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.

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.

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.

How do we measure inequality? Part one: Gini coefficient (Continued)

In my last blog post I discussed the Gini Coefficient as a way of measuring inequality. In this post I want to use this Coefficient to see if inequality in New Zealand has changed in the last 10 years or so.

As discussed in the previous post, I have used income data from the IRD, and excluded people who I knew were definitely working part-time.The following results were obtained using excel:

  

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Year	Gini Coefficient
2001	0.356
2002	0.360
2003	0.353
2004	0.355
2005	0.353
2006	0.342
2007	0.320
2008	0.318
2009	0.314

As we discussed in the last post, a higher Gini value indicates higher inequality. From the table and chart we can see that income inequality has fallen in the last ten years, particularly in the period from 2005 to 2009.

The New Zealand Institute, the privately funded think-tank have also provided data on inequality and Gini Coefficients. Their figures roughly correspond to my own figures (Which is hugely encouraging from my own standpoint, I know my calculations are correct). The NZ Institute have compared our Gini figure to the rest of the OECD, where in terms of equality, we rank 25 out of 34 (http://www.nzinstitute.org/index.php/nzahead/measures/income_inequality/).

So although equality has improved in recent years, there is still some work to do to catch up with the rest of the developed world. The NZ Institute link above has some great information for those wanting to know more about Inequality in New Zealand.

I don't really want to draw any conclusions over these figures, but the downward trend is encouraging. I need to point out that data I have used is far from perfect. For starters I have effectively excluded any unemployed individuals, as on the dole they would not earn enough to enter my analysis (discussed in the previous post).

If you have any questions or comments, please feel free to make a comment. In the next post I will stop talking about inequality for a while and will discuss a few minor issues I have with Statistics New Zealand.

Bye

How do we Measure Inequality? Part one: Gini coefficient

In this post I will discuss inequality and the Gini coefficient, which is one particular way of measuring inequality. In this post I will discuss the concept and how it is calculated, and in the next post I will use it to see if income inequality in New Zealand has changed in the last 10 years.

Inequality is a slightly more exotic and complicated concept when compared the basic economic indicators of GDP, unemployment, and inflation  When we are talking about inequality in economic terms, we are talking about differences in the distribution of wealth and income. All societies have some inequality, as some people are richer and earn more than others. Throughout history, high levels of inequality have been associated with revolution, the creation of political systems and the formation of new governments. The recent worldwide Occupy movement and uprisings in the Arab world are recent examples of this.

Defining and discussing inequality are simple matters. Trying to measure it however opens up a very contentious can of worms. Firstly, are we measuring wealth inequality, or income inequality? (This is not a big issue, as people with high levels of income are generally wealthy).

Secondly,because of its arbitrary nature inequality cannot be measured in the same way as GDP, unemployment, or inflation. For example the statement "Society A is 50% percent more equal than society B", makes no sense. There are many indices for measuring inequality (for example, the Hoover Index, the Theil Index, Gini Coefficient,...). The common inequality indices all give results between 0 (perfect equality) and 1 (perfect inequality), or 0% and 100%. However, because these indices use different formulas, each index will give a different value of inequality for the same society. compared to GDP or unemployment, interpretations of inequality figures cannot be made with the same authority.

Now that I have discussed a few issues with inequality, I will use the Gini coefficient to measure it. Subsequent posts will look at the other measures. I have started with Gini because it has an elegant visual basis.

The Gini coefficient is based on the Lorenz Curve. This curve plots the cumulative share of people ordered from lowest to highest income (from 0-100%) on the x-axis, and the cumulative share of income earned (from 0-100%). The Lorenz Curve for New Zealand income in 2009 is shown below. For this curve I only want consider full-time workers, so I have removed anyone who earns less than $19500 in that year (assuming a minimum wage of $12.50 per hour and a 30 hour work week, 12.5x30x52 weeks = $19 500) from this analysis.

A society that is perfectly equal will have a Lorenz curve that shoots out from the origin at a 45 degree angle. This is represented by the red line in the diagram below. With this red line, the cumulative share of population and the cumulative share of income increase at the same rate, resulting in perfect equality.  (For example, the "bottom" 10%  of the population would earn 10% of the income, the "bottom" 20% of the population would earn 20% of the income, and so on). Lorenz Curves that are closer to this 45 degree line will be associated with societies that are relatively equal. Conversely, societies that are more unequal will have more "bent" Lorenz Curves farther away from the 45 degree line.

From the Lorenz Curve we can find the Gini Coefficient of an economy by calculating A/A+B.

Using New Zealand individual income data from the IRD, I have calculated that the Gini Coefficient for New Zealand in 2009 was 0.31, so I know my calculations and methods are robust. This figure is very close to the Ministry of Economic Development's own figure of 0.32 for the same time period. The small difference arises due to the Ministry's use of household income for the calculations, while I used individual income.

In my next post I will the Lorenz curve to Calculate the Gini Coefficient for previous years to see how inequality in New Zealand has changed.

Bye for now.

Is New Zealand moving to a new steady state? The effects of a change in the savings rate

In this post I have no new data to analyse. Instead, I want to give my thoughts on what I think is happening, or what I hope is happening to the economy of New Zealand.

According to just about every social, political and economic commentator in the country, we have an abysmal rate of saving. In the past, only economists and the Reserve Bank Governor said this. However, it seems that these cries were ignored. Not many people are going to listen to advice from a gloomy old economist or Reserve Bank Governor when they are thinking about buying a new TV.

Now However, it seems that insulting some of our ingrained habits is the "in" thing at the moment. Apparently we are terrible drivers and apparently we are terrible savers. but has this increase in derision at our poor level of saving (combined with the recent recession), increased our rate of saving?

Well maybe it has. Since 2007 retail sales figures have struggled to gain momentum (see chart below). You could argue that this is due to high unemployment figures, but there is another more basic piece of evidence to suggest our savings rate has gone up in recent times: Trade surpluses.

As you can see in the chart below, New Zealand has had a better trade balance in recent years, suggesting that our spending has decreased and saving increased.

So if our saving rate has gone up, what does this mean for the country? well in economist terms, it could mean that we experience an increase in our steady-state  rate of growth, which I will proceed to explain by example.

Suppose we have a person earning a constant $100 000. They decide to spend 80% of what they earn and save the remaining 20% at an interest rate of 7%.

In year one they will earn $100 000, spend $80 000 and save $20 000.

In year two they will earn $100 000 plus $1400 (interest income $20 000 X .07), spend $81 120, and save $20 280.

Over time, their expenditure over a 40-year period will look like this:

So expenditure increases over time which is nice. In this example, income and expenditure is increasing at a rate of 1.4% each year, which is the steady-state rate of growth.

But what if this person decided after ten years to increase their savings rate to 50% of income? We would get the situation with the red line in the figure below.

In the years immediately following the saving rate change, expenditure drops sharply, but eventually catches up to and overtakes the amount of spending that would have taken place (dashed line) due to the increase in income from saving dividends. In this example the steady-state rate of growth has increased to 3.5%.

If we use this example to discuss the New Zealand economy (approximating expenditure to Gross Domestic Product, or GDP) then the shaded area in the above chart is where I think our economy is now, given my earlier theory of an increase in savings. If this is true, then the current stagnation in GDP and high unemployment figures are partly caused by a change in spending/saving rates. However, this should only be temporary, and GDP in a relative sense will increase as the dividends from our extra savings start to kick in (and as our steady state rate of growth improves).

Of course, this model is only an example. It can only reflect a few aspects of reality and it has some limitations:

• The time needed to "overtake" the dashed line in the real world could be more or less that that taken in the example, where only arbitrary numbers were used. 
• The New Zealand economy is not just affected by the saving rates of different citizens, but by other global and domestic events, making the situation not quite as straightforward as that described by this post.
• For the increase in the steady-state rate of growth to be permanent, individuals and governments need to stick with the habit of saving at the increased rate. I have serious doubts that this will happen.

In conclusion, global and domestic events may make the picture on saving and spending a little murky. Murky or not however, an increase in saving will definitely help improve prosperity and the long-term future of New Zealand. 

Minimum wage v inflation

Just a short post today on how the real value of the minimum wage has changed in the last few years.

A few days ago, the Labour party released their employment policy, confirming their plan to raise the minimum wage to $15 per hour. Some say it is needed to help workers keep pace with the increasing cost of living, while others say it is needed like a hole in the head. The latter group point out that conventional supply and demand theory predicts an increase in unemployment if the minimum wage is raised.

This got me thinking. The minimum wage is changed every year or every second year (see chart below) but have these changes kept up with inflation?

Date of minimum wage change	Minimum wage rate
1-Mar-97	$7.00
6-Mar-00	$7.55
5-Mar-01	$7.70
18-Mar-02	$8.00
24-Mar-03	$8.50
1-Apr-04	$9.00
21-Mar-05	$9.50
27-Mar-06	$10.25
1-Apr-07	$11.25
1-Apr-08	$12.00
1-Apr-09	$12.50
1-Apr-10	$12.75
2-Apr-11	$13.00

 This table is interesting in itself, as we can see that the nominal rate (without taking the effects of inflation into account) has almost doubled in fourteen years. However, if we include inflation data, we can see how the real minimum wage has changed relative to the cost of living.

Date of minimum wage change	Minimum wage rate (nominal)	Consumer price index	Minimum wage rate (real, 2011 prices)
1-Mar-97	$7.00	821	$9.86
6-Mar-00	$7.55	849	$10.29
5-Mar-01	$7.70	876	$10.17
18-Mar-02	$8.00	900	$10.28
24-Mar-03	$8.50	913	$10.77
1-Apr-04	$9.00	935	$11.14
21-Mar-05	$9.50	962	$11.43
27-Mar-06	$10.25	1000	$11.86
1-Apr-07	$11.25	1020	$12.76
1-Apr-08	$12.00	1061	$13.09
1-Apr-09	$12.50	1081	$13.38
1-Apr-10	$12.75	1099	$13.42
2-Apr-11	$13.00	1157	$13.00

As you can see, in real terms the minimum wage has increased by around 30% from 1997. This tells us that for the last decade and a half, the minimum rate of pay in New Zealand has kept pace with the cost of living.

A 14 year span of analysis is hardly comprehensive however. As a final thought, consider this:

In 1969 the minimum weekly rate of pay for adult males was $42. Assuming a 40 hour work week, this corresponds to a minimum wage rate of $16.40 per hour in 2011 prices.

In the future, I may try and get more data to continue this analysis, but for now I'll say goodbye.

See you later