studies are based on EUROMOD, the tax-benefit model for EU-28, and its spin-off models for nonEU countries.

The paper by Paulus et al. (2009) uses EUROMOD to assess the impact of the flat PIT reform on fiscal revenues and on the redistribution of individuals’ incomes in three EU countries. They show that the most radical scenario with a flat tax rate of 20 percent and no tax concessions (apart from exempting pensions from tax) could result in a dramatic increase in inequality and poverty because most of the cost of the reform would be borne by lower income groups.

Using a EUROMOD spin-off for Serbia (SRMOD), Randelovic & Zarkovic Rakic (2013) simulate the distributional effects of changing a SIC formula in Serbia, specifically the abolishment of a mandatory minimum SIC, which in theory should increase incentives for formal employment. Authors indeed find a reduction in average and marginal tax rate as a consequence of this reform, and therefore an improvement in incentives for formal employment, but show that this does not necessarily lead to an increase in labor supply per se. The distributional impact of the reform is assessed as positive (i.e., reductions in poverty and inequality) but rather small. The abolishment of a minimum SIC payment is especially beneficial for lower income workers.

RLMS-HSE captures informal employment at the main job, the additional (second) job and from occasional ad hoc jobs.<sup>14</sup> In RUSMOD informal workers were excluded from simulations of SIC, PIT and earnings-related benefits. In order to simulate SIC, the model needs to distinguish between employees and the self-employed/individual entrepreneurs because the formula of contributions and tax base are different for these two categories. The simulation exercise excludes the self-employed workers because the tax maneuver would not affect the taxation mechanism for this group. Table A- 10 shows how the informality status was defined for these two categories of workers using the survey questions. Since one individual may have more than one job, some individuals may be classified as both employee and the self-employed and receive both formal and informal income at different jobs.

For this study, we opted for a wide definition of informality where a worker is defined as informal if it has any of the following jobs: (i) a main job without contract, or with contract but part of its payment is not subject to SIC and PIT (i.e., envelope payments); (ii) a second job as self-employed or in the corporate sector but without contract, or (iii) an occasional job without a labor contract. According to RLMS data, as of 2016, the share of informally employed amounted to 19.8 percent at the main job and 44.2 percent at the second job, among employees. Among the self-employed, 63 percent were classified as informal workers at the main job. Among those who reported occasional selfemployment 89 percent were informal. According to this definition, 32.6 percent of all jobs (either primary, secondary or occasional) are informal. If focusing on workers, rather than jobs, 33.4 percent

> 14 In this study we focus only on informal employment, not the informal sector. Hence, accounting and behavioral simulations focus on individual workers and their jobs, not on firms. This is due to our use of a household survey, rather than firm data, as well as our methodological approach. An analysis of informal firms would require different data sources and methods. For an analysis of firms and informality, see Galiani & Weinschelbaum (2012) and Ulyssea (2018). For an explanation of the distinction between informal employment and informal sector, see Chapter 25 in “Informal aspects of the economy” in _System of National Accounts 2008_ (United Nations Department of Economic and Social Affairs, 2010) and Chapter 8 “Employment in the Informal Economy” in Key Indicators of the Labour Market 2015 (ILO, Geneva, 2016).

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