Mexico inflation calculator
Consumer prices in Mexico rose 67.0% between January 2015 and August 2026. 100 in January 2015 has the buying power of 167.0 in August 2026, an average of 4.5% a year.
100.00 in January 2015 has the buying power of 166.98 in August 2026.
- Price change
- 67.0%
- Per year, compounded
- 4.5%
- Conversion factor
- 1.6698
What 100 from each year is worth in August 2026
| From | 100 then, in today's prices | Price change | Conversion factor |
|---|---|---|---|
| January 2015 | 167.0 | 67.0% | 1.6698 |
| January 2016 | 162.7 | 62.7% | 1.6273 |
| January 2017 | 155.4 | 55.4% | 1.5541 |
| January 2018 | 147.2 | 47.2% | 1.4723 |
| January 2019 | 141.1 | 41.1% | 1.4107 |
| January 2020 | 136.6 | 36.6% | 1.3665 |
| January 2021 | 132.0 | 32.0% | 1.3198 |
| January 2022 | 123.3 | 23.3% | 1.2327 |
| January 2023 | 114.2 | 14.2% | 1.1423 |
| January 2024 | 108.9 | 8.9% | 1.0891 |
| January 2025 | 105.1 | 5.1% | 1.0515 |
| January 2026 | 101.3 | 1.3% | 1.0130 |
Questions
How does the Mexico inflation calculator work?
It divides Mexico's consumer price index in the month you convert to by the index in the month you start from. That ratio is the conversion factor: multiply any amount by it to restate the amount in the other month's prices. The index is the national, all-items CPI as republished by ILOSTAT, the International Labour Organization's statistics service, under CC BY 4.0.
How much has money lost its value in Mexico?
Consumer prices in Mexico rose 67.0% between January 2015 and August 2026. 100 in January 2015 has the buying power of 167.0 in August 2026, an average of 4.5% a year.
Can I use the conversion factor for IAS 29 restatement?
The conversion factor is the ratio of two general price index levels, which is the arithmetic IAS 29 restatement uses. Which index to use, and whether the standard applies at all, is a judgement for the reporting entity and its auditor. This page is not accounting advice.
Why does the calculator start in 2015?
The monthly series we hold starts in 2015. Older months are left out rather than estimated.
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