Template, which compiles information on fuel subsidies for 192 nations from 2015 to 2025. To estimate the indirect effects, this analysis draws upon data from the input-output matrix, incorporating the IMF's industry subsidy ratios and the approach devised by Jellema and Inchauste (2018) for estimating these secondary impacts. For gas subsidies, our estimates incorporate the subsidy ratio based on consumer prices, as estimated by the IMF. In this calculation, the indirect effects are estimated by applying the rate above to industries, while the direct effects are calculated from the explicit subsidy applied to households.

**We assume the following on the distribution of tax burden and evasion.** Regarding tax burden, it is assumed that workers carry the economic weight of personal income taxes. At the same time, employees shoulder the burden of social security contributions, encompassing employer and employee contributions. Additionally, the weight of consumption taxes is placed on consumers. These assumptions are robust but strongly assume that labor supply exhibits perfect inelasticity and that consumers possess perfectly inelastic demand. While this may not align with real-world behaviors, these assumptions provide a practical approximation and are widely employed in the literature for analytical purposes. On tax evasion, Personal income taxes (PIT) and social security contributions (SIC) evasion are assumed to occur. Individuals earning below the minimum wage and those not contributing to SIC are categorized as informal workers and, consequently, are excluded from paying PIT and SIC, reflecting a potential form of evasion. Regarding indirect taxes, the Value Added Tax (VAT) calculation is determined using the effective tax rate. However, our analysis does not account for potential evasion of either VAT or excises due to a lack of information on the place of purchase in the 2021 HBS. Transactions in informal places, typically within the informal market, often evade VAT payments. Unfortunately, the Bulgaria HBS does not provide data on whether VAT is paid in these informal market transactions, limiting a more detailed assessment of indirect tax evasion.

**It is important to highlight that this fiscal incidence analysis (CEQ) offers insights into how fiscal policy affects monetary income poverty, measured by the at-risk- of poverty (AROP) and international poverty lines; other non-monetary welfare measures are not analyzed.** It is essential to acknowledge that this analysis does not extend to providing evidence on potential effects on non-monetary indicators, such as severe material deprivation, as they are not encompassed within the modeling framework. Consequently, our study lacks simulations or results about the composite indicator of being at risk of poverty or social exclusion, commonly referred to as AROPE. Moreover, it does not look at multidimensional poverty measures.

Identifying the child incidence of fiscal interventions

**Although fiscal incidence analysis is the most widely used methodology to assess the distributional effects of fiscal policies, it is not common to have a child or even a gender lens, given the methodological challenges that emerge once we need to reconcile individual and household-level concepts; this means some assumptions need to be made on how these fiscal resources are allocated within the household** . While examining fiscal incidence by age or gender, it is essential to consider the individual as the primary unit of analysis; however, it is important to acknowledge that most household transfers and expenditures occur at the household level. This introduces a challenge in the analysis, as one must make certain assumptions about how fiscal resources are allocated within the household. Since fiscal policies often target households as a whole, resources may not be evenly distributed among family members. Some individuals within a household might receive more benefits or bear a higher burden than others. For

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