The Economist

The dataset has brought under the license: This software is published by [The Economist](https://www.economist.com)_ under the [MIT licence](https://opensource.org/licenses/MIT). The data generated by _The Economist are available under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).

Data cited at: The Economist THE Big Mac index was invented by The Economist in 1986 as a lighthearted guide to whether currencies are at their “correct” level. It is based on the theory of purchasing-power parity (PPP), the notion that in the long run exchange rates should move towards the rate that would equalise the prices of an identical basket of goods and services (in this case, a burger) in any two countries. For example, the average price of a Big Mac in America in January 2018 was $5.28; in China it was only $3.17 at market exchange rates. So the "raw" Big Mac index says that the yuan was undervalued by 40% at that time.

The Economist has devised a “normalcy index” to track how behaviour has changed, and continues to change, because of the pandemic. Index comprises eight indicators, split into three domains. The first grouping is transport and travel: public transport in big cities; the amount of traffic congestion in those same cities; and the number of international and domestic flights. The second looks at recreation and entertainment: how much time is spent outside the home; cinema box-office revenues (a proxy measure for cinema attendance); and attendance at professional sports events. The third is retailing and work: footfall in shops; and occupancy of offices (measured by workplace footfall in big cities). Index covers 50 of the world’s largest economies which together account for 90% of global GDP and 75% of the world’s population. Our aggregate measure is the population-weighted average of each country’s score. The pre-pandemic level of activity is set at 100 for ease of comparison. The tracker is updated with new data once a week.

This data has been collected, cleaned and analyzed by  James Tozer  and  Martín González .

The dataset has brought under the license: This software is published by [The Economist](https://www.economist.com)_ under the [MIT licence](https://opensource.org/licenses/MIT). The data generated by _The Economist are available under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).

The dataset has brought under the license: This software is published by [The Economist](https://www.economist.com)_ under the [MIT licence](https://opensource.org/licenses/MIT). The data generated by _The Economist are available under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).

The dataset has brought under the license: This software is published by [The Economist](https://www.economist.com)_ under the [MIT licence](https://opensource.org/licenses/MIT). The data generated by _The Economist are available under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).   Data details: A file containing the pairwise correlations between simulated state-level Biden vote shares across all of the model's simulations. The column and row names correspond to each state.

The dataset has brought under the license: This software is published by [The Economist](https://www.economist.com)_ under the [MIT licence](https://opensource.org/licenses/MIT). The data generated by _The Economist are available under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/).   Data contains: A file containing our model's most recent simulations for what could happen on election day.