## background

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### Annex 1. COVID-19 in Latin America and the Caribbean
- Latin America locked down early, when total cases were still low. Lockdowns were stringent, and mobility plummeted for a while.
- Lockdowns were not fully effective; mobility started rising even before the relaxation of mobility restrictions and when new cases and deaths were still on the rise, producing a slow-burn pattern of deaths rather than a rapid explosion seen in Europe.
- Structural factors contributing to difficulties in containing the pandemic: high degree of poverty and informality, urban agglomeration, weak state capacity and lack of fiscal resources, weak health systems, and lack of tests and tracing.
- Local projection estimates: in countries with low informality/high government effectiveness, the increase in total cases 30 days after the introduction of containment measures was about 75/65 percent lower compared with similar countries that did not introduce such measures. By contrast, countries with high informality/low government effectiveness that imposed containment measures experienced an increase/no change in total cases relative to comparators.
- IMF staff analysis links high total death toll to weak hospital capacity, high population density, and in some cases, large populations and geographic location; relatively favorable demographics and BCG vaccination helped reduce total death toll in the region.
- Quantitative analysis suggests the impact of both lockdowns and self-imposed quarantines induced by rapid spread diminished over time.

Key statistical correlates of total deaths (from Annex Table 1.1; dependent variable: total deaths per million)
- Population over 70 years: Old14.8***15.7*** (2.93)(4.73)
- bCG dummy: 2117***2107*** (30.9)(47.6)
- Hospital beds per 10,000 People: 212.5214.3 (5.14)(7.10)
- Log (total population): 10.20*20.05** (2.68)(8.90)
- LAC dummy: n.s.153.2***
- R2: 0.350.27
- Number of Countries: 152124
- Number of Countries in LAC: 2217
- Note: Population density is not significant at the country level but is significant at the municipal level. Geographic latitude is significant at the municipal level (IMF 2020a). Standard errors are in parentheses. bCG = bacillus Calmette–Guérin; LAC = Latin America and the Caribbean; y = yes. *p = 0.1; **p = 0.05; ***p = 0.01.

### Annex 2. Latin American Labor Markets during COVID-19
- The pandemic has severely affected labor markets; employment losses were distributed unevenly across the population of LAC.
- Employment fell more steeply for women, especially in Brazil, Colombia, and Peru.
- Young and older workers were affected more than those between 25 and 60 years of age.
- Workers with tertiary education suffered smaller reductions in employment; in Brazil and Chile, employment levels for this group were back to pre-pandemic levels by June.
- Informal employment declined substantially; except in Colombia, informal employment fell at a higher rate than formal employment.
- The shock’s uneven impact relates to exposure differences: contact-intensive occupations are more common among women and informal workers; ability to work remotely is more prevalent among formal and high-skilled workers.
- The link between job losses and educational attainment and informality highlights the shock’s regressive nature because low educational attainment and informality are more pervasive among poor and vulnerable households.

Selected graphical notes (Annex Figure 2.1)
- Employment changes measured percent; period February to June 2020.
- Country coverage includes Brazil, Chile, Colombia, Mexico, and Peru (Peru data for Lima); Mexico changes are for June relative to the first quarter of 2020.
- Brazil age groups used: younger than age 24, 25–40, 41–60, and older than age 60.

### Annex 3. Fiscal Policy at the Time of a Pandemic: How Has Latin America and the Caribbean Fared?
- Governments in LAC announced packages of fiscal support amounting to 8 percent of GDP on average (includes above-the-line and below-the-line and off budget measures).
- Simulations based on a structural model show exceptional measures play a key role in mitigating pandemic effects.
- Effects of above-the-line fiscal measures on real GDP: increase of about 5 percent relative to the baseline without fiscal support.
- Debt-to-GDP ratio effect: increases by about 2 percentage points relative to baseline within a year.
- Effects dissipate in the medium term as stimulus is unwound and partial consolidations occur; initial boost materializes through a jump in consumption from transfers and income support, with investment providing considerable stimulus in outer years supported by monetary accommodation.
- Below-the-line and off-budget measures could add between 1 and 2 percentage points to real GDP levels.
- Combined effect of above- and below-the-line measures, if implemented fully, would raise LAC real GDP by about 6 to 7 percent within a year relative to the counterfactual.

Policy guidance and recommendations highlighted
- As lockdowns are gradually lifted and uncertainty persists, fiscal actions could focus on gradually scaling down lifelines.
- Broad-based fiscal stimulus could support recovery when there is fiscal space, but additional support should be conditional on a clear commitment to adjustment over the medium term to restore sustainability.
- Fiscal rules will play an important role.
- Passing legislation to ensure fiscal consolidation over the medium term (such as preapproval of tax reforms) would help as a commitment device.
- Enhancements to automatic stabilizers and safety nets would strengthen a more inclusive recovery.

Selected simulation notes (Annex Figure 3.1)
- Panels include: LAC effects of above-the-line measures (real GDP level percent difference; government debt percent of GDP difference) and effects of below-the-line and off-budget measures on real GDP growth (percentage points).
- Time labels include years 2019, 2020, 2021, 2022, 2023, 2024, 2025 in model horizon.
- Components mentioned: Total, Contingent liabilities and other, Below the line.

### Annex 4. Assessing the Impact of the COVID-19 Pandemic on the Corporate and Banking Sectors in Latin America
- COVID-19 has large negative effects on the nonfinancial corporate sector in LAC. Corporate performance was weakening before the pandemic, with falling profitability and increasing leverage.
- Corporate performance worsened further in Q2 2020 and is expected to remain weak for the rest of 2020 and in 2021.
- Share of corporate debt at risk (debt of firms with earnings before taxes and interest lower than interest expense) rose from 14 percent in December 2019 to 29 percent in June 2020, and could rise to near 50 percent in 2021 in an adverse scenario in which corporate earnings do not grow and interest expenses increase in line with the rise in corporate debt.
- LAC banks entered the pandemic with ample capital and liquidity buffers and low nonperforming loans. Financial soundness indicators worsened somewhat in H1 2020, but the impact has been moderate so far, reflecting financial sector policies that mitigate bank balance sheet stress.
- IMF performed forward-looking top-down solvency stress tests for WEO baseline and adverse scenarios using publicly available data for a sample of 61 major banks in the six largest economies in LAC, covering over 75 percent of bank assets in each jurisdiction.

Key stress-test findings
- Under the WEO baseline scenario, most LAC banks would maintain capital ratios well above regulatory minimums, even under higher responsiveness of nonperforming loans and profitability than historical standards.
- Under the WEO adverse scenario, weaker banks with high nonperforming loans and low profitability at the pandemic onset would face significant deterioration in capital positions; some could experience capital shortfalls without a policy response.

Selected vulnerability indicators (Annex Figure 4.1)
- Corporate leverage (median of nonfinancial corporations of Argentina, Brazil, Chile, Colombia, Mexico, and Peru) shown as debt to assets percent.
- Capital adequacy ratio and CET1 distributions presented for Brazil, Chile, Colombia, Mexico, Peru, Uruguay; sample counts by jurisdiction noted (e.g., 56 banks, 5 banks, 18 banks, 21 banks, 22 banks in panels).
- Note: CET1 = common equity Tier 1; EME = emerging market economies. Shaded ranges refer to percentiles where indicated.

*International Monetary Fund | October 2020*

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_Source: https://www.imf.org/-/media/files/publications/reo/whd/2020/oct/english/background.pdf_