Currency valuation: Liquidity and the Big Mac Index
The problem with a Masala Dosa index, or a Big Mac Index, or even a Butter Chicken index, is that whatever food item we choose, it is likely to be much more liquid in its home market
One of the most popular trackers of relative values of currencies around the world is the Big Mac Index (mintne.ws/1GdLDM3 ). Introduced by The Economist magazine in 1986, this index is used as a barometer for different under- or overvalued currencies. The concept is rather simple—all over the world the Big Mac hamburger uses pretty much the same ingredients, and hence the cost of the Big Mac around the world should be pretty much the same (there is an adjustment factor in terms of per capita gross domestic product that accounts for differences in labour cost). Thus, comparing the dollar prices (at current exchange rates) of the Big Mac in different countries, we can estimate which currencies are under- or overvalued, and by how much.
For example, going by the latest edition of the Big Mac Index published in January, the rupee is undervalued by about 30% against the dollar. In other words, the number of rupees required to purchase one dollar should be 30% lower than what it is today, or about 42 rupees to the dollar. According to the same index, back in mid-2011 (the index is calculated twice a year), the rupee was only 10% undervalued against the dollar.
There are several shortcomings with the Big Mac Index, with the most glaring one being that it is rather simplistic. In fact, The Economist explains, “Burgernomics was never intended as a precise gauge of currency misalignment, merely a tool to make exchange-rate theory more digestible. Yet the Big Mac index has become a global standard, included in several economic textbooks and the subject of at least 20 academic studies.” Yet, the widespread adoption of the Big Mac Index indicates that it is perhaps ok to subject it to rigorous analysis. We look at the index from the point of view of liquidity.
Liquidity is that concept in economics (more often used in financial economics than otherwise) that studies markets as a function of the number of buyers and sellers at a particular point in time. The more the number of buyers and sellers, the more likely that a deal can be reached, and the more likely that an individual buyer or seller can get a good price for their goods. If there are few buyers in a market, the seller is uncertain of selling his wares, and thus includes a risk premium in the price that he wants to charge for his wares (to account for damages he suffers in case he is unable to sell), leading to a higher price. When there are more potential buyers, however, the seller can set a lower risk premium which leads to a better price for all buyers, and potentially higher transactions.
This is best illustrated in financial markets where markets that are liquid (or have a large number of buyers and sellers) often have a low bid ask spread (price difference between what buyer is willing to pay and what seller is willing to accept). In other words, a more liquid market imposes lower transaction costs on participants, leading to more certainty in prices and greater volume of transactions.
Where does liquidity come into play while calculating the Big Mac Index? To understand this, let us study another food item that is a commodity in large parts of India—the Masala Dosa. Now, the cost of ingredients of a Masala Dosa (rice, urad dal, potato, salt, chillies, etc.) does not vary widely across different parts of the country. In fact, relative to the price of the Masala Dosa, the variation in costs across different parts of the country is rather insignificant.
Beyond a point, it can be argued that the amount of skill involved in making a Masala Dosa is also not too high (this point is definitely debatable but still a reasonable assumption), and thus the cost of labour in making the Dosa should not vary much by location. Yet we find that the price of a Masala Dosa in Bengaluru or Chennai (where the dish is consumed widely ) is much lower than at a comparable establishment in Delhi, for example (where the dish is not as popular). What gives?
The answer lies in liquidity. The market for Masala Dosas in Bengaluru and Chennai are liquid in that there are a large number of buyers and sellers for the food item at any point in time. Drawing an analogy from financial markets, this implies that the bid ask spread for Masala Dosas in these cities is low, or that the price charged by restaurants is close to the fair price of the dosas.
In Delhi, on the other hand, where both demand and supply are lower, the demand for Masala Dosa in a particular establishment is more volatile, which means that the seller of a Masala Dosa in a Delhi restaurant is much less certain of clearing his inventory compared with a seller in Bengaluru. Consequently, to cover for the volatility, the Delhi restaurant applies a risk premium in the price of the Masala Dosa, which means that prices in Delhi are going to be higher.
Apart from the above financial reason, there are operational reasons (again tied to liquidity) that lead to prices in Delhi being much higher than prices in Bengaluru.
The Masala Dosa requires a hot wok for preparation. Most good restaurants keep the wok perennially heated up (whether there are dosas being cooked or not), and this is a fixed cost in the preparation of the dosas. In restaurants in Bengaluru or Chennai where volumes are high, the utilization of the wok thus kept heated up is high, perhaps close to 100% at certain times of the day. In Delhi with lower volumes, utilization is much lower. And that leads to further widening of the price between Bengaluru, Chennai and Delhi.
Coming back to the Big Mac Index, the problem with the index is that it assumes that the price of the Big Mac in different countries is a function of the cost of preparation. What it ignores is that there is significant difference in market conditions across countries, which has a pretty wide impact on the Big Mac. For example, in the US, the Big Mac is a pretty common item, and McDonald’s are everywhere. In other words, it is a rather liquid item and thus has a low bid-ask spread.
In a place like India, on the other hand, the demand for a Big Mac is much lower, or it is rather illiquid. The liquidity doesn’t stop at the final product also. Even some of the ingredients of the Big Mac, such as the minced meat or the lettuce, have different levels of liquidity in different countries. This adds to the liquidity premium of the Big Mac in countries such as India.
What then is the solution? Should we use a Masala Dosa index instead of a Big Mac Index (Saravana Bhavan is present in several countries, for example)? Or perhaps a butter chicken index? The problem with any such index is that whatever food item we choose, it is likely to be much more liquid in its home market than in markets abroad, and we inevitably end up with a skewed index.
Footnote: McDonalds doesn’t sell the Big Mac in India, given local sensitivities towards beef. Instead, The Economist uses the Maharaja Mac (which has chicken instead) as India’s entry to the Big Mac Index.
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