I have submitted and published an article on the innovative prevent disease website. To access this article which will also be featured up coming on the Labyrinth of Life please click here. The article is titled: *A new Paradigm to measure welfare* and it centralises its discussion around the unsustainable measurement of welfare as dictated by an economic model. It discusses how GDP is an unrealistic marker of individualised and even group health and well-being. Enjoy the read. SS.

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Some interesting thoughts you’ve got there Stef.

I think your proposed “markers” are good.. the question though is how to achieve them… but before i go any further, I just want to say that the word you should have used was “Metric” not marker. A metric is an analytical measurement intended to quantify the state of a system. So, GDP is a metric, suicide rate is a metric etc because the all objectively measure something at a point in time. this data can tracked over time and by analysing it you get a good understand of the behaviour of the system over time.

I have 2 points to make

Point 1) So, in relation to your point about the GDP not being a good measure of overall health, well being and productivity of an individual you are absolutely correct. I’m about to start talking statistics so i’d like to define some terms. A statistical parameter is a number which describes a data set. For example, the average, standard deviation, mode and median are statistical parameters. They are used typically in two ways, Firstly to get an understanding of a larger data set, and secondly to be able to compare data sets.

there are two parameters that i would like to talk about in detail. Mean and Median. A datasets mean is it average. don’t ask me why there are two words for the same thing.. i don’t know. To calculate the mean you add al the values up and divide the total by the number of data points. The median is different. it is the middle number. so you take all the numbers in the data set and arrange them in order, the median is the middle number.

Both describe what we call the “central tendency”. in normal language, it means they give you an understanding of where the “middle” of the data is. Average income, median house prices are both examples of economic data described through central tendencies.

As a side note, GDP is a metric that describes the size of the data set.. but that is a bother story.

The problem with these parameters is that although they describe the dataset, they don’t give you all of the information. Let me give you an example. lets look at two data sets and calculate the mean and median

dataset 1:

1,3,3,4,5,5,7 Mean = 4 Median = 4

Dataset 2

1,3,3,4,5,5,49 Mean = 10 Median = 4

All i have done is changed 1 number, but you can see that it has had no effect on the median, but a huge affect on the mean (average). by comparing the mean and median, you can get an idea of how lopsided (or skewed) the data set is.

So what does this mean in economics? GDP tells you how big the economic pie is. it tells you nothing about how that pie is cut up. Likewise, GDP per capita (which is effectively an average) gives you an idea of how the pie might be cut up, but we know that the dataset is heavily skewed to one side because there are relatively few people making the majority of the money. If we were able to know how much each individual contributed to the gap we could work out the Median GDP per person and that would give a better understanding of how your GDP is being generated. Median GDP per person would be a much better way of determining the “average” persons economic status… it would also allow you to compare countries in a more informed way.

Point 2) choosing metrics is HARD… really hard. you need to be so careful because metrics drive behaviour. You see it in business all the time. if the metric is wrong then the desired behaviour will not manifest itself. Lets give an example.

Call centres. A call centre is getting complaints about how long people are on hold before they can actually talk to someone. so, in an effort to get an understanding of the problem they start measuring waiting time… lets say the average is 30 minutes.. “this isn’t good enough” says the bright spark manager. so he decides to put a target in for the staff to work towards. The decree goes out that the target average waiting time is now 5minutes…. so the staff have to reduce the average waiting time by 25 minutes… how do they do this? does management hire more people to comp with the load? do they write better procedures to make handling the customers questions a bit easier? do they put a FAQ on their website? NO.. what happens is that the management team don’t support and berate the staff for not working fast enough. So what do the staff do? Every second call they pick up the phone and hang up immediately. they cycle through more calls, the average waiting time plummets, the manager pats himself not eh back for being such a great leader, call centre staff get a nice bonus and every second customer is fuming and takes their business elsewhere.

Metrics drive behaviour… if you don’t get them right.. you fuck yourself over. Just something to bear in mind when thinking about alternate measures of a countries economy, welfare and well being