The Big Mac Index - Global Marketing Professor

Based on the early presentations in class, this is my obligatory food focused post. As with any economic index, the goal is to accurately measure purchasing power based on an identical “basket of good”. McDonalds has locations in 120 countries, which makes its signature burger the ideal product to compare the price of from place to place. Developed in 1986 by The Economist magazine, what originally was a humorous parody of other economic forecasting tools has been noted as quite accurate by expert economists.

The main purpose of the Big Mac Index is to compare purchasing power between nations. It also serves investors as a raw tool to determine which country may have an undervalued currency. These investors will compare the difference in pricing of Big Macs in each location with the actual exchange rate between currencies. For example, if a burger in China costs 9.84 yuan and costs $2.75 in the United States, the Big Mac Index would view the exchange rate as far as buying power goes should be appropriately 3.59 yuan for each US dollar. If in reality the exchange rate is 6.05 yuan per US dollar, this suggests that the yuan is undervalued by about 40% (6.05-3.59)/6.05.

Currently, Switzerland is topping the charts with an average Big Mac price of $8.17, while Taiwan brings up the bottom at $2.39. Based on current data, European nations trend towards higher pricing with Asian countries showing low prices. Currently, the United States ranks 8th with a price of $5.69. This topic seemed interesting as California recently passed a minimum wage increase to $20 per hour. With the change I was curious to see if this had any effects on the US benchmark for the scale. As of yet, it does not look like this has made enough of an impact to move the needle. Overtime, it will be interesting to see if more minimum wage movements cause this to change and the US to move up more spots on the Big Mac Index. I recommend checking out the index for yourself below. You can check out historical data as far back as 2000!