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chapter 4 Equity and Fiscal Policy: Income Distribution Effects of Taxation and Social Spending

Author(s):
Dominique Desruelle, and Alfred Schipke
Published Date:
November 2008
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Author(s)
Rodrigo Cubero and Ivanna Vladkova Hollar 

Introduction

Central America’s high levels of poverty and income inequality place the distributional effects of fiscal policy at the center of policy dialogue. Central American governments have made poverty reduction one of their key policy objectives; even while its incidence has edged down in the past decade, poverty in Central America remains well above that in Latin America as a whole. Inequality in income distribution, moreover, is as high as in other parts of Latin America and stands out in a global context. Distributional outcomes are, fundamentally, a function of the distribution of productive resources (physical and human capital, land) and their rates of return, factors that are deeply embedded in historical and geographical conditions. However, public policies can affect the market-determined distribution of income, either through changes in the distribution of resources and their returns or through a redistribution of market income. Through appropriate policies, governments in the region can also help address the mechanisms that perpetuate inequality.

This chapter is concerned with the distributional effects of taxation and social spending in Central America, taking the underlying distribution of resources as given. The chapter surveys a number of existing tax and expenditure studies for the countries in the region, and assembles their underlying data in a coherent comparative framework to assess the combined distributional impact of taxation and social spending in Central America. The chapter also presents, as a reference, some evidence for other countries in Latin America and Europe.

The focus on the distributional impact of taxation merits justification. There is some consensus in policy circles that the redistributive goals of fiscal policy can best be achieved through well-targeted spending. The empirical evidence for developed and developing countries suggests that the overall effect of taxes on income distribution is generally limited, and that even relatively profound changes in tax structures have only a small distributional impact.1 In contrast, the distributional effects of public spending, especially of well-targeted social spending, can have substantial positive effects on equity and poverty reduction.2 Many analysts thus conclude that tax policy considerations should focus on efficiency issues, and that the redistributive aim of fiscal policy should be accomplished through the expenditure side.3 However, the distributional impact of taxation remains a relevant question for tax policy debates, which are largely influenced by incidence and equity considerations.4,5 A clearer understanding of the distributional effects of certain taxes, and of the determinants of such effects, may help shape more equitable tax systems without necessarily sacrificing efficiency.

The scope of the analysis in this chapter imposes some limitations. First, the chapter focuses on taxation and social spending, and thus does not reflect all components of fiscal policy. The direct distributional effects of other components of spending, and the indirect effects of the overall fiscal stance, are not included in the analysis. Second, the incidence and distributional impact are treated in a static sense. For instance, the analysis of social spending on education does not take into consideration its impact on the future earning potential of the poor; neither does the chapter consider how taxation and the public provision of social services and transfers might interact with each other or affect behavior (for example, in changing incentives to work or invest).6 Third, although the efficiency, effectiveness, and administrative simplicity of taxation and social spending are clearly important subjects for policy discussion, and may impinge on distributional outcomes, this chapter does not directly address them. Fourth, the reliance on existing studies of tax and spending incidence limits the degree to which cross-country comparisons can be taken literally: methodology and assumptions made for estimating the incidence of taxation and spending differ from study to study. It also constrains the time frame of the data: the available studies for the region are mostly based on data for 2000 (2003 for Panama and 2004 for Guatemala).

Nonetheless, the main findings and conclusions of the chapter are qualitatively robust. We find that the overall distributional effect of taxation in the region is small. In contrast, the redistributive impact of social spending is much larger, leading to a progressive combined redistributive effect of these two components of fiscal policy in all countries of the region. We also show that raising tax revenues, even if solely through the value-added tax (VAT), and devoting the proceeds to social spending would unambiguously result in an improvement in the income of the poorest households. Despite the limitations noted in the previous paragraph, the main qualitative conclusions of the chapter are robust: they hold for all countries in the region for which data are available and are consistent with evidence elsewhere. Moreover, they are unlikely to have been affected by changes in taxation or social spending in Central America in recent years. Tax structures change only slowly, and existing studies suggest that the distributional impact of major recent tax reforms in Nicaragua (Gasparini and Artana, 2003) and Guatemala (Auguste and Artana, 2005) have been small. Social spending has continued to trend up across the region, so the combined redistributive effect of taxation and social spending is likely to have become more progressive.

The chapter is organized as follows. The next section examines the features and distributive effects of tax systems in the region, while the third section focuses on social spending trends and distributive effects. The fourth section integrates the conclusions from the tax and spending incidence analysis, allowing an overall view of the net distributive impact of fiscal policy across Central America. The final section draws some policy implications.

Tax Systems in Central America: Structure and Distributional Impact

This section surveys the effects of the tax system on income distribution in Central America. For a given pattern of income distribution, the distributional effects of the tax system are a function of two factors: the size of tax collections relative to GDP and the incidence of the tax system on different income groups. The analysis below considers these two factors in turn. After a brief description of the structure and evolution of tax systems in the region, we survey the existing evidence on the incidence of taxation in Central America and discuss the progres-sivity of individual taxes.

Structure and Evolution

Tax systems in Central America are characterized by a low share of tax revenue in GDP. The average tax burden of the central government in Central America in 2003 was around 13 percent of GDP, marginally higher than its 1995 level (Table 4.1).7 The regional average was below the tax ratio for Latin America as a whole, which in turn is low by international standards. In the Organization for Economic Cooperation and Development (OECD) countries, for instance, central governments collected an average of 21 percent of GDP in 2003. However, there were important variations across Central America: central government revenues were only 8.7 percent of GDP in Panama in 2003 but 16.3 percent in Honduras. It must be noted, though, that throughout the region governments have strived to increase tax collections relative to GDP. With the exception of Guatemala and Costa Rica, the ratio went up by as much as 2 percentage points of GDP between 2003 and 2006. Appendix Table 4.A1 highlights another import characteristic of government revenue in Central America: tax revenue accounts for most central government revenues across the region. The exception is Panama, where taxes represented just 56 percent of central government revenue in 2006.8

Table 4.1.Evolution and Structure of Tax Revenue
Total Tax RevenueIncome TaxesTaxes on Goods and ServicesTrade TaxesOther Taxes
VAT and salesExcises
199520031995200319952003199520031995200319952003
(In percent of GDP)
Costa Rica12.313.63.14.04.24.71.42.73.61.50.00.6
Dominican Republic13.614.93.14.46.53.80.03.14.03.50.00.1
El Salvador11.411.53.23.34.96.1n.a.0.62.11.2n.a0.4
Guatemala8.011.71.61.52.95.31.01.21.91.40.62.3
Honduras17.816.34.93.53.56.02.61.42.01.54.83.9
Nicaragua12.215.21.73.83.66.25.14.10.91.01.00.1
Panama11.48.74.73.41.71.51.61.22.21.51.21.1
Central America, Panama, and Dominican Republic average12.413.13.23.43.94.82.02.02.41.71.01.2
OECD average119.720.88.89.95.76.03.33.20.50.21.51.5
Latin America average211.913.53.13.43.95.51.82.11.91.41.21.1
(In percent of total tax revenue)
Costa Rica10010025.429.633.734.811.619.829.411.30.04.5
Dominican Republic10010022.829.547.825.5n.a.20.829.423.50.00.7
El Salvador10010028.229.043.252.5n.a.4.818.510.410.23.3
Guatemala10010020.012.836.345.312.210.123.812.07.819.8
Honduras10010027.521.519.736.814.68.611.29.227.023.9
Nicaragua10010013.725.029.440.841.726.77.46.67.80.9
Panama10010041.039.114.817.214.013.819.317.210.912.6
Central America, Panama, and Dominican Republic average10010025.526.632.136.118.815.019.812.93.79.4
OECD average110010044.647.628.828.816.715.22.51.07.57.4
Latin America average210010025.824.932.840.815.315.615.710.510.48.1
Source: IMF staff calculations, based on data from country authorities.

Includes Canada, Mexico, United States, Australia, Japan, Korea, New Zealand, Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovak Republic, Spain, Sweden, Switzerland, Turkey, and United Kingdom.

Includes Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Mexico, Nicaragua, Panama, Paraguay, Peru, Uruguay, and Venezuela.

Source: IMF staff calculations, based on data from country authorities.

Includes Canada, Mexico, United States, Australia, Japan, Korea, New Zealand, Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovak Republic, Spain, Sweden, Switzerland, Turkey, and United Kingdom.

Includes Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Mexico, Nicaragua, Panama, Paraguay, Peru, Uruguay, and Venezuela.

Compared with advanced economies, Central America relies much more on indirect taxes (VAT and trade taxes) and less on income taxes. Tax structures in Central America are similar to those in other Latin American countries but very different from the structure prevalent in OECD countries. First, income taxes contribute on average about one-quarter of overall collection in Central America (and Latin America as a whole), compared with one-half in the OECD (Table 4.1). The exception is Panama, where income taxes account for more than 40 percent of tax collections. By contrast, the average share of trade taxes in total tax revenues is about 14 percent in Central America (and about one-fourth in Panama and the Dominican Republic), compared with only 1¼ percent in the OECD. Taxes on goods and services (VAT, sales, and excise taxes) account for similar shares of total revenue in Central America and the OECD. Other taxes, including property taxes, play a relatively small role in Central America (with the exception of Honduras), Latin America, and, to a lesser extent, OECD countries.

There has been an important shift in Central American tax structures away from trade taxes and toward VAT in recent years. Between 1995 and 2006, and despite a substantial increase in international trade volumes in the region, the share of trade taxes in total tax revenue fell from a regional average of 20 percent to just over 10 percent as a result of the rapid process of trade liberalization the region has undergone (Table 4.1 and Appendix Table 4.A1). The revenue loss has been made up by an increase in VAT, whose share in total collections rose from 32 percent to 38 percent. Also, the contribution of income taxes has slightly increased, while the share of excise taxes has fallen.

Distributional Effects of Taxation

Methodological Considerations

Analysis of the distributional effects of the tax system requires assumptions about the economic incidence of taxes. Determining how much tax a person pays implies making judgments about who ultimately bears the burden of the taxes (economic incidence), as opposed to who is legally liable to pay them (statutory incidence). These two notions of incidence can and do differ, given that statutory taxpayers may shift the tax liabilities partly or fully to others. The extent to which they can do so depends on a number of country-specific factors, such as the price elasticities of supply and demand for the goods concerned, the openness of the economy, its market structure, and regulations on business competition. Incidence can be established through computable general equilibrium (CGE) models or, more often (given the formidable data requirements of CGE models), by imposing tax shifting assumptions. The conventional assumptions made are that consumption taxes (VAT, sales, excise, and import taxes) are fully shifted forward to consumers,9 export taxes are paid by the producers, and personal income taxes are paid by the income recipients. For payroll taxes, employee contributions are assumed to be borne by the employees, but the cost of employer contributions can be either borne by the employer or shifted to the employee. In the case of corporate income taxes, more demanding assumptions are needed, as they can be shifted backward to capital owners or workers (through lower returns) or forward through higher consumer prices.10

Conclusions on the distributional effects of taxation are sensitive to incidence assumptions. They must, therefore, be taken with caution. CGE models suggest that changes in incidence assumptions can substantially alter the conclusions about who bears the cost of taxes (Gemmell and Morrissey, 2002). Moreover, some of the standard assumptions may be less appropriate for developing countries, in particular those regarding the incidence of indirect taxes. Shah and Whalley (1991) argue that import quotas, price controls, informal markets, and widespread evasion limit the scope for forward shifting of import and sales taxes. However, analytical convenience and lack of reliable data on the price elasticities of demand and supply limit researchers’ options.

The distributional impact of taxes and their redistributive potential can be measured using several indicators. The following are the most commonly used indicators:

  • Tax progression. Tax progression measures the effective tax ratio—that is, the tax effectively paid relative to income—per quantile (decile, quintile, quartile) of income. A tax is proportional, progressive, or regressive if the effective tax ratio remains constant, grows, or falls, respectively, as one moves up the income distribution scale.11 The analysis below uses a normalized measure of tax progression, referred to as the relative tax burden. It is defined as the effective tax rate, as a proportion of income, that each income group pays divided by the average tax rate for the population as a whole.
  • Lorenz and concentration curves. The progression of a tax can be graphically represented by a concentration curve, which measures the cumulative tax paid per quantile of pre-tax income. The progressivity of a tax can then be assessed by comparing the pre-tax Lorenz curve for income with the concentration curve for that tax.12 A tax is progressive over the entire income distribution scale if the concentration curve lies consistently under the pre-tax Lorenz curve (Lorenz dominance).
  • Quasi-Gini coefficients. Tax progression and concentration curves are local indicators of progressivity: they show the progressivity or regressivity of the tax as one moves from one section of the income distribution scale to the next. But if the pretax Lorenz and concentration curves cross one or several times (so that Lorenz dominance fails), no unambiguous conclusion can be reached about the overall progressivity or regressivity of the given tax. In this case, summary global indicators are useful, because they allow for a complete ordering of distributions. A simple and widely used global measure of tax incidence is the quasi-Gini coefficient for a given tax—that is, the Gini coefficient for that tax’s concentration curve.13 The higher the quasi-Gini coefficient for a given tax, the more progressive it is.
  • Kakwani index. A closely associated measure is the Kakwani index (K), which is the difference between the quasi-Gini coefficient for a given tax and the Gini coefficient for pre-tax income. If K > 0, the tax burden is distrib uted more unequally than pre-tax income, and thus the tax is progressive (it contributes to reducing inequality in income distribution). If K < 0, the tax is regressive.
  • Reynolds-Smolensky index. The Kakwani index does not take into account the importance of the revenues associated with a given tax relative to the economy and, therefore, does not provide an indication of the redistributive potential of the tax. The Reynolds-Smolensky (RS) index, defined as the pre-tax Gini coefficient minus the quasi-Gini index for post-tax income, addresses this problem directly. It measures how income inequality changes (in terms of Gini points) as a result of the introduction of the tax.14 The sign of the RS index is consistent with that of the K index: if positive (negative), the tax is progressive (regressive). But the magnitudes of K and RS may be very different: a tax that is highly progressive but whose revenues account for a small share of total income would have a negligible redistributive capacity. The tax’s Kakwani index would be high, but its Reynolds-Smolensky index would be very small.

The analysis above was expressed in terms of income, but the progressivity of taxes can also be measured in terms of the underlying distribution of expenditure or consumption. The foundation for the use of consumption rather than current income as a measure of welfare (or capacity to pay) lies in the argument that consumption patterns are less volatile and may be a more reliable indicator of actual or perceived permanent income. But whether current consumption levels provide a better measure of a household’s (or individual’s) capacity to pay is a highly controversial issue (see Box 4.1).

The Distributional Impact of Taxes in Central America

This section summarizes the available evidence on the incidence of taxation in Central America and its distributional effects.15 The analysis below is based on current total income as a measure of welfare, to impart some consistency or comparisons across countries.16 Data for the incidence of taxation in Honduras (from Gillingham, Newhouse, and Yakovlev, forthcoming) and Nicaragua (from Gómez Sabaini, 2005b), and for social spending in all countries, are based on quintiles of income. Thus, to enable the netting out of tax and social spending effects in the section on “Net Distributional Effects of Fiscal Policy,” data for tax incidence for Costa Rica and El Salvador, which were based on deciles, were converted to quintiles of income.17 Finally, the underlying data are limited to central government taxes, except in the case of the case of Honduras, where municipal taxes are included, and Nicaragua, where taxes for the city of Managua are reflected. Implicit taxes (such as price controls) and the inflation tax are excluded.18 To provide a broader international perspective, the regional data on the incidence and distributional effects of taxation are complemented by data for other Latin American countries, the United States (federal taxes only), and the European Union. Comparator countries were chosen on the basis of both relevance19 and the availability and comparability of data.

Box 4.1.On What Basis Should the Tax Burden Be Measured? Income vs. Consumption1

The notions of progressivity and regressivity refer to how the tax burden is distributed relative to some measure of an individual’s or household’s welfare level, which in turn is an indicator of the household’s capacity to pay taxes. The traditional measure used in tax incidence studies is current income per household (or per income group), which may be seen as a proxy for the set of opportunities available to the household. However, there are several problems with current income:

  • It is volatile and subject to temporary shocks. A survey conducted over a particular period ignores the position of the household relative to its life cycle, and may over- or underestimate the income of a household over longer horizons. Ideally, the capacity to pay should be measured relative to permanent or lifetime income.
  • There is a bias toward underrepresentation of certain types of income in surveys, particularly income from self-employment, professional services, and capital (interest, dividends), or the implicit income from nonmarket transactions such as in barter and subsistence economies.
  • Inheritances, transfers, and family remittances are often not well captured in survey-based measures of household income. This is a particular concern in the case of Central American countries, where family remittances are an important source of income and welfare, especially for the poor.2

To avoid some of these problems, many researchers have proposed the use of consumption, instead of income, as a measure of welfare for tax incidence analyses.3 Consumption is less volatile than current income and might be taken as a reasonable proxy for permanent income. It is also less likely to be under-reported. Finally, donations, remittances, and other transfers, even if not fully captured in income, are usually reflected in consumption levels. Consequently, consumption tends to be more evenly distributed than income in most countries, and studies that use consumption as a welfare measure tend to find that overall taxation, and consumption-based taxes in particular, are more progressive than studies that use current income (Fullerton and Rogers, 1993). This is indeed what is found for El Salvador, Nicaragua, Panama (Appendix Table 4.A4), Guatemala (Auguste and Artana, 2005), and Honduras (Gillingham, Newhouse, and Yakovlev, forthcoming).

But the use of consumption is also not without problems. Conceptually, consumption may be a deficient measure of permanent income in the presence of bequest motives or precautionary savings, so that present savings cannot be clearly interpreted as future consumption. Indeed, richer households are empirically found to permanently consume a lower share of their income than poorer households, even at later stages of their life cycles. An even more serious difficulty with consumption is practical: many household surveys do not measure it. Therefore, data availability, especially for cross-country comparisons, constrains the analyst to use current income. The use of income in this chapter was forced by that constraint.

2Another problem with current income is that it does not consider the number and age of members in a household, which clearly affect the household’s welfare and capacity to pay for a given income.

The tax systems in Central America are generally regressive. While the richer segments of the population pay the bulk of the taxes in Central America (Table 4.2, Panel B) just as in other parts of the world, the poor pay more taxes relative to income, as shown by the relative tax burden (Table 4.2, Panel C).20 This is also reflected in negative Kakwani indices, implying that the tax burden is distributed more evenly than income. The tax systems in Guatemala and Panama, however, provide examples of conflicting evidence between tax progression measures and Gini indices, so that no unambiguous conclusion about the progressivity or re-gressivity of the systems can be reached. In these two countries, as in the rest of the region, the poorest quintile pays more taxes relative to income than the richest quintile and the population as a whole. Yet the quasi-Gini index for taxes is slightly larger than the Gini for income (the Kakwani index is positive), suggesting that the overall tax systems are mildly progressive (in the case of Guatemala, basically proportional) according to this summary measure.21 For the Dominican Republic, there are no recent studies on the incidence of overall taxation, but Santana and Rathe (1993) find that the Dominican tax system was progressive in 1989.22

Table 4.2.Distribution of Income and Taxes, by Income Quintile
Panel A. Distribution of Pretax Income (Percent of total)Gini

Index
1st2nd3rd4th5th
Costa Rica (2000)4.28.812.119.855.245.1
El Salvador (2000)2.97.512.921.555.247.4
Guatemala (2004)4.07.912.419.556.146.3
Honduras (2004)3.27.612.820.855.647.2
Nicaragua (2000)3.66.810.416.862.451.0
Panama (2003)1.75.910.919.162.453.8
Bolivia (2000)1.05.111.120.162.855.6
United States (federal, 2004)4.08.913.820.253.143.8
EU-15 (2001)4.19.215.924.546.339.9
Panel B. Distribution of Overall Tax Payments (Percent of Total)Quasi-Gini

for Taxes
1st2nd3rd4th5th
Costa Rica (2000)4.49.011.919.255.544.9
El Salvador (2000)7.612.016.022.442.031.7
Guatemala (2004)4.57.811.918.857.046.4
Honduras (2004)6.18.813.719.851.640.8
Nicaragua (2000)7.110.413.918.949.737.4
Panama (2003)2.25.58.814.469.157.1
Bolivia (2000)1.67.213.320.357.649.8
United States (federal, 2004)0.94.49.717.667.358.4
EU-15 (2001)2.16.312.722.656.450.0
Panel C. Relative Tax Burden1Kakwani

Index
1st2nd3rd4th5th
Costa Rica (2000)104.3102.898.596.9100.5-0.2
El Salvador (2000)261.4159.8123.7104.476.1-15.7
Guatemala (2004)112.298.495.796.3101.60.1
Honduras (2004)190.7116.7106.395.192.8-6.4
Nicaragua (2000)195.9154.7133.4112.479.6-13.6
Panama (2003)127.893.580.475.6110.83.3
Bolivia (2000)151.7143.5120.4101.492.0-5.8
United States (federal, 2004)23.050.170.187.2126.814.6
EU-15 (2001)51.268.579.992.2121.829.6
Sources: Acevedo and González Orellana (2005); Auguste and Artana (2005); Barreix, Roca, and Villela (2006); Bolaños (2002); Gillingham, Newhouse, and Yackovlev (forthcoming); Gómez Sabaini (2005b); Cossío Muñoz (2006); Rodríguez Arosemena (2007); U.S. Congressional Budget Office (2006); and EUROMOD.

Effective tax/income ratio relative to the average ratio; a value greater than 100 indicates that the income group pays a higher percentage of its income relative to the average.

Sources: Acevedo and González Orellana (2005); Auguste and Artana (2005); Barreix, Roca, and Villela (2006); Bolaños (2002); Gillingham, Newhouse, and Yackovlev (forthcoming); Gómez Sabaini (2005b); Cossío Muñoz (2006); Rodríguez Arosemena (2007); U.S. Congressional Budget Office (2006); and EUROMOD.

Effective tax/income ratio relative to the average ratio; a value greater than 100 indicates that the income group pays a higher percentage of its income relative to the average.

The degree of overall tax regressivity varies substantially across Central America. In El Salvador, Honduras, and Nicaragua, the burden of taxation falls disproportionately on the poor (Table 4.2, Panel C). In El Salvador, for instance, the poorest quintile of the population pays more than two and a half times as much taxes relative to their income as the average citizen, and three and a half times what the richest quintile pays. This stark pattern of regressivity stems from the combination of a relatively even distribution of absolute tax payments across income groups (the low tax quasi-Ginis and higher concentration curves shown in Table 4.2, Panel B and Figure 4.1, respectively), and a highly unequal distribution of income (Table 4.2, Panel A). By contrast, the relative burden of taxes is distributed fairly evenly in Costa Rica and Guatemala. In these two countries, tax progression is U-shaped: mildly regressive in the first three (Guatemala) or four (Costa Rica) quintiles and then progressive. This pattern of distribution favors the middle classes. The distribution of the tax burden is also U-shaped in Panama, but with a much deeper trough: there, the bottom quintile pays 28 percent more taxes than the average household, while the top fifth pays 11 percent more.

Figure 4.1.Incidence of Total Taxes

Sources: IMF staff calculations based on Agosin (2004); Acevedo and González Orellana (2005); Auguste and Artana (2005); Bolaños (2002); Gómez Sabaini (2005b); Gillingham, Newhouse, and Yackovlev (forthcoming); and Barreix, Roca, and Villela (2006).

Note: EU-15: Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxemburg, Netherlands, Portugal, Spain, Sweden, and United Kingdom.

Tax systems in the Central American countries for which data are available are found to be much less regressive or more progressive if consumption is used instead of income as a measure of welfare. As Appendix Table 4.A4 shows, the distribution of consumption or expenditure is more even than that of income in El Salvador, Nicaragua, and Panama: the quasi-Gini indices for consumption in those three countries are smaller than the Gini coefficients for income by 15.7, 11.6, and 15.3 percentage points, respectively. Therefore, the incidence of taxation results in a much less regressive effective rate measured relative to consumption. In El Salvador and Nicaragua, overall taxation—found to be steeply regressive relative to income—becomes almost proportional when consumption is used, while the Panamanian system becomes strongly progressive. Similar results are reported by Auguste and Artana (2005) for Guatemala, and by Gillingham, Newhouse, and Yakovlev (forthcoming) for Honduras. As Box 4.1 indicates, this is consistent with the international evidence. The box also notes the limitations of using consumption for tax incidence analyses.

On the basis of income, taxation in Central America is generally more regressive than in the Andean countries, the United States, and the European Union (EU). As shown in Tables 4.2 and 4.3 and in Figure 4.1, the quasi-Gini indices for overall taxes in Central America, with the exceptions of Guatemala and Panama, are low compared with those in the Andean countries, the United States, the EU-15 as a whole, and most of its member countries. The low tax quasi-Ginis indicate, as explained above, a fairly even distribution of absolute tax payments across income groups. Given the prevailing income disparities, this results in an unequal distribution of the tax burden relative to income and negative Kakwani indices for taxes across the region (except Guatemala and Panama). In contrast, for the United States, most European countries, and the EU-15 as a whole, the tax systems are progressive, as reflected in consistently upward-sloping tax progression patterns, high quasi-Gini coefficients for taxes, and positive Kakwani indices. Two interesting exceptions are Sweden and Denmark, where the tax systems are regressive, though, as shown below, the overall effect of fiscal policy is powerfully progressive.

Table 4.3.Redistributive Impact of the Overall Tax System1
Gini for

pre-tax

income

(A)
Quasi-Gini

for taxes

income

(B)
Kakwani

Index

(C = B - A)
Tax

pressure2
Quasi-Gini

for post-tax

(D)
RS

Index3

(E = A - D)
Central America
Costa Rica (2000)45.144.9-0.220.845.10.0
El Salvador (2000)47.431.7-15.78.148.8-1.4
Guatemala (2004)446.346.40.117.346.30.0
Honduras (2004)47.240.8-6.414.448.3-1.1
Nicaragua (2000)51.037.4-13.627.556.2-5.2
Panama (2003)53.857.13.36.453.60.2
Andean countries5
Bolivia (2000)55.649.8-5.816.656.7-1.1
Colombia (2003)53.753.2-0.57.753.70
Peru (2000)53.546.0-7.57.654.3-0.8
United States (federal, 2004)43.858.414.619.840.23.6
Europe6
EU-15 (2001)39.950.010.137.72.2
Denmark (2001)41.938.2-3.744.1-2.2
Ireland (2001)45.657.011.443.32.3
Italy (2001)40.148.38.238.71.4
Portugal (2001)42.269.427.238.73.5
Spain (2001)39.960.020.136.03.9
Sweden (2001)38.935.2-3.741.1-2.2
Sources: Acevedo and González Orellana (2005); Auguste and Artana (2005); Barreix, Roca, and Villela (2006); Bolaños (2002); Gillingham, Newhouse, and Yackovlev (forthcoming); Gómez Sabaini (2005b); Cossío Muñoz (2006); Rodríguez Aro-semena (2007); U.S. Congressional Budget Office (2006); and EUROMOD.

All data are based on total current income by current income quintiles, unless otherwise noted.

Tax pressure is the ratio of total taxes paid to total household income before taxes; for Colombia and Peru it is total taxes paid/GDP.

RS is the Reynolds-Smolensky index.

Data are before constitutional court rulings in 2003 and 2004 and the tax reform in 2004. But Auguste and Artana (2005) show that these reforms had little impact on income distribution (an RS index of 0.5; see Auguste and Artana; Table 23, p. 60).

Data for the three countries are based on, and ordered by, per capita income; data for Colombia and Peru are based on deciles.

Data for European countries are based on, and ordered by per capita income.

Sources: Acevedo and González Orellana (2005); Auguste and Artana (2005); Barreix, Roca, and Villela (2006); Bolaños (2002); Gillingham, Newhouse, and Yackovlev (forthcoming); Gómez Sabaini (2005b); Cossío Muñoz (2006); Rodríguez Aro-semena (2007); U.S. Congressional Budget Office (2006); and EUROMOD.

All data are based on total current income by current income quintiles, unless otherwise noted.

Tax pressure is the ratio of total taxes paid to total household income before taxes; for Colombia and Peru it is total taxes paid/GDP.

RS is the Reynolds-Smolensky index.

Data are before constitutional court rulings in 2003 and 2004 and the tax reform in 2004. But Auguste and Artana (2005) show that these reforms had little impact on income distribution (an RS index of 0.5; see Auguste and Artana; Table 23, p. 60).

Data for the three countries are based on, and ordered by, per capita income; data for Colombia and Peru are based on deciles.

Data for European countries are based on, and ordered by per capita income.

Tax systems in the region, whether progressive or regressive, have a limited effect on the overall distribution of income. This is consistent with international experience. The impact of taxes on income distribution is a function of three variables: the pre-tax distribution of income, the distribution of tax payments across income groups, and the ratio of total taxes considered in the incidence analysis to total income before taxes (here called the tax pressure).23 The overall redistributional impact of taxation can be measured by the difference between the pre-tax income Gini coefficient and the quasi-Gini coefficient for after-tax income, that is, the Reynolds-Smolensky index. As Table 4.3 shows, the redistributive potential of taxes in Central America, whether progressive or regressive, is fairly small. This results from the low rates of tax pressure in some countries, and the relatively similar distributions of taxes and income (small Kakwani indices) in others. Only for Nicaragua is the implied redistribution effect somewhat large, because the marked regressivity of the tax system combines with a relatively high ratio of taxes to household income.24Table 4.3 shows that in the Andean countries, the United States, and Europe, as in Central America, taxation has only modest effects on the distribution of income. This is indeed a common finding in tax incidence studies. As will be shown in the third and fourth sections of this chapter, this finding contrasts with the large redistributive potential of social spending.

How Progressive Are Individual Taxes?

Income taxes are generally progressive in Central America, but—with the exceptions of Panama and Honduras—less so than in comparator countries, and they contribute little to overall income redistribution. Global measures of incidence indicate that income taxes are progressive in Central America, particularly in Panama (Appendix Table 4.A2 and Figure 4.2).25 In Guatemala and Panama, the progression of income taxation from lower to upper income quintiles is U-shaped rather than smoothly upward-trending.26 Given that income taxes contribute on average about one-fourth of an already small tax take across Central America, their overall redistributive impact is, however, quite small (at or under 0.4 percentage point of the pre-tax Gini coefficient for all countries) (see Appendix Table 4.A3). Even in Panama, where the income taxes considered27 are strongly progressive (a large positive Kakwani index) and account for a greater share of total tax revenue, their low share in income results, as in the rest of the region, in a small redistributive effect. Although the finding that income taxes are progressive in Central America is consistent with the evidence for developed and developing countries,28 Appendix Tables 4.A2 and 4.A3 also show that income taxes are much more progressive in the Andean countries and the United States (except, in some cases, with respect to Panama and Honduras), and that their distributional effect is much stronger in these comparator countries.29

Figure 4.2.Progression of Taxes

(Relative tax burden by income quintile)

Sources: IMF staff calculations based on Agosin (2004); Acevedo and González Orellana (2005); Auguste and Artana (2005); Bolaños (2002); Gillingham, Newhouse, and Yackovlev (forthcoming); and Gómez Sabaini (2005b).

Note: QG= Quasi-Gini coefficient of taxes. RS=Reynolds-Smolensky index. Positive values denote progressivity. VAT=Value-added tax.

With the exception of Costa Rica, VAT and sales taxes are notably regressive if assessed relative to income, and account for much of the regressive impact of overall taxation. Despite the conventional wisdom that VAT or sales taxes have a regressive impact on income distribution, the cross-country literature surveys present mixed results.30 The evidence for Central America, however, is clear. As Appendix Table 4.A2 and Figure 4.2 show, VATs and sales taxes have a steeply regressive structure in Guatemala, Honduras, Nicaragua, Panama, and, more prominently, in El Salvador. In the latter, the poorest 20 percent of the population pay over three times more VAT relative to their income than the average household in the country and five times as much relative to the rich est 20 percent. Yet, the Kakwani index for the VAT in Nicaragua is even higher than in El Salvador, because the underlying income distribution is more unequal.

Because VATs or sales taxes are the single most important source of tax revenue for most Central American countries, their pronounced regressivity does have a tangible effect on the overall income distribution in El Salvador, Honduras, and especially Nicaragua, as reflected in the negative and substantial Reynolds-Smolensky indices for these three countries (Appendix Table 4.A3). In contrast, local and global indicators of regressivity are much lower for the VAT in Costa Rica, where all income quintiles but the richest pay a slightly higher effective rate than the average. This seems to be the result of targeted exemptions; in particular, the exclusion from the tax of a basic basket of goods and services consumed mostly by the poor. On average, the VAT is more regressive and has a stronger negative redistributive effect in Central America than in the Andean countries, as Appendix Table 4.A3 suggests.

The regressivity of the VAT in Central American countries is partly explained by the high ratio of consumption to income in the poorer households, and is thus substantially reduced or reversed if measured relative to consumption. The standard economic explanation for the regressivity of consumption-based taxes is that consumption is more evenly spread than income, so that the ratio of consumption to income tends to be very high (and the savings rate correspondingly low or negative) for the poorest income groups and much lower for the richer ones. This explanation holds true in Central America. For instance, in El Salvador, the ratio of consumption to income is 177 percent for the lowest quintile, compared with 52 percent for the highest.31 Indeed, as Appendix Table 4.A4 shows, if consumption is used instead of current income as an indicator of welfare or of permanent income, the VAT becomes much less regressive in El Salvador and Nicaragua, and turns progressive in Panama. Similarly, Auguste and Artana (2005) and Gillingham, Newhouse, and Yakovlev (forthcoming) find, for Guatemala and Honduras, respectively, that the VAT turns from regressive relative to income to mildly progressive when measured relative to consumption. Jenkins, Jenkins, and Kuo (2006) investigate the incidence of the VAT in the Dominican Republic on the basis of household expenditure, and find that the tax is highly progressive: the effective tax rate paid by the richest quintile is twice as large as that paid by the poorest.

Moreover, in developing countries with subsistence economies and large informal markets, the regressivity of the VAT may be overestimated. As Jenkins, Jenkins, and Kuo (2006) argue, the goods and services on which poor households spend most of their income in developing countries are often traded in informal markets and, even if they are legally included in the tax base, administratively it is impractical to tax them. The study by these authors of the incidence of VAT in the Dominican Republic addresses this issue. Also, barter and self-consumed production, which are more prominent in poorer countries, are naturally excluded from the VAT. These economic factors introduce progressivity in the tax.

In addition to economic factors, the regressivity of the VAT may also be due to tax design factors. Appendix Table 4.A4 shows that even when measured relative to consumption, the VAT is regressive in El Salvador and Nicaragua. This suggests that the exemptions from the tax may be disproportionately benefiting the rich in these countries.32 Many VAT exemptions fall on services, which normally account for a larger share of expenditures for higher income groups. The regres-sivity of the VAT can be reduced if exemptions and zero-ratings are reduced to a narrow and well-targeted basket of goods and services consumed disproportionately by the poor.

Excise taxes are also regressive, except in Costa Rica and Guatemala. In El Salvador, Honduras, and Nicaragua, excise taxes are strongly regressive. Indeed, in the latter two countries, they are the most regressive tax, and because their share in total taxation is also sizable, they have a palpable effect on the overall distribution of income, as indicated by the Reynolds-Smolensky index (Appendix Tables 4.A2 and 4.A3). As in the case of VAT, the incidence of the tax depends largely on the consumption patterns for the taxed goods. The regressive incidence of excise taxes in these countries is driven mainly by taxes on alcohol, tobacco, and fuel, because consumption of these goods accounts for a larger share of the income of poorer households.33 In Panama, excise taxes are also regressive as a whole, but much less so.34 By contrast, excise taxes are essentially neutral in Guatemala (with a somewhat U-shaped progression pattern and a small positive Kakwani index) and fairly progressive in Costa Rica. In Costa Rica, excise taxes are even more progressive than income taxes (as measured by their quasi-Gini and Kakwani indices) because of their broader coverage, which includes luxury goods.35 As in Central America, the evidence on the incidence of excise taxes is mixed for other countries: as Appendix Tables 4.A2 and 4.A3 show, excise taxes are highly progressive in Bolivia but regressive in the United States.

International trade taxes are highly regressive in all countries but Guatemala. The tax progression and global incidence indicators in Appendix Tables 4.A2 and 4.A3 show that, in Central America, the burden of taxes on international trade (mostly import tariffs, as export taxes are very small in the regional economies) also falls disproportionately on the poor. The main reason for the regressivity of trade taxes is that tariffs tend to be higher on imported consumption goods that are also produced domestically, especially food and lightly processed manufactured goods, which represent a larger share of the consumption basket of poorer households. Guatemala appears to be an exception, suggesting that imported goods subject to tariffs may be more prominent in the consumption patterns of the rich in this country.36

Social Spending in Central America: Trends and Distributional Impact

The overall impact of social spending on income distribution depends critically on the resources devoted to social spending and the distribution of those resources across income groups. Social spending includes capital and current spending on education, health, social protection (social insurance and social assistance), housing, water and sewage, and culture, sports, and recreation. The first part of this section surveys the trends in social spending in Central America, addressing the issue of whether countries have been devoting more resources to social spending and drawing attention to the signs of improved stability of those resources. The second part of the section surveys existing studies on the incidence and distributive impact of social spending.

Social Spending Trends

Though social spending in Central America has increased considerably over the past decade, it remains relatively low in some countries. The share of social spending in GDP—a measure of the macroeconomic priority assigned to social spending37—was on average 11½ percent of GDP in 2004 for Central America, an increase of 2¼ percent of GDP since 1995 (Table 4.4). There are, however, substantial differences across the region in the levels of social spending: Costa Rica and Panama continue to devote by far the highest amount of resources to social spending (18½ and 17 percent of GDP, respectively), followed by Honduras (13 percent), while Guatemala directs only 6½ of GDP to social spending. Public spending on education and health in the region is roughly similar, as a share of GDP, to the Latin American average (and median), but the aver- age and median levels of public spending on social protection38 are significantly below those of Latin America as a whole. Public spending on social protection varies significantly across Central America, largely a reflection of differences in pension spending (Figure 4.3). Social assistance spending (including, for example, any conditional cash transfer programs) amounts to about 1¾ percent of GDP on average for Central America.

Table 4.4.Evolution of Social Spending, 1995 vs. 2003/2004(In percent of GDP)
19952003/04Increase19952003/04Increase
Total Social SpendingOf which, Education Spending
Costa Rica15.818.62.84.25.71.4
Dominican Republic6.17.41.32.13.00.9
El Salvador6.28.62.42.13.00.9
Guatemala4.16.52.41.72.60.8
Honduras7.813.15.33.87.23.5
Nicaragua7.28.81.72.84.11.3
Panama17.317.30.04.34.70.4
Regional average:
Central America9.211.52.33.04.31.3
Latin America111.012.61.63.44.30.9
Regional median:
Central America7.28.81.72.84.11.3
Latin America17.812.44.63.64.10.5
Of which, Health SpendingOf which, Social Protection2
Costa Rica4.75.71.05.25.60.4
Dominican Republic1.21.60.30.41.10.7
El Salvador1.41.50.12.13.11.0
Guatemala0.91.00.10.71.20.4
Honduras2.63.50.90.20.50.3
Nicaragua2.83.00.2
Panama5.86.00.25.75.5-0.2
Regional average:
Central America2.83.20.42.42.80.4
Latin America12.52.70.24.45.00.6
Regional median:
Central America2.63.00.41.42.10.7
Latin America12.42.40.12.44.21.8
Sources: ECLAC (2006); and Ministry of Finance of El Salvador.

Includes Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Uruguay, and Venezuela.

Includes social insurance and social assistance programs.

Sources: ECLAC (2006); and Ministry of Finance of El Salvador.

Includes Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Nicaragua, Panama, Paraguay, Peru, Uruguay, and Venezuela.

Includes social insurance and social assistance programs.

Figure 4.3.Composition of Social Protection Spending

(In percent of GDP)

Sources: IMF staff calculations based on ECLAC (2006); Lindert, Skoufias, and Shapiro (2006); Petrei and Rodriguez Arosemena (2006); and country authorities.

The increase in public social spending levels has reflected an increase in total expenditures as well as an increase in the share of social spending in overall public expenditures. While the overall level of central government expenditures has grown over the past decade (by upwards of 3 percentage points of GDP in El Salvador, Guatemala, and the Dominican Republic), so has the share of social expenditures in total expenditure (Figure 4.4). At one end of the distribution, social spending represents 68½ percent of total expenditure in Costa Rica, increasing by 6 percentage points from its 1994–95 level. At the other end of the distribution, Honduras, the Dominican Republic, and Nicaragua all direct less than 40 percent of expenditure to social spending. However, Honduras has increased the share of social spending in total expenditure by a notable 13 percentage points over the past decade, and Nicaragua by about 5 percent, aided by a significant decline in interest payments under debt relief from the Heavily Indebted Poor Countries (HIPC) Initiative. Developments in all countries indicate that higher fiscal priority is being placed on social spending. The evidence also suggests that public funding of social programs, although procycli-cal, has become less volatile over time.39 A commitment to protecting social spending would generally be reflected in acyclical behavior of total public social expenditures and countercyclical behavior of expenditure on social assistance programs. The evidence indicates, however, that public social spending in Central America, as well as across Latin America, has instead been procyclical. A simple analysis of the correlation between the cyclical component of real output growth and the cyclical component of real spending40 shows that, with the exceptions of Costa Rica and Honduras, social spending varied positively with the economic cycle in both the early 1990s and in more recent years (Appendix Table 4.A5). However, despite the increase in the volatility of growth observed in the second sub-period (1998–2004), the volatility of overall social spending, as well as of some key categories, decreased over that same sub-period (Appendix Table 4.A6).

Figure 4.4.Evolution of Government Expenditures

Sources: IMF staff calculations based on ECLAC (2006); and national data sources.

The Incidence and Distributional Impact of Social Spending

Methodological Considerations

An analysis of the incidence of social spending requires identifying the actual beneficiaries of social spending programs. This can be done directly in some cases but only indirectly in others, resulting in the potential for heterogeneous assumptions on incidence across different studies. Although only a few of the studies surveyed in this section provide methodological details, there appears to be relative homogeneity in the way some beneficiaries are identified (e.g., for primary spending, by way of primary school enrollment ratios based on household surveys) and heterogeneity in others (e.g., for social assistance to the disabled, by various proxies such as general share of the disabled in total population or enrollment in programs for the disabled).

In discussing the incidence of social spending, it is useful to distinguish between two concepts: absolute incidence (the share of total spending that each income group receives) and relative incidence (the distribution of social spending relative to the distribution of pre–fiscal policy income in the economy). A distribution of social spending in which, for example, the lowest quintile receives 45 percent of the total while the top quintile receives 5 percent of the total is progressive in absolute terms. In contrast, a distribution of social spending in which the bottom quintile receives 10 percent of spending and the top quintile receives 30 percent is not progressive in absolute terms, but can improve the income distribution if it is more equally distributed than income itself. The latter would thus be progressive in relative terms.41

The absolute and relative incidences of social spending are measured with the same set of indicators used to assess the distributional impact of taxation, but with a different interpretation. The quasi-Gini coefficient of spending is conceptually analogous to the quasi-Gini coefficient for a given tax, because it represents the Gini coefficient for the concentration curve of spending. However, the possible values of the quasi-Gini coefficient of spending lie between–1 and 1, with a negative value denoting progressivity in absolute terms (in other words, the concentration curve of spending lies above the 45-degree line). The Kakwani index (K), defined as the difference between the quasi-Gini coefficient of spending and the Gini coefficient of the original income distribution, measures relative progressivity of spending. If K < 0, spending is progressive relative to the original income distribution.

Distributional Impact of Social Spending in Central America

Available data suggest that total public social spending in Central American countries is progressive in relative but not absolute terms. Costa Rica, Guatemala, and Panama (the three countries for which available incidence studies provide information on the most comprehensive definition of social spending) all have positive quasi-Gini coefficients of spending (Table 4.5, Panel A, column 2), which means that, in absolute terms, social spending is not progressive. However, social spending is much more equally distributed than pre-spending income, and thus is progressive in relative terms, as denoted by the negative values of the Kakwani index (Table 4.5, Panel A, column 3).

Table 4.5.Redistributive Effect of Total Social Spending: Central America and Selected Regional Comparators
Pre-Spending

Gini (Income)

(1)
Quasi-Gini of

Spending

(2)
Kakwani

Index

(3=2–1)
Share of

Social

Spending1

(4)
Impact on Gini

(RS Index)2

(5)
Post

Spending

Gini

(6=1–5)
Panel A. Total Social Spending, Including Social Security
Central America
Costa Rica (2000)45.13.0-42.118.26.238.9
Guatemala (2004)46.314.0-32.36.33.043.3
Panama (2003)53.811.2-42.717.46.847.0
Latin America: worst and best income distribution
Brazil (1997)56.027.0-29.019.17.049.0
Uruguay (1998)41.023.0-18.021.22.039.0
Selected other comparator countries
EU-15 (2001)41.7-24.5-66.224.08.832.8
Denmark (2001)43.7-79.9-123.629.213.130.6
Ireland (2001)47.8-38.0-85.813.813.234.6
Italy (2001)42.87.2-35.624.46.136.6
Portugal (2001)44.4-12.2-56.621.16.138.4
Spain (2001)42.10.9-41.219.66.335.8
Sweden (2001)40.7-18.3-58.928.911.329.4
Panel B. Total Social Spending, Excluding Social Security
Central America
Costa Rica (2000)45.1-9.0-54.112.56.039.1
El Salvador (2000)47.4-12.9-60.35.33.643.8
Guatemala (2004)46.32.4-43.95.23.143.2
Honduras (2004)47.20.7-46.410.53.244.0
Nicaragua (1998)51.011.2-39.88.65.645.5
Panama (2003)53.8-3.5-57.311.97.446.4
Andean countries
Bolivia55.615.3-40.38.04.551.1
Colombia53.7-13.2-66.95.55.048.7
Peru53.5-2.5-56.05.53.550.0
Sources: IMFstaff calculations based on Barreix, Roca, and Villela (2006, for the Andean countries); ECLAC (2006), EUROMOD (for the European countries); World Bank (various country poverty assessment reports); Gillingham, Newhouse, and Yackovlev (forthcoming); and Petrei and Rodriguez Arosemena (2006).

For Latin America, the average share of social spending in GDP over 2000–04. For Europe, 2001 data.

Reynolds-Smolensky index. Positive values represent progressivity.

Sources: IMFstaff calculations based on Barreix, Roca, and Villela (2006, for the Andean countries); ECLAC (2006), EUROMOD (for the European countries); World Bank (various country poverty assessment reports); Gillingham, Newhouse, and Yackovlev (forthcoming); and Petrei and Rodriguez Arosemena (2006).

For Latin America, the average share of social spending in GDP over 2000–04. For Europe, 2001 data.

Reynolds-Smolensky index. Positive values represent progressivity.

If social security is excluded, however, social spending becomes much more progressive (Table 4.5, Panel B, column 2, and Figure 4.5). In fact, social spending excluding social security is progressive in absolute terms (i.e, strongly pro-poor) in Costa Rica, El Salvador, and Panama.

Figure 4.5.Incidence of Total Social Spending

Sources: IMF staff calculations based on data from ECLAC (2006); and national authorities.

1Excluding public spending on social protection.

Though progressive in relative terms in all cases, the magnitude of the distributional effect of social spending varies considerably across the region. The redistributive potential of social spending is a function of both the incidence and the level of social spending. Combined with high shares of social spending in GDP, the distributional impacts of social spending in Costa Rica and Panama are the two highest in the region, with reductions in the Gini coefficient of 6 and 7.4 points, respectively. In contrast, despite pro-poor targeting, El Salvador finds itself toward the opposite end of the distribution, with a more muted reduction in its Gini coefficient (3.6 points), roughly on par with Guatemala and Honduras, where social spending achieves a reduction in inequality of about 3 Gini points.

A comparison with the distributional impact in other regions reveals a number of interesting observations:

  • In absolute terms, as measured by the reduction in Gini points, the redis-tributive impact of social spending in Costa Rica and Panama is comparable to that of some European countries and exceeds that observed in the Andean countries. The reduction of the pre–fiscal policy Gini coefficient of 6–7.5 Gini points in Costa Rica and Panama is in line with the absolute distributional impact of social spending in Italy, Spain, and Portugal (Table 4.5, column 5), and greater than the redistributive impact of social spending in the three Andean countries, which ranges between 3.5 and 5 Gini points. However, given the initial income distribution, post–social spending inequality in Central America remains high. With the exception of Costa Rica, the post–social spending Gini in Central America is still above the pre–social spending Gini in European countries (Table 4.5, column 6). In other words, the incidence and scale of social spending is insufficient to bring down inequality in Central America even to pre–fiscal policy levels in Europe.
  • Although the progressivity of total spending in Central America is not substantially different from that of some European countries, other European countries show that it is possible to improve targeting further. The average quasi-Gini coefficient of—24.5 for social spending in the EU-15 is linked to an incidence of social spending in which 81 percent accrues to the lowest three quintiles. By contrast, the lowest three quintiles receive about 70 percent of social spending in El Salvador; 60–65 percent in Costa Rica, Guatemala, Panama, and Honduras; and about 50 percent in Nicaragua.

How Progressive Are Individual Social Spending Components?

Public spending on social protection—mainly pensions—is pronouncedly regressive in Central America. This conclusion emerges from a comparison of the quasi-Gini coefficients of spending with and without social protection. The findings for Costa Rica, Panama, and Guatemala (summarized in Table 4.6) corroborate those of a World Bank study of public transfers across Latin America and the Caribbean (Lindert, Skoufias, and Shapiro), which found that all 16 social insurance programs studied are regressive in absolute terms.42 This result was due in large part to the fact that coverage of these programs was defined by participation in formal labor markets, which excludes the majority of the poor. Moreover, in Guatemala, the study found that net pension subsidies were even more unequally distributed than pretransfer income. The findings for social assistance, where eligibility is not tied to formal labor market participation, are mixed: although a “typical” social assistance program43 in Latin America and the Caribbean transfers 38 percent more to the bottom quintile than a universal or neutral allocation, targeting varies tremendously (Lindert, Skoufias, and Shapiro, 2006). Furthermore, despite better targeting, the overall impact of social assistance transfers on poverty and income distribution tends to be muted by the low share of public spending allocated to these programs.44

Table 4.6.Incidence of Social Protection Spending(Share of total spending on social protection accruing to each quintile, in percent)
Population Income Quintiles (lowest to highest)Percent of Social

Spending
12345
Costa Rica (2000)
Social protection121212184528.9
Pensions8912195224.5
Contributive regime15911195622.9
Noncontributive regime5122151121.6
Work protection2126242180.4
Assistance to vulnerable groups3825161484.0
Panama (2003)
Social protection137197023.2
Pensions036197221.7
Labor standards and inspection291828430.0
Labor complaints and resolutions291828430.1
Labor force formation9121626381.1
Protection of minors30272012120.2
Assistance to the elderly and disabled922511800.0
Other11141724340.0
Guatemala (2000)
Social protection81315184625.2
Social insurance135157610.2
Pensions1241281
Survivorship4441375
Alimony16102460
Social assistance142124212015.0
Sources: Trejos, 2001 (Costa Rica); Petrei and Rodriguez Arosemena, 2006 (Panama); and World Bank, 2003a (Guatemala).

Pension benefits are assessed on a gross basis (not net of contributions).

Sources: Trejos, 2001 (Costa Rica); Petrei and Rodriguez Arosemena, 2006 (Panama); and World Bank, 2003a (Guatemala).

Pension benefits are assessed on a gross basis (not net of contributions).

While overall education spending has generally neutral redistributive effects, spending on primary education is strongly progressive, even in absolute terms. In Costa Rica, Guatemala and Honduras, overall education spending accrues relatively equally across all quintiles. It is progressive in absolute terms in El Salvador and to a lesser degree in Panama (Figure 4.6). In Nicaragua, although public education spending is progressive in relative terms, it accrues disproportionately to the richest quintile, which receives about 35 percent of total public spending. The distributional effects of education spending, however, differ considerably among different levels of education. Thus, public spending on primary education is unambiguously pro-poor in all countries of the region. Public spending on secondary education follows an inverted U-shape, with the highest share of benefits accruing to the middle three quintiles, except in Guatemala, where it exhibits strong regressivity. In sharp contrast, spending on tertiary education is regressive across the board, with an average of only 25 percent of public spending on tertiary education accruing to the bottom 3 quintiles of the income distribution. In Guatemala and Honduras, tertiary education spending is regressive even in rela tive terms; that is, its distribution is worse than the original income distribution, reflected in the positive Kakwani index.

Figure 4.6.Incidence of Public Spending on Education

(In percent of total, by quintile, noncumulative)

Sources: IMF staff calculations based on ECLAC (2006), World Bank (various country Poverty Assessment reports); and Petrei, Rodriguez, and Arosemena (2006).

Note: QG = Quasi-Gini of education spending; K = Kakwani index.

The distribution of public spending on health is progressive in absolute terms in four of the seven Central American countries surveyed. Costa Rica and El Salvador are able to direct 26–27 percent of total public spending on health to the poorest quintile, and 70–74 percent of total to the bottom three quintiles (Figure 4.7). Nicaragua and the Dominican Republic show a more modest, but still pro-poor, incidence of public health spending, while health spending in Guatemala, Honduras, and Panama has a neutral absolute incidence, with about 60 percent of spending accruing to the bottom three quintiles, in proportion with their share of total income.

Figure 4.7.Incidence of Public Spending on Health

(Percent of total, by quintile, noncumulative)

Sources: Staff calculations based on ECLAC (2006); World Bank (various country Poverty Assessment reports); and Petrei and Arosemena (2006).

Net Distributional Effects of Fiscal Policy: A Summary Analysis

This section examines the combined net distributional impact of taxation and social spending in Central America. The information on the distribution of income before fiscal policy, and on the incidence of taxes and social spending, can be pieced together to produce an estimate of the net direct distributional effect of fiscal policy. The latter can be measured by comparing the concentration patterns of income before and after fiscal policy interventions, as summarized by the Reynolds-Smolensky index.

In Central America, available data suggest that the net redistributive effect of fiscal policy is progressive but modest, especially given the extent of income inequality. The net distributional effects of taxes and social spending result from the interaction of several channels of transmission: the initial distribution of income, the shares of taxation and social spending in income, and their distribution across income groups. Tables 4.7 and 4.8 summarize the main findings on the incidence of taxation and social spending in Central America: Table 4.7 provides an estimate of the net impact of these components of fiscal policy as reflected in the Reynolds-Smolensky index, and Table 4.8 shows the percentage changes in the income of each quintile that result from these policies. The conclusion that emerges is clear: while taxation has a small regressive effect, social spending has a larger progressive impact. The net effect is therefore progressive: the quasi-Gini index for income after fiscal policy is smaller than the Gini coefficient for pre-fiscal policy income (a positive Reynolds-Smolensky index), and the income of the upper quintiles is redistributed to the poorer two quintiles. Therefore, inequality falls as a result of fiscal policy interventions.

Table 4.7.Redistributive Effect of Taxation and Social Spending: Central America and Selected Regional Comparators
Pre-Fiscal

Policy Gini

(Income)

(1)
Post-Taxation

Gini1

(2)
Post-Social

Spending

Gini1

(3)
Post-Fiscal

Policy Gini

(4)
RS Index2

(5)
Central America
Costa Rica (2000)45.145.139.138.36.8
El Salvador (2000)47.448.843.845.81.6
Guatemala (2004)46.346.343.242.63.7
Honduras (2004)47.248.344.044.52.7
Nicaragua (1998)51.056.245.548.03.1
Panama (2003)53.853.646.445.88.0
Andean countries
Bolivia55.656.751.151.34.3
Colombia53.753.748.748.35.4
Peru53.554.350.050.43.1
Selected other comparator countries
EU-15 (2001)41.739.232.829.112.5
Denmark (2001)43.745.830.625.718.1
Ireland (2001)47.845.334.630.417.4
Italy (2001)42.840.736.633.79.1
Portugal (2001)44.440.638.434.310.2
Spain (2001)42.137.935.831.310.8
Sweden (2001)40.742.829.426.114.5
Sources: Barreix, Roca, and Villela (2006, for the Andean countries and European comparators); and IMF staff calculations based on ECLAC (2006); World Bank (various country poverty assessment reports); Bolaños (2002), Agosin et al. (2005); and Gillingham, Newhouse, and Yackovlev (forthcoming).

For Latin America, excludes social security. For Europe, includes social security.

Reynolds-Smolensky Index. Positive values denote progressivity.

Sources: Barreix, Roca, and Villela (2006, for the Andean countries and European comparators); and IMF staff calculations based on ECLAC (2006); World Bank (various country poverty assessment reports); Bolaños (2002), Agosin et al. (2005); and Gillingham, Newhouse, and Yackovlev (forthcoming).

For Latin America, excludes social security. For Europe, includes social security.

Reynolds-Smolensky Index. Positive values denote progressivity.

Table 4.8.Impact of Fiscal Policy on Prefiscal Policy Income, by Quintile1(In percent of prefiscal policy income)
Population Income Quintiles (from lowest to highest)
12345
Central America
Costa Rica59.118.46.1-1.8-10.1
El Salvador19.02.0-1.8-4.5-5.2
Guatemala12.82.2-3.1-8.1-15.0
Honduras19.41.9-3.8-6.6-10.6
Nicaragua8.60.8-3.9-11.5-14.8
Panama161.851.922.810.6-3.0
Andean countries
Bolivia48.022.111.57.8-2.8
Selected European

comparator countries
EU-1592.239.67.9-8.0-20.4
Denmark164.531.3-19.6-33.2-44.2
Ireland525.278.312.9-6.8-21.9
Italy56.928.314.50.5-14.0
Portugal92.231.08.41.8-14.5
Spain82.437.114.40.3-15.5
Sweden114.133.9-6.5-17.8-28.9
Sources: IMF staff calculations based on country studies, EUROMOD; and Barreix, Roca, and Villela (2006).

Fiscal policy refers to only taxation and social spending.

Sources: IMF staff calculations based on country studies, EUROMOD; and Barreix, Roca, and Villela (2006).

Fiscal policy refers to only taxation and social spending.

The size and composition of the overall redistributive effect of fiscal policy vary considerably in the five Central American countries for which full information is available. The net impact is strongest in Costa Rica and Panama, with a reduction in income inequality of 7–8 percentage Gini points, and an increase in the income of the poorest quintile of 60 and 162 percent, respectively. In both, a broadly neutral tax system combines with high levels of fairly well-targeted social spending, although in Panama the importance of nontax revenues enhances the progressivity of the estimated net impact.45 In Guatemala, despite the broadly neutral effect of the tax system, low levels of social spending and its incidence limit the distributive impact to a modest 3.7 Gini points. In Nicaragua, taxation is highly regressive but more than offset by social spending, so that fiscal policy brings the Gini coefficient down by 3.1 points. However, the amount of redistribution through social spending is small relative to the tax burden, and thus the net increase in the income of the poorest quintile is only 8 percent. Finally, in El Salvador and Honduras, the effects of both taxation and social spending on income distribution are modest, yielding a correspondingly small net impact.

The net redistributive impact of fiscal policy in Central America is similar to that of the Andean region, but much smaller than in European countries. As shown in Tables 4.7 and 4.8, in the Andean countries tax systems tend to be regressive and social spending progressive, with the latter offsetting the former and yielding a modestly progressive net effect. The situation is very different in the European Union, where tax systems are on average progressive (but with a small distributional impact) and social spending is not only sharply progressive but also very-powerful. The net effect is large and strongly progressive, with the post–fiscal policy quasi-Gini index 12.5 points lower than the pre–fiscal policy Gini coefficient, and the income of the poorest quintile almost doubling as a result of fiscal redistribution. Even Costa Rica’s and Panama’s relatively good performance (by regional standards) is dwarfed by the experience of the EU countries. Interestingly, Tables 4.7 and 4.8 show two different distributive patterns in the EU comparators: one in which the tax system is progressive, even strongly so, and redistribution is complemented by social spending (Ireland, Italy, Portugal, Spain); and another in which the tax system is moderately regressive, but where social spending is so potent and well targeted that it yields a very strong progressive effect overall (Sweden, Denmark).

The Central American and international evidence clearly shows that the redistributive potential of taxes is much smaller than that of social spending. As Tables 4.3, 4.5, and 4.7 illustrate, fiscal policy interventions through social spending tend to have a much larger effect on the income Gini coefficient than taxation, for two main reasons. One is economic: globalization of trade and capital flows, the extent of the informal economy, and efficiency considerations pose limits on the capacity of governments to raise revenue through income taxes, as well as on the progressivity of these taxes. Inevitably, a considerable share of revenues must be raised through taxes on the consumption of goods and services. Social spending, in contrast, can be designed so that funds are directed in absolute terms mainly or solely to the poorest households. Therefore, although the relative pro-gressivity of taxation (i.e., the burden of taxation each income group faces relative to its income) is constrained in practice, absolute progressivity (i.e., in which poorer households receive more in absolute monetary terms than richer ones) is possible in social spending programs. The second reason is purely arithmetic: every dollar redistributed through absolutely progressive social spending, even if raised through neutral or even regressive taxes (in relative terms), would have a stronger proportional effect on the income of the poor than on the income of the rich. The more unequal the original distribution of income, the more powerful the redistributive power of fiscal policy through well-targeted social spending.

Tax-financed increases in social spending would reduce inequality and raise the income of the poor in the sampled Central American countries. Table 4.9 shows the results of various simulations in which social spending is raised by 1 percent of GDP and financed through an equivalent increase in tax collection.46 There are four different simulations, combining two sets of permutations. First, the increase in taxes is assumed to be financed by an increase in all taxes proportional to their current shares in total collection (admittedly, an unrealistic case) or, alternatively, to come solely from an increase in the VAT.47 Second, the proceeds are assumed to be distributed according to the current incidence of social spending or, alternatively, in an equal amount to everyone (i.e., for every additional $100, $20 is channeled to each quintile). These alternative scenarios are designed to provide a minimum benchmark for the redistributive power of tax-financed increases in social spending: any reform that improves the incidence of taxation (e.g., through the elimination of regressive exemptions) or the targeting of spending beyond its current level or beyond an unambitious flat distribution would yield much stronger redistributive effects. The outcome of the exercise is qualitatively the same across all permutations. The net distributional effect of a fiscal policy reform that increases tax revenue by 1 percent of GDP and devotes the proceeds to social spending is progressive. It would reduce the income Gini coefficient between 0.5 and 0.8 percentage points in Costa Rica, Guatemala, Nicaragua, and Panama, and between 0.2 and 0.4 percentage points in El Salvador and Honduras.48 Two key messages emerge:

Table 4.9.Simulated Impact of Specified Fiscal Policy Reform on Postfiscal Policy Income(Percentage Change in Postfiscal Policy Income Before the Reform)
Population income quintiles (from lowest to highest)Change in

Gini1
12345
Simulation 1: 1 percent of GD P increase in overall tax collection devoted to social spending
Costa Rica3.31.40.6-0.1-0.9-0.6
El Salvador4.41.30.4-0.2-0.5-0.4
Guatemala3.72.11.10.2-1.1-0.7
Honduras4.01.40.50.0-0.7-0.5
Nicaragua3.32.11.30.1-0.8-0.6
Panama5.42.71.20.4-1.2-0.8
Simulation 2: 1 percent of GD P increase in overall tax collection channeled evenly to income groups
Costa Rica2.51.10.70.0-0.8-0.5
El Salvador3.20.90.3-0.1-0.4-0.3
Guatemala4.62.10.90.1-1.1-0.7
Honduras3.91.60.60.0-0.7-0.5
Nicaragua6.12.71.20.1-1.1-0.8
Panama5.52.31.20.4-1.1-0.7
Simulation 3: 1 percent of GDP increase in V AT collection devoted to social spending
Costa Rica3.31.40.5-0.2-0.8-0.6
El Salvador3.91.10.3-0.2-0.4-0.4
Guatemala3.31.70.90.1-0.9-0.6
Honduras3.31.10.3-0.1-0.5-0.4
Nicaragua2.21.40.9-0.2-0.4-0.4
Panama5.42.50.90.1-1.0-0.7
Simulation 4: 1 percent of GDP increase in VAT collection channeled evenly to income groups
Costa Rica2.51.10.60.0-0.7-0.5
El Salvador2.70.70.2-0.1-0.3-0.2
Guatemala4.21.70.6-0.1-0.8-0.6
Honduras3.21.30.3-0.1-0.5-0.4
Nicaragua5.12.00.7-0.2-0.7-0.6
Panama5.42.00.80.1-0.9-0.7
Source: IMF staff calculations.

Quasi-Gini coefficient for postfiscal policy income after the reform minus quasi-Gini coefficient for postfiscal policy income before the reform, times 100.

Source: IMF staff calculations.

Quasi-Gini coefficient for postfiscal policy income after the reform minus quasi-Gini coefficient for postfiscal policy income before the reform, times 100.

  • First, improving the targeting of social spending beyond a mere absolute neutrality results in considerable gains in inequality reduction. In the case of Nicaragua, if the current pattern of absolute regressivity in social spending were improved to at least a flat distribution, the impact of a rise in social spending on the income of the poorest quintile would be doubled.
  • Second, the redistributive impact of the increase in social spending is not much affected by whether it is financed through an increase in the VAT (despite its regressivity) compared with other taxes: the differences in terms of Gini index impact are small, except in the case of Nicaragua, where the VAT is more regressive relative to other taxes and to the original (pre–fiscal policy) income distribution.

Conclusions

The limited redistributive potential of taxation, especially compared with that of social spending, suggests that a key focus of tax policy should be raising revenue efficiently. The distributional impact of taxes is generally small, whether a tax is progressive or regressive. Moreover, there is often a tradeoff between the progressivity of a tax and its potential to raise revenue: if the progressivity of the tax derives from the granting of exemptions or the application of differential tax rates, its base may be eroded.

Therefore, increasing the progressivity of the tax system may reduce the pool of resources available for redistribution through social spending and may ultimately be detrimental for reducing poverty and inequality. By contrast, broadening the tax base—even if that implies eliminating progressive exemptions—may enhance the overall progressivity of fiscal policy.

This, however, does not imply that equity should not be a consideration in tax policy debates. The evidence in this chapter shows that income taxes can be much less progressive and VATs and sales taxes much less regressive in some countries than others. This might in part reflect different economic structures, but weaknesses in tax design can also be a factor, and one that may simultaneously harm equity, efficiency, effectiveness, and administrative simplicity. Exemptions that disproportionately favor the richer segments of society may, for instance, make the tax more regressive, elicit evasion, and reduce revenue.

Although social spending can potentially have a powerful redistributive effect, its impact on poverty and income distribution in Central America is undermined by its relatively low level. Countries in the region have made a visible effort in recent years to increase social expenditures. But, despite broad variations across the region, public social spending remains generally low both relative to GDP and as a share of total public spending.

The targeting of social spending in the region can also be improved. The evidence discussed in this chapter suggests that spending on health and primary education is strongly progressive. By contrast, spending on pensions and tertiary education is very regressive. The access and coverage of these two components of spending should be improved to enhance their impact on the poor. Well-targeted social assistance programs, such as cash transfers to households conditional on children attending school, can have a significant effect on poverty reduction, especially in the long run.

The combined effect of taxation and well-targeted social spending can substantially improve the income of the poor, even if the tax system individually considered is regressive. In Panama, for instance, as in many European countries, the net effect of fiscal policy is estimated to more than double the income of the poorest 20 percent of the population.

Table 4.A1.Central America: Evolution and Structure of Tax Revenue
Total

Revenue
Total Tax Revenue
Total1Income TaxesVAT/SalesExcisesTrade Taxes
200320062003200620032006200320062003200620032006
In percent of GDP
Costa Rica13.913.813.613.64.04.04.75.12.72.71.51.5
Dominican Republic15.918.014.916.94.44.53.85.13.14.73.52.6
El Salvador12.713.811.512.93.34.16.16.70.60.61.21.1
Guatemala12.512.611.711.71.52.35.35.41.21.11.41.1
Honduras18.419.716.318.13.54.96.06.61.41.01.51.4
Nicaragua16.418.815.217.53.85.16.27.34.14.01.01.0
Panama15.318.48.710.33.45.11.51.91.20.71.51.6
Central America, Panama, and DR average15.016.413.114.43.44.34.85.42.02.11.71.5
Source: IMF staff calculations, based on data from the authorities.

Other taxes are excluded from the table, so the sum of income, VAT, excise and trade taxes is not equal to total tax revenue.

Source: IMF staff calculations, based on data from the authorities.

Other taxes are excluded from the table, so the sum of income, VAT, excise and trade taxes is not equal to total tax revenue.

Table 4.A2.Progression of Taxes in Central America and Comparator Countries
Relative tax burden by income quintile1
1st2nd3 rd4th5th
Income taxes
Costa Rica (2000)88.092.891.392.2106.6
El Salvador (2000)40.571.668.396.3115.8
Guatemala (2004)95.888.586.781.7111.2
Honduras (2004)40.649.657.270.9131.0
Nicaragua (2004)62.569.876.185.7113.3
Panama (2003)70.115.111.626.7146.7
U.S. (Fed, 2004, with Social Sec)12.145.767.886.2129.3
U.S. (Fed, 2004, w/o Social Sec)-53.1-3.631.560.2161.9
VAT/Sales Tax
Costa Rica (2000)104.6109.5105.5104.795.1
El Salvador (2000)320.4183.9136.0106.666.0
Guatemala (2004)145.6122.1114.9108.487.4
Honduras (2004)272.1144.6125.4104.476.5
Nicaragua (2004)255.6189.8158.2129.963.5
Panama (2003)144.3121.6109.896.396.2
Bolivia (2000)86.0109.9105.899.998.5
Excise Taxes
Costa Rica (2000)70.883.990.0105.9104.7
El Salvador (2000)188.8127.0129.798.885.2
Guatemala (2004)104.195.587.597.0104.1
Honduras (2004)192.2178.2181.0131.153.7
Nicaragua (2004)269.9198.2158.7112.166.4
Panama (2003)120.3121.1102.396.598.1
Bolivia (2000)86.0109.9105.899.998.5
U.S. (Federal, 2004)274.4169.9130.7104.665.3
Trade Taxes
Costa Rica (2000)129.8140.5131.2118.577.6
El Salvador (2000)258.6157.8124.9105.575.8
Guatemala (2004)53.654.765.084.5122.8
Honduras (2004)282.8164.1133.9109.669.3
Nicaragua (2004)172.9144.6131.2116.581.3
Panama (2003)216.0161.4135.0108.682.2
Sources: Acevedo and González Orellana (2005); Auguste and Artana (2005); Barreix et al. (2006); Bolaños (2002); Gillingham, Newhouse, and Yakovlev (forthcoming); Gómez Sabaini (2005b); Cossío Muñoz (2006); Rodríguez Arosemena (2007); U.S. Congressional Budget Office (2006); EUROMOD.

Effective tax/income ratio relative to the average ratio; a value greater than 100 indicates that the income group pays a higher percentage of its income relative to the average.

Sources: Acevedo and González Orellana (2005); Auguste and Artana (2005); Barreix et al. (2006); Bolaños (2002); Gillingham, Newhouse, and Yakovlev (forthcoming); Gómez Sabaini (2005b); Cossío Muñoz (2006); Rodríguez Arosemena (2007); U.S. Congressional Budget Office (2006); EUROMOD.

Effective tax/income ratio relative to the average ratio; a value greater than 100 indicates that the income group pays a higher percentage of its income relative to the average.

Table 4.A3.Redistributive Impact of Taxation in Central America and Comparator Countries
Gini pre-tax income (A)Quasi-Gini for taxes (B)Kakwani Index (C = B - A)Tax pressure1Quasi-Gini post-tax (D)RS Index2 (E = A - D)
Income taxes
Costa Rica (2000)45.148.13.09.644.80.3
El Salvador (2000)47.456.38.91.347.30.1
Guatemala (2004)46.350.44.13.746.20.2
Honduras (2004)47.261.614.44.946.40.7
Nicaragua (2000)51.058.67.64.550.70.4
Panama (2003)53.873.920.12.153.40.4
Colombia (2003)53.789.435.71.451.32.4
Ecuador (2003)40.883.142.30.740.30.5
Peru (2000)53.558.24.71.453.50.0
Venezuela (2003)42.384.041.70.442.10.2
U.S. (Federal, 2004)343.859.916.119.040.03.8
U.S. (Federal, 2004)443.875.531.711.139.84.0
VAT/Sales taxes
Costa Rica (2000)45.142.9-2.25.145.3-0.2
El Salvador (2000)47.425.3-22.15.448.7-1.3
Guatemala (2004)46.339.1-7.28.247.0-0.6
Honduras (2004)47.231.3-15.97.048.4-1.2
Nicaragua (2000)51.027.8-23.211.153.9-2.9
Panama (2003)53.850.5-3.31.953.9-0.1
Bolivia (2000)55.654.7-0.95.655.7-0.1
Colombia (2003)53.746.9-6.86.354.1-0.4
Ecuador (2003)40.844.53.76.440.60.2
Peru (2000)53.535.8-17.74.954.7-1.2
Venezuela (2003)42.347.35.04.742.7-0.4
Excise Taxes
Costa Rica (2000)45.149.34.22.645.00.1
El Salvador (2000)47.437.9-9.50.547.50.0
Guatemala (2004)46.347.91.62.046.30.0
Honduras (2004)47.224.4-22.80.847.4-0.2
Nicaragua (2000)51.027.5-23.67.352.9-1.9
Panama (2003)53.851.8-2.01.353.80.0
Bolivia (2000)55.685.329.71.855.50.1
U.S. (Federal, 2004)43.821.3-22.50.844.0-0.2
Trade Taxes
Costa Rica (2000)45.134.4-10.71.145.3-0.2
El Salvador (2000)47.431.8-15.70.947.6-0.2
Guatemala (2004)46.358.312.03.245.90.4
Honduras (2004)47.227.7-19.51.847.5-0.4
Nicaragua (2000)51.039.5-11.62.451.3-0.3
Panama (2003)53.842.6-11.21.153.9-0.1
Sources: Acevedo and González Orellana (2005); Auguste and Artana (2005); Barreix et al. (2006); Bolaños (2002); Gillingham, Newhouse, and Yakovlev (forthcoming); Gómez Sabaini (2005b); Cossío Muñoz (2006); Rodríguez Arosemena (2007); U.S. Congressional Budget Office (2006); EUROMOD.

Tax pressure is the ratio of total taxes paid to total income before taxes.

RS is the Reynolds-Smolensky Index.

Including social security taxes.

Excluding social security taxes.

Sources: Acevedo and González Orellana (2005); Auguste and Artana (2005); Barreix et al. (2006); Bolaños (2002); Gillingham, Newhouse, and Yakovlev (forthcoming); Gómez Sabaini (2005b); Cossío Muñoz (2006); Rodríguez Arosemena (2007); U.S. Congressional Budget Office (2006); EUROMOD.

Tax pressure is the ratio of total taxes paid to total income before taxes.

RS is the Reynolds-Smolensky Index.

Including social security taxes.

Excluding social security taxes.

Table 4.A4.Comparison of Income- vs. Consumption-Based Measures of Progressivity for Total and VAT Taxes1
Tax ProgressionGini

Income or

Cons.2
Quasi-Gini

Taxes
Kakwani

Index
Quintiles
12345
El Salvador
All taxes (income)261.4159.8123.7104.476.147.431.7-15.7
All taxes (consumption)101.1101.299.198.9100.431.831.7-0.1
VAT (income)320.4183.9136.0106.666.047.425.3-22.1
VAT (consumption)123.9116.5108.9101.087.131.825.3-6.5
Nicaragua
All taxes (income)195.9154.7133.4112.479.651.037.4-13.6
All taxes (consumption)113.3107.0101.796.597.939.537.4-2.1
VAT (income)255.6189.8158.2129.963.551.027.8-23.2
VAT (consumption)147.8131.2120.6111.578.139.527.8-11.6
Panama
All taxes (income)127.893.580.475.6110.853.857.13.3
All taxes (consumption)45.251.656.667.7144.938.557.118.6
VAT (income)144.3121.6109.896.396.253.850.5-3.3
VAT (consumption)51.067.277.386.3125.838.550.512.0
Sources: Acevedo and González Orellana (2005); Gómez Sabaini (2005b); Rodríguez Arosemena (2007)

Household are ordered by income quintiles.

Quasi-Gini index for consumption, as consumption distribution is ordered by income quintiles.

Sources: Acevedo and González Orellana (2005); Gómez Sabaini (2005b); Rodríguez Arosemena (2007)

Household are ordered by income quintiles.

Quasi-Gini index for consumption, as consumption distribution is ordered by income quintiles.

Table 4.A5.Cyclicality of Public Social Spending in Central America
Correlation of Cyclical Components of

HP-Filtered Series
Overall periodt -value1990–97t -value1998–2004t -value
Costa Rica
Total Social Spending0.110.410.360.96-0.35-0.85
Education-0.06-0.230.461.29-0.87-3.95
Health0.090.330.350.91-0.27-0.63
Social Protection10.271.030.160.390.390.94
Dominican Republic
Total Social Spending0.301.09-0.04-0.090.883.67
Education0.663.060.100.250.924.63
Health0.713.490.340.900.935.00
Social Protection10.532.190.591.770.531.23
Guatemala
Total Social Spending0.552.38-0.08-0.200.823.23
Education0.522.18-0.14-0.360.762.65
Health0.481.99-0.26-0.650.803.01
Social Protection10.020.06-0.22-0.560.020.05
El Salvador
Total Social Spending0.451.830.391.040.641.86
Education0.130.470.020.040.320.75
Health0.825.230.813.430.853.64
Social Protection10.120.45-0.18-0.450.641.88
Honduras
Total Social Spending0.110.400.080.190.140.33
Education-0.23-0.85-0.24-0.62-0.14-0.32
Health-0.08-0.31-0.03-0.06-0.16-0.36
Social Protection10.281.030.180.450.471.19
Nicaragua
Total Social Spending0.441.770.411.100.551.48
Education0.512.110.451.230.641.88
Health0.562.410.581.760.581.58
Panama
Total Social Spending0.542.340.773.000.360.85
Education0.683.350.631.980.752.54
Health0.170.61-0.13-0.330.411.00
Social Protection10.150.540.471.29-0.18-0.41
Sources: ECLAC; country national authorities; and IMF staff calculations. Bolded values indicate significance at a 5 percent significance level.

Social protection includes social insurance (social security) and social assistance.

Sources: ECLAC; country national authorities; and IMF staff calculations. Bolded values indicate significance at a 5 percent significance level.

Social protection includes social insurance (social security) and social assistance.

Table 4.A6.Average Annual Rate of Growth and Volatility of GDP and Public Social Spending
1991–971998–200411991–20041
Average

annual

growth rate
Coefficient of

variation
Average

annual

growth rate
Coefficient of

variation
Average

annual

growth rate
Coefficient of

variation
Regional Comparison
Central America
Gross domestic product4.490.203.500.334.000.28
Public social spending6.450.798.090.587.270.66
Education6.281.067.970.577.120.78
Health3.921.117.170.935.541.02
Latin America (20 countries)
Gross domestic product3.600.411.401.152.600.73
Public social spending4.601.162.801.083.801.19
Education4.102.483.301.753.702.30
Health2.302.361.702.582.002.47
By Individual Country
Costa Rica
Gross domestic product4.850.594.710.644.780.59
Public social spending5.851.245.670.665.760.96
Education7.061.567.790.767.421.14
Health3.691.466.390.985.041.15
Dominican Republic
Gross domestic product5.170.534.980.785.080.62
Public social spending11.472.205.022.338.492.31
Education16.021.164.464.5610.691.83
Health11.362.214.804.758.332.79
El Salvador
Gross domestic product5.270.412.510.313.890.55
Public social spending10.160.816.911.068.540.90
Education8.280.676.281.447.281.00
Health9.811.224.771.277.291.30
Guatemala
Gross domestic product4.100.173.120.343.610.28
Public social spending8.921.478.001.638.461.49
Education6.211.508.631.377.421.39
Health2.913.966.042.864.473.17
Honduras
Gross domestic product3.780.662.880.833.330.72
Public social spending3.144.2812.940.858.041.60
Education0.755.9514.780.597.771.27
Health0.8315.8011.331.196.082.29
Nicaragua
Gross domestic product3.010.983.750.533.380.73
Public social spending2.143.6710.752.386.452.90
Education5.734.348.412.197.072.98
Health-0.19-60.068.572.484.194.06
Panama
Gross domestic product5.930.474.070.635.000.55
Public social spending8.481.114.261.356.371.22
Education9.651.031.921.725.781.41
Health6.471.275.901.896.181.53
Sources: ECLAC, 2006; and IMF staff calculations on data from national authorities.

Calculations through 2003 for the Latin American average.

Sources: ECLAC, 2006; and IMF staff calculations on data from national authorities.

Calculations through 2003 for the Latin American average.

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1See, for example, Pechman (1985) for the United States and Engel, Galetovic, and Raddatz (1999) for Chile.
2See Chu, Davoodi, and Gupta (2000), who find that a large revenue-neutral increase in the ratio of direct to indirect tax revenues (i.e., increasing the share of taxes that are potentially more progressive) has only a small impact on the Gini coefficient, whereas an increase in secondary school enrollment (an outcome of public spending) has a relatively large impact on improving income distribution.
3See, for instance, Harberger (2003), IDB (1998), and Lora (2007).
4As Bird (2003, p. 12) states, “… tax recommendations that assume that distributional considerations are either unimportant or can easily be accommodated by (unspecified) adjustments somewhere else simply do not resonate in the policy context of most countries. Distributional issues not only matter in tax policy but often dominate in the minds of those who shape that policy.”
5In tax policy, there are two different notions of equity. There is said to be horizontal equity if individuals or households that earn the same income, regardless of its source, pay the same taxes. Vertical equity, on the other hand, is generally taken to imply that the tax burden should increase with income. This latter notion is the one that is relevant for an analysis of the incidence and distributional effects of taxation.
6In particular, the potentially negative effects of income taxation on capital accumulation, and of certain categories of social transfers on the incentives to work, impose a constraint on the degree of redistribution that can optimally be achieved through fiscal policy.
7The choice of years for Table 4.1 (1995 and 2003) was dictated by data availability for the set of comparator countries and the fact that the underlying studies on which the following tax and social spending incidence analysis is based use data that range between 2000 and 2004. However, Appendix Table 4.A.1 presents data on the level and structure of central government revenue (including nontax revenue) for the Central American countries in 2006.
8Income from the Panama Canal accounts for a large share of government revenues.
9This assumption implies infinitely elastic supply curves, so that producers shift the taxes fully to the prices paid by consumers. In practice, the actual extent of shifting will be a function of price elasticities of demand and supply.
10For these taxes, the key assumptions are about the intersectoral and international mobility of capital. See Mintz (1996) and Cullis and Jones (1998).
11A less stringent indicator, called average rate progression, measures how the effective tax ratio changes as income increases. There is progression if the marginal effective tax ratio is greater than the average ratio as income increases. Progression, in this broader sense, indicates progressivity only under certain assumptions (e.g., that there is no re-ranking of individuals between pretax and post-tax). For a description and mathematical expression of different measures of progression, see Gemmell and Morrissey (2002).
12Conceptually, a concentration curve and a Lorenz curve differ in that the former plots cumulative shares of X (e.g., tax payments) with respect to the percentile distribution of Y (e.g., pre-tax income), whereas the latter represents the cumulative share of Y with respect to the quantile distribution of Y. The concentration curve for post-tax income relative to pre-tax income is the same as the post-tax Lorenz curve if, and only if, the ranking of individuals by their pre- and post-tax income does not change.
13The Gini coefficient for a concentration curve is called quasi-Gini (as opposed to the Gini coefficient proper, which corresponds to a Lorenz curve). If two concentration curves coincide, their quasi-Gini coefficients are the same; the reverse, however, does not necessarily hold: a given quasi-Gini may derive from different patterns of distribution.
14Obviously, the Kakwani and Reynolds-Smolensky indices for a given tax have the same signs.
15The section is based on the most recent studies available for Costa Rica (Bolaños, 2002), El Salvador (Acevedo and González Orellana, 2005), Guatemala (Auguste and Artana, 2005; and Schenone and de la Torre, 2005); Honduras (Gillingham, Newhouse, and Yakovlev, forthcoming), Nicaragua (Gasparini and Artana, 2003; and Gómez Sabaini, 2005b), and Panama (Rodríguez Arosemena, 2007). For Honduras, see also Gómez Sabaini (2005a). Unfortunately, there are no recent data for the Dominican Republic; however, some information is drawn from Santana and Rathe’s (1993) assessment of tax incidence, based on 1989 data.
16In the case of Panama, the data for the incidence of taxes and social spending in Rodríguez Arosemena (2007) are based on income per capita, and were approximated to total income using the number of individuals per decile.
17For this reason, the figures for tax progression and global measures of incidence shown in this paper are not the same as those presented by the authors of the source papers. Measures of tax progression and distribution are sensitive to the number of income groups used. For a given underlying distribution, the larger the number of groups, the higher the several indicators of inequality will be. In the case of Panama, the data are ordered by quintiles of income per capita.
18The inflation tax, however, is broadly acknowledged to be regressive, because the poor normally have a higher ratio of money to income and a reduced ability to hedge against the effects of inflation. Bolaños (2002) finds that the inflation tax has a very regressive effect in Costa Rica.
19Latin American countries offer an interesting comparator set, because they have levels of economic and institutional development that are broadly similar to those of Central American countries. The comparison with the European Union and the United States brings into perspective both the experience of rich countries and also what are widely perceived to be two different models for the role of the state in the economy.
20An analysis of tax progression combines two pieces of information: the distribution of income before taxes, and the distribution of overall tax payments across income groups. The three panels in Table 4.3 show the interplay of these factors.
21This paradox arises because the concentration curve for taxes and the Lorenz curve for income cross (Lorenz dominance fails). It also illustrates the potential weaknesses of the Gini coefficient as a summary measure of inequality. The Gini index implicitly gives the same weight to equal transfers of resources between quintiles separated by the same distance, regardless of their position in the income scale. Thus, if $10 were taken from both the lowest quintile and the richest quintile and given to the middle quintile, or given to the second and the fourth, the Gini coefficient would remain unchanged, even though such redistributions would imply a much larger relative loss in the income for the poorest quintile. Consider a situation in which the concentration curves for taxes and income coincide (i.e., the tax system is neutral), implying that their Ginis are the same. Assume now that the taxes paid by the middle quintile are reduced by $30, $10 of which is shifted to the bottom quintile and the other $20 to the top quintile. If the pretax income of the richest quintile is more than double that of the poorest, this redistribution of tax payments would increase the relative tax burden of the poorest much more than that of the richest, yet the quasi-Gini for taxes would become greater than the Gini for income. The result for Panama seems driven by the strong progressive effect of income taxes, which have a much greater weight in total tax revenues in this country than in the rest of the region.
22The effective tax rates paid (as a percentage of income) by the poorest 40 percent of households, the following 35 percent, the next 20 percent, and the top 5 percent were, respectively, 11.5 percent, 13 percent, 15.6 percent, and 17.2 percent.
23This latter ratio may differ, sometimes substantially, from the tax-to-GDP ratio. The differences may arise in the numerator; for example, if the coverage of taxes used for the analysis of incidence is limited to a subset of total taxes. The differences may also arise in the denominator, and may stem from a considerable gap between GDP and national income, as well as from differences in total income measured from national accounts vis-à-vis household surveys. This is the case for Nicaragua, as explained in the next footnote.
24The measured tax pressure for Nicaragua is high because the coverage of taxes for the incidence analysis is broad (including property and sales taxes for the city of Managua) and total disposable income was only 51 percent of GDP for 2000, according to the information used by Gómez Sabaini (2005b).
25Social security contributions are treated as taxes on wages by Bolaños (2002), and are therefore included under the income tax for Costa Rica. This contributes to underestimate the progressivity of income taxes in Costa Rica relative to the rest of the region.
26This pattern of incidence is consistent with what Gemmell and Morrissey (2005), in their survey article, find for corporate income taxes: a U-shaped progression (regressive, then progressive). This may be due to the existence of exemptions for particular types of income or taxpayers and to the fact that small but poor entrepreneurs tend to be less capable of exploiting deductions and other tax-minimizing opportunities in self-employment taxes.
27The underlying study (Rodríguez Arosemena, 2007) considers only taxes on income from wages and self-employment. Corporate income taxes are excluded.
28Gemmell and Morrissey (2005) conclude, from their review of the existing literature, that income taxes are generally progressive, although personal income taxes are more consistently so than corporate taxes. Chu, Davoodi, and Gupta (2000) summarize tax incidence studies on a cross-section of developing countries in various regions over 1975–98. Their tabulation suggests that, regarding income tax systems, 12 of the 14 cases studied for 8 different countries show progressivity, 1 is regressive, and 1 inconclusive. See also Engel, Galetovic, and Raddatz (1999) for Chile. Payroll taxes, on the other hand, are more likely to be regressive (Chu, Davoodi, and Gupta, 2000).
29Income taxes without social security are negative for the bottom two income quintiles in the United States because of earned income tax credits.
30Although several studies suggest that the incidence of VATs and sales taxes is regressive when considered relative to income (e.g., Gemmel and Morrissey, 2005, in their survey), there is evidence that VATs have a progressive incidence in some African countries (Sahn and Younger, 1999; and Muñoz and Cho, 2004). Appendix Table 4.A.3 shows that the VAT is progressive in Ecuador and Venezuela, even when considered relative to income.
31It is likely that in El Salvador and other Central American countries, remittances from abroad are under-represented in household income but not in consumption, contributing to consumption rates well over unity for the poorer households.
32A VAT with no exemptions should, in principle, be roughly proportional to consumption. To the extent that there are well-targeted exemptions that reduce the effective VAT rate relative to the consumption basket of the poorer households, the VAT should be slightly progressive when measured in terms of consumption. In this sense, as Bar-reix, Roca, and Vilella (2006) argue, the consumption- or expenditure-based analysis of VAT incidence provides a way to check who ultimately benefits from the VAT exemptions.
33Taxes on fuel, tobacco, and alcohol are assessed and designed for the purpose of mitigating potential externalities. Equity issues are not a consideration. They do, however, play a role in the case of taxes on luxury goods.
34Consistent with the findings for other countries, in Panama excise taxes on tobacco and alcoholic and other drinks are very regressive, but those on cars and other luxury items are progressive (Rodríguez Arosemena, 2007).
35Nonetheless, Bolaños (2002) argues that a legal reform in 2001—which substantially reduced average tax rates and their dispersion—may have reduced or eliminated the progressivity of these taxes in Costa Rica.
36Auguste and Artana (2005)—on whose data the figures in the aforementioned tables are based—admit that the progressivity of import tariffs may be considerably overestimated in their study, because they excluded intermediate good imports from the analysis. The authors also explain that some imported goods, despite being classified as final goods, may have been used as intermediate goods for the production of other goods and services whose consumption may be distributed more evenly across income groups. A previous study (Mann, 2002) found that import tariffs are roughly proportional.
37The share of social spending in total public expenditure is, on the other hand, a measure of the fiscal priority of social spending.
38Social protection includes both social insurance (mainly pensions) and social assistance.
39Overall public spending in Central America has also been pronouncedly procyclical. Empirical evidence suggests that procyclical government expenditure seems to be the norm rather than the exception outside the Group of Seven (G-7) industrial countries, where fiscal policy appears to be acyclical (Talvi and Végh, 2005). A survey of recent trends in public expenditure in Latin America shows that the procyclicality of government spending is, on average, higher for Latin American countries than for other developing countries, and notably higher for Costa Rica and Guatemala (Clements, Faircloth, and Verhoeven, 2007).
40The cyclical components were extracted using a Hodrick-Prescott filter.
41Box 8.1 of IDB (1998) provides a very clear mathematical and graphical illustration.
42The bulk of social insurance spending is public pension spending. Conceptually, despite formal contributions to the scheme, social security systems that incur tax-financed deficits are financed by tax revenues and compete for resources with other social protection programs. The World Bank study focuses on net transfers (pension benefits received minus total contributions). Clearly, although necessary owing to data constraints, this treatment is an oversimplification of the true concept of “net pension benefits”—the net present value (NPV) of the pension benefits versus the NPV of the pension contributions of each household.
43The “typical” distributional effect is derived from the median value of a distributional capacity index, calculated for a wide range of social assistance programs in eight countries: Argentina, Brazil, Chile, Colombia, the Dominican Republic, Guatemala, Mexico, and Peru. This distributional capacity measure is not directly comparable to the measures used in this paper.
44See Lindert, Skoufias, and Shapiro (2006) for case studies of specific social protection programs in Guatemala and the Dominican Republic; and Regalia and Robles (2005) for a discussion of social assistance programs in the Dominican Republic.
45The large share of social spending to tax revenue in Panama—made possible by the large proportion of nontax revenue in total government revenue (see Appendix Table 4.A.1)—explains the redistributive impact of fiscal policy shown in Table 4.8, whereby the income of the top quintile is reduced by only 3 percent while the income of all other quintiles increases, substantially so in the bottom two.
46For simplicity, it is assumed that no revenues are lost in the process of redistribution.
47Two considerations motivated the focus on the VAT as one alternative permutation. The first, already referred to above, is the fact that globalization limits the scope for the taxation of capital and—to a lesser extent—labor income, which leads developing countries to raise taxes mainly through increases in the VAT. The second is the weight given in policy debates to the potential regressivity of the VAT taken in isolation, without acknowledging its overall distributional effects once the allocation of the proceeds is considered.
48These findings are in line with those from a similar simulation exercise reported in IDB (1998), which finds that a hypothetical 1 percent of GDP rise in VAT revenues that is distributed equally (in absolute terms) among all income groups would reduce the income Gini coefficient by between 0.4 and 0.6 percentage points in Guatemala, Colombia, and the Dominican Republic, and between 0.3 and 0.4 in Argentina and Chile.

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