Monthly Archives: August 2009

How Important Is China?

Today I attended a presentation by TD Securities global strategist Stephen Koukoulas. While exploring the “green shoots” of recovery, Koukoulas made an interesting observation about China. Many observers of the Australian economy, Reserve Bank governor Glenn Stevens included, place great weight on the importance of China for Australia’s economy. But Koukoulas pointed out that, while exports to the US make up over 20% of Canada’s GDP, Australia’s exports to China only contribute 3% of GDP. In fact, the Australian Capital Territory (ACT) contributes more to GDP than China does.

As soon as I got back to my desk, I went straight to the Australian Bureau of Statistics to confirm these figures. Sure enough, merchandise exports to China for the 12 months to March 2009 were 3.1% of seasonally adjusted GDP, while the contribution of the ACT to GDP was 3.2%. So far, so good, but a historical perspective is revealing.China GDP

Australian Annual Exports to China

While the contribution of Chinese exports is still relatively small, it has been accelerating over the last few years. Over the 12 months to March 2009, Chinese exports grew by 0.8%, so they were a significant contributor to economic growth, despite the low base. Not surprisingly, China has been taking a growing share of total Australian exports over this period.

China Exports Share

China’s Share of Total Australian Exports

As for the nation’s capital (and surrounds), on current trends, it will not exceed China for very much longer.

ACT China GDP (III) ACT versus Exports to China

Of course, these figures do not disentangle volume and price effects and whether or not China’s own growth will remain strong enough to keep pushing our exports up is an interesting question. But, based on these charts, I can understand why Glenn Stevens considers China so important for an economic recovery.

Note: the code used to produce these charts is available on github.

Taking It Too Far: Verb and Adjective Clouds

I will freely admit that I am now going overboard, but commenter Lettuce All Rejoice asked what the Rudd word cloud would look like if it was broken down into nouns, verbs and adjectives. Fortunately, the Stanford Natural Language Processing Group make a statistical parser freely available for download. So, I used this to parse the speeches of Rudd and Turnbull and then filter for different parts of speech. Since the original word clouds featured nouns so prominently, I will restrict myself to verbs and adjectives here. After this I am done with word clouds. For now at least.

Wordle: Rudd VerbsRudd Verb Cloud

Wordle: Turnbull verb cloudTurnbull Verb Cloud

Wordle: Rudd Adjective CloudRudd Adjective Cloud

Wordle: Turnbull adjective cloud
Turnbull Adjective Cloud

Malcolm Turnbull’s Word Cloud

My last post looked at the favourite words of Australia’s prime minister, Kevin Rudd. In the interests of balance, I will now turn the word cloud lens onto the opposition leader, Malcolm Turnbull. Turnbull’s speeches are conveniently assembled online and the graphic below illustrates the frequency of his words from speeches made in 2009. Unlike the analysis of Rudd’s speeches, this analysis does include some speeches given in parliament.

Turnbull Word Cloud

Just like Rudd, Turnbull’s favourite word is “Government”, and “Australia” is not far behind. But from there, differences appear. The word “billion” is far more prominent, reflecting the opposition leader’s obsession with growing public debt. The appearance of “Rudd”, “Labor” and “Coalition” clearly reflect the realities of life in opposition where so much time is taken attacking the other side.

Interestingly, the word “emissions” is clearly visible in the cloud, whereas nothing relating to climate change was visible in Rudd’s cloud.

“Now” is as prominent as Rudd’s “also”. Does this reflect a constant sense of urgency from a man of little patience?

What is Kevin Saying?

Last week, Politico published an analysis of Barack Obama’s language. The words he used most often were “America”, “Health” and “Economy” (Politico included “American” in the count along with “America”). This prompts the obvious question: what are the favourite words of our own Kevin Rudd?

Fortunately, the prime minster’s website publishes transcripts of all Kevin’s public utterances (although this does not include his speeches in parliament). There is a lot there and the Stubborn Mule was lucky enough to have OldFuzz do the hard work, assembling over 400 pages of text constituting Kevin Rudd’s speeches from 2009. If he has the time and inclination, prior years may follow. And here is what it looks like as a word cloud.

Kevin Rudd word cloud

It is no surprise that, just as Barrack Obama is fond of saying “America” and “American”, so too Kevin Rudd likes to say “Australia” and “Australian”. He also throws in “Australians” reasonably frequently. It seems in keeping with his public servant mandarin style that Rudd uses the word “Government” more liberally than does Obama. While “global”, “world”, “national”,  “economy” and “economic” are all appropriately big-picture words for a prime minister to be using.

There are a few intriguing words looming from the cloud. It seems that Mr Rudd says “also” a lot. Given that this analysis is case sensitive*, we can also glean that Rudd frequently starts his sentences with the word “Building”.  It may seem fleeting strange that the word “cent” appears so prominently, but then again it is matched in size by the word “per”, so we are just seeing common use of “per cent” not some homespun wisdom about watching the small denominations of money.

So, peruse the cloud at your leisure and make of it what you will. Of course, please share your thoughts in the comment section below.

UPDATE: an abridged version of this post has appeared on The Punch.

* Here is a case-insensitive version of the word cloud.

Where Have the Fish Come From?

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 Imports and Exports

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.

The Big Arms Traders

My last post looked at the international arms trade. Taking data from SIPRI, I produced maps showing arms exports for a number of countries, including Australia and the USA. While these maps gave an indication of the spread of arms trading, it did not show which are the biggest overall importers and exporters of arms.

To remedy this, I have created two “word clouds”. The first shows arms importers. The size of the text varies with the total value of arms imported over the period 1980 to 2008 (figures are adjusted for inflation and are expressed in 1990 US dollars). The three biggest arms importers over this period were India ($58 billion), Japan ($37 billion) and Saudi Arabia ($35 billion). Australia’s imports over this period totaled $15 billion.

Arms Import Cloud

Arms Importers (1980-2008)

The word cloud for exporters is far more concentrated. Between them the USA and Russia* accounted for almost 65% of total arms exports, with exports of $60 billion and $48 billion respectively. France then comes in at a distant third with exports totaling just under $12 billion.

Arms Imports Cloud

Arms Exporters (1980-2008)

If you like the look of these word clouds, you can easily create your own. With Wordle you can create word clouds which are based on word frequency. This example is based on words used here on the Stubborn Mule (notice the prominent appearance of the word “debt”). For a bit more flexibility, IBM have a freely available Word-Cloud Generator, which can either work on word frequencies or take columns of words and numbers. It is written in java and is very easy to configure and run. I used it to produce the images in this post.

* As in the previous post, figures for the USSR and Russia have been aggregated.