Treemap of the NZX

As you would have noticed in my previous posts, I am currently fascinated with treemaps. I recently
constructed a couple of treemaps of the New Zealand Stock Exchange, and thought you may be interested in viewing them.

In the attached treemaps, each listed company on the NSZX is represented by a coloured box. The size of the boxes are determined by the market capitalisation of each company, and the colour of the boxes are determined by their performance on the NZSX from the start of the year to July (A deep red shade indicates very poor performance, a deep Green shade indicates very good performance, and lighter shades indicate less extreme positive or negative performance).

The first treemap shows the contribution of each sector (i.e. services, property, primary, goods, investment, energy) to the overall size of the NZSX. In the second treemap, each box/company is in the same position as the first treemap, and is identified by their three-letter-code. A good test to check your knowledge of the NZSX would be to try and name as many of these companies as possible.

It would be great to know what you think about these graphics and the improvements that could be made to improve them.

The Size of National Economies Version 2

In this post I wanted to  have a another go at the figures I made a few months ago in "The Size of National Economies".

I have since found out that these diagrams are called treemaps. Treemaps can display hierarchical data by placing appropriately sized rectangles nested within each other. The data I am using (World GDP) has been grouped into the six continents, then into individual nations. The size of each box represents the size of the respective nation's economy, and the colour of each box indicates the level of per-capita income, with blue boxes indicating a very low per-capita income and orange boxes indicating a very high per-capita income. A couple of these treemaps are displayed below.

I think these charts are very informative on wealth and income levels in different parts of the world. The first treemap illustrates the point that the economic world is dominated by the Northern Hemisphere. Asia, Europe and North America contribute over 90% of World GDP. It is also interesting to compare the wealth of different continents. The colouring of the rectangles shows us that European countries generally have a high level of income while African countries have a low level of income.

Any comments or questions are welcome. Thanks for reading.

Visualising the Structure of Economies

For this post, I wanted to show an economic graphic I have been working on. For the last year or I have become increasingly interested in innovative ways of presenting data, which has been inspired partly from a Statistics New Zealand working paper from August last year called “Visualising official statistics”. Recently, I have been experimenting with a graphic that shows the size and structure of a particular country’s economy. I am now at the stage of gathering feedback from friends and experts in order to improve its clarity and effectiveness.
The particular graphic I have been working on is based partly on the work of Hidalgo’s tree representation of the Human Development Index, and Hans Rosling’s “Gapminder World” dynamic graphic, both of which are discussed in the Visualising official statistics paper.

In its current form, the above graphic I have constructed above resembles a tree with three parts. The base shows the size of a nation’s economy, with the shape determined by population and per-capita income. The second part displays three branches, showing the contribution to national GDP by the primary, secondary and tertiary sectors. The topmost section splits these three sectors up further into more branches.

To see how effective this graphic would be, I have applied the graphic to the following countries (only the bottom two parts are shown):

As you can see, the economy of Australia is much larger than New Zealand, due to their greater population and higher per-capita income. Both countries economies rely largely on the service sector.

The three images above portray the world's three largest economies: The United States, China, and Japan. China has a large Gross Domestic Product despite their low per-capita income level ($8 400), due to their large population. The United States has a smaller population but a much larger per-capita income ($48 100). The service sectors in Japan and the US make the greatest contribution to GDP in their respective countries (76% and 77% respectively). In China, the contribution to the economy is mostly spread between industry and services (44% & 47% respectively). 

It would be great to know what you think about this graphic and the possible improvements that could be made to make it better at conveying information.

Productivity in different sectors of the economy

In this post I wanted to look at productivity in different sectors of the New Zealand economy. Productivity is an important measure in economics, as it measures what can be produced with a given amount of inputs. The greater the productivity, the greater the amount of goods and services that can be produced. It is one of the main reasons why countries like Luxembourg and the United States are as rich as they are. Their high productivity means the workers in these countries are able to produce more in less time than workers in other countries.

So now I pose a question:

Who are the most productive workers in the New Zealand economy?

In principle, this should be a very easy question to answer. Simply look at the production figures for each sector of the economy, and divide this by the number of workers in each sector. Unfortunately, it’s not quite that simple, as the data makes no distinction between part-time and full-time workers.

The figures for this analysis are taken from Statistics New Zealand, which is a reliable source of information. I have, on the chart below, the number of workers in each sector, and each sector's contribution to GDP for 2011.

The missing element that lets this analysis down however, is the lack of data on hours worked in each industry. In some sectors such as retail and restaurants, there is a greater proportion of people working part-time compared to other industries such as manufacturing. Statistics New Zealand does have data on total hours worked in New Zealand, but unfortunately, this is not broken down into different economic sectors. A true analysis of worker productivity would divide total production by hours worked, instead of dividing by the number of workers. This means that the figures below need to be taken with a pinch of salt. Figures are in current NZ dollars

Table 1: Output per-worker in New Zealand
 

Sector	Number of workers in sector	GDP  per sector	GDP per worker
Agriculture, fishing, forestry, and mining	159,900	$15,398,000,000	$96,298
Manufacturing	256,800	$24,699,000,000	$96,180
Electricity, gas, and water	16,800	$3,996,000,000	$237,857
Construction	178,800	$7,981,000,000	$44,636
Wholesale trade	109,000	$14,861,000,000	$136,339
Retail, Accommidation and Restaurants	335,500	$15,394,000,000	$45,884
Transport and communication	140,600	$21,177,000,000	$150,619
Finance, insurance, and business services	346,700	$59,347,000,000	$171,177
Government admin and defence	126,900	$10,116,000,000	$79,716
Personal and Community services	558,400	$24,737,000,000	$44,300
Total	2,229,400	197,706,000,000	$88,681

As you can see, the most productive sectors according to this analysis are electricity, gas and water, finance, and transport and communication. This is likely to be because these sectors normally produce high-value goods and services, and use capital such as computers and heavy transport machinery to increase production. As I suspected, the sectors where there is more part-time employment were the least productive, but as I stated above, a different result may occur if hours worked was used instead of the absolute number of workers per sector. Nevertheless, it is still interesting to see the number of workers involved in each industry and their contribution to national production.

The Size of National Economies

In this post I want to show you a couple of images I have made. These images show how the sizes of different economies compare to each other. The figures (Gross Domestic Product) are taken from the IMF and  are calculated using Purchasing Power Parity (PPP) calculations. PPP adjusts international currencies so that a certain amount of money has the same purchasing power in each country, and allows for a more realistic comparison of incomes between different countries.
The first image below divides the world into six continents, and shows how much the different economies contribute to world GDP. As you can see, the northern continents of Asia, Europe and North America dominate the world economically, making up nearly 90% of total world GDP.

The second image I have splits these continents up into individual countries, with the table below showing their individual percentage contributions to total world GDP. There are no surprises to see that countries like America, China and Japan dominate this picture. It is interesting to see how some countries dominate their respective regions economically, such as Australia, Brazil, or the USA. Some countries like Brazil unexpectedly feature quite prominently in this picture, while other nations have a surprisingly small contribution to world GDP.

Country	Percentage contribution to World GDP
Asia
China	14.34%
India	5.67%
Japan	5.57%
Korea, South	1.97%
Indonesia	1.42%
Iran	1.18%
Taiwan	1.12%
Saudi Arabia	0.86%
Thailand	0.79%
Pakistan	0.62%
Malaysia	0.57%
Philippines	0.50%
Hong Kong	0.45%
Singapore	0.40%
Vietnam	0.38%
Bangladesh	0.36%
Rest of Asia	2.60%
Europe
Germany	3.92%
Russia	3.01%
United Kingdom	2.86%
France	2.81%
Italy	2.32%
Spain	1.79%
Turkey	1.34%
Poland	0.97%
Netherlands	0.90%
Belgium	0.53%
Sweden	0.48%
Austria	0.45%	1
Switzerland	0.43%	2
Ukraine	0.42%	3
Greece	0.39%	4
Czech Republic	0.35%	5
Norway	0.34%	6
Romania	0.33%	7
Portugal	0.31%	8
Denmark	0.27%	9
Finland	0.25%	10
Hungary	0.25%	11
Ireland	0.23%	12
Rest of Europe	2.00%
North and Central America
United States	19.10%
Mexico	2.10%
Canada	1.76%
Rest of Nth and Ctl America	0.64%
South America
Brazil	2.93%
Argentina	0.90%
Colombia	0.59%
Venezuela	0.47%
Peru	0.38%
Chile	0.36%
Rest of South America	0.37%
Africa
South Africa	0.70%
Egypt	0.65%
Nigeria	0.53%
Algeria	0.34%
Morocco	0.21%
Rest of Africa	3.40%
Oceania
Australia	1.16%
New Zealand	0.16%
Rest of Oceania	0.08%

Any comments or questions are welcome. Thanks for reading.

Median Income in New Zealand

In this post I want to discuss median income, and how it has changed in New Zealand in the last ten years.

When economists want to analyse how the wealth and living standards of people within a country are progressing, most of the time they look at GDP per-capita. The use of this statistic has a couple of key advantages:

• It is (relatively) straightforward to measure.
• It is positively correlated with many other standard-of-life indicators (e.g. life expectancy, education, life satisfaction).  

However, there is one key disadvantage of GDP per-capita, and that is it is a very indirect way of approximating living standards. many items that are included in GDP calculations do nothing to improve living standards (e.g. profits from foreign owned companies sent back overseas) while some activities that improve living standards are not included in GDP estimates (e.g. a new public transport initiative that reduces pollution and commuter time). To get a better grip on changes in living standards, researchers use other data sources to complement GDP data, such as wage levels, indices like the human development index, or even happiness surveys. To analyse standard of living changes, I like to use yearly median income, as it directly measures what people are earning in the country. Compared to average income, median income is less biased as it can't be skewed upwards the average income inevitably is.

And so on my analysis. I have used inflation adjusted New Zealand income data from the IRD. As with my Gini coefficient study, I only wanted to consider full-time workers, so I removed anyone who earns less than the full-time wage for each year. I thought that this would reduce the bias in my investigation, and besides, I am more interested in the changes in median income and not the actual value.

Year	Median income (nominal values)	Median income (2010 prices)
2001	$28,500	$35,800
2002	$29,500	$36,000
2003	$30,500	$36,700
2004	$32,500	$38,200
2005	$35,500	$40,600
2006	$37,600	$41,300
2007	$40,500	$43,600
2008	$42,500	$44,000
2009	$43,500	$44,200
2010	$43,500	$43,500

As you can see from the table and chart, the first ten years of 2010 have been a decade of two halves. From 2002 to 2007 median yearly income jumped from $30 000 to $40 000, an increase of around 4% per-year in real terms. After 2007, growth in median income vanished, probably as a result of the Global Financial Crisis and subsequent recession. It would be very interesting to see how median income will change in the coming years.

Are the quarterly GDP growth announcements misleading?

In this post I want to talk about an issue that has been bugging me slightly over the last year, which is the quarterly Gross Domestic Product (GDP) growth announcements made by Statistics New Zealand. These announcements are important as they are an indicator of prosperity within the country.

Every three months the latest GDP figures are released, generally following this schedule:

Late March:            GDP figures for the previous December quarter are released
Late June:               GDP figures for the previous March quarter (January to March) are released
Late September:     GDP figures for the previous June (March to June) quarter are released
Late December:      GDP figures for the previous September quarter are released

Other economists, the Treasury, and the Reserve bank make their own predictions on GDP figures, but the table above shows when the definitive GDP numbers are released. If you want concrete, hard facts on how the economy is actually doing, you have to use GDP figures that are at least 3 months old, or even older. Say for example it was early December and you wanted to describe the state of the economy. One of the most important pieces of information you need to that is five months old!

The other thing that annoys me about the GDP announcements is that they are generally only released and reported in aggregate (and not per-capita) terms. As an indicator of prosperity, aggregate measures of GDP are not quite as useful as per-capita measures. GDP per-capita figures are more likely to be affected by things that have an impact on our quality of life, such as productivity or income. Aggregate, or total GDP is affected by productivity and income, but can also be affected by changes in population, which does not necessarily improve the quality of life experienced by people within a country.

If you were planning on using GDP figures to get a better picture on how we are doing as a nation, It would be far better to to use per-capita values rather than the aggregate values. However, Statistics New Zealand make no mention of GDP per person at all in their releases!

The table and chart below shows how the total production of NZ has changed from quarter to quarter, and it is these figures that are broadcast by the media to discuss the health of the economy. At the moment, the the most up to date figure on GDP is from September 2011, when an increase of 0.8% was recorded over the June 2011 quarter. These increases are recorded in real terms (i.e. taking inflation into account). The table below shows how GDP has changed in the last three years. (At the moment, total GDP in New Zealand stands at around 200 Billion $NZ, and per-capita GDP is around 42 000 $NZ). Between the start of 2008 and September 2011, Total GDP (measured in constant prices) fell slightly by 0.3%

Quarter		Percentage increase in GDP from previous quarter
2008	Mar	-0.3
	Jun	-0.6
	Sep	-0.5
	Dec	-1.2
2009	Mar	-1.1
	Jun	0.1
	Sep	0.1
	Dec	0.8
2010	Mar	0.3
	Jun	0.3
	Sep	-0.1
	Dec	0.3
2011	Mar	0.7
	Jun	0.1
	Sep	0.8

The following chart and table show how per capita GDP has changed in the last four years. Over this period, per capita GDP fell by 3.9%. These figures are generally not reported by Statistics New Zealand

Quarter		Percentage increase in per capita GDP from previous quarter
2008	Mar	-0.5%
	Jun	-0.7%
	Sep	-0.8%
	Dec	-1.5%
2009	Mar	-1.4%
	Jun	-0.1%
	Sep	-0.3%
	Dec	0.5%
2010	Mar	0.0%
	Jun	0.1%
	Sep	-0.4%
	Dec	0.1%
2011	Mar	0.5%
	Jun	0.0%
	Sep	0.6%

If we compare the two growth rates in the same chart, we can see that total GDP quarterly change figures (in blue) are consistently higher than the per-capita change figures (in red). This because the total figures are augmented by New Zealand's increasing population. At the moment, Statistics New Zealand only release the figures in blue. If people are only glancing at these figures in the news, (which most are) they will get a slightly distorted, sugar-coated summary of the economy at any point in time. This is why I think the announcements are slightly misleading.

As I have stated above, per-capita GDP growth figures are a better indicator on how the quality of life within a country has improved, and its inclusion in growth announcements would improve people's understanding on the state of the economy. Now, I don't think the Statistics department have deliberately sought to pull the wool over any one's eyes. I just believe that Statistics New Zealand could include per-capita GDP figures in order to inform the public a bit better on how the economy is going.

So, those are my two issues with Statistics New Zealand. For the first issue, on the lengthy delay between quarters and their corresponding growth figures, I'm not really upset. I know there is a trade off between accuracy and speed. I would rather wait for accurate figures than have incorrect figures quickly.

On the second issue, I just want to say that if Statistics New Zealand go to so much trouble to collate these figures, It would make sense to present their data in a way that allows for an open and honest interpretation.

Finally, I want point out that GDP and GDP per-capita are not a perfect measures of the quality of life experienced by a society, and they should not be the primary focus of a government. They are just ways of measuring how we are doing as a nation. If we focus on more important issues, economic growth will take care of itself.