Category Archives: charts

Hot and Dry Days Ahead for Australia

Earlier this month, the Australian Bureau of Meteorology released the October figure for the Southern Oscillation Index (SOI). It showed a precipitous plunge of almost 20 points down to -14.6. Just how significant a drop this is can be seen in the chart below, which shows the distribution of monthly changes in the SOI going back to 1876 (-14.6 is at the lower 5% quantile, which means that a fall as big as this, or bigger, has only occurred 5% of the time).

Distribution of SOI changes (Jan 1876-Oct 2009)

But what exactly is the SOI and what is the significance of this decline in the index? The index is the standardised anomaly of the monthly average difference in sea-level air pressure between Tahiti and Darwin. “Standardised anomaly” means that the index measures the deviation of this pressure difference from the long-term average and is scaled by the standard deviation of the pressure difference and then multiplied by 10. The significance of the index lies in its relationship to the El Niño weather phenomenon. According to the Bureau of Meteorology:

Sustained negative values of the SOI often indicate El Niño episodes. These negative values are usually accompanied by sustained warming of the central and eastern tropical Pacific Ocean, a decrease in the strength of the Pacific Trade Winds, and a reduction in rainfall over eastern and northern Australia. The most recent strong El Niño was in 1997/98, although its effect on Australia was rather limited. Severe droughts resulted from the weak to moderate El Niño events of 2002/03 and 2006/07.

The chart below gives a historical perspective of the SOI over the last ten years. To get a better sense of the trends in the index, I have overlaid two different types of curve smoothing: a lowess (“locally-weighted scatterplot smoothing”) curve and a spline curve. The two give very similar results and make the 2002/03 and 2006/07 SOI downturns clearly visible. The timing of these downturns suggest that the corresponding droughts follow with something of a lag.

Southern Oscillation Index (Jan 2000-Oct 2009)

Over the last couple of years, the SOI has been solidly in positive territory and, again with a lag, there has followed an improvement in drought conditions. Indeed, New South Wales recently replaced the tight water restrictions which had been in place for a number of years with the less onerous “Water Wise” rules. Unfortunately, this change may turn out to have been premature. If the downward trend in the index seen over the last few months persists, Australia may face a return to severe drought conditions.

For anyone who is interested in how these charts were created, here is the R code. It is also available from the Stubborn Mule files section.

UPDATE: at the request of singingfish, here is a chart showing the full recorded history of the SOI back to 1876. The blue line is a spline smoothed curve.

Southern Oscillation Index (1876-2009)

Melbourne Cup by Numbers

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I don’t know anything about horses. Ever since I was bitten by one at the Easter Show as a small child, they have ranked very low on my animal preference list: only just above geese. Still, at this time of year almost everyone in Australia gets caught up in some way with the Melbourne Cup, the race that stops the nation. As usual, I expect that my involvement will only stretch as far as participating in the $2 sweep at the office, thereby avoiding the need to actually make any kind of ignorance-based horse selection.

But, with a mule as this blog’s mascot, you would think that I could do better than that, so I have thrown my charting skills at the history of previous winners in as slap-dash a manner as I can to see where playing the historical odds would get me.

I thought I would start with colour because, even as a racing-form novice, I suspect that should have no bearing on the result and so it seems like a safe place to start. Based on the winners going back to 1861, here is the distribution of winning colours.

Cup Winners by Colour (1861-2008)

This suggests that bay-coloured horses have an edge (or maybe it is just a common colour for a horse). What about the “sex” of horse (please do not ask me what all of these terms mean, but apparently “horse” is a sex)?

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Petrol Price Update

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Another five months on since my last petrol price update and oil prices have continued to rise, but so has the value of the Australian dollar. So while crude oil prices in US dollars are up around 75% since their lows in February, they are only up 29% in Australian dollar terms.

West Texas Intermediate Oil Prices

The Australian dollar has been rising steadily for the last six months, pushed along by the Reserve Bank of Australia which has started raising their target cash rate. Higher interest rates in Australia make it more attractive for offshore investors to buy Australian securities and they have to buy Australian dollars to do so. Australian investors holding foreign assets may do the same.

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A better view of the asylum-seeker league tables

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The last post looked at how many applications for asylum Australia and other countries have received this year on a per capita basis. The top three countries in the resulting league table are Malta, Cyprus and Norway and their figures are so much higher than other countries that they skew the data, making it hard to differentiate the lower rankings. To remedy this, I have reproduced the chart using a logarithmic scale.

Asylum-seekers per capita 2009

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Is Australia taking its fair share of asylum-seekers?

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In Crikey this week, Bernard Keane made the point that Australia accepts a disproportionately small number of asylum-seekers given our population size. So, where exactly do we rank in the world in terms of generosity towards displaced persons? The United Nations Refugee Agency provides a wide range of statistics about refugees and asylum-seekers. The latest monthly data gives the number of asylum-seeker applications by country for 2009 up to and including August. The chart below shows a ranking of the 44 countries who reported accepting asylum-seekers over this period. Australia finds itself well down the list in 20th place. Mind you, the United States ranks a few spots behind us and, despite having a better reputation when it comes to taking refugees, New Zealand is even further behind. Malta is by far the most welcoming country for refugees.

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Does Switzerland have the world’s best universities?

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Today @jgzebra drew my attention to the Times Higher Education league table of the top 200 univerities in the world. A quick glance at the list shows two US universities in the top three and six in the top 10. And indeed the United States dominates the results, claiming 54 spots out of the 200. The United Kingdom comes in next, taking 29 spots.

Country Count in Top 200 Universities List

Of course, this tally does not take into account the differing sizes of each country: with a population of over 300 million people, you would expect a good showing from the United States. So the obvious question is, what would the national ranking look like if population were taken into account? Rather than doing this based on the number of appearances each country makes in the list, I aggregated the overall “score” awarded to each univerity (which combines scores based on surveys of peers, employers, staff and students, citations and international staff and students) and then ranked each country by aggregate score per million population*.

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Junk Charts: Secondary Axes

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Data visualisation is a fascination of mine and, as a result, the posts on this blog have featured a wide array of charts. My aim is always to use graphics to help explore data and provide greater insight into whatever phenomena might be lurking in the data. While I have tried to make use of “good” charts, I have never talked about “bad” charts. There is no end to the things that can be said about bad charts. Indeed, one of my favourite blogs, Junk Charts, is dedicated to the subject. Nevertheless, I have decided that I will begin to assemble some bad charting habits to avoid.

Inspired by a chart on the Australian Stock Exchange (ASX) web site, brought to my attention by Danny Yee, I will start by considering the perils of the “secondary axis”. This is a topic that has been covered on Junk Charts, but it seems to be poorly understood by many people in finance. Bank economists seem to be particularly fond of secondary axes.

Since the ASX chart is dynamically generated, I have reproduced a static snapshot showing the key features of the chart. The chart shows (in blue) the history of the S&P/ASX 200 share price index over the last six months. The axis on the left hand side is the “primary axis” and shows the values of this share price index. Overlaid in red is the share price of Alchemia Limited (ACL), a biotech company. The price of Alchemia is shown on the axis on the right hand side, the “secondary axis”.

Alchemia Share Price on a secondary axis (on the right)

At face value, it would appear that the price of Alchemia shares has tracked the performance of the overall share market very closely. However, this is an illusion created by the use of a secondary axis. When considering performance of shares, what is important is not the share price itself, but the returns these prices generate. The upper and lower limits of each axis bear no relation to one another, but are simply determined by the range of values each price series takes and so give no insight into the returns of Alchemia compared to those of the S&P/ASX 200.

A better approach is to create a return index by considering what would happen to $100 invested in either Alchemia or the market as a whole (ignoring dividends and any costs such as brokerage fees and stamp duty). Both these indices can then be plotted on the same axis and this gives a very different picture.

Alchemia Share Price on a common axis

It now becomes clear that Alchemia shares performed dramatically better than the market as a whole. In fact, over this six month period, while the sharemarket index returned a very healthy 32%, the return on the Alchemia share price was an enormous 304%. This return was helped, no doubt, by Alchemia’s progress in drug trials with the US FDA.

The most that can be said for the ASX chart with the secondary axis is that it reveals some correlation in the ups and downs of the Alchemia share price and the broader market. However, the chart completely missed the big story in the data.

It is worth noting that producing the secondary axis in the first chart above using the R package is rather fiddly, while creating secondary axes in Microsoft Excel is very straightforward. This points to what I expect to be a theme in future bad chart posts: if it is easy to do in Excel, it is probably bad.

Alchemia