficiaries belong to the first decile, and 80 percent of them are poor using a relative extreme poverty definition in line with that adopted by Eurostat. The program’s resources are used very effectively towards supporting poor households. About two-thirds of the benefits go to households in the first decile, and almost 85 percent of the program’s resources reach poor households; 95 percent of the program’s funds are spent on households in the first three deciles. The program constitutes a significant source of income for households in the bottom decile and for poor households. The SSI benefits represents about 69 percent of the aggregate income of households in the first decile, and about one third of the aggregate income of the poor. The program is de facto functioning as an unemployment assistance scheme, particularly for the long term unemployed who do not receive unemployment benefits. Expectedly, the SSI does not have much of an impact on poverty incidence, but it does reduce the poverty gap and inequality. The main reasons why the SSI is not affecting the national poverty rate much are two. First, the eligibility thresholds for the program are very low, and well below the poverty line even using the extreme relative poverty definition adopted throughout this report. This means that most SSI beneficiaries, even considering the transfers received, would not make it over the poverty line. Second, because the benefit appears to be so well targeted and effective at reaching the poorest, the poverty rate is not affected much even though beneficiary households are better off because of the program. Indeed, the program appears to be very well- received by the population, who consider it a significant help. The program suffers from low coverage among its intended and potential beneficiaries . Using a relative definition of extreme poverty, only about one third of households with a total disposable income below 40 percent of the national median receive SSI support. Most importantly, only 37 percent of households in the first decile are currently receiving the benefit, even though, according to the data collected, the program’s income eligibility criteria should ensure coverage of all households in the first decile and a of portion of households in the second decile. The analysis of households in the first decile shows that almost 60 percent of said households did not apply to the SSI. A sizeable portion of these (about one-fourth, or 15 percent of households in the first decile) had never heard of the program, and half (or 31 percent of households in the first decile) had heard about the SSI without knowing any detail and hence never applied. Eleven percent of households in the first decile reported being familiar with the program but chose not to apply for unspecified reasons. The analysis explores possible reasons for the low take up of the program and finds that lack of information about the program within the target population is an important constraint, pointing to the need to stronger communication and outreach efforts. Even though, thanks to the well-designed information system, the program’s application process has been proceeding without major obstacle, about 40 percent of 2 applicants paid someone to help them file an application. This is not only in direct contrast to the poverty alleviating objective of the program, but also reinforces the point above related to the need for better communication and outreach efforts. The program’s effectiveness at identifying the poor, combined with the low coverage in the first decile, suggest that an expansion of the SSI to cover a greater portion of the program’s intended beneficiar ies would represent an efficient use of resources towards further alleviating poverty in Greece. This of course assumes an increase in the budgetary allocation of the SSI program and that a careful assessment of the SSI interaction with other benefits (namely the newly introduced housing benefit, but also the reformed family benefits) has been carried out prior to any change to the SSI design. Expectedly, the implementation of the second and third pillars of the program remain very limited. Three out of four beneficiaries reported not having received information on complementary services and other social programs. International experiences show that it is normal for programs such as the SSI to focus first on effective implementation of the first pillar and then on additional features such as granting beneficiaries access to additional social services (second pillar) or labor reintegration measures (third pillar). Almost two years since the national rollout, and five since the initial pilot, the implementation of the SSI’s second and third pillars will remain the single biggest challenges for the SSI going forward, and the key to its long-term impact on families’ well-being. The proportion of single-member households is considerably larger among SSI units than across the country, which is unusual by international standards. The proportion is even higher in the administrative database. Considering the design parameters of the program, that assign 200 euros to the first adult and 100 euro to the second, it is likely that a sizeable share of SSI beneficiary households is splitting to maximize the benefits they receive from the SSI program. This could be costing the program up to 30 million euros per year. This points to the urgent need to review applications submitted by single-member households, ideally implementing random checks among a subset of these, or carrying out a mass suspension of said applications until the information provided can be re-checked. This also points to the need of rethinking the benefit structure and key parameters of the program. 3 Table of Contents Table of Contents ................................................................................................................................................... 4 Introduction ............................................................................................................................................................ 5 1. Data and Methodology ................................................................................................................................ 6 1.1 Program Coverage .........................................................................................................................................................8 1.2 Targeting effectiveness ............................................................................................................................................. 11 1.3 Relative Incidence and Generosity....................................................................................................................... 13 2.4 Poverty Incidence ................................................................................................................................................................ 15 2. Evaluation of program’s implementation and processes............................................................ 16 3. Profile of Beneficiary Households ....................................................................................................... 19 4.1 The Unusually Frequent Single Member Households ................................................................................. 23 Conclusion and Policy Implications ............................................................................................................. 24 Annex 1. SSI Eligibility Determination: Criteria ...................................................................................... 27 Annex 2. Low Take up in the First Two Income Deciles - Regression Analysis ............................ 33 Annex 3. Summary of The Process Evaluation of the Implementation of the First Phase of the SSI ……………………………………………………………………………………………………………………………………...36 Annex 4. Comparison between EU-SILC and SSI Survey Income Data ............................................. 38 4 Introduction This note presents the results of the evaluation of the first two years of implementation of the Greek Social Solidarity Income (SSI) program, the last resort safety net program targeted to extremely poor households with the objective of alleviating poverty in Greece. The program, also referred to as Guaranteed Minimum Income program (GMI), was piloted in 2014/2015 in thirteen selected municipalities across the country. After a process evaluation of the pilot experience, the program’s parameters and operational procedures were revised and adjusted, and from 2016 onwards the SSI was gradually expanded. In July 2016 the first phase of the rollout of the SSI began, extending the program to 30 municipalities across the country. After a second process evaluation, the program was further refined, and in February 2017 the SSI was finally launched nationally. At the time of writing this note, the SSI, the first means tested program in the country targeting explicitly extremely poor households solely on the basis of their poverty1 status and without categorical exclusions2 reaches over 300,000 households, and well over 600,000 individuals (6.5 percent of population) and is widely considered an important and successful means of public basic income support for the poor. The findings presented are based on data collected through a World Bank designed nationally representative survey run for the purposes of evaluating the SSI. The survey was carried out by KAPA Research, a survey firm based in Greece, on behalf of and financed by the World Bank. The World Bank, in turn, has been providing technical assistance to the Greek Government, and in particular to the Ministry of Labor, Social Insurance and Solidarity (MoLSISS) towards the design, piloting, evaluation and implementation of the SSI program since 2013, first through a Reimbursable Advisory Services3 agreement with the Greek Government directly, and more recently thanks to a trust fund kindly made available to the World Bank by the European Commission’s Structural Reform Support Services. The objective of the evaluation, and hence of this report, is to assess the effectiveness of the program’s targeting methodology as well as its performance with respect to selected poverty indicators, and to identify possible changes to the program design and implementation arrangements. The evaluation is critical to analyzing the rigor of the chosen design and the implementation arrangements and assessing the “value for money� of the program. It assesses the extent to which the SSI, and its targeting parameters, eligibility requirements, benefit formula are effective in reaching the intended beneficiaries of the program (i.e. the extreme poor), and whether the program’s resources are being spent well to alleviate poverty in the country. The report proceeds as follows. Section 1 describes the survey design and the data collected. Section 2 presents the results of the performance analysis of the SSI program (targeting, coverage, incidence, and poverty effects). Section 3 discusses process-related issues linked to the implementation of the program. Section 4 describes the profile of SSI beneficiary households based on this newly acquired survey data. Some policy relevant observations conclude the note. 1 It should be noted that, for the purposes of the SSI, poverty is defined differently than for statistical purposes (that is, to be eligible for the program, a household as to have an income and assets below certain equivalized thresholds, as detailed in Annex 1). 2 In other words, belonging to a certain “category� has no bearing on SSI eligibility (for instance being disabled, having children, being above a certain age, etc.). Income and assets, other than being lawfully resident in Greece, are the only relevant criteria for the SSI. 3 Reimbursable Advisory Services (RAS) are provided by the Bank to meet emerging client needs and demand through the provision of customized/specialized advisory services. They are requested by the client institutions and paid using national funds or other resources available to the client. 5 1. Data and Methodology The data used for the analysis of GMI was collected through a survey among 2,575 households in Greece. The sampling enabled countrywide representation and the necessary statistical power for evaluation estimates of the SSI program. The total sample consists of two distinct sub-samples. First, the beneficiary sample was selected using random sampling by IDIKA4 from the administrative data. Second, the non-beneficiary sample was selected using with stratified random sampling with cluster selection probability proportional to its size to ensure that the final dataset is representative of the nationwide population5. The total sample of 2,575 households includes 515 households whose SSI application had been accepted at the time of the interview, and 2,050 non-beneficiary households. The sample is representative for the greater Athens metropolitan area, the Thessaloniki prefecture, and the rest of Greece. It is also representative at urban, semi-urban and rural divisions. The survey was conducted in the respondents’ homes between September 2017 and February 2018 by enumerators recruited and trained by KAPA Research, a survey research firm based in Greece. The questionnaire was developed by the World Bank, and the survey enumerators utilized the World Bank’s Computer Assisted Personal Interview survey solutions technology (CAPI6). A copy of the questionnaire used is available separately. The questionnaire was adapted for CAPI implementation to collect information on employment, incomes, participation in social protection programs, living conditions, asset information, and education. The questionnaire also asked questions specific to the SSI’s implementation (application process, program communication, etc.). The survey data underwent extensive quality controls during implementation and cross checks with EU-SILC after the survey field work was completed. The data compares well to the EU-SILC statistics in terms of household characteristics (composition, income and poverty). A key focus of the survey was to obtain high quality income information that was partially based on the EU-SILC methodology, in order to rank households with an income aggregate similar to that by EU-SILC, as well as that used to establish eligibility for the SSI program7. The income data collected and used to rank households is a measure of disposable income that includes: income from employment (both wage employment and self-employment) and income from social transfers (including child benefits, disability benefits, unemployment benefits, old-age benefits, namely pensions and the EKAS pension), the social dividend (for households surveyed from January to February 2018), income from rental of a property or land, and interests, dividends, profit from capital investments in unincorporated business, minus regular inter-household cash transfers received.8 Respondents were asked to report income in net terms9, as is done in EU-SILC questionnaire. Incomes were then converted to gross terms using the methodology used by the EUROMOD team for Greece and social insurance contributions were also taken into account in order to approximate the means test used to establish SSI eligibility.10 4 IDIKA is the E-government agency of the MoLSISS responsible for setting up and maintaining the IT system supporting the SSI. 5 If SSI households were encountered in the non-beneficiary sample, these were dropped from the sample and replaced. 6 https://www.facebook.com/mysurveysolutions 7 Annex 4 presents a comparison of mean total disposable incomes by decile both according to the data collected for this evaluation and according to EU-SILC. 8 Other incomes included in EU-SILC such as company car, sickness benefits, survivor benefits and education allowances were not included. These incomes account for a very small percentage in EU-SILC data and would not impact results. 9 Self-employed individuals were however given the option of reporting income in either net or gross terms. 10 An important way in which the income used for SSI eligibility differs from that used to rank households is that the income for SSI purposes does not include non-contributory disability benefits, transfers from other households and 20 percent of 6 The questionnaire also focused on households’ assets with the objective of simulating all SSI eligibility criteria, and not only the income-related one; however, particularly for real estate assets, the data collected is not sufficient or of good enough quality to replicate the asset test. As further discussed in Annex 1, which lists all the eligibility criteria of the SSI program, in addition to the income criteria stated above, potential recipient units must also meet the assets criteria. If either the value of their real estate, financial, or movable (cars and motorcycles) assets surpasses the relevant thresholds, the applicant unit is considered ineligible for the program, regardless of their income level. However, the real estate criterion relies on the taxable value of property, and households did not report accurate enough information, or information at all, to allow for the simulation of this criterion. Similarly, the bank deposit criterion relies on information on households’ income derived from interests on deposits, and respondents did not report said information. The data however allows to impute the value of cars of interviewed households, in line with the SSI rules and regulations, and the analysis shows that this criterion is non-binding (i.e. does not significantly impact program eligibility among households); we therefore omit it from the discussion that follows. income from employment and self-employment. Another way in which the income used for SSI eligibility differs from that used to rank households is that the former refers to the 6-month period prior to the benefit receipt whereas the latter refers to the whole year. A further important difference is the equivalence scales used. To calculate total household disposable income within the survey data collected we followed EU-SILC’s methodology, which in turn uses the modified OECD equivalence scale (assigning a weight of 1 to the first adult, 0.5 to any additional household members aged 14 and above, and 0.3 to household members under age 14). In contrast, the equivalence scale used for SSI eligibility determination assigns a 1 to the first adult, 0.5 to additional household members ages 18 and above, and 0.3 to household members under 18 (and 0.5 to the first household member under 18 if in a single-parent household). More details on the SSI eligibility determination can be found in Annex 1. 7 2. Program’s Performance This section presents an assessment of the performance of the SSI program. The analysis below shows some results in terms of the coverage of the SSI, its effectiveness in reaching the poor, the incidence and generosity of the benefit, and the overall effects of the program on poverty measurements in Greece. Unless otherwise stated, all facts and figures are based on the household survey data collected for the purposes of this evaluation. Poverty is calculated at the household level and is defined as having a total disposable income below 40 percent of the yearly national median of 7,200 euro according to SSI data11, in line with EUROSTAT’s relative extreme poverty definition used widely within the EU. As the SSI is a program explicitly supporting the extreme poor, and as Greece does not have a nationally recognized definition of absolute extreme poverty, we deem the poverty line mentioned above the most appropriate12. 2.1 Program Coverage Nationally, about 6.5 percent of the population receives the SSI, and just over one third of the poor benefit from SSI support13. Approximately 277,000 households, or roughly 660,000 individuals benefitted from SSI support based on survey data collected in the last two months of 2017 and throughout January 2018. This corresponds to about 6.5 percent of the country’s population, remarkably close to the program’s target of reaching about 7 percent of the Greek population. Using a relative definition of extreme poverty, the most stringent poverty metric as per Eurostat methodology, about one third of households with a total disposable income below 40 percent of the national median receive SSI support, and only 1.6 percent of those not classified as poor using this definition benefit from the program. Figure 1: Proportion of Households Receiving the SSI 37.3 40.0 34.0 35.0 30.0 25.0 19.0 20.0 15.0 6.5 6.9 5.9 10.0 5.8 1.5 0.6 0.3 0.3 0.1 0.2 0.0 1.6 5.0 0.0 Source: WB Calculations based on SSI Household Survey Data (Poverty defined as being below 40% of national median income) Just over a third of households in the first decile14 of the income distribution receive SSI benefits, pointing to a significant problem of non-take up or under-coverage of the poor. As Figure 1 above shows, about 37 percent of households in the first decile (ranked by total disposable income) benefit from the SSI. This is an impressive result, compared to other countries, as evidenced 11 By this measure, 15.2 percent of the Greek population is poor. 12 All the poverty analysis used pre-GMI income. 13 The Greek GMI is an entitlement program and does not have a coverage quota in mind, but by design had an indicative budgetary allocation which, to a certain extent, allows the Government to accept applicants even when the budgetary projection go over the limit. 14 Income deciles were constructed using pre-transfer welfare, i.e. without taking the SSI benefit itself into account. 8 in Figure 2, which shows coverage of social assistance programs in selected countries. The Greece GMI program performs better than any other program included in the graph: despite the low coverage of the population as a whole, one of the lowest in the region, the program displays the highest coverage of households in the first quintile, almost at sixty percent. Figure 2: Proportion of Households Receiving Social Assistance in Greece and Selected Countries 60 50 40 30 20 10 0 GRC 2018 BIH 2015 BLR 2015 KSV 2016 ALB 2012 ROU 2011 SRB 2015 MNE 2010 Total Q1 Source: WB Calculations based on WB SpeeD data base and SSI Household Survey Data. Note: The SpeeD database does not include EU countries yet. The countries included in this graph were selected according to two criteria: 1) having data more recent than 2010; 2) being in the Balkan or Baltic Region. Greece outperformed all countries included in the Speed Database for which comparable social assistance data was available. (In all countries other than Greece, the poverty line is set as the maximum consumption of the first quintile post transfer; in Greece poverty is defined as being below 40% of national median income However, as the program was set up to cover the bottom 7 percent of the population, one would expect the coverage of the program among households in the bottom decile to be much higher, and somewhat close to 70 percent.15 Figure 3 below breaks down households in the first decile by their application status, and shows that almost 60 percent of said households did not apply to the SSI; a sizeable portion of these (about one-fourth, or 15 percent of households in the first decile) had never heard of the program, and half (or 31 percent of households in the first decile had heard about the SSI but did not know any detail and hence never applied. Eleven percent of households in the first decile reported being familiar with the program but chose not to apply for various reasons (mostly because they thought they would not qualify); one can only speculate that 15 As the household income definition used for SSI eligibility purposes, and the definition of “total household disposable income� differ, it is unlikely that the bottom 7 percent of the country’s population for SSI purposes and the bottom 7 percent of households in the nationally representative sample overlap completely. This may explain why coverage of the program in the first decile according to survey data may not reach 70 percent (i.e. 7 percent of the total country’s population). However, one would still expect coverage in the first decile to be higher than 37 percent. 9 such households may have informal sources of income and wanted to avoid scrutiny by applying for a welfare program. Asset filters may also be playing a role in the lower than expected coverage of the first decile, but, unfortunately, we were not able to collect reliable data that would have allowed us to replicate the SSI eligibility criteria in full. Box 1 below looks into this issue more in depth. Figure 3: Proportion of Households in First Decile 100% 11% 90% 80% 31% 70% 60% 50% 15% 40% 5% 30% 20% 38% 10% 0% Accepted Rejected or still need to present documents Never heard of the program Heard of the program but know no details Well aware of the program but did not apply Source: WB Calculations based on SSI Household Survey Data Box 1: Zoom on low take up The data presented above suggests that take-up of the SSI among households potentially eligible for the program is low. As this is a surprising result, we considered some alternative explanations. • Different income definitions. As explained above, and as further detailed in the Annex, there are several differences in the way in which the different sources of household incomes are treated and aggregated for SSI eligibility determination and the way in which these same sources are summed up to rank households according to their disposable income (and to then construct the income deciles used in the analysis). These differences could, at least in theory, explain why some households appear eligible in the dataset and based on the total household disposable income variable, but are not benefitting from the program in practice. To verify this hypothesis, we created a variable at the household level replicating the income definition for SSI eligibility purposes and reconstructed income deciles using this alternative income definition. The results presented in Figure 2 change only slightly, and the overall picture of low-take up in the first decile remains. Benefit recipiency in the first decile goes up from 38 percent to 40 percent, and about 60 percent of the first decile remains out of the program despite, for the most part, being potentially eligible. • Assets. At least some households might not be eligible for SSI support due to the high value of their immovable property. As mentioned in Annex 1, one of the criteria which households must meet to qualify for the SSI benefit is linked to the taxable value of their first residence. As mentioned above, unfortunately the lack of data on households’ dwellings cadas tral values does not allow to verify how binding this criterion is. However, 70 percent of households of the first decile who did not apply for the benefit are living in owned dwellings (with or without financial obligations) and as such, it is possible that some of them would not qualify for the SSI under the assets criteria. • Weights. One should note that the unweighted data show a very different picture. Building income deciles using a total household disposable income definition shows that 65 percent of individuals in the first decile are SSI recipients (729 out of 1,129). If deciles are constructed based on the income definition used for the SSI means-testing, 68 percent of observations located in the first decile are SSI recipients (777 out of 1,145 individuals). However, once we apply weights to the data to ensure nationally- 10 representative results, the figures decline significantly, to 38 percent and 40 percent, respectively, as shown in Figure 2 and as discussed in the previous point. This shift is due to the fact that, to allow for a meaningful analysis, we purposefully oversampled SSI beneficiaries in the dataset. In fact, SSI beneficiary households constitute about 20 percent of the sample and of the dataset, even though nationwide only 6.5 percent of households receive the benefit. Weights for the dataset were carefully constricted to ensure national representativeness and we can exclude that they are a factor behind the low take up observed in the data. • Benefit non-take-up due to employment in the informal sector or informal sources of income. Part of the reason why we observe low take up within the first decile and among potentially eligible families based on their self-reported income data is that some of these households/individuals may be working informally or have informal sources of income and therefore prefer not to apply to the program to avoid the state’s scrutiny. • Benefit non-take up due to ignorance about the program, isolation, and/or social detachment. The data collected shows that, no matter which income definition is used, there are many households which are on paper eligible for the SSI which do not receive the program. This is possibly a consequence of the limited efforts around the communication and outreach of the program, driven mainly by concerns of overshooting the initial budget estimates. A sizable share (almost one third of households in the first decile) have never heard of the program, and another 11 percent don’t know the details of it. To understand the characteristics and the factors more closely related to someone’s decision to apply for the SSI we run a regression analysis among households who applied to the program in the first two deciles. According to the results, the decision to apply is related in a statistically significant matter to: i) someone’s level of awareness of the program (the greater the level of awareness the greater the chance of apply to the program other variables held constant); ii) his/her perceived eligibility; iii) his/her employment status (being unemployed is related to a greater chance of applying, other variables being hold constant, and being an employee or self-employed is related to a lower chance of applying for the SSI relative to other employment groups such as students, pensioners, and disabled, other things being equal); and iv) size of the household (with single member households being more likely to apply for the program). Furthermore, we run a regression analysis to understand which variables affect a household/individual’s awareness of the SSI. The factors that are found to be positively associated in a statistically significant manner to someone’s awareness of the program are the person being unemployed, having received the social dividend (or other social benefits) and being a single-member household. Annex 2 presents the details of the regression analysis carried out. 2.2Targeting effectiveness The SSI program is very effective in identifying poor households; almost 60 percent of all SSI beneficiaries belong to the first decile, and 80 percent are poor. Figure 4 below shows the proportion of beneficiaries by income level and poverty status16. Remarkably, virtually all SSI recipient households are in the bottom 30-40 percent of the income distribution and 80 percent can be characterized as poor using an extreme relative poverty definition. Even those households which are not defined as poor still fall almost entirely in the bottom deciles of the income distribution, and therefore cannot be considered well-off. This, again, is impressive even in comparison with international standards. Recent figures from selected countries, show, for example, that the best performing programs cover at best seventy percent of the poorest households (Figure 5). Finally, about 65 percent of the program’s beneficiaries live in urban areas, broadly in line with the overall 16 The figures presented in Figure 4 are defined as the ratio of the number of individuals in a given group/category/income decile who live in a household where at least one member receives the transfer over the total number of SSI beneficiaries in the country. The total number of SSI beneficiaries in the country is calculated assuming that households split the benefit amount equally among all household members (in other words, it is the sum of all household members in SSI beneficiary households). All figures are of course weighted using nationally representative weights. 11 distribution of households within the country; according to ELSTAT data, 61 percent of households in Greece lived in urban areas in 2010. Figure 4: Share of Total SSI Beneficiaries in Each Group (%) 79.6 80.0 65.3 70.0 57.1 60.0 50.0 34.7 40.0 29.4 30.0 20.4 20.0 8.9 10.0 2.4 1.0 0.5 0.5 0.1 0.3 0.0 0.0 Figure 5: Share of Social Assistance Beneficiaries that are Poor in Greece and Selected Countries 90 80 70 60 50 40 30 20 10 0 GRC 2018 KSV 2016 SRB 2015 BIH 2015 ROU 2011 MNE 2010 BLR 2015 ALB 2012 Source: WB Calculations based on WB SpeeD data base and SSI Household Survey Data. Note: The SpeeD database does not include EU countries yet. The countries included in this graph were selected according to two criteria: 1) having data more recent than 2010; 2) being in the Balkan or Baltic Region. Greece outperformed all countries included in the Speed Database for which comparable social assistance data was available. (In all countries other than Greece, the poverty line is set as the maximum consumption of the first quintile post transfer; in Greece poverty is defined as being below 40% of national median income The program’s resources are used very effectively towards supporting poor households. Figure 6 presents the results of the same analysis carried out above but focusing on the program’s monetary resources. About two-thirds of the total benefits go to households in the first decile, and almost 85 percent of the program’s resources reach poor households.17 Once again, about 95 percent of the program’s funds are spent on households in the first three deciles, suggesting that the vast 17 The figures presented in Figure 4 are defined as the ratio of the transfer amount received by households in a given group/category/income decile over the total transfers received by all households in the country. All figures are of course weighted using nationally representative weights. According to the data collected for the purposes of this evaluation, the SSI program costs about 68.7 million Euros per month, above the average cost of the program in the October 2017- February 2018 period (63.6 million euros), but close to the current actual cost of the program according to IDIKA’s administrative database (69.7 million euros per month as of August 28, 2018). 12 majority of monies spent to provide SSI support to “non-poor� households are still being devoted to households which are not faring particularly well. Figure 6: Share of Total Transfer Amount Received by Each Group 100.0 84.1 80.0 66.7 65.5 60.0 34.5 40.0 22.1 15.9 20.0 6.6 2.5 0.9 0.2 0.6 0.2 0.3 0.0 0.0 Source: WB Calculations based on SSI Household Survey Data (Poverty defined as being below 40% of national median income) 2.3 Relative Incidence and Generosity The benefits granted through the SSI program constitute a significant source of income for households in the bottom decile and for poor households. Figure 7 shows the share of a given group or income decile’s total income made up by SSI benefits. According to the data, SSI benefit represent about 69 percent of the aggregate income of households in the first decile, and about one third of the aggregate income of the poor comes from the program. 18 One interesting feature of the analysis below is the dramatic fall between the incidence of the program in the total welfare aggregate of households in the first decile and those in the second decile (among which the SSI benefit constitutes only 5.6 percent of total income). This is related to two factors. First, there is a large proportion of zero-income households in the first decile, which results in a large difference between the welfare aggregate of the first and the second decile. Second, there are much fewer households in the second decile receiving the SSI relative to the first decile. Figure 7: Proportion of Group’s Aggregate Income Made up by SSI 69.4 70 60 50 40 31.5 30 20 5.6 10 1.0 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0 Source: WB Calculations based on SSI Household Survey Data (Poverty defined as being below 40% of national median income) 18The figures presented in Figure 7 refer to the relative incidence (in monetary values) of the program and are defined as the ratio of the transfer amount received by a group as a share of total welfare aggregate of the group. All figures are of course weighted using nationally representative weights. 13 The SSI is a fundamental contributor to the welfare of beneficiaries. Restricting the analysis to SSI beneficiaries only, Figure 8 shows that the SSI payments make up 73 per the total income of the SSI beneficiaries in the first decile; 56 percent of the total income of the poor is composed by the benefit. For households benefitting from the SSI in the second decile, the benefit makes up just over a fourth of their incomes, still a sizeable portion, and the share declines to about 17 percent in the third decile19. Figure 8: Transfer Received by Beneficiaries as a Share of Income of Beneficiaries 73.2 80.0 56.2 60.0 40.0 26.5 17.1 17.9 12.6 16.1 20.0 6.9 11.8 10.7 7.3 0 0.0 Source: WB Calculations based on SSI Household Survey Data (Poverty defined as being below 40% of national median income) Accordingly, beneficiaries consider the SSI benefit Table 1: Importance of SSI benefit on a very substantial contribution to their budget. household budget (%) Survey enumerators asked SSI beneficiaries to rate the Very insignificant 4.3 importance of the benefit received on their total Rather insignificant 6.9 budget. Almost 90 percent judged the SSI a very Rather significant 18.6 significant or a significant help. Only 4 percent of Very significant 70.1 respondents classified the help as very insignificant. Source: WB Calculations based on SSI Household Survey Data Note: Self-reported The targeting analysis of the SSI programs reveals that, overall, the benefit is effective at identifying the poor. However, it has a problem of under coverage, partly by design and due to budget limitations, and partly due to issues of non-take up. Table 2 presents the summary of the targeting assessment of the SSI. Using the relative extreme poverty definition, 20 percent of SSI beneficiaries are not-poor (the so-called leakage rate), but about two-thirds of the poor don’t receive the benefit (the so-called under coverage rate). As discussed above, the program’s eligibility thresholds and amounts were established with the intent of covering about 7 percent of the country’s population and to align the SSI’s coverage with the budgetary envelope available. As such, it is to be expected that a portion of the poor would not be covered by the program, considering that the extreme poverty rate now hovers around 15 percent. However, as the analysis of the first deciles alone reveals, a sizeable share of households at the bottom end of the income distribution did not apply to the program and have no knowledge of the SSI, pointing to the fact that outreach and communication efforts need strengthening to ensure that eligible households receive support, assuming of course that the budget to absorb a greater share of the population were to be made available. 19Estimates for deciles past the third should not be given too much weight as are based on a very limited number of observations (as shown above in the figures relative to the coverage of the program). We present them nevertheless for completeness. 14 Table 2: Under-coverage and Leakage of SSI Benefit – Different Poverty Lines Coverage of Under- Leakage the poor (%) coverage (%) (% of beneficiaries) 40% of median income 34.0 66.0 20.4 60% of median income 10.2 89.8 6.9 Source: WB Calculations based on SSI Household Survey Data 2.4 Poverty Incidence Quite expectedly, the SSI does not have much of an Table 3: Poverty* and Inequality Indicators20 impact on poverty incidence Poverty Poverty Inequality and inequality, but it does Headcount Poverty Gap Severity Inequality (Atkinson) reduce the poverty gap. (Gini) Rate According to the survey data, Pre-SSI 15.2% 9.9% 8.1% 38.3% 25.5 the program reduces poverty Post-SSI 14.4% 8.1% 6.2% 37.4% 23.0 by 0.8 percentage points, from % 15.2 percent in the absence of change -5.3% -17.9% -23.5% -2.4% -9.9% the program, to 14.4 percent Source: WB Calculations based on SSI Household Survey Data once the SSI benefits are taken *Poverty defined as being below 40% of national median income into account. Inequality, on the other hand, decreases by 0.9 percentage points, with the country’s Gini coefficient declining from 38.3 to 37.4 percent.21 However, the program is making a dent in the poverty gap, which declines by almost 2 percentage points (20 percent change) nationwide. In general, indicators more sensitive to the bottom end of the distribution (the poverty severity gap and the Atkinson index of inequality) display much larger variation following the transfer. This is likely related to the fact that the majority of beneficiaries are positioned at the very bottom of the income distribution. It is important to remember the reasons why the SSI is not affecting the national poverty rate much. First, the eligibility thresholds for the program are very low, and well below the poverty line even using the extreme relative poverty definition adopted throughout this report. This means that most SSI beneficiaries, even considering the transfers received, would not make it over the poverty line. Second, and strictly related to the above point, but more positively, precisely because the benefit appears to be so well targeted and effective at reaching the poorest, the poverty rate is not affected much even though beneficiary households are better off because of the program. 20The Poverty Gap is calculated as the average distance from the poverty line; the Poverty Severity index or FGT2 is calculated as the squared poverty gap; the Atkinson index is calculated as a measure of inequality more sensitive to changes in the income distribution. 21 The simulated impact is the change in a poverty or inequality indicator due to transfer, assuming that household welfare diminishes by the full value of that transfer. 15 3. Evaluation of program’s implementation and processes An important part of the questionnaires and the data collection carried out for this evaluation, and hence the analysis, focused on the business processes supporting the program’s implementation. This section presents selected results of this analysis, focusing on outreach channels, application and enrollment processes, payments, and linkages to other social services. The media (television in particular) and “word-of-mouth� are the main channels through which people heard about the SSI. Most of the respondents who were aware of the program heard about the SSI from media sources. Of these, about 75 percent heard about the program from television, while one out of three respondents derived information from the internet. “Word of mouth� also seems like an important source of information, with more than half of respondents being made aware of the program from relatives and friends. Figure 9: Source through which households found out about the SSI (% of Households) NGO Church / priest Sole answer Library With other Pamphlets Newspaper (Paper version) Radio Other Municipality staff KEP staff Paid tax preparer 5% Internet 3% 26% Family /friends /neighbors 13% 43% Television 22% 53% 0% 10% 20% 30% 40% 50% 60% 70% 80% Source: WB Calculations based on SSI Household Survey Data Thanks to the well-designed information system, the program’s application process has been proceeding without major obstacle; however, about 40 percent of applicants paid someone to help them file an application. Anecdotal evidence on the role of accountants in helping households apply for SSI support has been abundant over the last years and documented in the process evaluation of the program22, but the data collected finally allows us to verify and quantify this issue. One quarter of applicants paid an accountant as their sole source of support during the application process, while another 15 percent used the paid services of accountants along with other support (a friend or a relative, a social worker, etc.). Considering that municipalities’ employees, social workers or KEPs staff were available to help applicants filing an SSI application, the fact that 40 percent of applicants had to pay someone to file an application is worrying, and of course in direct contrast with the poverty alleviating objective of the program. Despite the many improvements in the application 22Marini, A., Zini M., Kanavitsa E. and Karakitsios A. (2016). A summary of the process evaluation of the first phase of the SSI implementation is included in Annex 3. 16 form, and the fact that more than one point of access was available for free (social services of municipalities and KEPs), the fact that many people still relied on accountants suggest that there is still room for improvement in the intake process. Be it as it may, the heavy reliance of accountants and the low SSI take up within the first decile of the income distribution does also point to the need for better communication and outreach efforts. Figure 10: Who helped applicants apply for the SSI Other Call center Sole answer Friend or relative With other KEP Social worker or employee at municipality office Paid individual (e.g. an accountant) 0% 10% 20% 30% 40% 50% Source: WB Calculations based on SSI Household Survey Data During their participation in the program, one fourth of beneficiaries saw their situation change, and 60 of these reported it. According to the rules of the program, beneficiaries facing any change in their household or economic status after the submission of the SSI application, had to report such changes within one month. The main changes that occurred after SSI application submissions were related improvements in household income, with 10 percent of beneficiaries having seen their income increasing and around 7 percent of beneficiary units having a member who became employed. Even if the percentage of reported changes remains relatively low, this is a big improvement compared to first phase of the rollout, when individuals were less aware of the importance of declaring such changes. However, the fact that about 40 percent of households which witnessed a change did not report it points to the lack of understanding of the program among the population, and to the relatively limited consequences for not abiding by its rules. The high number of changes in application status translated in a significant administrative burden for municipality officials and for IDIKA. With the objective of simplifying procedures for municipalities’ officials, the program’s key business processes have been recently modified. According to the new Joint Ministerial decision, which was approved on June 15, 2018, the benefit will remain constant for 6 months after acceptance into the program, and almost no changes to applications will be allowed. 17 Figure 11: Changes occurred after submission of SSI application Death of a household member Divorce Marriage Sole answer Change in total taxable value of assets With other Household member lost job A household member who declared being a guest… Birth of a household member Household member became employed. even as… Increase in household income Decrease in household income 0% 2% 4% 6% 8% 10% 12% Source: WB Calculations based on SSI Household Survey Data In contrast to what economic theory predicts, most beneficiaries are indifferent between receiving the SSI’s income support in cash in their bank account or in in the form of a prepaid bank card23. Economic theory suggests that individuals should always prefer cash to other (and less liquid) form of payments, as cash can be used for more purposes. However, about 58 percent of beneficiaries reported being indifferent between the two forms of payment. Thirteen percent preferred receiving the money in a prepaid bank card (which does not allow for cash withdrawals but allows for payments at any POS). About 29 percent preferred cash deposited directly in their bank account (which can be withdrawn at ATM machines), as they planned to use the funds for expenses which did not accept electronic payments. The implementation of the second and third pillars of the program remains very limited. Apart for the first pillar of the program, income support, the SSI envisions linking beneficiaries to labor reintegration measures and to other social services. During the first phase of the rollout of the SSI no conditionality was imposed on beneficiaries: municipality and community center officials were expected to provide information and proactively connect them to existing services to which they were eligible. Yet, three out of four beneficiaries reported not having received any information on complementary services and other social programs, which was expected to be the first step towards the second pillar of the SSI. Quite tellingly, only about 55 percent of beneficiary units had applied and benefitted from the European Fund for the Most Deprived (FEAD) program, or less than 50 percent received discounts on their electricity bills, which in theory are granted automatically to SSI beneficiaries who apply for them (see section 4 for more details). 23 In line with the program’s legislation, the SSI benefit is paid monthly partly in cash and partly through a prepaid card (unless the benefit amount has been calculated to be less than €100, in which case it is paid all in cash). 18 4. Profile of Beneficiary Households According to the data collected for Figure 12: Size of SSI Beneficiary Households this evaluation, SSI beneficiary 40 households are on average larger 35 35 than households nationwide. 35 However, the proportion of single- Percentage of Households 30 26 member households is considerably 25 22 larger among SSI units than across 20 the country, which is unusual by 18 20 16 14 international standards. The 15 average SSI recipient household in the 10 6 dataset is composed of 2.47 4 individuals, against a national average 5 12 01 00 00 of 2.36. The share of single-member 0 households is however much higher 1 2 3 4 5 6 7 8 9 among SSI beneficiary households Household members relative to the country average (35 all households SSI recipient households percent versus 26 percent), and the Source: WB Calculations based on SSI Household Survey Data share of 2-member households is much higher nationwide than within SSI households. Over 95 percent of SSI households have 5 members or fewer. Households with four, five, and six members are however more prevalent within SSI beneficiary units relative to what one observes nationwide, driving the average for the SSI category upwards and above the national average. Worryingly, the figures presented above on the distribution of the size of SSI households, based on the data collected for the purposes of evaluating the SSI are in sharp contrast to IDIKA’s SSI administrative database, which shows smaller households. According to IDIKA’s data, which relies on the program’s application forms, the average SSI household has 2.14 members, lower than the average among SSI units according to the evaluation data but, most importantly, well below the average household size nationwide. This raises serious concerns for two reasons. First, international experiences tell us that it Figure 13: SSI Beneficiary Households by Number of is highly unusual for poor households Dependent Children to be smaller on average than the average household within a given Percentage of Households 80 71 country. Second, what seems to be 70 60 driving the average down in IDIKA’s 60 database is the extremely high 50 proportion of SSI single-member 40 30 households, which reaches 49 percent, 1516 16 against the 35 percent among the same 20 12 2 6 group based on survey data presented 10 01 00 00 0 above. This evidence points to the 0 1 2 3 4 5 6 possible occurrence of “household splitting� (i.e. reporting a household Number of Dependent Children composition different from the actual all households SSI recipient households one for tax or benefit reasons) among households at the bottom end of the Source: WB Calculations based on SSI Household Survey Data income distribution. As the prevalence of 19 single member households is unusual and still largely unexplained, these households are the focus of the next section. In line with expectations, on the other hand, SSI Table 4: SSI beneficiary households by beneficiary households tend to have more Dependent Children children than the average Greek household. While Number of Percent Percent 71 percent of Greek households have no dependent dependent (all (SSI children24, 60 percent of SSI households are made of children households) Households) adults25 only. SSI beneficiary units with two and three 0 70.85 60.14 children are significantly more prevalent than across 1 14.61 16.31 the country. 2 11.67 16.26 SSI beneficiaries tend to be more vulnerable than 3 2.43 5.96 the overall population: relatively less educated, 4 0.40 0.76 unemployed, and with higher proportion of people with disabilities. Two-thirds of SSI main 5 0.02 0.36 applicants are men, while a third women. More than 6 0.01 0.21 half of SSI beneficiaries (52 percent) have completed 7 0.01 0.00 primary/lower secondary education or less, against a Total 100.00 100.00 national average of 35 percent. Less than 7 percent of Source: WB Calculations based on SSI Household beneficiaries have completed tertiary education, Survey Data more than half of the countrywide figure (15 percent). The share of individuals with disability among SSI beneficiaries is twice as high the national average (4 percent versus 2 percent). About 71 percent of SSI main applicants report being unemployed in the survey, and three out of four reported being registered with OAED, the Greek Public Employment Service. This is in contrast once again to the administrative database managed by IDIKA, according to which while the share of unemployed SSI main applicants is at 77, only 54 percent report being registered with OAED. The proportion of the SSI beneficiaries who are not Greek (16 percent), is higher than the national figure (7 percent). About one third of the program’s beneficiaries live in a rented dwelling, against a national average of 20 percent, and about 16 percent live in an accommodation provided to them rent-free, a figure twice as high as the national average. Figure 14: Benefits received by SSI beneficiary households Social tariff of municipalities and Municipal 2% Sole answer Companies with other Social tariff of water providers 10% Transport allowance 6% 34% Free Medical Treatment of persons not entitled to 8% 26% health benefits by a social security institutions Social tariff of power providers 16% 32% 0% 20% 40% 60% Source: WB Calculations based on SSI Household Survey Data 24 Dependent child is here defined as per tax declarations (i.e. being below 18, or being below 24 and being a student or unemployed). Adults, on the other hand, are non-dependent children. 20 Many beneficiaries benefit from Table 5: Benefits received by SSI beneficiary discounted tariffs, especially electricity households related expenses, and 70 percent received Humanitarian Crisis recipients % the social dividend. About 48 percent of Yes 16.29 survey respondents reported receiving No 83.71 discounts on their electricity bills (either as Social Dividend recipients % the only support received by their Yes 69.82 households, or in addition to other No 17.77 measures). This is however a very low Missing Data 12.41 proportion given that SSI beneficiaries are, at Source: WB Calculations based on SSI Household Survey Data least in theory, automatically eligible for electricity subsidies according to the law. Box 2 below sheds some light on the electricity subsidy program and the possible reasons for the very low take up. Again, this is very surprising given that SSI beneficiaries would be automatically eligible for the benefit. Finally, even though 7 out of 10 SSI households received the social dividend, this is again a relatively low share as all SSI beneficiaries should have benefited from the one-off payment given the eligibility thresholds of the social dividend.26 Box 2: Zoom in on the Electricity Subsidy The electricity subsidy (or social residential tariff) was first introduced in 2010. Its main objective was to provide some discount on the electricity bill of the long term unemployed, families with three or more children, and people with disabilities. A 2018 Ministerial Decision (Government Gazette 242/B/01.02.2018), amended the groups of eligible beneficiaries and the eligibility criteria (reducing the number of eligibility brackets from four to two), the discount rates on electricity consumption, and simplified the application process allowing people to apply online. Beneficiaries, eligibility criteria & discount rates The beneficiaries27 of this subsidy can be split into two categories: A & B. Category A includes anyone who meets the criteria for the Social Solidarity Income (SSI) and has been already determined as eligible for the SSI program. Category B includes anyone who meets the following criteria: i. The actual or imputed total annual household income, based on the latest income tax return should fall below the thresholds listed below: Table B.1. Income threshold per household type28 Income threshold Household type (€) One-person household 9,000 Household with two adults or a single parent family with one child 13,500 Household with two adults and one child or a single parent family with two children 15,750 26 Part of the explanation for the low coverage of the social dividend among SSI beneficiaries could be linked to the timing of the survey, which began in December 2017, slightly before the social dividend payment. 27 According to the most recent assessed income tax return, members of the household should not fall within the provisions on luxury tax and do not report expenses for fees of recreational boats’ crews, for tuition in private schools, for domestic workers, car drivers, private tutors and other staff, as specified in the respective codes of the tax declaration form (E1 form). 28 If households include one or more individuals who are 67 percent or more disabled, the income thresholds are increased by €8,000. If households include one or more persons requiring mechanical support from medical devices provided at home, which are vital for them, the income thresholds above a re increased by € 15,000. For each additional adult, the income thresholds are increased by € 4,500 and for each additional minor member by € 2,250, up to a total threshold of € 31,500, irrespective of how many people live in the household. The upper threshold of €31,500 is increased by € 8,000 for a household which has one or more persons with 67 percent or more disability and by €15,000 for households with one or more persons who require mechanical support from medical equipment, provided at home, which is vital for them. 21 Household with three adults or two adults and two children or a single parent family with 18,000 three children Household with three adults and one child or two adults and three children or a single 24,750 parent family with four children Household with four adults or two adults and four children or a single parent family with 27,000 five children ii. Households must have real estate property in Greece or abroad with a taxable value below €120,000 for single-member households, increased by €15,000 for each additional member, up to €180,000. The electricity subsidy applies to the total 4-months consumption (or 120-days consumption), up to the consumption thresholds specified for each category of beneficiaries in the table B.2 below: Table B.2. Consumption limits per household type29 4-months consumption Household type threshold One-person household 1,400 kWh Household with two adults or a single parent family with one child 1,600 kWh Household with two adults and one child or a single parent family with two children 1,700 kWh Household with three adults or two adults and two children or a single parent family 1,800 kWh with three children Household with three adults and one child or two adults and three children or a single 1,900 kWh parent family with four children Household with four adults or two adults and four children or a single parent family 2,000 kWh with five children The electricity subsidy is not applied to consumption levels below 200 kWh in any 4-months period, which is likely to be too low of a threshold to deter people from applying to the program. To give some context, in 2011, based on ELSTAT data, the average yearly household consumption of electricity in Greece was 3,750 kw/h, or about 1,250 kw/h every 4-months, well above the 200 kw/h threshold mentioned above. The electricity supplier will apply the discount rates as shown in the table 3 below. Table B.3. Discount rates on electricity supply charges in €/kWh30 Category A (SSI beneficiaries) 0.075€/kWh Category B 0.045€/kWh Application process • The application must be submitted by the person responsible for submitting the household’s income tax return or his/her spouse, provided that the electricity meter is already in his/her name or that of his/her 29 If households include one or more individuals who are 67 percent or more disabled, the consumption thresholds are increased by 300 kWh, while if households include one or more persons requiring mechanical support from medical devices provided at home, which are vital for them, the consumption limits above are increased by 600 kWh. For each additional adult, the consumption levels are increased by 200 kWh and for each additional minor member by 100 kWh, up to a total threshold of 2,400 kWh, irrespective of the number of persons that the households consist of. The upper threshold of 2,400 kWh is increased by 300 kWh for a household which has one or more persons with 67 percent or more disability and by 600 kWh for households with one or more persons who require mechanical assistance from medical equipment, provided at home, which is vital for them. 30 For example, based on 2018 prices, for a total 4-months consumption of 1,100 kWh, the supply charge is 0.0946 €/kWh plus a fixed amount of €1.52. Thus, the total cost of the 4 -months consumption is 1,100*0.0946 = €104.06 adding €1.52 results €105.58, without applying any discount and not adding several other charges that are usually included in the final amount of the bill. Now, replicating the same exercise for both categories of potential beneficiaries we will get, ✓ Category A: Supply charge after the discount rate: 0.0946 – 0.075 = 0.0196 €/kWh. The total cost of the 4-months consumption for a SSI beneficiary unit would be: 1,100*0.0196= €21.56 plus €1.52. The total cost of electricity supply after the subsidy would be €23.08 so the subsidy corresponds to €82.50 (€105.58 - €23.08). ✓ Category B: Supply charge after the discount rate: 0.0946 – 0.045 = 0.0496 €/kWh. The total cost of the 4-months consumption would be: 1,100*0.0496= €54.56 plus €1.52. The total cost of electricity supply after the subsidy would be €56.08 so the subsidy corresponds to €105.58 - €56.08 = €49.50. 22 spouse (i.e. to the main applicant). Other members of the household are not able to apply to the electricity subsidy even if the meter is in his/her name. • Applicants must apply for the subsidy every year. If they submit the application before the income tax return period and are accepted, they must resubmit it within one month from the tax filing deadline, so that their eligibility for the subsidy program can be re-examined based on the most recent tax data. • Applications to join the new program are submitted electronically via IDIKA’s website online (there is not any deadline for receiving applications. Households can only receive the electricity subsidy for their main dwelling. Coverage Around one third of SSI beneficiaries benefiting the discount in electricity bills. As of July 18 2018, 105,574 SSI beneficiary units had applied and been deemed eligible for the Category A of the electricity subsidy, corresponding to 249,217 individuals. This number remains relatively low compared to the total number of households receiving the SSI (over 300,000 households as of early September 2018). One possible explanation for the low take up rate of the electricity subsidy among SSI beneficiaries could be found in the cost related to changing the name on the electricity meter . As we have seen above, applications for the electricity subsidy must be submitted by the person responsible for submitting the household’s income tax return or his/her spouse, provided that the household’s electricity meter is in his/her name or in that of his/her spouse (i.e. to the main applicant). However, many people in Greece do not change the name linked to the electricity meter when they move to a new house since to do so households must pay a non-refundable deposit of a minimum €130 to cover potential future arrears31. This amount is quite considerable both in light of the subsidy received (about 90 euros every four months for the average Greek family, and likely less for extremely poor households, which tend to consume less energy than average), and given the severe cash and budget constraints faced by the vulnerable population the SSI program is targeting. Sources: https://www.dei.gr/en/oikiakoi-pelates/timologia/enimerwsi-gia-to-koinwniko-oikiako-timologio- kot, and Government Gazette 242/B/01.02.2018 4.1The Unusually Frequent Single Member Households Single member households among SSI beneficiary units are suspiciously more frequent than survey data tells us. As shown above, the share of single-member households is almost ten percentage points higher among SSI beneficiary households relative to the national average; more worryingly, and in contrast to what our survey shows, IDIKA’s database reports that almost half of SSI beneficiary households are made of a single person. To complicate matters further, analyzing the profile of these households alone does not reveal any major clue as to why we observe so many of them. They do tend to be a little younger than all SSI recipients and of all single-member households in Greece (about 30 percent of SSI single member households are between 25 and 39, against 22 percent among all SSI recipients, and 15 percent among all single-member households in the country. About 57 percent of single member households are between 40 and 64, against 50 percent among all SSI beneficiaries). They are also relatively less educated than all SSI recipients and of all single- member households in Greece, and tend to live in rent-free dwellings more frequently (24.5 percent versus 16.2 percent). However, they are no more rural than the rest, and the share which report being unemployed is broadly in line with that observed among all SSI beneficiary units (78 percent versus 77 percent). Overall, there is no feature that stands out among SSI single-member households that can point to the reason behind their frequency. 31 This cost depends on the size of the house (the square meters based on which the estimation of electricity consumption will be calculated) or the agreed power supply between the client and the provider. However, this cost cannot exceed (apart from some specific exceptions) the estimated cost for two sequent electricity bills. 23 Differences in the way in which households are defined in our survey and for the purposes of the SSI explain only part of the discrepancy in the shares of single-member households. One could argue that the reason for the discrepancy observed could be linked to the fact that the SSI application process relies, in practice, on household composition as declared in the most recent tax return32, whilst the data collected through the survey relies on a “pure� definition of households (i.e. all those living under the same roof). To verify whether these definitional discrepancies are the ones driving the “unexplained� share of single-member households, we recreated in our data set households following the tax code. Using this definition, the share of single-member households reaches 40 percent, higher than the 35 percent observed by sticking to a “pure� definition of household, but still below the 48 percent found in the SSI administrative database. Therefore, there are approximately 25,000 households (9 percent of about 275,000 total accepted application nationwide according at the time of our survey) which claimed to be single-member for SSI purposes and were receiving benefits but cannot be verified in the data. Incentives are likely to matter a lot more; most likely a sizeable share of SSI beneficiary households could be splitting to maximize the benefits they receive from the SSI program. Given the structure of the SSI benefit, which assigns 200 euros to the first adult individual (the main applicant) and 100 euros to the second adult (or first dependent child in the case of single parent households), households have the incentive to tinker with their household composition and split for SSI purposes.33 Based on the figures above, assuming all of 25,000 single member households which cannot be verified in our survey are the result of some form of household splitting, at 100 euros per month in extra benefits, this could be costing the program about 30 million euros on a yearly basis, or 3.5 of the total budget. Finally, these results point to the need of revising some of the current parameters of the program, including the benefit amount and the equivalence scale. One could for example consider the possibility of decreasing the amount of the benefit granted to the first individual whilst increasing the weight of the children. The World Bank team remains available to carry out additional simulations and analysis to suggest options and possible revisions to the program’s parameters. Conclusion and Policy Implications This note presents the results of the evaluation of the Greek Social Solidarity Income (SSI) program, a last resort safety net program targeted to extremely poor households with the objective of alleviating poverty in Greece. The objective of the evaluation, and hence of this report, is to assess the effectiveness of the program’s targeting methodology as well as its impact on poverty indicators. The findings presented are based on data collected through a tailor-made nationally representative survey run especially for the purposes of evaluating the SSI. The findings of the evaluation are largely positive. First, the SSI program is very effective in identifying poor households, with almost 60 percent of all SSI beneficiaries belonging to the first 32 For SSI purposes, a household is made of all those living under the same roof. However, the IT platform supporting the program’s verification and eligibility determination pre-populates one’s application for with the household information drawn from one’s most recent tax return. Households have of course the possibility of amending such information if the household composition has changed relative to the tax filing period. However, in practice, the composition of a household for tax purposes is the one really used in most instances for the purposes of the program. 33 Consider, for example, the case of a household of two individuals. If eligible for the SSI, they would receive a monthly payment of 300 euros. However, if they managed to claim to live separately (and their tax records could somehow support that), they could each apply to the SSI separately and, if eligible, receive 200 euros each per month. Alternatively, consider the case of a household made off two adults and one dependent child. Their total monthly benefit, if determined eligible for the SSI, would be 350 euros per month. However, by registering as two households (one single-member household, and a single-parent with one dependent child household) they could receive 500 euros per month. 24 decile, and 80 percent of them being poor using a relative extreme poverty definition in line with that adopted by Eurostat. This is impressive especially when compared to many social assistance programs in Europe and Central Asia. Second, the program’s resources are used very effective towards supporting poor households. About two-thirds of the total benefits go to households in the first decile, and almost 85 percent of the program’s resources reach poor households; 95 percent of the program’s funds are spent on households in the in the first three deciles. Third, the program constitutes a significant source of income for households in the bottom decile and for poor households, with SSI benefits represent about 69 percent of the aggregate income of households in the first decide, and about one third of the aggregate income of the poor. The program appears to be very well-received by the population, who consider it a significant help. However, the program still suffers from low coverage, in line with the program’s design and budgetary allocation. Nationally, about 6.5 percent of the population receives the SSI, remarkably close to the program’s target of reaching about 7 percent of the Greek population. Using a relative definition of extreme poverty, about one third of households with a total disposable income below 40 percent of the national median receive SSI support. These findings reveal that the SSI is extremely effective at identifying the poor; the program displays in fact inclusion errors almost unheard of by international standards. In light of the above, and considering that the system built around the GMI has set new standards for social assistance programs in Greece, an expansion of the program to cover a greater portion of the poor would probably represent an efficient use of resources towards further alleviating poverty in Greece. Most worryingly, a third of households in the first decile of the income distribution receive SSI benefits, pointing to a significant problem of non-take up or under-coverage of the intended program beneficiaries. One would expect the coverage of the program among households in the bottom decile to be much higher, and somewhat close to 70 percent. By analyzing households in the first decile we find that almost 60 percent of said households did not apply to the SSI; a sizeable portion of these (about one-fourth, or 15 percent of households in the first decile) had never heard of the program, and half (or 31 percent of households in the first decile0 had heard about the SSI but did not know any detail and hence never applied. Eleven percent of households in the first decile reported being familiar with the program but chose not to apply for unspecified reasons. We explore different possible explanations for the low take up of the program and find that lack of information about the program within the target population is at least part of the explanation, pointing to the need to stronger communication and outreach efforts. Thanks to the well-designed information system, the program’s application process has been proceeding without major obstacle; however, about 40 percent of applicants paid someone to help them file an application. This is worrying, and of course in direct contrast with the poverty alleviating objective of the program; it also reinforces the point above related to the need for better communication efforts. Expectedly, the implementation of the second and third pillars of the program remain very limited. Three out of four beneficiaries reported not having received any information on complementary services and other social programs. International experiences show that it is normal for programs such as the SSI to focus first on an effective implementation of the first pillar and then to focus on additional features such as granting beneficiaries access to additional social services or labor reintegration measures. Almost two years since the launch of the program nationally, and five years since the initial pilot, the implementation of the SSI’s second and third pillars will remain the single biggest challenges for the SSI going forward, and the key to its long-term functioning and to addressing some of the concerns around the participation of households with informal income in the pogram. The proportion of single-member households is considerably larger among SSI units than across the country, which is unusual by international standards. Furthermore, single member 25 households among SSI beneficiary units based on the program’s administrative database are many and suspiciously more frequent than survey data tells us. Most likely a sizeable share of SSI beneficiary households is splitting to maximize the benefits they receive from the SSI program; this could be costing the program up to 30 million euros per year. This points to the urgent need to review applications submitted by single-member households, ideally implementing random checks among a subset of these, or carrying out a mass suspension of said applications until the information provided can be re-checked. Finally, these results point to the need of revising some of the current parameters of the program, including the benefit amount and the equivalence scale. One could for example consider the possibility of decreasing the amount of the benefit granted to the first individual whilst increasing the weight of the children. The World Bank team remains available to carry out additional simulations and analysis to suggest options and possible revisions to the program’s parameters. 26 Annex 1. SSI Eligibility Determination: Criteria To determine program eligibility, adequate targeting procedures are needed to reduce both inclusion and exclusion errors that lead to other negative consequences throughout the implementation of the Program. Objective targeting uses information provided by potential beneficiaries on key income and socioeconomic variables of their households, which are assessed to determine eligibility. Below is a description of the process and different criterion for determining eligibility. To be eligible for the program, individuals or families belonging to the potential recipient unit must simultaneously meet ALL three criteria: A. Income criteria B. Assets criteria C. Residency criteria If at least one criterion is not met, the applicant unit is deemed ineligible for the program. A. Income criteria The income (calculated for eligibility purposes) of the potential recipient unit in the 6 months prior to submission of the application cannot exceed the income threshold for each type of household; that is, the maximum amount of income support is (See Figure A1.1 for additional information on monthly payments and Table 2 for examples): ✓ 200 euros per month for a one-person household ✓ 100 euros for each additional adult (i.e. an extra 50 percent added to the basic amount) ✓ 50 euros for each minor (i.e. an extra 25 percent is added to the basic amount). However: ✓ Single parent household: the first minor receives a maximum of EUR 100 income support. ✓ For single parent families, one parent must be unmarried, widow or divorced and must actually and exclusively or by court have custody of the child or children: the first underage child is counted as an adult for the calculation of the guaranteed amount. The monthly benefit amount is the difference between the six-month guaranteed amount and the six- month declared income of the household divided by six. 27 Figure A1.1 Monthly Maximum Benefit Amount or Income Eligibility Criteria The table below provides examples of 6-month guaranteed amount for different recipient units (the monthly guaranteed amount is in parenthesis): The total household income, after receiving the SSI benefit amount, cannot be below these amounts: Table A1.1: Examples of semi-annual guaranteed amounts for different recipient unit Six-months guaranteed amount Recipient unit composition Single adult (€200)*6 = € 1,200 Single adult with one minor child (€ 200 + €100)*6 = € 1,800 Couple with no dependents (€200 + €100)*6 = € 1,800 Couple with one minor child (€200 + €100 + €50)*6 = € 2,100 Couple with two minor children (€200 + €100 + €50 + €50)*6 = € 2,400 Single adult with one adult dependent (€ 200 + €100)*6 = € 1,800 Couple with one adult dependent (€ 200 + €100 + €100)*6 = € 2,400 Couple with one adult dependent and one minor child (€ 200 + €100 + €100 + €50)*6 = € 2,700 Single adult with two minor children (€200 + €100 + €50)*6 = € 2,100 ✓ Each additional adult in the recipient unit: the guaranteed amount is increased by 50 percent, i.e. €100 per month (€600 per 6-month). ✓ Each additional child in the recipient unit: the guaranteed amount is increased by 25 percent, i.e. €50 per month (€300 per 6-month). ✓ For single parent families, one parent must be unmarried, widow or divorced and must actually and exclusively or by court have custody of the child or children: the first underage child is counted as an adult for the calculation of the guaranteed amount. 28 Total income is calculated to determine potential eligibility according to pre-established rules. What follows is an explanation of the types of incomes that will be reported in the application, and how total income will be assesses to compare against the corresponding threshold for each recipient unit in order to determine potential eligibility. If the assessed income falls below guaranteed amount, the recipient unit will be considered potentially eligible and incomes will be cross checked with the latest income tax data and other available databases. If inconsistencies or missing information are found, the applicant will be notified and will be asked to provide additional documents to the corresponding municipality office within 15 days. ✓ Income refers to income received by each member of the recipient unit during the 6 months prior to the month of application. ✓ The following incomes are considered for eligibility purposes and are declared in the application form: o Total gross income of all classes (of domestic or foreign origin) prior to deducting taxes, but net of contributions for social security. o All benefits and other support received by the members of the recipient unit, and income exempt from tax or taxed in a special way. The following are not counted as income: ✓ 20 percent of the actual net income from salaried services, including those supplied with services rendered invoice or labor ticket (ergosimo) and amounts from training, community work, or any other employment program; ✓ All non-contributory disability benefits provided by the State. In those cases when adult members of the recipient unit find a job (temporary, occasional or permanent job) after being accepted in the program, the following income will be disregarded: ✓ 100 percent of the salary from the new job will be discounted from the calculation of income during the first month; ✓ 40 percent of the salary from the new job will be discounted for the next 2 months. After 3 months the household’s eligibility will be re-determined and if the income puts the household above the relevant thresholds, SSI will be discontinued. The disregard from income related to a new job will be granted only once during the duration of phase one of the roll out. 29 Box A1.1: Determining Total Income for Eligibility Determination – An Example Consider a recipient unit made up of a couple with 1 minor child and one additional adult (for instance one grandparent, all living under the same roof) The table below shows the income of each individual for the past 6 months. Grand Income category Husband Wife Child TOTAL Parent Gross income Salaried services, income acquired with services € 2,000 – rendered invoice or labor 20% = € ticket and amounts by €0 € 2,000 €0 €0 2,000 – training sources, charity €400= € work programs or other 1,600 programs Pensions €0 €0 €0 € 2,760 € 2,760 Farming activities €0 €0 €0 €0 €0 Commercial enterprises € 500 €0 €0 €0 € 500 Liberal professions €0 €0 €0 €0 €0 Real estate €0 €0 €0 €0 €0 Capital € 50 €0 €0 €0 € 50 Foreign-source income €0 €0 €0 €0 €0 Non-taxed benefit income Family benefit € 480 €0 €0 €0 € 480 TOTAL ASSESSED € 5,390 INCOME The total assessed income for the household above is € 5,390 per year, or 2,695 per semester, which is below corresponding guaranteed amount ((€ 200 + €100 + €100 + €50)*6 = € 2,700), this household is potentially eligible for the program according to the income criterion. Notice that the total income for the household is really € 5,790. However, because the wife earned € 2,000 in net income from “salaried services, including those supplied with services rendered invoice or labor ticket (ergosimo) and amounts from training sources, charity work programs or any other employment program�, 20 percent of € 2,000, or € 400, were deducted from her income. Total assessed income is thus lower than total income, and in this example it is also lower than the threshold, making this household potentially eligible for the program. Total assessed income will be lower than total income whenever any members of the recipient unit receive income from “salaried services, including those supplied with services rendered invoice or labor ticket (ergosimo) and amounts from training sources, charity work programs or any other employment program�. Note that income that is taxed and subject to social security incomes is assessed before taxes (i.e. gross of taxes), but after social security contributions. All declared incomes will be subject to crosschecks with government databases as explained in the section below. Any inconsistencies will trigger a validation process with the municipality. B. Assets criteria In addition to the income criteria stated above, potential recipient units must also meet the assets criteria. If either the value of their real estate or financial assets surpasses the thresholds stated below, the applicant is considered ineligible for the program, regardless of their income level. The same occurs if the objective expenditure of their movable property surpasses the threshold found below. Finally, the ownership of certain assets (as listed below) will also render potential beneficiaries ineligible for the program. Applicants (including all members of the household) will be asked to report information regarding real estate and moveable property, in Greece and/or abroad, in the same format as they submitted it in the E1 form (the tax declaration form) and ENFIA (the single property tax form). Applicants will also be asked for information regarding the value of holdings in bank accounts and other financial institutions for all members of the household. In order 30 to prove their financial situation, applicants may later be asked to provide statements from banks and/or other financial institutions. The explanations below serve as guidance to the municipalities and KEPs in case the applicants have questions or corrections to the pre-populated application forms or questions about rejections. Following are the thresholds that must be met with respect to assets: Real property in Greece and/or abroad: ✓ Total taxable value may not exceed €90,000 for the first individual, increased by €15,000 for each additional household member with an overall maximum threshold for each recipient unit of €150,000. ✓ Example: Consider a household consisting of a married couple, one additional adult (for instance a grandparent), and one child. The taxable value of the real estate owned by all of the members of the household may not exceed (€90,000 + €15,000 + €15,000 + €15 ,000) = €135,000. Movable property (passenger cars of private or mixed-use and motorcycles) in Greece and/or abroad: ✓ The objective expenditure may not exceed €6,000 in total; and, The objective expenditure for motor vehicles is calculated according to Article 31 of Law 4172/2013 and is based on the first year of circulation and cubic centimeters (cc’s) of the vehicle. The annual objective expense for a passenger car for private use is fixed as follows: Table A1.2: Annual objective expense for a passenger car Cubic centimeters Objective expenditure Up to 1,200 €4,000 More than 1,200 up to 2,000 €4,000 + €600 per 100 cc’s over 1,200 More than 2,000 up to 3,000 €4,000 + €900 per 100 cc’s over 1,200 More than 3,000 €4,000 + €1,200 per 100 cc’s over 1,200 The above amounts of annual objective expense from each car are reduced according to its age, which is calculated as of the first year of circulation in Greece, as follows: ✓ At a rate of 30 percent for a period of more than 5 years and up to 10 years. ✓ At a rate of 50 percent for a period of more than 10 years. The annual objective expense does not apply to passenger cars for private use with a certificate of authenticity issued by an international or domestic body competent to issue such certificate, as well as passenger cars for private use, which are especially adapted for physically disabled people. Box A1.2: Determining the Annual Objective Expenses Related to Private Motor Vehicles – An Example Consider a household that has three cars, as shown in the table below. Because the total objective expenditure for the three cars belonging to this household is equal to €5,640 and thus below the threshold of €6,000, the household is potentially eligible for the program. Adapted for Year of first Car CC’s physically disabled Objective expenditure circulation person 1 1,200 2001 No €4,000 * 0.5 = €2,000 (€4,000 + (€600*2))* 0.7 = 2 1,400 2008 No €3,640 3 2,200 2014 Yes No objective expenditure TOTAL OBJECTIVE €5,640 EXPENDITURE 31 Financial assets (in Greece and/or abroad): ✓ The total amount of deposits of all the members of the recipient unit in all credit institutions and/or the current value of shares, bonds, etc. over the period of the 6 months prior to the application may not exceed six times the six-month amount of the income threshold corresponding thereto. ✓ Example: Consider a household consisting of a married couple and two minor children. Both the wife and the husband each have separate checking and savings accounts, for a total of four accounts; none of the children have any financial accounts.. If the total value of the four accounts combined exceeded (€2,400*6) = €14,400 during any of the 6 months prior to the month of application, the household would not be eligible for the program. Asset Filters: Finally, if any of the following assets are owned by a member of the assistance unit, the entire unit is rendered ineligible for the program: ✓ private recreational boats (exceeding 5 meters in length and with engine power exceeding 50 cubic centimeters), ✓ aircraft, ✓ helicopters, ✓ gliders and ✓ swimming pools C. Residence criteria The applicant and all the members of the applicant unit (except newly born[1]) must also meet a residence criterion. They must reside lawfully and in Greece. [1] Newly born is defined at 6 months of age or less. 32 Annex 2. Low Take up in the First Two Income Deciles - Regression Analysis The first regression run had as a dependent variable “SSI_app� (i.e. the yes/no answer to the question “did your household apply for participation in the SSI program �). The sample was restricted to the household heads of the first two deciles. Only the heads were chosen as most of the relevant questions for this analysis were asked at the household level. Both SSI beneficiaries and non- SSI beneficiaries were included in the analysis as excluding those who receive the benefit would have restricted the sample to levels too low for confidence. The regression was therefore run among 796 observations (out of which 492 had applied and 304 had not). The explanatory (independent) variables that were selected are listed in Table A2.1. Table A2.2 presents the results of the regression. Table A2.1. Description of explanatory variables used in regression Variable Description Type Reference category age continuous - sex dummy female people who have never attended any level of education, people with higher educ_low have some pre-primary education or incomplete primary, dummy education have primary or lower secondary education labor status = student, in retirement, disabled, unemp labor status = unemployed dummy soldier, domestic tasks, other labor status = student, in retirement, disabled, employed labor status = employee or self-employed dummy soldier, domestic tasks, other living in the rest of reg_at living in Athens or Thessaloniki dummy Greece size2 two-person households dummy single-person households size3 three-person households dummy single-person households size4pl four or more people households dummy single-person households people who know the aware2 people who have heard of SSI but don’t know the details dummy program quite well people who know the aware3 people who are not aware of the program dummy program quite well living in rural/semi-rural urban living in urban areas dummy areas non-recipients of social dividend recipients of social dividend dummy dividend recipients of child benefits, unemployment benefits, non-recipients of these othben disability benefits, food card or humanitarian crisis dummy benefits benefits recipients of free medical treatment, transport allowance, social tariff of power providers, social tariff of water non-recipients of these othassist dummy providers, social tariff of municipalities & municipal social services companies (“otherbenefits� variable) people with negative perceived eligibility (SSI_notapply=1 i.e. they have stated that they didn’t no negative perceived notqual dummy apply because the household would not qualify for the eligibility program) accommodation is rented owner accommodation is owned by the household dummy or provided rent-free 33 Table A2.2. Linear regression coefficients Variable Coefficient Std. error age 0.000 0.001 sex 0.025 0.021 educ_low 0.023 0.020 unemp 0.105*** 0.029 employed -0.071*** 0.027 reg_at -0.018 0.023 size2 -0.090*** 0.025 size3 -0.052* 0.029 size4pl -0.055* 0.028 aware2 -0.317*** 0.025 aware3 -0.756*** 0.027 urban -0.003 0.023 dividend 0.045** 0.021 othben 0.011 0.025 othassist 0.007 0.020 notqual -0.525*** 0.025 owner -0.028 0.021 _const 0.831 0.056 N 796 Notes: * p<0.10; ** p<0.05; *** p<0.01 Adjusted R-squared: 0.7319 The second regression run had as a dependent variable the level of awareness of the SSI (i.e. whether or not the respondent knew the program quite well, with the reference category being not knowing about the program or having heard about it but not knowing any detail. The sample was restricted to the household heads of the first two deciles. Only the heads were chosen as most of the relevant questions for this analysis were asked at the household level. Both SSI beneficiaries and non-SSI beneficiaries were included in the analysis as excluding those who receive the benefit would have restricted the sample to levels too low for confidence. The regression was therefore run among 796 observations (out of which 503 knew the program quite well). The explanatory (independent) variables that were selected are listed in Table A2.3. Table A2.4 presents the results of the regression. Table A2.3. Description of explanatory variables used in regression Variable Description Type Reference category age continuous - sex dummy female people who have never attended any level of education, people with higher educ_low have some pre-primary education or incomplete primary, dummy education have primary or lower secondary education labor status = student, in retirement, disabled, unemp labor status = unemployed dummy soldier, domestic tasks, other labor status = student, in retirement, disabled, employed labor status = employee or self-employed dummy soldier, domestic tasks, other living in the rest of reg_at living in Athens or Thessaloniki dummy Greece size2 two-person households dummy single-person households size3 three-person households dummy single-person households size4pl four or more people households dummy single-person households 34 living in rural/semi-rural urban living in urban areas dummy areas non-recipients of social dividend recipients of social dividend dummy dividend recipients of child benefits, unemployment benefits, non-recipients of these othben disability benefits, food card or humanitarian crisis dummy benefits benefits recipients of free medical treatment, transport allowance, social tariff of power providers, social tariff of water non-recipients of these othassist dummy providers, social tariff of municipalities & municipal social services companies (“otherbenefits� variable) accommodation is rented owner accommodation is owned by the household dummy or provided rent-free Table A2.4. Linear regression coefficients Variable Coefficient Std. error age 0.004*** 0.001 sex -0.027 0.035 educ_low -0.063* 0.034 unemp 0.409*** 0.046 employed 0.067 0.045 reg_at 0.042 0.038 size2 -0.149*** 0.042 size3 0.092* 0.048 size4pl -0.091* 0.048 urban -0.061 0.039 dividend 0.199*** 0.035 othben 0.095** 0.042 othassist 0.049 0.033 owner -0.064* 0.035 _const 0.085 0.087 N 796 Notes: * p<0.10; ** p<0.05; *** p<0.01 Adjusted R-squared: 0.263 35 Annex 3. Summary of The Process Evaluation of the Implementation of the First Phase of the SSI The paper presented the results of a process evaluation carried out by the World Bank team on the Phase 1 of the national rollout of the Guaranteed Minimum Income (GMI) program, named “Social Solidarity Income (SSI)� and implemented in thirty municipalities in Greece from July until December 2016. The evaluation results confirmed that the program was implemented smoothly and was very well accepted by both beneficiaries and municipal staff. Some beneficiaries and municipal staff defined the SSI Phase 1 the most important social program in Greece at the time. As of November 2016, more than 47,500 applications were approved, representing 7 percent of the overall population in the 30 Phase 1 municipalities, in line with expectations. Payments of accepted applicants were smooth and regular, contributing to the acceptance of the program at the local level. The majority of beneficiaries and municipal staff appreciated the clarity of the application form and the fact that the applicants were informed of the outcome immediately after submission. At the same time, qualitative work highlighted how the fact that the application form could be filled with the help of municipality and KEP staff likely limited the exclusion of those applicants that did not feel comfortable with an online application. The information system supporting the program coped very well with the volume of applications. Most importantly, the ability of the IT system to verify and validate information through several electronic platforms proved to be a fundamental shift in the way social assistance is delivered in Greece. Municipalities were able to organize a comprehensive communication campaign using the material distributed ahead of the launch of the program therefore exploiting the program’s take up. The call center and email list created by the MoLSISS and IDIKA provided an important support to municipalities throughout implementation. Municipal staff deserved a lot of credit for the overall trouble-free implementation of the program given that a lot of burden was placed on municipalities, especially during the initial months. Most municipalities lamented the lack of staff to handle the volume of work associated with the implementation of the SSI and complained about the lack of additional financial and human resources allocated for what is, for the most part, a locally run program. They appreciated the support received through the mailing list set up by MoLSISS and IDIKA’s helpdesk. At the same time, local staff lamented the limited and mostly theoretical training received prior to the launch of the program, when the application was not ready yet. The report found that more support on the side of the MoLSISS was needed going forward. A fully-fledged training, guidance on communication materials and on social inclusion and labor integration measures, and financial support needed to be provided to municipalities. To ensure that citizens’ rights are fully respected once the program goes national, and to maximize acceptance of the program, a grievances and appeals process needed to be developed to allow for a systematic procedure in dealing with citizens’ concerns. 36 The first phase of the rollout proceeded smoothly. However, the program still missed the definition and implementation of critical components, which were deemed fundamental to the success of the full rollout. In line with the experiences from other countries, such as Cyprus for example, in the starting phases of similar programs, the initial focus should be and rightly was on delivering monetary benefits to citizens in a targeted manner, and getting the main processes up and running. However, at the time of writing this process evaluation, some key building blocks of a GMI were missing in view of the January 2017 deadline to scale up the program. A necessary condition for success continued to be the functioning of a full-time SSI program unit with clear roles and responsibilities, including a specialized and dedicated IT team who could work on the IT infrastructure. Ensuring timely and extensive communication at the local level and implementing a fully-fledged training and retraining strategy for the remaining municipalities was deemed fundamental towards a trouble-free and sustainable rollout; as well as setting up a grievance and appeal mechanism. These building blocks were assessed as crucial to supporting Pillars 2 and 3 of the SSI, which had yet to be developed and implemented. 37 Annex 4. Comparison between EU-SILC and SSI Survey Income Data The table below presents a comparison of the mean equivalized disposable income by decile, according to the data collected for the purposes of this evaluation (labelled, for simplicity, World Bank Survey Data), and the EU-SILC survey data. By and large, the table below shows that incomes are comparable between the data collected by KAPA Research and those found in EU-SILC data. The divergence which can be observed at the bottom of the distribution is likely due to the fact that the World Bank survey data, having oversampled poor households in Greece (i.e. SSI beneficiaries), measures incomes at the bottom end of the distribution more precisely than EU-SILC, which relies on a more limited number of observations. Table A.5. Mean Household Equivalized Disposable Incomes - World Bank Data vs. SILC - Euros WORLD BANK SURVEY, 2017- SILC, 2016 (Uprated to 2018 2017) decile 1 601 1,733 decile 2 2,929 3,765 decile 3 4,481 5,022 decile 4 5,544 6,062 decile 5 6,642 7,100 decile 6 7,727 8,207 decile 7 8,791 9,528 decile 8 10,077 11,259 decile 9 12,037 13,652 decile 10 22,009 22,249 Source: WB Calculations based on SSI Household Survey Data and EU-SILC 2016 data Notes: SILC variable HY020 (total disposable hh income) uprated to 2017 using GDP growth = 2% as an uprating factor. 38