Purchasing power or how much is your money worth?

Suppose that you earn $50,000 or its equivalent. How much is this amount exactly worth? What can you buy from it? The answer of course differs by country, matter of fact it differs by state and by city. The more you can buy from a dollar, the more purchasing power your money is said to have. Therefore, purchasing power is an important measure of economic well-being.

I have always argued that while GDP may be a good measure of economic activity, it doesn’t necessarily say that much about the quality of life. One very simple metric that I believe could shed more light on this question is simply quantifying how many “things” you can buy from an average salary in a given country. I will attempt to do just that in this post.

Carrying out this exercise is easy in principle. At first, I’d have to identify a product that is roughly identical all over the world, is mostly locally sourced (so that its price will depend on local costs) and whose price is dependent on key sectors of the economy. Luckily for us, The Economist already identified such a product: the Big Mac. Does it really fit the description? Well, kind of. I mean the Big Mac is identical and is mostly locally sourced (its most substantial input is probably labor), furthermore its price will depend on the prices of food/groceries and services, both important sectors. The Big Mac is therefore often considered an ideal proxy for the general price level in an economy. (For a critical evaluation of this statement see the “Methodological appendix” at the end of the post.)

So the idea is to look at average wages in each country and see how many Big Macs you could buy from an average annual wage. Seems simple enough and if the Big Mac really reflects general price levels, the results will also be quite informative. Here are the results:

Purchasing power by country, chart

Purchasing power by country, table

So in this table 100BM is how many hundreds of Big Macs an annual average salary could buy, GDPpc is GDP per capita (PPP), RankDiff is the difference in the country’s ranking in GDPpc and 100BM (negative numbers indicate that a country’s GDP figure overestimates its citizens’ purchasing power), BMDev is the percentage by which a country’s 100BM figure is different from the average, GDPDev is the percentage by which a country’s GDPpc figure is different from the average and DevDiff is the difference between BMDev and GDPDev (the lower this number the more GDP overestimates the purchasing power of an average citizen in the given country).

We can see that if we are interested in knowing how much purchasing power an average person has in a given country, GDP per capita figures are not what we should turn to (even if they are corrected for PPP). Countries whose citizens’ purchasing power is grossly underestimated by regular GDP figures include Australia, Japan, the UK and Denmark. On the other hand, countries whose citizens’ purchasing power seems to be substantially overestimated include Norway, the Czech Republic and Sweden.

To get the best bang for your buck, you should consider relocating to Australia, the United States, Japan or Switzerland. On the other hand, you should probably try to avoid working in the Czech Republic, Hungary or Poland. What must be emphasized here is Australia’s performance. Australians have a 16% higher purchasing power than Americans who come in second. Meaning that not only is Australia the #1, they are so by a huge margin. The chart above also visualizes this.

All of the above applies to those earning the average salary. But what about the rest of society? Consider performing the same exercise as above but now for minimum wage earners:

Purchasing power of minimum wage earners, chart

Purchasing power of minimum wage earners, table

(due to the lack of federally/centrally mandated minimum wages certain countries are missing from this data)

GDP figures grossly underestimate the well-being of minimum wage earners in Australia, Japan, France, the Netherlands, Belgium, the UK and Ireland. They, however, grossly overestimate the well-being of minimum wage earners in the United States, the Czech Republic, Estonia, Hungary and Spain.

An interesting way to interpret these results is the following: minimum wage earners in the United States have a considerably worse purchasing power than the average citizen of an Eastern European country does (here this means Czech Republic, Hungary or Poland). The Australian living on minimum wage lives like an average citizen in Greece or Spain (well kind of in-between). Or a person on minimum wage in Ireland lives like an average citizen of Estonia. And so on.

In general, if your salary is expected to be close to the minimum wage because you do unskilled labor or similar, then you may want to consider relocating to Australia, the Netherlands or Ireland. You should, however, still avoid countries like Estonia, Hungary and the Czech Republic. The U.S. minimum wage earner may only do marginally better by relocating to Canada, however relocating to Australia, the UK or Ireland is something one should seriously consider. It could substantially improve the quality of life of an American living on minimum wage and it is perhaps not as unrealistic as relocating to say the Netherlands, because there are no language barriers.

If we calculate what percentage of an average-salary-guy’s purchasing power a minimum-wage-guy has (i.e. minimum wage purchasing power relative to average wage purchasing power; this is the column called Gap), then we pretty much reconstruct the OECD’s “Minimum relative to average wages” statistic. But there are some differences. The result is that there is more inequality (in terms of purchasing power) in countries like Estonia, the United States, Hungary, while countries like France, Belgium and Poland are much more egalitarian (especially France, whose minimum-to-average gap is 12% lower than Belgium’s, which comes in second). In roughly the middle of the spectrum lies the UK, Japan and Korea.

A graph constructed from this data looks like this:

Inequality across countries, purchasing power-based

Methodological appendix:

All these results are, however, highly dependent on one assumption: that the Big Mac is a good measure of the general local price level. At the beginning of the post I argued that the Big Mac was originally chosen as a purchasing power indicator by The Economist because it is (i) a globally identical product, (ii) locally sourced and (iii) its price reflects costs in various important economic sectors.

However, I would argue that while the Big Mac may be physically identical across countries, in various other aspects it isn’t. Where the Big Mac may differ from country to country is its market positioning. Is it a mass product or a luxury/premium product? Countries where people eat a lot more fast food will have

  1. more fast food restaurants that are McDonald’s competitors, and
  2. higher demand for Big Macs.

Both of these will act to push the price of Big Macs down. No one can possibly believe that fast food is equally popular in all the countries in the list above. So much for point (i).

How about point (ii)? Is Big Mac locally sourced? I would argue it mostly is. As far as I know, most Big Mac ingredients are sourced from local manufacturers (who are licensed by McDonald’s). I am not 100% familiar with this though. One may argue that countries where fast food is less popular will have fewer restaurants. Fewer restaurants will make it less profitable for McDonald’s to license ingredients manufacturers in the area. Fewer licensed manufacturers will mean that ingredients may perhaps have to be shipped from plants that are farther away from the restaurants on average, maybe even from abroad. In any case, this would drive up transportation costs. But if the source is abroad, then it would destroy the locally sourced assumption as well.

One may think about the Eastern European countries that are at the bottom of the list. I don’t know how popular fast food is in these countries but if it isn’t overly so, then it may be that McDonald’s restaurants in those countries actually ship ingredients from neighboring richer countries like Germany where there may be more restaurants and thus licensed manufacturers. This would of course completely distort their price structure.

Finally, consider point (iii). I would say there is at least one very important economic sector whose costs may not influence Big Mac prices: property prices. One may argue of course that restaurants are rented as well, so if rental prices are high in a country this will drive up Big Mac prices. I am not convinced though that rental prices get passed through in this manner and that they significantly influence Big Mac prices.

Property prices and rents are a quite often the largest portion of one’s budget. And there are stark differences between countries. So if the price of renting a property does not get included (significantly) in the Big Mac’s price, then an important potential difference in purchasing power across countries gets ignored.

With these caveats in mind, take this ranking with a grain of salt. Despite the possible shortcomings, however, I believe (and this is based purely on personal judgment) that the ranking of the countries is more or less correct. The differences may not be as big as the data suggests, though.

Also note that this is not a measure of economic performance. I.e. this “BM100” metric is not an alternative to GDP. GDP implicitly takes into account other important variables such as unemployment, BM100 doesn’t. BM100 may, however, provide a more accurate answer to the question: in which country could you live better provided that you have a job and that you spend most of your income within the country.

Sources: The Economist for Big Mac prices (full dataset downloadable at the bottom of the page; January 2012 data used for average wages, January 2013 data used for minimum wages), OECD Statistics for average annual wages (2011 data used at current prices) and for minimum wages (2012 data used at current prices), this page for the nice flag pictures on the chart.

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