Six years of formally registered jobs in Brazil, from the pandemic collapse to the 2025 slowdown, and what the forecasts and the debate over ending the 6×1 work schedule signal for formal employment through 2027.
Brazil's formal employment is in a phase of decelerating expansion: it still adds jobs every month, but at a slower pace than at the peak of the post-pandemic rebound.
The recovery was real, but it ran out of steam. Between Jan/2020–Mar/2026, the cumulative balance reached 10,006,260 net formal jobs. Over the last 12 months the country created 1,211,827 formal jobs, versus 1,554,585 in the previous 12 months, a change of -22.0% that confirms the loss of traction amid high interest rates and costlier credit.
From the free fall of 2020 to the recent normalization: the monthly series tells the country's economic story better than any headline.
Apr/2020 is the bottom. In the first shock of the pandemic, the country shed -902,317 formal jobs in a single month, the worst result in the series. A V-shaped recovery followed, with record balances in 2021 and 2022 as the economy reopened.
Since then the moving average has settled into a positive plateau: Brazil keeps creating jobs, but momentum cooled in 2024–2026. The sawtooth pattern that recurs every year is not noise; it is seasonality, and it has a sectoral signature, as we will see.
Formal job creation is deeply concentrated. The Southeast accounts for about 41% of the recent balance, and São Paulo alone for 24%.
Explore each state's series and forecast:
The average balance per month reveals an annual clock: the country hires in the first half and during harvests, and lays off in December. Retail and services set the rhythm.
This pattern is dominated by labor-intensive sectors and full-time contracts, precisely those at the center of the debate over the 6×1 schedule. That is what we turn to next.
Five models, SARIMA, ETS (Holt-Winters), Seasonal Naive, Random Forest and LightGBM, project the series through June 2027. The one selected by validation was Seasonal Naive.
The central reading is seasonal stability, not acceleration. For Jun/2027 the model projects a balance of 166,654 jobs, with a 95% interval between -200,211 and 533,519, a width that reflects the strong seasonality and the heteroskedasticity (unstable variance) detected in the series.
The proposal to replace the 6×1 schedule (six days of work, one of rest) with 5×2 is mobilizing Congress and the streets. What the CAGED microdata say about who would be affected, and what to expect.
What is at stake. The 6×1 schedule organizes the week into six workdays and one rest day, typically adding up to the 44 weekly hours allowed by the Constitution. The constitutional amendment to end 6×1 proposes capping the week at five days (5×2) and reducing hours, with no pay cut. It is the biggest debate over working time in the country since 1988.
Hiring data show that the 44-hour week is the norm, not the exception: about 81% of all formal hires since 2020 were agreed at the constitutional ceiling. Cutting the schedule therefore hits the modal contract of the Brazilian labor market.
But exposure is uneven across sectors. The map below crosses how dependent on a 44h week each sector is (horizontal axis) with how much employment it generates (vertical axis).
The most exposed are also large employers. Sectors such as Agropecuária, Construção, Comércio e reparação and Indústria de transformação combine heavy dependence on the 44h week with significant job creation. Sectors above the average exposure account for about 64% of recent formal hiring; in other words, the reform falls precisely on the engine that hires the most.
| CNAE | Sector | % at 44h | Balance 12m | Hires 12m |
|---|---|---|---|---|
| A | Agropecuária | 96% | -716 | 1,213,989 |
| F | Construção | 95% | 111,091 | 2,493,025 |
| G | Comércio e reparação | 90% | 226,533 | 6,214,111 |
| C | Indústria de transformação | 89% | 75,465 | 3,680,512 |
| H | Transporte e armazenagem | 87% | 94,338 | 1,454,659 |
| E | Água, esgoto e resíduos | 87% | 14,168 | 161,557 |
| L | Atividades imobiliárias | 85% | 5,585 | 93,904 |
| I | Alojamento e alimentação | 84% | 82,647 | 1,684,840 |
There is no consensus, and the final effect depends on the design (size of the cut, transition period, offsets). We cross the most-discussed scenarios with peer-reviewed economic literature (numbered at the end):
Productivity per hour tends to rise when long shifts are cut: in empirical data output grows less than proportionally to hours1,2, and compressed schedules raise satisfaction and work attitudes4. There are also health and sleep gains from reducing long shifts7,8.
It raises the hourly cost in labor-intensive sectors (retail, food service, services); employers tend to react by adjusting base pay and hours5. France's 35-hour experience did not produce a robust positive effect on employment3, suggesting caution about automatic job gains.
Reorganization of shifts, hour banks, more part-time shifts and 5×2 hires at 40h4,6. The burden would fall on the sectors in the right-hand quadrant of the map above, those with the greatest 44h exposure.
A transition would change the level and seasonality of the series, a structural break. The forecasts in this report serve as a baseline (the “no reform” scenario) against which to measure the effect.
References located by the paper-lookup scientific search protocol (k-dense scientific-agent-skills) via OpenAlex, with no fabrication: each item has a verifiable DOI.
An economic and exploratory analysis based on the composition of formal hiring. CAGED records contracted hours, not the number of days worked; 44h is used as a proxy for the 6×1 universe. The cited evidence comes from institutional contexts different from Brazil's and should not be read as a forecast of the amendment's effect, nor as advice.
Recent balance, selected model, forecast for Jun/2027 with confidence interval and diagnostics by state. Click the headers to sort.
| State | Name | Balance 12m | Model | Forecast Jun/27 | 95% CI | Seas. | Heter. |
|---|---|---|---|---|---|---|---|
| RO | Rondônia | 7,199 | SARIMA | 984 | -1,981 a 3,949 | 0.67 | yes |
| AC | Acre | 4,289 | Seasonal Naive | 605 | -364 a 1,574 | 0.80 | no |
| AM | Amazonas | 18,520 | SARIMA | 3,735 | -1,054 a 8,524 | 0.58 | yes |
| RR | Roraima | 1,402 | Random Forest | 226 | -2,681 a 3,133 | 0.61 | no |
| PA | Pará | 30,876 | SARIMA | 6,258 | -1,308 a 13,825 | 0.85 | yes |
| AP | Amapá | 6,042 | LightGBM | 1,123 | -1,598 a 3,845 | 0.69 | yes |
| TO | Tocantins | 4,731 | Seasonal Naive | 513 | -1,368 a 2,394 | 0.84 | yes |
| MA | Maranhão | 30,316 | Seasonal Naive | 6,247 | 1,867 a 10,627 | 0.78 | yes |
| PI | Piauí | 20,923 | Random Forest | 2,746 | -5,342 a 10,834 | 0.73 | no |
| CE | Ceará | 55,335 | Seasonal Naive | 7,320 | -4,947 a 19,587 | 0.70 | no |
| RN | Rio Grande do Norte | 16,184 | Random Forest | 2,278 | -10,166 a 14,722 | 0.80 | yes |
| PB | Paraíba | 28,390 | SARIMA | 2,434 | -1,644 a 6,511 | 0.80 | no |
| PE | Pernambuco | 73,554 | Random Forest | 6,316 | -30,150 a 42,782 | 0.82 | yes |
| AL | Alagoas | 16,347 | SARIMA | 2,394 | -3,286 a 8,075 | 0.86 | yes |
| SE | Sergipe | 18,526 | Seasonal Naive | 2,407 | -485 a 5,299 | 0.82 | yes |
| BA | Bahia | 87,732 | Random Forest | 9,207 | -40,334 a 58,749 | 0.52 | yes |
| MG | Minas Gerais | 72,941 | SARIMA | 28,572 | -21,987 a 79,132 | 0.74 | yes |
| ES | Espírito Santo | 18,230 | Seasonal Naive | -3,348 | -12,089 a 5,393 | 0.65 | yes |
| RJ | Rio de Janeiro | 113,440 | Random Forest | 12,776 | -86,566 a 112,119 | 0.44 | yes |
| SP | São Paulo | 288,486 | SARIMA | 49,375 | -80,240 a 178,991 | 0.64 | yes |
| PR | Paraná | 75,469 | Seasonal Naive | 9,377 | -15,893 a 34,647 | 0.75 | yes |
| SC | Santa Catarina | 52,795 | SARIMA | 8,199 | -18,353 a 34,751 | 0.68 | yes |
| RS | Rio Grande do Sul | 28,211 | Random Forest | 584 | -62,261 a 63,428 | 0.67 | yes |
| MS | Mato Grosso do Sul | 20,922 | Seasonal Naive | 2,709 | -2,372 a 7,790 | 0.84 | yes |
| MT | Mato Grosso | 27,718 | Seasonal Naive | 9,388 | 1,939 a 16,837 | 0.96 | yes |
| GO | Goiás | 43,169 | SARIMA | 8,033 | -8,038 a 24,103 | 0.77 | yes |
| DF | Distrito Federal | 50,080 | SARIMA | 5,833 | -2,102 a 13,769 | 0.69 | yes |