# 1. Introduction

The COVID-19 pandemic coupled with the inflationary effects of the war in Ukraine have put enormous economic pressure on countries, with consequential negative effects on their populations. Global GDP decreased by 3.4% in 2020, with drops varying from -6.4% in Latin America and the Caribbean (LAC) to - 2% in Europe and Central Asia (World Bank, 2022e). Inflation reached high levels equivalent to 3.5% in 2021 globally, 2.6% in Europe, 4.7% in the U.S., and 3.9% in LAC. The combination of lower economic opportunities with higher costs of living is expected to have largely affected low-income and the most vulnerable households, such as women and non-college-educated youth, as they used to work in sectors that were hit the hardest by closures (Agrawal et al., 2021, OECD, 2022), and devote a larger share of their resources to purchase food (MacDonald et al., 1991, Kaufman et al., 1997).

Countries across the globe put in place a myriad of emergency measures aimed at shielding the most vulnerable households. Ranging from cash transfers to incentives for firms to reduce contracted hours of employees or offering loan guarantees and direct lending facilities to preserve jobs (OECD, 2021, Gentilini et al., 2022a), these programs are estimated to have cost over USD 3 trillion in 2020-2021 (Gentilini et al., 2022b). As economies were slow to recover, countries face a major fiscal crunch, with more than 80 percent of the emerging markets and developing economies projected to have higher debt-to-GDP ratios in 2022 than in 2019 (World Bank, 2021a). At the same time, poverty rates are expected to be as high as the pre-pandemic period (World Bank, 2022d), highlighting large potential scarring effects – as poverty is linked to reduced intergenerational educational mobility (d'Addio, 2007, Black et al., 2020, Razzu and Wambile, 2022), and limited access to both high-quality jobs (Brummund et al., 2018) and family planning resources (Lee and Miller, 1990, Cavalcanti et al., 2021). Thus, continuous support to vulnerable populations poses an ever-pressing question for policy makers in the context of historically low fiscal space.

This paper studies the Brazilian case. Being the 12<sup>th</sup> largest economy of the world, Brazil is home to over 210 million, or about a third of the population in Latin America (World Bank, 2022d). Between 2019 and 2020 its GDP fell by 4.6%, and its GDP per capita by 4.1%, yet poverty in 2020 decreased due to the Auxílio Emergencial program, which cost BRL 293 billion (World Bank, 2022c). By some accounts, Brazil’s response was one of the strongest in LAC (Busso et al., 2021), and possibly one of the largest in the world (World Bank, 2022c). Nevertheless, in 2021 poverty bounced back up. The Brazilian government will thus need to substantially increase the efficiency of its spending if it is to continue helping the poor and vulnerable in a fiscally sustainable way. In this context, this paper aims to contribute to the dialogue on the possible avenues to achieve this goal by analyzing the incidence of fiscal policies in Brazil with an emphasis on their impacts on poverty and income inequality among vulnerable populations. Both the system as a whole and each fiscal policy separately are analyzed in terms of its contribution to poverty and inequality using the Commitment to Equity (CEQ) methodology (Lustig, 2018). The study focuses on a pre-pandemic year (2019) to circumvent potential data issues and represent a relatively stable fiscal situation. 0F<sup>1</sup>

> 1 The years 2020 or 2021 witnessed substantial changes in the social safety system in Brazil. The changes were, however, temporary and the emergency programs have been lifted as of 2022. The year 2019 is also preferred because there were significant changes in the data collection approach of the national household survey that was used for this analysis. For a short presentation of those changes, see Lara Ibarra and Vale (2022).

2