Tag: Redistribution

When Fair Isn’t Fair: Framing Taxes and Benefits

Posted on March 26, 2018 | Policy Brief

Taxes and benefits create incentives for people to adopt or avoid certain behaviours. They create premiums for (socially) preferred states. A premium can be determined by either taxing unwanted behaviour or by subsidizing desired behaviour. The resulting economic incentive for changing one’s behaviour is nominally equivalent under both mechanisms. However, the choice of frame for an incentive to be either described in terms of a tax or as a benefit can strongly influence perceptions of what is fair treatment of different, e.g. income, groups. Using a survey-experiment with Flemish local politicians, we show policy-makers to be highly susceptible to such tax and benefit framing effects. As such effects may (even unintendedly) lead to sharply different treatment of the same group under the two mechanisms, important questions arise, particularly for the design of new tax and benefit schemes.

The design and implementation of redistributive policies usually evoke much discussion. Opinions, both in public and often also in political debate, tend to be driven by ethical and fairness considerations. However, such concerns can lead to unintended consequences and – at least in terms of ex-ante intended fairness – to ex-post imbalanced incentive structures for different (income) groups.

An important function of taxes and benefits is the creation of premiums for certain behaviours or actions. Either unwanted behaviour may be taxed and thereby sanctioned, or desired behaviour may be encouraged through benefits. Irrespective of the method chosen, an economic incentive is created for individuals to opt for the desired behaviour.

The way such premiums are defined can usually be thought of as a two-step process. First, a baseline for a given behaviour, action, or state is chosen as a reference-point. For instance, baseline behaviours could be to not have retirement savings, to not use safety-certified equipment or follow accepted standards at work, or to not have children. Arguably, these are cases warranting the creation of incentives to encourage people to adopt the socially desirable behaviours of saving money for their old age, working in a safe environment, and having children. The second step, then, requires a choice of mechanism to create an incentive. The mechanism can be to either punish the unwanted behaviour – such as not adhering to safety standards at work – or to grant (cost-reducing) subsidies and benefits for taking the desired action, such as saving for old age or having children.

Importantly, the combination of the chosen reference point and the mechanism to create the incentive can influence the way people think about the fairness of an incentive when the targets belong to different (income) groups. Schelling (1981) demonstrated this point in an in-class experiment, which, somewhat simplified, runs as follows:

Families typically receive some child benefit: they get a certain sum per child. Imagine there are two families, one poor and one rich, both with their first child. What amounts of child benefit should each family get? Should the poor get more than the rich, should both families get the same, or should the rich family get more for having a child than the poor family? Schelling’s students would tend to voice support for either the poor getting more or both families getting the same. After all the rich family is surely already affluent enough to support their child. At the extreme, the rich family would get nothing for having a child, and the poor family quite a lot.

Now think of a world where the standard is to have a child, and couples who do not have a child have this ‘socially undesirable’ behaviour ‘penalised’ through a fee, for instance in the form of a tax. Should the poor couple pay a higher fee, should both couples pay the same, or should the rich couple pay a higher fee? The students now overwhelmingly supported requiring the rich couple to pay more. After all, they have more disposable income. However, in this case, the rich couple receives a lot for having a child (they no longer need to pay the steep fee), whereas the poor family may get no (additional) economic incentive for having a child. The treatment of the same family thus obviously drastically differs between the two frames. At the extreme, the poor family gets quite a lot for changing from having no children to having one child in the first frame, but nothing in the second frame. For the rich family, the situation is the reverse: there is no premium for having a child in the first frame, but potentially quite a high premium for having a child in the second frame.

Does this thought-experiment matter outside the classroom (see also Traub 1999, McCaffery & Baron 2004), beyond the context of child benefit, and among those actually exposed to the design considerations of tax and benefit systems? In a recent paper (Kuehnhanss & Heyndels 2018), we test the occurrence of such framing effects with elected local politicians in Flanders, Belgium, who are involved in the budgetary decision-making in their municipalities.

Framing experiment

We invited 5,928 local politicians to take part in an online survey on economic and social preferences in spring 2016. Participation was voluntary, not incentivised, and questions were not compulsory, allowing respondents to skip them if they so chose. In total, 869 responses to the survey were registered and (N₁=) 608 participants provided usable answers to the questions relevant to the framing effect described above.

Participants were randomly allocated to one of two groups, each receiving a slightly different wording of the following question:

“In Belgium couples receive financial benefits from the state. Suppose that it is not relevant how the transfer is funded, and ignore any other benefits, which might come into play. How much [more / less] should a couple [with their first child / without children] receive per month than a couple [without children / with their first child]?”

One group saw the question in the benefit frame with only the italicised phrases in the brackets displayed; the other group saw the question in the tax frame with only the phrases in boldface displayed. In both groups, participants were then asked to fill in amounts they would consider appropriate for each of three couples with different monthly net incomes: €2,000, €4,000, or €6,000, respectively.

With framing effects – and distinct from classic rational choice models – the expectation is that the three couples would be treated differently depending on the phrasing of the question. In the italicised benefit version the amount granted should be decreasing with the income of the family. In the boldface tax version the stated amount should be increasing with the families’ income.

Figure 1. Results child scenario

Source: Kuehnhanss & Heyndels (2018, p.32)

As Figure 1 shows, the results strongly conform to this pattern. The low-income (€2,000) couple is granted an average of €330 in the benefit frame, but only €178 in the tax frame (recall that the premium in the latter arises from no longer receiving less – or ‘paying a fee’ – once there is a child). For the high-income (€6,000) couple, the amounts granted average €132 in the benefit frame, but a much higher €368 in the tax frame.

Environmental taxes and benefits

Child benefit systems are usually a well-established part of countries’ tax and benefit systems. The design of new instruments is more common in policy areas undergoing, for instance, technological change or being newly regulated. A relevant example is policy on the promotion of environmentally friendly behaviour and technologies, e.g. through ‘green’ taxes and subsidies. To test the validity of the hypothesised framing effect, we also included a second scenario in our survey related to the municipal interests of our respondents, namely car taxes. Flemish municipalities receive income from a surcharge levied on the car taxes paid by motorists. Consequently, we asked our participants (N₂ = 525, see the paper for details) to imagine the introduction of a new environmental certificate for cars in Belgium, and to provide amounts they would consider appropriate for the difference in annual tax paid on cars with or without the certificate. Specifically, roughly one half of participants was asked how much less the owner of a certified car should have to pay in annual car tax than the owner of a non-certified car (the subsidy frame). The other half was asked how much more the owner of a non-certified car should pay in annual car tax than the owner of a certified car (the tax frame). The question was again asked for three different levels, proxying wealth via the cost of the cars: €15,000, €30,000, and €45,000, respectively.

Figure 2. Results car scenario

Source: Kuehnhanss & Heyndels (2018, p.32)

Figure 2 shows the results. The effect is less pronounced in this scenario, as the slope for the granted amounts in the subsidy frame remains largely flat or slightly increases. Nonetheless, a substantial framing effect remains. In the tax frame, the amount of the premium (i.e. the amount of taxes no longer owed once a certificate is obtained) strongly increases with the cost of the car. Taking the most expensive car (€45,000) as an example, we thus observe differential treatment across frames also in this scenario. In the subsidy frame, the premium for having a certificate is €778, in the tax frame it is a much higher €1,333.

Conclusion

These results suggest a strong and economically meaningful effect of framing among policy-makers with a stake in tax and benefit systems. While the exact mechanism driving the results invites further research, the strongly divergent premiums, and hence distribution of incentives, across baseline frames raise concerns of unintended effects in the design of taxes and benefits. Especially new schemes – e.g. ‘green’ policy, reform, or regulatory expansion – may benefit from increased scrutiny in the design process. Awareness of susceptibilities to framing and its potential influence on the formulation of individual tax and benefit instruments may help to align intended fairness, incentive structures, and redistributive outcomes.

References

Kuehnhanss Colin R.; and Bruno Heyndels, 2018. ‘All’s fair in taxation: A framing experiment with local politicians’ Journal of Economic Psychology, 65, 26-40.
McCaffery, Edward. J.; and Jonathan Baron, 2004. ‘Framing and taxation: Evaluation of tax policies involving household composition’ Journal of Economic Psychology, 25(6), 679–705.
Schelling, Thomas C., 1981. ‘Economic reasoning and the ethics of policy’ Public Interest, 63, 37–61.
Traub, Stefan, 1999. Framing Effects in Taxation. Heidelberg: Physica-Verlag

Increasing Resources for Families with Children Through the Tax System: Recent Reform Proposals from Poland

Posted on December 2, 2013 | Policy Brief

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This brief discusses the consequences of a recent reform proposal that aims to redistribute resources to low-income families with children through the income tax system in Poland. The proposed reform replaces the current child tax credit with additional amounts of the universal tax credit, and by changing the sequence in which tax deductions are accounted for, it increases resources of low-income families with children by about 1.7 billion PLN per year (0.4 billion EUR). The brief examines four possible ways of additional tax system modifications that would make the reform package neutral for the public finances, and presents distributional implications of the reforms.

The level and structure of financial support for families with children has become an important policy focus in Poland; a country that faces high levels of child poverty and one of the lowest fertility rates in Europe (Immervoll et al., 2001; Haan and Wrohlich, 2011; Eurostat, 2013). In this brief, we outline recent tax reform proposals that aim to increase financial support for low-income families with children through the tax system. A range of such potential reforms has been examined in Myck et al. (2013b); a report prepared for the Chancellery of the President of the Republic of Poland. One of the options became the key element of the President’s family support program Better climate for families proposed in May 2013. Below we discuss its main features and various options for financing the proposals.

The proposed modification of financial support for families would replace the current child tax credit with additional amounts of the universal tax credit conditional on the number of children, and increase tax advantages for families by changing the sequence in which tax credits are accounted for in a way that is favorable for families with children (Chancellery of the President of Poland, 2013). The main beneficiaries of this reform would be low-income families with children whose income is too low to take full advantage of the current child-related advantages. The overall cost of the reform would amount to about 1.7 billion PLN (0.4 billion EUR). In the final section of the brief we discuss potential ways of making the reform budget neutral.

The analysis has been conducted using CenEA’s micro-simulation model SIMPL on reweighted and indexed data from the 2010 Household Budget Survey (HBS) collected annually by the Polish Central Statistical Office (see Morawski and Myck, 2010, 2011; Myck, 2009; Domitrz et al., 2013; Creedy, 2004).

Financial Support for Polish Families in 2013

In Poland, financial support for families with children depends on the level of family income and the demographic structure of the household. The system consists of two main elements – family benefits on the one hand, and tax preferences for families with children on the other. Following Myck et al. (2013a), we define financial support for a family j (FSF_j) as the sum of family benefits received by the family (FB_j), and tax preferences that families with children collect in the PIT system is defined as the difference in the level of tax liabilities and health insurance contributions paid by the family (PITHI_jD0 – PITHI_jDn) supposing they have no children (D0) and on condition them having n number of dependent children (Dn):

FSF_j = FB_j + (PITHI_jD0 – PITHI_jDn) [1]

Figure 1a presents the current level of the financial support for single-earner married couples and Figure 1b presents the same for single parents with one and three children in relation to the level of gross earnings.

Family benefits

Family benefits, which include family allowance with supplements, childbirth allowance and nursing benefits, are means-tested and related to the number and age of dependent children in the family and specific family circumstances. Family benefits are granted only to low-income families and are subject to point withdrawal once the family crosses the income eligibility threshold (539 PLN of net income per person). For example, the stylized married couples in Figure 1 lose family benefits when their monthly gross income exceeds 2,060 PLN if they have one child and 3,435 PLN if they have three children (for single parents these thresholds equal 785 PLN and 1,825 PLN respectively).

Figure 1. Monthly level of financial support received by families with one and three children dependent on their age and family gross income in 2013 (PLN/month)

(a) Married couple with one spouse working

b) Single parent working

Note: FB – family benefits; CTC – child tax credit; joint taxation preferences: UTC – additional amount of universal tax credit; IB – shift of tax income bracket. In case of the single parent alimonies from the absent parent are assumed at the median value from 2010 data, which is 410.50 PLN for 1 child and 724.67 PLN for 3 children. Gross income of the single parent includes income from work only. Alimonies are taken into account for FB income means testing. Source: Myck et al. (2013a).

Tax preferences

Taxpayers with children can deduct a non-refundable child tax credit (CTC) from the accrued tax, with the maximum values of the CTC related to the level of universal tax credit available to all tax payers (UTC is 46.37 PLN per month). For each of the first two children in the family, taxpayers can deduct up to two values of the UTC (92.67 PLN per month), for the third child up to three values (139.00 PLN per month) and for the fourth and following children up to four values of the UTC (185.34 PLN per month). The CTC is not available for high-income parents with one child (whose annual taxable income exceeds 112,000 PLN per year).

Further tax advantages are available for single parents through joint taxation, which translates into substantial gains in particular for high-income parents. As Figure 1 shows, single parents whose gross income exceeds the second tax income bracket (15,745 PLN per month) gain up to 1,044.19 PLN per month if they have one child and 1,368.54 PLN if they have three children. With the same income levels, the system grants nothing to married couples if they have one child and 324.34 PLN if they have three.

In the current system, the CTC can be deducted from the accrued tax only after the full amount of UTC and the tax-deductible part of health insurance (HI) contributions have been exhausted. As a consequence, there is a large group of low-income families whose income is too low to take full advantage of the CTC. As Figure 2 illustrates, the higher the number of children is in a family, the lower is the proportion of families who take full advantage of the credit. Although the percentage of those using the full CTC is 76.1% for families with one child, it decreases to 67.6% for those with two children and is as little as 30.8% for families with three or more kids. Over 40% of the latter use only half of the CTC they are entitled to.

Figure 2. Use of maximum amount of CTC by number of children

Note: Proportions of families with taxable income satisfying other conditions for CTC. Source: Myck et al. (2013a).

Recent Reform Proposals

In a recent report for the Chancellery of the President of Poland, we have analyzed several options for the reform of the family-related elements of the tax system (Myck et al., 2013b). One of these has become the key element of the presidential reform proposal (Chancellery of the President of Poland, 2013). The reform assumes that the CTC is replaced with the amounts of the Universal Tax Credit conditional on the number of children in the family in such a way as to maintain the current maximum advantages offered to families through the CTC system. The main purpose of the reform is to reverse the tax deduction sequence so that tax advantages related to having children are deducted from the accrued tax before considering credits related to health insurance contributions. Such construction would enable low-income families to make greater use of child-related tax advantages, while leaving the situation of higher-income families unchanged.

Figure 3. Monthly tax advantages from the reform among families with 1-4 children (PLN/month)

Source: CenEA – own calculation based on SIMPL model and 2010 HBS data.

Figure 3 presents monthly levels of tax advantages resulting from the proposed reform conditional on the number of children in the family and the level of gross income. We note that families with children gain from the reform if their income exceeds 735 PLN per month. Tax advantages resulting from the proposed modifications are exhausted at different levels of gross income depending on the number of children (from 2,630 PLN for families with one child to 8,010 PLN for those with four children). The higher the number of children is, the greater is also the potential maximum gain – for example, families with four children and income of 4,010 PLN per month would gain up to 311.35 PLN per month.

The results of the analysis show that, overall, 2 million households with children would benefit from this reform (below referred to as System 1). The total annual change in households’ disposable income (equivalent to the total cost for public finances) would amount to 1.69 billion PLN (see Table 1 below).

Table 1. Average annual change in households’ disposable income by number of children in Systems 1-5 (billion PLN)

	No children	1 child	2 children	3+ children	Total
System 1	0,00	0,39	0,60	0,70	1,69
System 2	-0,45	-0,20	0,04	0,55	-0,08
System 3	-0,65	-0,09	0,17	0,59	0,02
System 4	-0,66	-0,15	0,23	0,59	0,01
System 5	-0,86	-0,04	0,31	0,63	0,04

Note: Total annual change in disposable income includes change in tax liabilities and level of social benefits. Source: Myck et al. (2013b).

Table 1 shows that most of the resources would be beneficial for families with three or more children (0.7 billion PLN per year), while families with one or two children would benefit about 0.39 billion PLN and 0.6 billion PLN per year, respectively.

The distribution of total income gains by income deciles is presented in Figure 4. The gains are clearly focused in the lower part of the income distribution. For example, families with children in the second income decile would receive a total of 0.4 billion PLN, while those in the bottom and third decile would recieve approximately 0.25 billion PLN. Only 0.04 billion PLN of the total cost would be distributed to families in the top income decile.

Figure 4. Distribution of total annual gains in households’ disposable income by deciles: Systems 1-5 (billion PLN)

Note: Total annual change in disposable income includes change in tax liabilities and level of social benefits. Source: Myck et al. (2013b).

Potential Ways of Financing the Reform

Concerns about the state of public finances naturally imply questions related to the potential ways of financing any additional tax giveaways. Myck et al. (2013b) presents four alternative modifications of the tax system that make the entire package of reforms neutral for the public finances. These are:

System 2 – CTC reform + limitations on joint-taxation preferences for married couples (both with or without children) and single parents;
System 3 – CTC reform + reduction of tax income threshold from 85,528 to 68,000 PLN per year;
System 4 – CTC reform + reduction of tax revenue costs from 1,335 to 475 PLN per year;
System 5 – CTC reform + reduction of tax-deductible part of health insurance from 7.75% to 7.45%.

The overall total outcomes of these proposals for household disposable income are illustrated in Table 1 and Figure 4. The implications in terms of the redistribution of the packages – with losses among childless households and gains among those with children – are clear under all of the proposed packages, although all of the reform combinations imply small losses also for families with one child. Total disposable income of childless households falls by 0.45 PLN per year under System 2 and by as much as 0.86 billion PLN under System 5. By shifting the majority of the costs to households without children, the latter is simultaneously the most generous for families with children since income of those with two children grows on average by 0.31 billion per year, while of those with more children see a growth of 0.63 billion PLN per year.

Figure 4 illustrates that in all of the revenue neutral reform packages, the households from the highest two deciles are the biggest losers. That the financing of the shift of resources to low-income families falls on households from the top income decile is particularly evident in the case of Systems 2 and 3 where total disposal income for these households fall by 1.64 billion PLN and 1.52 billion PLN, respectively. Since changes to revenue costs and deduction of HI contributions apply to almost all taxpayers, Systems 4 and 5 are less favorable for households from the lower deciles and generate losses for the upper part of the income distribution. However, a large part of cost is also born by households from the tenth decile (0.26 and 0.39 billion PLN, respectively).

While the combinations of tax changes presented above would be neutral with respect to the current system of taxes in Poland, it is worth noting that the policy of tax increases through the tax-parameter freezing implemented in 2009 has increased taxes by far more than the cost of the Presidential reform proposal. As we showed in Myck et al. (2013c), this policy increased taxes by 3.71 billions PLN per year, of which 2.21 billions was paid by families with children. The recent proposal could thus be thought of as a way of redistributing these resources back to families with children.

Conclusions

Financial support for families with children is an important element of government policy with implications for child poverty, labor-market participation among parents, as well as fertility (Immervoll et al., 2001; Haan and Wrohlich, 2011). In this brief, we outlined the results of a recent analysis of direct financial consequences of modifications in the Polish system of support for families through the tax system with the focus on a reform proposal presented by the Polish President in the program Better climate for families. The reform would benefit lower-income families with children at the cost of about 1.7 billion PLN. As a result, annual income of the families from the three bottom deciles would grow by 0.93 billion PLN. A high proportion of the gains (0.7 billion PLN) would go to families with three or more children.

We also presented four additional modifications of the tax system that would make the CTC reform revenue neutral. Reform packages that withdraw joint-taxation preferences and decrease the threshold of the income tax to a higher rate would be most effective in ensuring redistribution of support for low-income households. It is worth noting though, that the recent approach of the Polish government to the tax system has implied substantial increases in the level of income taxes through the freezing of income tax parameters, and these alone would be more than sufficient to finance the proposed tax changes.

▪

References

Creedy J. (2004). Reweighting Household Surveys for Tax Microsimulation Modelling: An Application to the New Zealand Household Economic Survey. Australian Journal of Labour Economics 7 (1): 71-88. Centre for Labour Market Research.
Domitrz A., Morawski L., Myck M., Semeniuk A. (2013). Dystrybucyjny wpływ reform podatkowo-świadczeniowych wprowadzonych w latach 2006-2011 (Distributional effect of tax and benefit reforms introduced from 2006-2011). CenEA MR01/12; Bank i Kredyt 03/2013.
Chancellery of the President of Poland (2013). Dobry klimat dla rodziny. Program polityki rodzinnej Prezydenta RP. (Better climate for families. Family support program of the Polish President.)
Eurostat online database 2013 – epp.eurostat.ec.europa.eu. Date of access: 28.11.2013.
Haan P., Wrohlich K. (2011) Can Child Care Encourage Employment and Fertility? Evidence from a Structural Model. Labour Economics 18 (4), pp. 498-512.
Immervoll H., Sutherland H., de Vos K. (2001). Reducing child poverty in the European Union: the role of child benefits. In: Vleminckx K. and Smeeding T.M. (eds.) Child well-being, Child poverty and Child Policy in Modern Nations. What do we know? The Policy Press: Bristol.
Morawski L., Myck M. (2010).‘Klin’-ing up: Effects of Polish Tax Reforms on Those In and on Those Out. Labour Economics 17(3): 556-566.
Morawski L., Myck M. (2011). Distributional Effects of the Child Tax Credits in Poland and Its Potential Reform. Ekonomista 6: 815-830.
Myck M. (2009). Analizy polskiego systemu podatkowo-zasiłkowego z wykorzystaniem modelu mikrosymulacyjnego SIMPL (Analysis of the Polish tax-benefit system using microsimulation model SIMPL). Problemy Polityki Społecznej 11: 86-107.
Myck M., Kundera M., Oczkowska M. (2013a). Finansowe wsparcie rodzin z dziećmi w Polsce w 2013 roku (Financial support for families with children in Poland in 2013). CenEA MR01/13.
Myck M., Kundera M., Oczkowska M. (2013b). Finansowe wsparcie rodzin z dziećmi w Polsce: przykłady modyfikacji w systemie podatkowym (Financial support for families with children in Poland: examples of modifications in the tax system). CenEA MR02/13.
Myck M., Kundera M., Najsztub. M, Oczkowska M. (2013c). Ponowne „mrożenie” PIT w kontekście zmian podatkowych od 2009 roku (PIT freezing in the context of tax reforms since 2009). Komentarze CenEA: 06.11.2013.

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* This brief draws on recent research at the Centre for Economic Analysis in the projects financed by the Chancellery of the President of the Republic of Poland and the Batory Foundation (project no: 22078). The analysis has been conducted using CenEA’s micro-simulation model SIMPL based on the 2010 Household Budget Survey data collected annually by the Polish Central Statistical Office (CSO). The CSO takes no responsibility for the conclusions resulting from the analysis. Any views presented in this brief are of the authors’ and not of the Centre for Economic Analysis, which has no official policy stance.

Preferences for Redistribution in Post-Communist Countries

Posted on May 13, 2013 | Policy Brief

Public attitudes toward inequality and the demand for redistribution can often play an import role in terms of shaping social policy. The literature on determinants of the demand for redistribution, both theoretical and empirical, is extensive (e.g., Meltzer and Richard 1981, Alesina and Angelotos 2005). Usually, due to data limitations, transition countries are usually considered to be a homogeneous group in empirical papers on the demand for redistribution. However, new data on transition countries allow us to look more deeply into the variation within this group, and to look at which factors are likely to play a significant role in shaping a society’s preferences over redistribution.

The data we use are from the second round of the EBRD and WB Life in Transition Survey (LiTS) (EBRD Transition Report 2011). This is a survey of nationally representative samples consisting of at least 1000 individuals in each of the 29 transition countries.[1] In addition, and for comparison purposes, this survey also covers Turkey, France, Germany, Italy, Sweden and UK. Furthermore, in six of the countries surveyed – Poland, Russia, Serbia, Ukraine, Uzbekistan and UK – the sample consists of 1500 individuals.

Redistribution is, in general, a complex issue, which can take various forms and rely on different mechanisms. In this policy brief, we will only focus on two forms of public attitudes towards redistribution. The first is direct income redistribution from the rich to the poor and public preferences for or against this form of redistribution. The second is indirect redistribution through the provision of public goods, some of which favor certain groups of population over others. In particular, we will consider preferences over extra government spending allocations in the areas of education, healthcare, pensions, housing, environment and public infrastructure. Generally, we would like to explore in greater detail to what extent there are differences across countries in terms of public preferences over redistribution and what might explain differences both within and across societies.

Both survey rounds include questions regarding public preferences towards income redistribution, direct (from the rich to the poor) and indirect (through government spending towards certain public goods). Data for exploring public preferences for direct redistribution can be obtained from a question in the survey that asks respondents to score from 1 to 10 whether they prefer more income inequality or less. More specifically, in the LiTS 2010, the question is the following:

Q 3.16a “How would you place your views on this scale: 1 means that you agree completely with the statement on the left “Incomes should be made more equal”; 10 means that you agree with the statement on the right “We need larger income differences as incentives for individual effort”; and if your views fall somewhere in between, you can choose any number in between?

Note, however, that we use the reverse of this so that 10 represents greater equality and 1 represents wider differences. Bearing this in mind, figure 1 shows the average scores for redistribution preferences for a selection of the countries for 2010 and shows a sizeable variation ranging from 4.4 (more inequality) in Bulgaria to 7.87 (greater equality) in Slovenia. The mean for Russia is 6.92.

The data also allows for a comparison to be made between these preferences in transition countries and in the developed economies covered in the survey. For instance, Russians are on average close to Germans in their preferences for redistribution, while Estonians and Belarusians prefer less redistribution and are closer to the British, on average.

Figure 1. Preferences for Direct Redistribution

Indirect measures of attitudes towards redistribution can add further depth to these societies’ preferences. In particular, the indirect measures in the 2010 survey are derived from a question that asks respondents to rate from 1 to 7 their first priorities for extra government spending.

Q 3.05a “In your opinion, which of these fields should be the first priority for extra government spending: Education; Healthcare; Housing; Pensions; Assisting the poor; Environment (including water quality); Public infrastructures (public transport, roads, etc.); Other (specify)”?

The country averages for these indirect measures for 2010 are presented in Figure 2. The graph reveals a sizeable cross-country variation. For instance, 43.5% of respondents in Mongolia preferred channeling extra government money to education, while 48.7% of respondents in Armenia selected higher healthcare spending. Almost 39% of respondents in Azerbaijan chose assistance to the poor as the first priority for government spending, while the corresponding figure was only 8.3% in Bulgaria and 4% in the Czech Republic. More than 34% of the Russians choose healthcare as their first priority, another 20% choose education, 15% would like the money to be channeled to housing, 14.5% to pensions, 11% to support the poor, 3% to support environment, and only 2% to public infrastructure (2010).

These numbers highlight that there are sizeable differences across the transition countries regarding preferences for redistribution. Also, regarding the form of indirect redistribution in terms of preferences over how government budgets should be prioritized and allocated. Several groups of factors or determinants are typically listed in academic literature to help explain what drives public preferences over the degree and form of redistribution. In the first group of factors, there are various determinants at the individual level. Within the group of individual determinants, self-interest or rational choice of a degree of redistribution favorable to the individual with usual (individual) preferences are stressed. Alternatively, motives behind a preference for redistribution can be related to social preferences (preferences for justice or equity) and reciprocity. Within this general group of self-interest, attitudes towards risks can be stressed as a crucial factor behind demands for social insurance and hence for indirect forms of redistribution. Individuals’ prospects of upward mobility, expectations about their future welfare or ‘tunnel effect’ in shaping their views and preferences over redistribution are also underlined. Also, the commonly held beliefs about the causes of prosperity and poverty are considered to be important in shaping the public’s attitudes under the umbrella of social preferences.

The literature covers possible institutional determinants for preferences towards redistribution and emphasizes the role of the level of inequality in a society and typically relates to the median voter hypothesis in democracies. It is also stressed that welfare regimes (liberal, conservative) can play a role in shaping the level of public support for redistribution.

Figure 2. Preferences for Indirect Redistribution

A closer examination of the data and estimates of the factors shaping individuals preferences over redistribution in the 2010 survey, are consistent with motives involving strong self-interests of the respondents.[2] Those from richer households have less support for redistribution, with the result being robust to the measure of household income used. The past trend in household income positions is insignificant, while the higher the expected income position of household in the coming four years, the less supportive the respondents are of income redistribution (elasticity -0.1). Those who experienced severe hardships with the recent crisis tend to support redistribution more than those who had little problems or not at all (elasticity 0.13).

Furthermore, the role of preferences towards uncertainty is confirmed: the higher the (self-reported) willingness to take risks, the less likely the individual is to support or favor redistribution. Respondents with tertiary education are less inclined to support redistribution of income from the rich to the poor, compared to those with secondary education (elasticity is -0.4). Having a successful experience with business start-ups also decreases demand for income redistribution from the rich to the poor (elasticity -0.3). Those living in rural areas are more in favor of redistribution compared to metropolitan areas, while living in urban areas shows the same level of support for redistribution as those living in metropolitan areas. In each of these cases, it appears that those who would benefit the most from redistribution favor it more than those who view it as coming at their expense, or possible expense in the future.

Beliefs regarding the origins of success and poverty are also shown to be statistically significant and negative, as predicted: those who believe effort and hard work or intelligence and skills are the major factors for success are less supportive of income redistribution (elasticity -0.16). Those who consider laziness and lack of will power the major factors for people’s lack of success are also, consistently, less supportive of redistribution (elasticity -0.2).

It also turns out that better democratic institutions are correlated with a higher demand for redistribution. The result is robust across the measures used, i.e. it does not seem to depend on the particular measure used. The size of the effect is quite pronounced: a one standard deviation increase in the democracy measure increases demand for redistribution from 16 percentage points, when the voice and accountability measure is used, to 33 and 36 percentage points when controls of the executives and democracy index are used.

Furthermore, the better the governance institutions, as measured by the rule of law and control of corruption indexes, the higher is the demand for redistribution. However, the result is not robust to the various measures used. Government effectiveness appears to be insignificant (though with a positive direction), and the regulatory quality measure is insignificant but with a negative direction. The size of the effects is again quite pronounced. A one standard deviation increase in the rule of law measure increases demand for redistribution by 17 percentage points, and a one standard deviation increase in the control of corruption measure increases demand for redistribution by 27 percentage points.

The higher the level of inequality, the larger is the demand for redistribution as might be expected. This result is robust across all measures used. The size of the effect varies from 16 to 18 percentage points in response to a one standard deviation increase.

A regression analysis of preferences towards indirect redistribution also shows that self-interest motives are very pronounced, but there are traces of social preferences as well. In particular, younger people (age 18-24) would like to have more subsidized education and housing at the expense of healthcare and pensions in comparison with the age 35-44 reference group. Those in the age 25-34 group would like to redistribute public spending to housing and environment at the expense of education, pensions and public infrastructure. Respondents in the age 45-54 group would also like to redistribute additional spending from education but to pensions. The two groups of older people (age 55-64 and 65+) would like to shift extra spending from education and housing to healthcare and pensions. The group of age 65+ would also like to shift money from assistance to the poor.

Respondents with tertiary education (in comparison with holders of a secondary degree) favor extra spending for education, environment and public infrastructure at the expense of healthcare, pensions and assisting to the poor, thus revealing additional elements of social motivations. Respondents with primary education, when compared to holders of secondary degree, would like to redistribute public money from education to pensions and assistance to the poor. Respondents with poor health favor additional spending on healthcare and pensions at the expense of education.

High skilled (in terms of occupational groups) respondents would like to redistribute public money from pensions to education. Those with market relevant experience of being successful in setting up a business tend to support education and public infrastructure at the expense of housing and pensions, though the result lack statistical power.

Respondents from households with higher income support extra spending for education, environment and public infrastructure at the expense of healthcare, pensions and assistance to the poor; again pointing to the other elements of possible social motivations. Those with a self-reported positive past trend in income position tend to support spending extra money on the environment at the expense of assistance to the poor (the latter lacks statistical power). If the respondent lives in its own house or apartment, s/he tends to support redistribution from housing and assistance to the poor, to healthcare and pensions.

Respondents whose households were strongly affected by the crisis would like expenditure on environment and public infrastructure to be reduced. Those with higher self-reported willingness to take risks would redistribute extra public money to education at the expense of healthcare and housing.

Respondents who believe that success in life is mainly due to effort and hard work, intelligence and skills favor education at the expense of assistance to the poor and public infrastructure, suggesting they might view education as the key to escape poverty. Those who think that laziness and lack of willpower are the main factors behind poverty would, unsurprisingly, redistribute extra public money from assistance to the poor to healthcare.

Males (as compared to females) favor extra spending on education, housing, environment and public infrastructure at the expense of healthcare. The self-employed favor extra spending of public money to pensions at the expense of housing. There is no difference across respondents living in metropolitan, rural or urban locations.

A regression analysis shows that better democratic institutions are correlated with higher support for allocation of additional public spending to education and healthcare, environment and public infrastructure. The effects are larger for education and healthcare: one standard deviation in the democracy index increases the support for spending money on education by 3 percentage points, for healthcare by 3.1 percentage points, and only by 0.4 and 0.6 percentage points for environment and public infrastructure, respectively. This reallocation is at the expense of assistance to the poor (3.5 percentage points), housing (2.6 percentage points) and pensions (1.1 percentage points). The pattern is robust to the measure of democratic institutions used, though the marginal effects vary slightly depending on the measure.

The influence of governance institutions is similar. Respondents in countries with better governance institutions favor allocation of extra public money to education (3.2 percentage points in response to one standard deviation in government effectiveness), health care (2.9 percentage points), environment (0.9 percentage points) and public infrastructure (0.6 percentage points). The reallocation is at the expense of assistance to the poor (4.2 percentage points), housing (3.3 percentage points) and pensions (0.2 percentage points). The pattern is also robust to the measure of governance institutions with the marginal effects varying slightly depending on the measure.

The higher the level of inequality in a country, the higher the demand for spending extra public money for education at the expense of assistance to the poor, pensions and public infrastructure. A one standard deviation increase in the index, increases demand for spending extra public money on education by 3.8 percentage points, and decreases spending on assistance to the poor by 2 percentage points, pensions by 1.9 percentage points, and public infrastructure by 0.06 percentage points. The results are robust to the inequality measure used.

Overall, the analysis provides empirical evidence that transitional countries are not homogeneous with respect to preferences for redistribution, with sizeable variations in country averages and in public preferences. The study of individual determinants of preferences for redistribution confirms a dominant role of self-interest, with some indications of social sentiments as well. In addition to the usual measures used in individual level analysis, these data allow better control for both positive and negative personal and household experience. The study of institutional determinants also confirms the role of income inequality in shaping public attitudes. In particular, higher inequality is confirmed to increase the demand for direct income redistribution. A novel motive of the paper is the influence of democracy and governance institutions on demand for redistribution. Better democracy and governance institutions are likely to stimulate demand for income redistribution, revealing both higher societal demand for redistribution and appreciation of the potential capability of the government to implement redistribution effectively.

The study of individual determinants of indirect demand for redistribution adds to the overall picture and confirms not only the self-interest motives but also social preferences especially pronounced among people with tertiary education and in high income groups. Better democratic and governance institutions stimulate redistribution of public money towards education, healthcare, environment and public infrastructure, while weaker democratic and governance institutions increases demand for allocation of public money to assistance to the poor, housing and pensions.

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References

Meltzer, A., Richards, S., 1981. “A Rational Theory of the Size of Government”. Journal of Political Economy 1989, 914–927.

Alesina, A., Angeletos, G.M., 2005. “Fairness and Redistribution”. The American Economic Review, 95(4), 960-98

[1] The countries covered were: Albania, Armenia, Azerbaijan, Belarus, Bosnia, Bulgaria, Croatia, Czech Republic, Estonia, FYROM, Georgia, Hungary, Kazakhstan, Kosovo, Kyrgyzstan, Latvia, Lithuania, Moldova, Mongolia, Montenegro, Poland, Romania, Russia, Serbia, Slovak Republic, Slovenia, Tajikistan, Turkey, Ukraine and Uzbekistan.

[2] The basic empirical equation to study individual determinants of public preferences towards income redistribution is the OLS with country fixed effects (for direct redistribution) and multinomial regression with country fixed effects (for indirect measures). When studying the influence of institutions, the equations are transformed to replace country fixed effects with an institutional measure (one at a time). To control for the basic economic differences, average GDP per capita was included.