Minimum income protection in Spain: characteristics and poverty effects

Transcription

1 Minimum income protection in Spain: characteristics and poverty effects Rafael Granell & Amadeo Fuenmayor Department of Applied Economics. University of Valencia Workshop: Minimum income protection in Europe... and how to study it Antwerp, November 2015 Abstract: Policy to prevent poverty and social exclusion is carried out by different administrations in Spain. The role of Central Administration is important, but sometimes leaves unattended a substantial part of the population. The Spanish Regions are responsible to guarantee a minimum income for those who cannot receive other benefits. In this paper, we analyse the characteristics of the minimum income policies developed by the Spanish Regions and simulate them. We find that there are large differences between the official data reported by the administrations and the simulated results. This finding indicates that the implementation of these policies has shortcomings, especially serious in some regions. If regions would strictly apply the requirements established in the law, there would be many more beneficiaries of these subsidies, and an important reduction of poverty and social exclusion. 1

2 1. Introduction In Spain, the policy to prevent poverty and social exclusion is carried out by different public administrations. The effort of the central administration is essential, thanks to several allowances, both contributory and non contributory. However, these benefits sometimes do not arrive to a substantial proportion of the population living in extreme poverty. The Spanish Autonomous Regions (hereinafter AR) are responsible for covering these deficiencies through the Minimum Insertion Income (hereinafter MII), which are intended to guarantee a minimum income for those who cannot access to other public benefits. At present, all regions have established benefits directed towards citizens who would otherwise be unprotected. Although regional regulations have many shared aspects, there are differences in the requirements for access to benefits and in the practical implementation, which results in uneven coverage level between different regions. In this paper, we first describe and analyse the situation of the MII in the Spanish AR. Based on this actual situation, we will study if the minimum income benefits arrive to all citizens who need them. We will use the data from the Survey of Living Conditions and simulate the requirements of the regulations in each region. This simulation allows us to know if there are significant differences between the actual situation and the potential (derived from the application of the regional legislation). These differences will indicate to us if the implementation of the MII is adequate or whether, by contrast, only arrives to a small part of potential beneficiaries. Once we have simulated these potential MII, we will use these data to determine their influence on poverty. That is, the reduction of the number of people at risk of poverty if the MII would reach all those who meet the requirements set by the AR. The paper is organized as follows. In the next section we describe the situation of poverty and social exclusion in Spain, showing the main indicators that are currently used in the European Union and analyse the tools that Spain is using to deal with these problems. The third section is devoted to detailing the regional MII. Based on the different configuration of the benefits in Europe, we analyse the characteristics of MII in each of the Spanish AR. In the fourth section, we simulate the legislation of all regions to know what would be the potential situation if all people who fulfil the requirements would receive the benefits. Subsequently, we use the information provided by the simulation to analyse the effects on poverty, and a final section is devoted to conclusions. 2

3 2. Poverty and social protection policy in Spain The reduction of the level of poverty and social exclusion has always been a priority for the European institutions. However, in the last years, with a severe economic crisis and high uncertainty about the future, the number of people under the poverty line is growing frighteningly. This problem is more intense in countries like Spain, where a sharp rise in unemployment is associated with the economic crisis. The European Union has been sensitive to this problem and has developed strategies trying to reduce poverty in the forthcoming years. Currently, the Europe 2020 strategy aims to reduce at least 20 million the number of people at risk of poverty and social exclusion. This is a very ambitious objective, because in 2010 the number of people who were in this situation exceeded 115 million 1. Despite the interest of the European institutions, their role in policies of poverty reduction is very small, focusing on the coordination of policies developed by individual Member States. Therefore, the success of poverty reduction will depend on the policies adopted in each country. In Spain, the National Reform Programme pretends to reduce the number of people at risk of poverty and social exclusion between 1,400,000 and 1,500,000 (in the period from 2009 to 2019). The concept of poverty is not unique, it could have different meanings which will have influence on the developing of indicators. In this paper, we are going to follow the criterion of relative poverty based on household income. This approach, used by the European institutions, includes people whose income is below the poverty line, defined as 60% of median income in each country. Figure 1 shows the evolution of AROPE (At Risk Of Poverty or social Exclusion) indicator from 2008 to 2013 (the latest year available across Europe), comparing data from Spain with the 27 countries of the European Union. In this figure, we can see that Spain begins this period with similar rates (around 24%) than the mean of the European countries. However, the effects of the crisis in Spain are worse than in other EU countries, and the poverty rate exceeds 27% in SF /EN/KS SF EN.PDF 2 3

4 Figure 1. Evolution of Population at Risk of Poverty and Social Exclusion (AROPE) 28 EU (27 countries) Spain AROPE % Source: Own elaboration based on Eurostat data Poverty in Spain is not homogeneous, but presents important differences between regions, as shown in Table 1. If we focus on 2014 figures, we see that there are regions with a poverty rate well above the average as Ceuta, Murcia and Andalusia (all with ratios above 40%). A second group of regions have above average ratios, but less than 40%, such as Extremadura, the Canary Islands, Castilla La Mancha and Valencia, while the rest of the regions is below the Spanish average, especially the Basque Country and Navarra, with poverty rates near 15%. 4

5 Table 1. AROPE Index by Autonomous Region. Evolution (%) CCAA % related to Spain % Change 2014_2010 Andalusia % 20.9% Aragón % 18.3% Asturias % 41.8% Balearic Islands % 8.5% Canary Islands % 3.6% Cantabria % 21.8% Castilla La Mancha % 14.2% Castilla y León % 9.7% Catalonia % 10.1% Ceuta % 33.4% Extremadura % 1.2% Galicia % 4.8% Madrid % 0.5% Melilla % 27.1% Murcia % 19.7% Navarra % 5.1% Basque Country % 6.1% La Rioja % 26.4% Valencia % 17.2% ESPAÑA % 11.9% Source: Own elaboration based on Eurostat data The figures of 2010 are also presented in this table, with the aim to compare the effects of the economic crisis on the risk of poverty. In the last column, the increase in poverty in almost all regions can be appreciated, especially in Asturias, Ceuta, Cantabria and Andalusia, where in four years the number of people in this situation has increased more than 20%. On the contrary, six regions have reduced the AROPE indicator in these difficult years: Baleares, Extremadura, Madrid, Melilla, the Basque Country and La Rioja. The policy of social protection in Spain does not correspond exclusively to one level of government. In a first analysis we can distinguish between the following levels of government involved: Central level: responsible for contributory benefits (unemployment, retirement, disability and survival) and some non contributory benefits that could be complementary to the above (non contributory pension, non contributory unemployment) and benefits that are sporadic and temporary (active insertion income). Regional level (Autonomous Regions): responsible for the minimum insertion income, which provide a minimum income for people who would otherwise be without assistance. 5

6 Local level: providing mainly in kind assistance. Social services dedicated to fight against poverty in close cooperation with NGOs. 3. The Spanish Minimum Insertion Income 3.1. The Minimum Insertion Income in the European countries The minimum income system is not unique in Spain, since it is present in most European countries. According to Busilacchi (2008) all EU countries except Greece, Italy and Hungary have a minimum income program. However, European programs have many differences and can be classified in several ways. A first classification would take into account the uniformity of the system, distinguishing between: Uniform Systems: minimum income is the most important benefit and the main measure to reduce poverty (Denmark, Sweden, Finland, United Kingdom and Luxembourg). Diversified Systems: minimum income plays the role of "last resource" (Belgium, Ireland, France, Austria and southern countries). They may also be differentiated according to the requirements to be eligible, and the generosity of programs. Busilacchi (2008) combines both elements, obtaining the following classification: Table 3. Models of Minimum Insertion Income Generosity/Rigidity Low Rigidity Medium Rigidity High Rigidity Low Generosity Bulgaria, Lithuania, Poland France, Latvia Medium Generosity Norway, Sweden Slovakia, Estonia, Portugal, Czech Republic, Romania, Austria (some Länder) Spain, Slovenia High Generosity United Kingdom, Finland Ireland, Austria (some Länder), Malta, Cyprus, Germany, Holland Denmark, Luxembourg, Belgium Source: Busilacchi (2008) These differences have to do with the lack of European harmonization on social protection. However, in recent years the debate on whether or not coordinate national programs through community institutions has been reopened, playing the European Anti Poverty Network a central role. This network has asked for the creation of an EU directive to harmonize European programs and provide 6

7 them with common minimum requirements. Following this approach, some authors, like De Giorgi and Pellezzari (2006) have proposed an identical European minimum income for all citizens of the Union. Despite the coordinating wish of different European agents, the portrait in Europe continues to be unequal. This inequality is especially worrying in the current situation, with very different poverty levels in European countries Characteristics of the Minimum Insertion Income in Spain The MII began to be considered in Spain in the late 80s of last century. In the first moment the politicians advocated a centralized common regulation system for Spain, which however was never been developed. The lack of a centralized instrument left unprotected certain risk groups, therefore regional governments tried to fill this gap. The result was an improvised and uncoordinated mechanism with great differences in requirements, amounts and rights 3. The first AR in implementing this type of benefit was the Basque Country in From this date, the remaining AR began to establish different minimum income programs, culminating in 1995 with the MII of the Balearic Islands. Currently these programs, which have changed names and characteristics, are still present in all Spanish regions including the autonomous cities of Ceuta and Melilla. All of these regional benefits have common characteristics but also many differences. The similarities mainly refer to the objectives pursued by such programs. A first objective is to give financial assistance to individuals or families who are in a very unfavourable economic situation. In this sense, MII act as a guaranteed minimum income. But this first goal is bound with an insertion mechanism. Recipients of these benefits must participate in labour, social or education programs that might lift them out of poverty and exclusion. Although each region has set its own conditions of insertion, we think that these differences are not important. However, the regional differences are important in the rest of requirements and in the formula used to calculate the amount that corresponds to each beneficiary. These differences are detailed in Table 4. These requirements relate to the year Arriba (1999) describes the process of implementation of the minimum insertion income in Spain. 7

8 Table 4. Characteristics of the Regional Minimum Insertion Income in 2009 CCAA Basic Amount (BA) Benefit (B) Requirements nº people Formula Amount Formula Conditional to.. Maximum Minimum Age Residence (years) Andalusia 1 =(0.62)*SMI B=BA income Income<BA =0.15*SMI 25 A<65 1 IMS 2 =( )*SMI Ingreso 3 =( )*SMI Mínimo de 4 =( )*SMI Solidaridad 5 =( )*SMI =SMI Aragón 1 = B=BA income Income<BA =SMI 18 A<65 1 IAI 2 =424*(1+0.3) Ingreso 3 =424*( ) Aragonés de 4 =424*( ) Inserción 5 + =424*( ) Asturias 1 =BASIC UNIT B=BA income Income<BA =165%*BU =10%*BU 25 A 2 SSBA Salario Social Básico Asturiano Balearic Islands 1 = BASIC BENEFIT B=BA income Income<BA =125%*IPREMP =25%*BB 25 A 0.5 RMI 2 =BB*(1.3) Renta 3 =BB*( ) Mínima de 4 =BB*( ) Inserción 5 =BB*( ) =BB*( ) =BB*( ) =

9 Canary Islands 1 =0.76*IPREMP B=BA income Income<BA =1.06*IPREMP = A<65 3 PCI 2 =( )*IPREMP Prestación 3 =( )*IPREMP Canaria de 4 =( )*IPREMP Inserción 5 =( )*IPREMP =( )*IPREMP Cantabria 1 =80%*IPREM B=BA income Income<BA =1.25*IPREM =0.25*IPREM 23 A<65 1 RSB 2 =(80%*IPREM)*125% Renta 3 =(80%*IPREM)*125%*110% Social 4 =(80%*IPREM)*125%*110%*110% Básica 5+ =125%*IPREM Castilla La 1 =60%*IPREMP B=BA income Income<BA = IPREMP =0.1*IPREMP 25 A<65 2 Mancha 2 =(60%+6.6%*AP)*IPREMP IMS Ingreso Mínimo de Solidaridad Castilla y León 1 =75%*IPREM B=BA income Income<BA 25 A<65 1 IMI 2 =(75%*IPREM)*112% Ingresos Mínimos de 3 =(75%*IPREM)*124% Inserción 4+ =IPREM Catalonia 1 =PREST. BASICA B=BA income =190%*PB =25%*PB 25 A<65 1 RMI 2 =PB (labour inc 75%) Renta 3 =PB+(53.5*2) Mínima de 4 =PB+(53.5*3) Inserción 5 =PB+(53.5* *AP)

10 Catalonia (cont.) Incomp Each child < Incomp Each handicapped child >= One parent family Dependent people living alone Ceuta 1 = B=BA income Income<BA A<65 1 IMIS 2 =270* Ingreso Míni 3 =270* mo de Inserción 4+ = Social Extremadura 1 =75%*IPREM B=BA income Income<BA =100*IPREM 18 A 1 RM 2 =(75%+8%)*IPREM Renta 3 =(75%+8%*2)*IPREM Mínima 4 =(75%+8%*3)*IPREM =100%*IPREM Galicia 1 =75%*IPREM B=BA income Income<BA =125%*IPREM 25 A<65 1 RISGA 2 =(75%+12%)*IPREM Renda de 3 =(75%+12%+10%)*IPREM Integración 4 =(75%+12%+10%+8%*AP)*IPREM Social de Galicia La Rioja IMI 1 =70%*IPREM B=BA labour inc Income<(IPREM*70%) 25 A<65 1 Ingreso Mínimo de Inserción Income<(IPREM*(70%+15%*AP)) AIS 1 =PNC B=BA income Income<BA =70%*IPREM =25%*BA 25 A 1 Ayudas de 2+ =PNC*(100%+10%) Do not receive IMI inclusión social 10

11 Madrid 1 = B=BA income Income<(IPREM*70%) =IPREM 25 A<65 1 RMI 2 = Income<(IPREM*(70%+15%)) Renta 3 = *AP Income<(IPREM*(70%+15%+10*AP)) Mínima de Inserción Melilla 1 =50%*SMI 312 Until 5/2009 Income<BA 25 A<65 2 IMI 2 =59%*SMI Ingreso 3 =67*SMI Melillense de 4 =74*SMI Integración 5 =80*SMI PBF 6+ =85*SMI =60%*SMI From 6/ =70%*SMI =80%*SMI =90%*SMI =100%*SMI 624 Prestación =35%*SMI Until 5/ Básica Familiar =50%*SMI 312 From 6/2009 Murcia 1 = B=BA income Income<BA A<65 MI 2 = in Murcia Ingreso 3 = in Spain Mínimo de 4 = * Inserción 5 = *2+46*AP

12 Navarra 1 =90%*SMI B=BA income Income<BA =10%*SMI 25 A<65 2 RB 2 =110%*SMI Renta 3 =120%*SMI Básica 4 =130%*SMI =140%*SMI =150%*SMI Basque Country 1 =88%*SMI' Income<BA =125%*SMI 23 A 1 RB 2 =113%*SMI' Renta 3+ =125%*SMI' Básica Para pensionistas Valencia 1 =100%*SMI' =125%*SMI' =135%*SMI' =62%*IPREMP B=BA (Income Income<BA =IPREMP 25 A< =(62%+5%)*IPREMP ) RGC 3 =(62%+5%+3%*AP)*IPREMP Renta Garantizada de la Ciudadanía NOTES: BA Basic Amount B Benefit BB Basic Benefit BU Basic Unit AP Additional person SMI 624 Monthly Inter professional Minimum Wage REAL DECRETO 2128/2008, de 26 de diciembre, por el que se fija el salario SMI' 728 Yearly Inter professional Minimum Wage/12 mínimo interprofesional para 2009 (BOE de 30/12) PNC Non contributory pension IPREM Monthly Multiple Effect Income Index D.A. 28ª Ley 2/2008, de 23 de diciembre, de Presupuestos Generales del IPREMP Yearly IPREM/12 Estado para el año 2009 (BOE de 24/12) Source: Dirección General de Política Social (2010), regional legislation and own elaboration. 12

13 As shown in the table above, all of the MII are based on the Basic Amount established by each of the AR. This theoretical amount is the minimum available income for a household in an AR, and it is established in relation to different indicators or can be a fixed amount. The most widely used indicator is the Multiple Effect Income Index, either in its monthly amount (IPREM, ; used in Cantabria, Castilla Leon, Extremadura, Galicia and La Rioja) or in its yearly amount divided by 12 monthly payments (IPREMP in the table, ; Canary Islands, Castilla La Mancha and Valencia). However, some regions continue to use as a reference the Inter professional Minimum Wage, in its monthly amount (SMI 6,244 in 2009, is the case of Andalusia, Melilla and Navarra) or in its yearly amount divided by 12 (SMI' in the table, 728, Basque Country). Other regions establish a discretionary basic amount (in the case of Asturias, the Balearic Islands, Ceuta, Catalonia, Madrid and Murcia). The use of a fixed amount represents greater discretion to the regional authorities, which each year can decide the basis for all calculations. Figure 2 compares the amounts established in each region. These are the basic amounts stipulated for a single individual (represented by the solid line in the right axis). The Basque Country and Navarre have the higher amounts, and Ceuta and Murcia have the lowest. In the remaining AR the Basic Amounts vary between 370 and 470 euros per month. Figure 2. Basic Amount of the MII and implicit equivalence scales by household size Equivalence scale Basic Amount Euros per month Source: Own elaboration 13

14 The Basic Amount varies, in general, with the number of members of the household. Usually the first member has a reference weight, which is reduced as the number of individuals grows. The design of these "implicit equivalence scales" is absolutely discretionary and is also reflected in Figure 2 (left axis). The bars of each region reproduce the relative change in the allowance in comparison with a household with one individual. This implicit equivalence scales are much lower than the OECD scale. Murcia, Madrid, Melilla, Baleares, Aragón and Asturias are the regions that consider the family size more strongly. By contrast, Ceuta, La Rioja and Valencia have a much flatter scheme. Finally, Catalonia has taken into account other variables such as children under 16, handicapped children, single parent families, or households with a dependent person living alone. Once the Family Amount is determined, the benefit is paid only if the family income is below that limit. Although this is the general pattern, there are some exceptions, such as La Rioja and Madrid. In both cases, the benefit is granted if the household income does not exceed a limit which grows with family size. In some ways, it is similar to modify the theoretical amount based on family size. In the case of La Rioja, the Basic Amount do not change with family size but does this limit, which is very similar (though a bit confusing). In the case of Madrid, the Basic Amount changes with the size of the family, and so does the threshold for which the benefit is paid. For example, in the case of a household with 3 members, the Basic Amount is 555, but the benefit is paid only if the household income is less than They are very similar amounts, but probably unnecessary complexity is added. To calculate the benefit that a home will receive the last step is to subtract from the Basic Amount the income earned by this household. In general this is done directly, calculating the difference between the two amounts. This calculating method can place some individuals in the poverty trap. If the benefit is the difference between household income and the Basic Amount, the incentive to get out of poverty disappears, unless the wage were significantly higher than the benefit. If as a result of labour, income is not clearly altered, there is no incentive to escape from poverty. To avoid this problem it would be desirable that the reduction in amount of the benefit were less than the increase in the labour income. Consequently, the incentive to find a job would remain, although the level of final income exceeds the theoretical amount. In some regions efforts to avoid this problem are made. For example, in Catalonia the full income is subtracted from the Basic Amount, except in the case of labour income, which is deducted from the theoretical amount by 75%. Therefore, a one person household only receive the benefit if its income is lower than 410, but this amount will rise to 547 if it is labour income. In Valencia, a fixed 14

15 amount of 10 euros is reduced by, regardless of its origin. In this case it is a kind of minimum without much sense. In some cases the minimum income are subject to minimum or maximum amounts. The minimum amount is intended to avoid benefits of few euros per month, while the maximum amount represents an additional limit. The maximum amount is only meaningful when the Basic Amount is unlimited (Castilla La Mancha, Catalonia, Galicia, Madrid, Murcia and Valencia), or as a ceiling when there is income at the household. In all the regions there are additional requirements to be eligible, as the beneficiary's age and residence. Regarding the first, there is some consensus in setting an age between 25 and 65, with some variations. The lower limit reflects the fact that most of the individuals under this age are part of another household. In any case, almost all AR reduce the age threshold in certain circumstances. The upper limit reflects the fact that people over 65 should receive a state contributory or noncontributory benefit, so theoretically they should not need the MII. The requirement about residence exists in all regions. This period varies between six months and three years, but the most frequent period is one year. Finally, although it is not shown in the table, there is another important difference. In most AR minimum income is established as an individual right of the citizens. That is, anyone who fulfils all the requirements of the legislation is entitled to receive the benefit (Andalusia, Aragon, Asturias, Canary Islands, Cantabria, Catalonia, Castilla La Mancha, Madrid, Navarra, Basque Country and Valencia). In the other six regions, as well as Ceuta and Melilla, fulfilling the requirements does not ensure the benefit, because the regional government can limit the number of beneficiaries based on the budget constraint. In summary, although there are not two similar instruments, the differences between MII are not so radical in Spain. The structure of any MII is identical: a Basic Amount is set according to family size, previous income is subtracted from this amount and the remaining quantity is paid to the beneficiaries. The greatest variability is in the way of fixing the Basic Amounts, but these differences do not justify the use of different indicators (SMI, SMI 'IPREM, IPREMP, PNC, discretionary amounts). It would be simpler and costless to establish a unique type of instrument in all the Spanish Regions with the possibility to change some regional parameters. 15

16 4. Simulation of the Regional Minimum Insertion Income 4.1. Methodology In this section we will implement a simulation of the MII of each AR. We have used as a database the Spanish Survey of Living Conditions (ECV) This is a survey designed at European level in a harmonized manner (EU SILC: European Statistics on Income and Living Conditions). In the Spanish case the survey was conducted by the National Institute of Statistics, mostly between March and June All the variables related to income are annual and correspond to 2009, so we focus on this year for the whole analysis 4. The ECV, whose advantages and disadvantages can be found in Fuenmayor and Granell (2009), is a useful instrument for simulating expenses and income of Spanish households, being representative at regional level, which will allow us to analyse the MII adopted by the different regions. In the file there are 37,026 individual observations, which are grouped in 13,597 households. To simulate the MII, we need to consider a variable that represents household income. Therefore we must add to the net market income all contributory and non contributory benefits, except for the MII of each AR. In this addition we had an important problem. The starting variable we used was hy002 (Total disposable household income, which contains the total household income, including income received from private pension schemes). From this variable we should subtract the variable hy060n (social assistance income in 2009). Finally, we would divide this result by 12 to obtain the monthly income. The problem is that the variable hy060n does not represent in any case the amount of the MII, so we have finally had to take into account exclusively the variable hy002, which also includes the MII. Therefore, we are going to simulate the additional MII that would result from applying strictly the rules of each region. We will come back to this point in next section. The minimum income calculating procedure has followed a relatively standardized method, but adapted to each AR. The general scheme is the following: BASIC AMOUNT=f (INDICATOR, MEMBERS) MII =BASIC AMOUNTS α INCOME s.t. Limits (minimum and/or maximum) The estimation process, with some particularities, consists of two steps. First we establish the Basic Amount. We calculate the minimum subsistence threshold, below which it is necessary that the AR 4 Although data on income refer to 2009, other social and demographic information refer to In fact the ECV 2010 combines data from both years, but we believe more correct to refer to 2009 because the income variables are those that have more importance in the simulations. 16

17 provides a MII. This Basic Amount is usually associated with some indicator (SMI, IPREM, PNC) or a discretionary amount, and it is modulated depending on the number household members. Based on this Basic Amount, the MII is determined as the amount required to complete the household income to the threshold mentioned above. To avoid the poverty trap, it would be desirable to subtract from the Basic Amount the household income weighted by a coefficient α lower than 1. But as we have mentioned before, this only happens in Catalonia. Finally, the amount of the benefit may be subject to minimum and maximum limits, which we consider in the simulation. In general, all regions require following some kind of integration path, with specific characteristics. As we cannot simulate these requirements, we have assumed that these conditions are always met, which implies an overestimation of benefits. In addition, we have taken into account the age requirements of the people in the household. To convert survey data to population figures we have used variable db090 as household elevation factor Simulation As discussed above, our simulation is based on the total household disposable income (hy002). This variable includes the market income, and all benefits the household has received. Based on this variable we simulate the potential MII that every household should have and estimate the final income of the household. Therefore, our simulation includes the MII that people have not received. Somehow it would represent the final ideal point, given the design of each instrument. Figure 3 can help to understand what we are doing. This is only an estimate, but the meaning is the following. In each region, its current policy would increase average income in the equivalent distance to the dark bar. However, if all the people who fulfil the requirements receive the MII, their average income will increase in an amount equal to the light bar. This figure shows two important things, the income change due to current policies and the way that lies ahead in accordance with the MII requirements. This figure shows the great effort made by the Basque Country and Navarra, far from the other regions. However there is an important difference between both regions: the way left to go to Navarra is shorter than that of the Basque Country. 17

18 Figure 3. Meaning of the simulation. Increase of average income Andalusia Aragón Asturias Balearic Islands Canary Islands Cantabria Castilla La Mancha Castilla y León Catalonia Ceuta Extremadura Galicia Madrid Melilla Murcia Navarra Basque Country La Rioja Valencia Current Policy Simulation Source: Own elaboration In Table 5 we present the results of our simulation and compare them with actual results. In the first three columns of our simulation it could be found the number of households that theoretically were MII recipients, the average amount of this benefit, and the total annual cost of the MII. The next two columns reproduce the figures provided by the administration, in a document that collects data provided by the AR. The last two columns are used for comparison of actual and simulated data. These figures are truly astonishing. Central administration collects data from actual MII paid in Spain to 156,858 families in The annual cost associated with these benefits amounted 619 million euros, implying an average monthly benefit of 329. However, in addition to these amounts, and analysing the disposable income in 2009, 861,190 more households should receive, on average, 325 more 5. This additional expense involves an additional expense of almost 3,354 million euros. Therefore, in addition to the actual expenditure, regional governments should make an additional effort of 5.42 times to arrive to the whole population who fulfil the requirements, which is 5.49 times more than the actual beneficiaries. These data are in line with the statements of other sources: EUROMOD simulations multiplied by 3.87 the number of beneficiaries and by 3.48 total spending 6. 5 Households that actually receive MII might or might not receive some additional amount, and there are new households entitled to receive this benefit. 6 Adiego et al. (2010), Table 20 (p. 120) and Table 21 (p. 122). 18

19 Table 5. Comparison of simulated and actual MII Estimation Results Monthly Average Total Annual Cost Official Data Total Annual Cost Households Ratio Cost Ratio Households Households Andalusia 170, ,533,744 27,212 62,380, Aragón 23, ,009,392 1,768 4,407, Asturias 17, ,122,028 7,902 29,641, Balearic Is. 39, ,470,752 1,937 4,565, Canary Is. 43, ,335,636 3,775 15,274, Cantabria 14, ,170,336 2,223 7,100, C La Mancha 24, ,134, ,120, Castilla y León 42, ,096,844 2,748 13,820, Catalonia 103, ,265,244 22, ,463, Ceuta ,148, , Extremadura 35, ,013,540 1,475 2,100, Galicia 33, ,889,136 6,360 21,084, Madrid 100, ,052,628 11,426 47,680, Melilla 1, ,935, , Murcia 35, ,614, ,537, Navarra 5, ,556,412 6,087 21,473, Basque Country 90, ,971,896 55, ,700, La Rioja 5, ,549, ,664, Valencia 75, ,740,692 4,001 11,370, TOTAL 861, ,353,610, , ,254, Source: Own Elaboration, ECV 2010 and Dirección General de Política Social (2010) Regarding the number of beneficiaries, our estimates may be clearly above the reality, for two reasons. First, because of problems related to the estimation itself. For example, we have considered as an applicant for an MII every home that fulfils the requirements. And there are many households who are entitled to trivial amounts. We have calculated the number of households that would receive less than 100 monthly, and these figures are 44% in the case of Asturias, 31.4% Extremadura, 42.9% Melilla, or 33.3% in the case of the Basque Country. Another problem that could influence the number of beneficiaries is the fact that the MII were or not a subjective right. However, apparently there is no relationship between these two variables. The AR that do not consider their MII as a subjective right (Baleares, Castilla y Leon, Extremadura, Galicia, Murcia and La Rioja), and therefore might reduce the benefits due to budgetary constraints, do not always have higher ratios than the other regions. The second problem is related to the low participation level, also known in the literature as non take up (Currie, 2004). In certain benefits, some individuals who theoretically have the right to participate really do not. There are three major reasons. 19

20 First, the stigmatizing effect associated with the benefit. Many instruments, like the MII have an important social rejection, and some people see their application and perception as a stigma. The applicant feels guilty for this benefit, and its demand can be lower. Some authors maintain that this stigmatizing effect could be positive, as it increases the efficiency of the benefit: only those who really need the benefit would apply for it. Obviously this viewpoint is subject to high controversy. Second, there are the problems related to information. The group of theoretically eligible citizens is a group close to marginalization, where education levels are low and do not always has adequate information to apply for the MII. In addition, the bureaucracy, associated with strict legal and formal requirements, is difficult to be understood by applicants. Finally, literature suggests factors related to transaction costs associated with the demand for the service: transportation costs, use of time, etc. The applicant may realize that it is much faster and easier to obtain the same amount of money making some kind of sporadic activity. However, the non take up effect or the limitations of the microsimulation cannot hide another feature that has no apparent explanation: the differences, especially in some AR, between the household ratio and the cost ratio. After removing the distorting effects of the number of applicants, one should expect that this effect was stable compared to spending. That is, if these benefits are awarded only 15% of those who need them, at least they should receive the full amount. That is, cost ratio is expected to be similar to household ratio. This is true if we take into account the national average, and also in several regions. However, there are some AR that do not follow this rule, especially Ceuta, Extremadura and Murcia. In our opinion the high discretion that have the autonomous governments is translated to different results among regions. This is the most surprising result of this microsimulation: the extraordinary diversity in the implementation of the MII by AR. Figure 4 shows these results. 20

21 Figure 4. Ratios simulated data/ actual data, beneficiaries and expenditure by AR Household Ratio Cost Ratio Source: Own elaboration The differences between regions are enormous. Regarding the household ratio, Navarra is especially noted. According to our data, Navarra should assist 87% more households than households that actually assist. The Basque Country (1.6) and Asturias (2.1) are in a comparatively favourable situation. At the other end, Murcia assists a tiny portion of households. According to the data of this study, it should multiply by 47 the number of households if the benefit arrives to all households that fulfil the requirements. Something similar happens with Castilla La Mancha (40.9), Extremadura (24.2) and the Balearic Islands (20.4). 5. Poverty effects In this section we present the effects that would have the potential MII over the most common poverty indexes. To carry out this analysis, we will compare the actual situation of households in 2009 with a potential situation in which these households would receive MII if they fulfil the requirements of each AR. That is, we try to measure the reduction in poverty indexes if all potential MII were granted. Although there are several poverty indexes, we will focus on the most common, referring to monetary poverty, distinguishing between incidence, intensity and a combination of them. The two key variables to calculate the effectiveness of the policies are: 21

22 Actual Income: Income declared by the household in ECV 2010, including MII and other benefits. Potential Income: Actual Income plus potential MII if the household fulfils the requirements. To work with households of different size and composition, Actual and Potential Income have been converted in equivalent units dividing the data from each household by the modified OECD equivalence scale. First, we analyse the changes in poverty incidence. We consider the poverty line most used in recent years and that is also used in AROPE index: 60% of the median income, which in Spain was 7,818 in Incidence indexes and average income of those falling below the threshold are shown in Table 6. Table 6. Effectiveness in the fight against poverty. Incidence CCAA Incidence Ratio Poor Mean Income Actual Potential % Real Potential % Income Income Income Income Andalusia 30.10% 30.10% 0% 4,536 4, % Aragón 13.60% 13.60% 0% 4,176 4, % Asturias 12.28% 12.28% 0% 4,626 5, % Balearic Islands 20.57% 20.57% 0% 4,189 5, % Canary Islands 31.09% 31.09% 0% 5,108 5, % Cantabria 17.25% 17.25% 0% 4,504 5, % Castilla La Mancha 27.79% 27.79% 0% 4,750 5, % Castilla y León 21.01% 21.01% 0% 4,227 4, % Catalonia 15.27% 15.27% 0% 4,212 4, % Ceuta 34.32% 34.32% 0% 4,499 4, % Extremadura 38.24% 38.24% 0% 4,801 5, % Galicia 16.85% 16.85% 0% 4,740 5, % Madrid 13.63% 13.63% 0% 4,089 4, % Melilla 27.63% 27.63% 0% 3,955 4, % Murcia 29.21% 29.21% 0% 3,784 4, % Navarra 7.29% 7.29% 0% 3,897 4, % Basque Country 11.62% 11.29% 0.33% 3,762 5, % La Rioja 20.55% 20.55% 0% 4,223 4, % Valencia 20.07% 20.07% 0% 4,257 4, % TOTAL 20.73% 20.72% 0.01% 4,410 4, % Source: Own elaboration Results are apparently negative, because the Potential RMI only would reduce poverty only 0.01%, equivalent to less than 7,000 people (out of a total of 9.5 million). Moreover, the reduction is 22

23 concentrated in a single region, the Basque Country, which would be reduced incidence indicator 0.33%. This exceptional situation is due both to the generous benefit policy of the Basque Country and its high per capita income. The results of the above table are apparently disappointing. A more generous policy would not almost have effects on poverty reduction. However, the reality is much more complex. While the number of poor people would be almost the same, these people would have an average income well above, as shown in the last column of the table. The increase in the equivalent average income of these people would grow 521 a year, representing 11.8% of their previous income. In our opinion, this result is very positive, because the new benefit could be vital to the subsistence and social integration of these families. This increase would not be uniform throughout the Spanish territory. While in the Basque Country the average income increases more than 50% in Ceuta would only 1.4%. Undoubtedly, these differences are motivated by the generosity of the different regional MII programs. Another issue to consider in terms of the incidence of poverty is the influence of the poverty threshold. We have chosen the most widespread threshold in developed countries, 60% of the median income. However, if we focus on extreme poverty we could have chosen a lower threshold. In Figure 5 we present the results on poverty incidence depending on the threshold. While it is true that the differences between actual and potential income do not exist with a threshold, and are very scarce from 5,000, below this threshold the effectiveness of the potential MII begins to be important. For example, if the threshold were 30% of median income, poverty would be reduced from 6.6% to 5,9%, but if the threshold were 30% of median income, the poverty reduction would be much higher, from 4.5% to 2.2%. Analysing this figure we can conclude that the successful implementation of regional MII would lead to a significant reduction of extreme poverty in Spain. 23

24 Figure 5. Poverty Incidence according different thresholds 25% Incidence Ratio 20% 15% 10% Actual Income Potential Income 20% Med. 30% Med. 5% 4.54% 6.60% 5.86% 2.16% 0% 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Poverty Threshold Source: Own Elaboration After analysing the incidence effects, we return to the intensity of poverty. If we measure the intensity as the relative distance between the income of the poor and the poverty line, the intensity is expected to be reduced by the increase in the average income of the poor, as discussed in Table 6. The results of intensity are shown in the first three columns of Table 7, while the last three show the combined ratio, multiplying incidence and intensity ratios. The intensity of poverty is reduced significantly in our simulation. If all the people who are eligible receive the corresponding benefit, the intensity of poverty would be reduced by 6.7% in Spain. It is true that the number of people below the poverty line hardly changes, but their income is much closer to the threshold. The regions with a greater reduction in the intensity of poverty would be the Basque Country and Navarra, while the most disadvantaged would be Ceuta and Castilla La Mancha. Although the combined ratio would be reduced in all regions, this reduction is much less important than that due exclusively to the intensity. However, the individual results of the AR do not follow the same pattern as intensity. While it is true that the Basque Country is the region that would reduce more the combined ratio, other communities like Baleares and Murcia also reduce this ratio significantly. 24

25 Table 7. Effectiveness in the fight against poverty. Intensity Indexes CCAA Intensity Ratio Combined Ratio Real Income Potential Income % Real Income Potential Income Andalusia 42.0% 36.8% 5.2% 12.6% 11.1% 1.6% Aragón 46.6% 36.2% 10.4% 6.3% 4.9% 1.4% Asturias 40.8% 33.7% 7.1% 5.0% 4.1% 0.9% Balearic Islands 46.4% 35.8% 10.6% 9.5% 7.4% 2.2% Canary Islands 34.7% 30.5% 4.2% 10.8% 9.5% 1.3% Cantabria 42.4% 33.1% 9.3% 7.3% 5.7% 1.6% Castilla La Mancha 39.2% 35.6% 3.6% 10.9% 9.9% 1.0% Castilla y León 45.9% 40.1% 5.8% 9.6% 8.4% 1.2% Catalonia 46.1% 38.4% 7.7% 7.0% 5.9% 1.2% Ceuta 42.5% 41.6% 0.8% 14.6% 14.3% 0.3% Extremadura 38.6% 34.3% 4.3% 14.8% 13.1% 1.6% Galicia 39.4% 34.7% 4.7% 6.6% 5.8% 0.8% Madrid 47.7% 38.3% 9.4% 6.5% 5.2% 1.3% Melilla 49.4% 45.2% 4.2% 13.7% 12.5% 1.2% Murcia 51.6% 45.0% 6.6% 15.1% 13.2% 1.9% Navarra 50.2% 36.3% 13.9% 3.7% 2.6% 1.0% Basque Country 51.9% 27.1% 24.8% 6.0% 3.1% 3.0% La Rioja 46.0% 38.8% 7.2% 9.4% 8.0% 1.5% Valencia 45.5% 39.4% 6.1% 9.1% 7.9% 1.2% TOTAL 43.6% 36.9% 6.7% 9.0% 7.7% 1.3% Source: Own elaboration % 6. Conclusions All Spanish regions have established benefits for the underprivileged under the generic term of Minimum Insertion Income. Although there are common features, there are differences that are reflected in a different number of beneficiaries and also in very unequal amounts between territories. Based on the ECV 2010 microdata, we simulate the MII legislation of all the autonomous regions. Our aim is to realize whether the differences discussed in the previous paragraph were due to the requirements of each region to participate in the program or to the practical implementation of these benefits. Our results support the second reason. While it is true that there are regions with more restrictive requirements than others, the differences are relatively small. By contrast, there are huge differences in the practical implementation of the MII. While regions such as the Basque Country give the benefit to more than half of those fulfil the requirements, in other regions as Murcia 25

26 and Castilla La Mancha the benefit arrives only to one of every 40 potential beneficiaries. These differences can be explained in part by the lack of participation which in the literature is known as non take up. However, it seems that the interest shown in the management of the MII is also very different between regions. Our simulation also provides other interesting results. First, if the requirements of the legislation were strictly applied the number of beneficiaries would increase massively in Spain, from the current 156,858 to 861,190 households. This increase in the number of recipients just vary the average monthly amount received would from 325 to 329. The only negative result from the simulation has to do with the cost that would have to bear regional administrations, which would increase million euros, going from 619 to 3,973 million. Although this increase may seem unattainable, really is not so high when it is compared to other public expenditures. On the other hand, both the number of beneficiaries and the cost would not increase similarly in all regions. Those regions that have a more developed system, such as the Basque Country, would not need to increase too many its benefits (in relative terms) as others that currently provide benefits to a limited number of people, such as Murcia and Castilla La Mancha. We have also used the simulation results to analyse its influence on poverty. While it is true that the MII would not allow people to escape from poverty (defined as 60% of median income), this result is not so negative because the aim of the MII is to fight against extreme poverty. Our simulation shows that the average income of poor people would increase significantly. This positive result is reinforced by changes in the intensity of poverty. The strict application of the rules would reduce this indicator from 43.6% to 36.9%. 26

27 7. References Adiego, M.; Cantó, O.; Levy, H.; Paniagua, M.M. y López, T. (2011). EUROMOD Country Report. Spain (ES). Mimeo, 30/12/2011 Arriba, A. (1999). Procesos de implantación de políticas de rentas mínimas de inserción en España. Unidad de Políticas Comparadas (CSIC), Documento de Trabajo 99 09, en Arriba, A. (2009). Rentas mínimas de inserción de las Comunidades Autónomas: Una visión conjunta de su evolución y alcance. Gestión y Análisis De Políticas Públicas, (2), Ayala, L. (2004). Las políticas contra la pobreza (II): Experiencias europeas y realidad española. En J. A. Gimeno Ullastres (Ed.), Exclusión social y estado de bienestar. Madrid: Centro de Estudios Ramón Areces. Busilacchi, G. (2008). The different regimes of minimum income policies in the enlarged Europe. XII International Congress of BIEN, Dublin, en Consejo Económico y Social (2009). Pobreza y rentas mínimas de inserción: Situación y perspectivas. Cauces: Cuadernos Del Consejo Económico y Social, (9), Currie, J. (2004). The Take up of Social Benefits. NBER Working Paper, No De Giorgi, G. y Pellezzari, M. (2006). Welfare migration in Europe and the cost of a harrmmonised social assistance. IZA Discussion Paper, nº 2.094, en Dirección General de Política Social (2010). Informe Rentas Mínimas de Inserción. Año Ministerio de Sanidad y Política Social, Madrid. Dirección General de Política Social (2011). Informe Rentas Mínimas de Inserción. Año Ministerio de Sanidad, Política Social e Igualdad, Madrid. Fuenmayor, A., y Granell, R. (2009). Registros fiscales y encuestas: Ventajas e inconvenientes. En F. Picos, y S. Díaz de Sarralde (Eds.), Las reformas fiscales bajo el microscopio (pp ). Madrid: Instituto de Estudios Fiscales. Levy, H., y Mercader, M. (2005). El impacto de los subsidios asistenciales en España. el sistema actual y posibles alternativas de reforma. In J. Ruiz-Huerta Carbonell (Ed.), Políticas públicas y distribución de la renta (pp ). Madrid: Moreno, G. (2010). Veinte años de rentas mínimas de inserción autonómicas: El caso vasco dentro del contexto español y europeo. Revista De Fomento Social, (259),