After reading my posts on the international arms trade, a friend thought I might be interested in some data on the international trade in fish. While I know almost as little about fish as about arms, I always welcome good data. The data in question is published by the Food and Agriculture Organization (FAO) of the United Nations. The FAO also hosts FAOStat, which looks like an interesting data repository. If I can get myself a subscription to this service, it may provide the subject matter for future posts on the Mule.
But back to the fish. The first point my correspondent made was that many fish exporters are also importers. Among the top 50 importers of fish, all but 16 countries also appear in the list of the top 50 exporters. The chart below* gives an indication of the relative scale of fish imports and exports in 2006 of the top 10 importing countries. Of these big importers, only China and Denmark export even more fish than they import.
Fish Trade by the Top 10 Importers (2006)
But the real mystery my fishy correspondent alerted me to is the difference between total worldwide imports and exports of fish. According to the figures, total worldwide imports of fish amounted to US $89.6 billion while exports only amounted to US $85.9 billion. That would appear to mean that US $3.7 billion worth of fish was imported in 2006 from nowhere! While I am sure that statistics of this kind may not be too accurate, the report does report each country’s trade figures to the nearest US $1000, so it seems to be a big difference. I speculated that some countries were not admitting to exporting whale meat to Japan, but my correspondent pointed out that whales are not fish. While the US Supreme court has ruled that tomatoes are vegetables, I do not know their view on whales, and this is probably not the answer anyway. Any theories out there, readers?
At the suggestion of singingfish, I will be making available the code used to produce charts here on the Stubborn Mule. Most of the charts are produced using the R statistical package, which is free and open-source. R can be downloaded here. The data and code for the chart above is here. I will gradually add the code for charts from older posts as well.
UPDATE: I forgot to mention that my correspondent also suggested fish rain as an explanation. I, however, am not convinced. Regardless of the original source, I am sure most countries would treat fish rain as a natural bounty rather than an import.
* Tip for reading the chart: there is no label on the right hand side for the USA and no label on the left for Denmark, but following the lines should make it obvious where they would be if there was room.
Possibly Related Posts (automatically generated):
- The Big Arms Traders (1 August 2009)
- The Arms Trade (27 July 2009)
- How Important Is China? (25 August 2009)
- Junk Charts #4 – Puns are dangerous (31 August 2010)
Maybe the discrepancy is related to this incident:
Thanks for posting the R code! Great blog
Interesting theory! If only the FAO accounted for fish imports from ospreys and other bird-life. Perhaps albatrosses and pelicans are also contributors.
The $3.7B could be round-off errors added up? Profit margin? It’s what, 4% error? Sounds pretty good for official statistics.
Rounding? Stil! Where’s the fun in that? Of course, you are probably correct. It does mean that if the error at the aggregate level is 4%, the average error at each country level must be bigger than that (or there’s a consistent bias, which still leaves something to explain). If that’s the case, then quoting figures in billions of dollars to the nearest $1000 is surely a triumph of precision over accuracy.
Oh quoting to five or six significant figures is complete rubbish, of course. But does not standard accounting practice consider that an actual expenditure being within 5% of a budget counts as “on budget”? As I say, 4% margin of error doesn’t seem too bad to me.
Stilgherrian: So often, truth lies in the mundane not the conspiracy, so appealing to some version of Hanlon’s razor, I will concede your answer is almost certainly correct.
Could a proportion of the error be attributed to the illegal fish trade?
Have you taken the interplanetary fish trade into account?
More plausibly, delays between exporting and importing may interact with foreign exchange rates. Or perhaps there’s some value-adding being done by processing in transit, or in “off-shore” processing plants?
Illegal fish trade wouldn’t appear in the statistics at all. My guess is tax evasion: exporters have an incentive to under-report the volumes and/or prices of their exports, while importers do not (or may even have the reverse incentive if they can claim deductions for costs). As a result measured exports are less than measured imports.
Oh, and kudos to Sean for posting the R codes on Github.
Yes, I do like the tax theory! There should be another razor/law for that: never attribute to X what can be attributed to tax avoidance (need to work on the X).
@Danny The anomaly is consistent through the three years, so I think we can rule out FX rate variation across timing differences.
@singingfish On second thoughts, illegal fishing might be a possible explanation if certain fish are illegal to export in some countries but legal to import in others. It seems unlikely it would add up to such a huge sum though, since the import reporting would attract attention from the exporting country authorities.
Mark’s tax evasion explanation seems most compelling. I’m curious now about the mechanics of the trade, though – the statistics are fascinating, but hide a lot.
Sean I would imagine there are a few factors relating to intermediary costs. If the value to the exporters is the price FOB the cost to importers will be greater because of shipping and insurance. Another leakage would be FX intermediaries spread (as most imports need to be paid in foreign currency.) Another would be the cost of refrigeration and examination at the receiving dock. I wonder if this is typical for trade statistics generally?
The variation of “truth lies in the mundane not the conspiracy” is always, having many years of government service, “always go for cock-up over conspiracy” it is far more likely….now having seen the Hanlon’s razor entry in Wikipedia I can see that I’m not alone!
It’s clearly high speed computerised fish arbitrage at work. Morgan Stanley and Goldman Sachs have recently built fish transfer centres as close as possible to the Tokyo Fish Exchange, and regularly move thousands of tonnes of fish out of and back into Tokyo in milliseconds, making enormous trading losses (which is why the total fish value appears to have increased) and arranging government intervention to pay multi million dollar directors bonuses! _Brilliant!_
Tim: “cock up over conspiracy” does have a better ring to it.
bigiain: if there’s a bubble in fish, we all know Goldmans will be there to exploit it!
Well, dolphins use bubbles to catch fish… And we all know about the dolphins. So I think this supports my interstellar fish trade hypothesis.
Interestingly, the same phenomenon does not seem to occur for beer (that’s “beer of barley” not “beer of sorghum”). In 2006 total world imports were US$8.99 billion, slightly lower than total exports of US$9.06 billion. And, of course, there are bubbles in beer.
Great post! I am new to R, so I hope you have a minute to help me out. I want to learn R by working through examples, and this is a great one. When you read in the data, what does the as.is =c(1,4) do? Are you only reading in 5 columns? I haven’t seen any reference to as.is before, at least I dont believe I have.
Brock: happy to help on your R journey. By default, when R reads data into a data frame, it performs type conversions on the original character data. Data that looks numeric is converted to a numeric data (which is fine), but other character data is converted to factors and in my case I wanted to keep the country names in the file as characters. The as.is argument of read.csv over-rides the conversion. So, when I set as.is = c(1,4) it meant that no conversion was performed on columns 1 and 4 of the data. For more info, you can type ?read.csv into R and it will bring up the full help details.
thanks for running with this one sean. i was listening to a radio national podcast earlier today: http://www.abc.net.au/rn/rearvision/stories/2009/2590761.htm and it describes in quite depressing – and graphic terms – how the rise rise of superior technology met the tragedy of the commons and lead to over-fishing.
the interesting thing is the first reaction of most countries was to extend their exclusive economic zones and “nationalise” fisheries, that is boot out the foreign trawlers. goodies fans will remember their immortal take on the “Cod Wars”. countries then tried to impose quotas, licences, restrictions on boat sizes, etc. in a an attempt to sure up local fishing industries but protect fish stocks. obviously they failed.
so here’s the theory: there are obviously a significant amount of fish being caught outside 200 NM EEZ of any particular country. it may very well be that no one ‘fesses up to this kind of ocean rape. so the fish are imported, by all of us – but mainly the japanese. but they are exported by no one. and certainly not from any country which supplies stats to the FAO.
Dan: I certainly do remember that Goodies episode. The explosion at the end resulting in raining fish and chips was one of the classic Goodies scenes. I also seem to recall that Graham played Max Bygraves to calm the giant cod. In any event, your theory sounds very plausible. My whale suggestion was based on a similar principle, but would clearly not be as comprehensive in it’s application as a general reluctance to admit to illegal fishing. I think that this, with a possible tax effect as icing on top, sounds like a solution, if a depressing one, to the mystery.