January 27, 2022

Introducing the “Gigabite” Index

                   

Back in 1986, The Economist newspaper introduced its inaugural Big Mac Index. The index is a light-hearted way to provide immediate and useful insights on a serious topic. That of possible international exchange rate distortions and the differing purchasing-power capabilities of different currencies. In theory, the long run exchange rates between any two countries should move towards the rate that would equalise the prices of an identical basket of goods and services (in this case, a burger) all else being equal.

A burger with some veg behind it

A Big Mac is a particularly interesting and useful product to compare across countries. Its local price to the consumer is easy to attain (just walk into a restaurant and read the menu). McDonalds has restaurants and franchises in over 100 countries around the world to facilitate international comparisons. But best of all, McDonalds prides itself on the homogeneity of its product – a Big Mac should be the same quality hamburger, whether you buy it in Shanghai or Mexico City. The production and sale of the product utilises almost wholly localised inputs, be they agricultural, logistics, labour, property rents, taxes and so on. The renowned burger is not only a tasty meal for many, it also packs in a lot of economic and financial data!

Which got me to thinking. In the telecoms sector there are arguably similar homogeneous products. Like-for-like monthly mobile call and data plans should provide similar homogenous connectivity to the Internet (a downloaded gigabyte of data is a downloaded gigabyte after all, regardless of country). The cost of those national smartphone connectivity subscriptions should also pack in a lot of information about localised operating conditions, the state of competition and economic inputs on the differing costs of factors of production such as equipment costs, infrastructure, utilities, logistics, labour costs, property rents, and taxes. High relative costs of subscription costs for basic connectivity for consumers is also one of the most important impediments to wider digital adoption and closing digital divides. Understanding the differences in relative costs would be helpful in developing digital economies.

High relative costs of subscription costs for basic connectivity is one of the most important impediments to wider digital adoption and closing digital divides. Understanding the differences in relative costs would be helpful in developing digital economies.

Nevertheless, there are differences in types of subscription agreements across countries and a variety of different services. It is not as standard as say a Big Mac or as easy to compare. Thankfully, the International Telecommunications Union (ITU) provides an invaluable service through its Measuring digital development: ICT price trends 2020 research report. The ITU team aims to standardise mobile and fixed broadband monthly subscription costs that make them comparable internationally.

In the spirit of investigation, I composed three rankings across 30 major economies based on the market exchange rate dollar conversion rate of the cost of three products (most expensive ranked 1st).

Three Rankings to Get Your Teeth Into

1) A Big-Mac. 2) Mobile phone monthly subscription (high-usage data and voice). 3) Fixed broadband monthly subscription. The results are shown below in Figure 1.

Figure 1: Comparative product prices at US$ market exchange rates 2020 / Source: The Economist, ITU

The country rankings are different across each product. The home of the Big Mac, the United States is where you will find the most expensive Big Mac in 2020 at market exchange rates. The cheapest is in South Africa. These differences are most likely a function of an unusually strong US dollar in 2020 (especially against currencies such as the South African Rand). That said, the multiple between the most expensive and cheapest Big Mac is just over 3. Chile is right on the mean value for the 30- country range (US$3.48).

For a typical monthly high usage mobile data and voice subscription, you’d have to go to India for the cheapest plan when converted to US dollars. Canada is the most expensive (the United States is fourth). South Korea is closest to the mean monthly fee (US$19). But the multiple between the most expensive and cheapest fee at 24, is much larger than that for a Big Mac, hinting at much wider differences in factor inputs and market environments.

For a standardised fixed broadband plan, the ITU suggest that the United Kingdom is the most expensive country. China is the cheapest, and Chile is closest to the mean value across the range (US$26.4). The multiple between most expensive and cheapest is 16.

Purchasing Power Parity

What’s also apparent is that the products in the advanced economies are usually more expensive across the groups. This makes sense as you would expect costs such as labour, land, property rents etc to be that much higher in those countries than in emerging markets such as Vietnam. Incomes are that much bigger too, so customers are able to pay more if pushed. Thankfully, the ITU also provide their mobile and fixed broadband connectivity prices as a proportion of national levels of Gross National Income (GNI) per capita at purchasing power parity (PPP) exchange rates. In other words, what proportion those monthly internet connectivity plans take of average monthly incomes per capita of a country adjusted for PPP. This should help stabilise comparisons considerably. The rankings are in Figure 2.

Figure 2: Mobile and Fixed Broadband monthly plans as a % of monthly GNI per capita at PPP 2020 / Source: ITU

The adjustment to level of economic development (and available household incomes) dramatically changes the rankings. Argentina now has the most expensive relative mobile voice and data plans. South Africa, Philippines, Thailand and Indonesia are all relatively high too. The advanced economies like the United Kingdom and the United States do that much better relatively. Malaysia and Mexico are the mid-ranking nations. The multiple between relatively cheapest and most expensive leaps to 29.

For fixed broadband plans, a similar story unfolds. China requires the least share of monthly income. Indonesia, Philippines and Argentina remain relatively costly to the other countries. Mexico and Malaysia are again the mid-ranking nations. The United Kingdom is proportionally almost twice the percentage share of the Euro Area. The multiple between most expensive and cheapest is 21.

But Gross National Income adjusted for purchasing power parities involves thousands of calculations and requires price gathering for hundreds of thousands of goods and services. What if we adjust simply by substituting two seemingly homogeneous products in the same country that must utilise similar inputs in the form of labour, land, property rents, infrastructure and constrained by the same average incomes? In other words, let’s introduce the ‘Big Mac Gigabite Index’ – how many Big Macs do I need to forego to pay for my monthly mobile phone subscription or fixed broadband plan? The results are in figure 3.

Figure 3: Number of Big Macs sacrificed for Mobile and Fixed Broadband monthly plans 2020 / Source: ITU, The Economist, Huawei

Based on a straight-forward substitution process in an average citizen’s monthly basket of goods and services, the results are striking. There is still wide variation in the amount of Big Macs that have to be sacrificed for a monthly mobile data and voice plan. In India, only 1 (and a crumb) need be foregone while in Argentina just over 14 are required. There is much more of a mix between developed and advanced economies. For fixed broadband, the easiest substitution appears to be in China with 1.4 Big Macs sacrificed. In the United Kingdom a hefty 16 need to be left off the dining table. Mexico, Thailand and Chile represent the mid-Giga Bite countries.

Why these sizeable differences exist certainly provides food for thought and requires more research.

Let us know what you think in the comments section.

Further Reading

Measuring the Digital Economy – It’s Harder & More Important than You ThinkEconomic Recovery: Go Digital or Go Under?

Read More

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