Equally, a tax system with low tax rates requires a highly progressive system to achieve the same degree of redistribution.<sup>17</sup>

# 2.3 Examples

This section presents examples of effective progressivity measures from the recent empirical literature. It focuses on PIT and VAT.

## 2.3.1 Income taxes

There is a significant literature examining the distributional impacts of the PIT (see, e.g., for OECD countries, Joumard et al., 2012; Causa and Hermansen, 2017). However, given the significant data requirements for calculating effective progressivity metrics, results for IDA countries are sparce. For example, results are available from detailed CEQ distributional analyses for more than 40 developing countries, but for only six IDA countries. The CEQ analyses emphasize the importance of examining the distributional impact of tax and expenditure systems together, particularly given the interactions between different fiscal instruments.<sup>18</sup> Nevertheless, results focusing on direct taxes can be drawn out from the CEQ’s database (Commitment to Equity Institute Data Center on Fiscal Redistribution, 2022). Results for the six available IDA countries are presented in Table 1. Direct taxes include the PIT together with SSC but excluding pension contributions (which are considered compulsory savings).<sup>19</sup> The results for IDA countries can be expected to predominantly reflect the PIT due to the minimal use of social contributions in IDA countries.

In addition to global metrics, it is quite common to present a visual representation of the distribution of tax burdens by plotting average tax rates across deciles or quintiles.<sup>20</sup> Table 1 presents both global indicators and graphical results for each country. To provide context to the IDA country results, Table 1 also presents results available for the United States. Results all relate to the particular year of the underlying microdata used in the analysis. Note that income survey microdata was available in only two of the six IDA countries (Honduras and Nicaragua).<sup>21</sup> In the other four countries, consumption data was used to proxy for income.<sup>22</sup> 17 A characteristic of the Gini-based dispersion measures on which the Kakwani and Reynolds-Smolensky indices are based is that they are less responsive to changes at the tails as compared to the middle of the distribution being examined. An alternative approach to measure redistribution is to calculate the difference in the Atkinson inequality index before and after tax. The Atkinson index enables greater emphasis to be applied to the bottom of the income distribution by specifying the degree of inequality aversion in its underlying social welfare function.

18 For example, Lambert’s conundrum illustrates that, due to path dependency, the combined impact of a regressive tax and a progressive transfer can lead to lower inequality than without the regressive tax (Lambert, 2001). 19 See Lustig (2018) for more detail on the CEQ methodology.

> 20 These remain _effective_ progressivity measures as they are the averages of the modelled tax burdens of the households in each decile or quintile.

21 Income survey data is now also available for Ethiopia and will be used in distributional analysis to be undertaken by the World Bank’s Fiscal Policy and Sustainable Growth Unit in the second half of 2022.

22 Because richer households tend to save more than poorer households, using consumption data can be expected to underestimate the income levels of high-income households and the resulting metrics may therefore underestimate the total progressivity achieved in the country. To a smaller extent this can also occur for the countries based on income survey data due to the underreporting of top earners in income survey data.

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