(March 2019)

Education and Investment identify countries with better economic growth potential

 

Deciding in which countries to invest or focus investment is an important decision.  There are no definitive rules which guarantee a correct choice.  However, there are certain relationships and parameters that tend to identify those that can be successful and those that, in all probability, will not.

Analysis of our database covering 109 countries, shows that two variables have a strong relationship with both the absolute level of worker productivity and the trend in it.  To put it simply, if more than 50% of the workforce have upper secondary education or above then there is a strong positive relationship between both the absolute level and trend in Fixed capital investment and productivity. 

Countries with an education profile below the defined level do not get the same benefit.  Furthermore, it could take 10-30 years for them to get to that position as improvements in education takes a generation to be effective in the workforce.

There are seven counties that are well educated, have low fixed capital per worker but are investing above average in fixed capital in the last 3 years and hence would appear to be a good opportunity.  Conversely there are eight countries with a good standard of education but potentially are not investing enough to fully leverage it in future.


Clearly it is useful to be able to identify countries (and markets) that have better than average prospects of growing and hence being attractive areas in which to invest.  It is difficult to always get it right, but often there are clear parameters that must be achieved if a successful outcome is to be achieved.

In this Monthly Insight we look at the levels that must be achieved in terms of education and fixed capital Investment for growth to take place.  If nothing else it segments the 96 countries on which we have appropriate data into three groups – slow growth, medium and high potential.

An analysis of those countries that have demonstrated good productivity (in terms of total GDP per worker) in the past meet two necessary conditions. First, a relatively well-educated adult population and workforce and an accompanying (lagged) good level of accumulated fixed capital investment per worker.  It also identified that while education is a necessary condition it is not a sufficient condition for both good and increasing productivity.  It can get to the point where it exceeds the capability of the workforce – China, might well be such an example. 

Given that it is reasonable to expect that education is a necessary but not sufficient precursor to productivity it is therefore useful to start by examining the relationship between those two variables (education and Productivity) and find the under performers.

Of the 96 countries for which we have education data, 56 have at least half of their adult population with upper secondary or above (vocational or tertiary) education.  However, there is a significant number of those countries, 29 to be precise (52%), who would appear to be under performing in term of productivity per worker. This is shown in Figure 1. This is a plot of the 96 countries with the vertical axis being percent of adult population with upper secondary and above and the horizontal axis is GDP per worker (a measure of worker productivity which is less easy to manipulate).

The Blue box is countries where education standard is high, but the productivity per worker is relatively low.  While these countries do perform better for the most part than those with a lower standard of adult education (Green Box) the opportunity afforded by a well-educated adult population has clearly not been fully realised (as compared to those in the Red Box).  The question is why?

Figure 1:  The Global Relationship between Proportion of the Population with Upper Secondary or better education and Productivity.  (2018)

Fig 1.jpg

The opportunity is the countries in the blue box – high education but low productivity.   Their productivity can be lifted by improving the accumulated fixed capital that the worker has at their resources.  As shown in Figure 2 later, there is a very close relationship between these two variables for the countries where the education standard is already high.  In short, enabling educated people pays very good dividends.

More importantly, fixed capital investment can be provided quickly where as education is somewhat entrenched and changes slowly.  This is the problem faced by the countries in the ‘Green’ box in Figure 1.  While they are all improving their standard of education it is going to take time before they reach the level of the Blue Box.

To explain, assume there was an improvement in education policy in this year 2018, such that every child aged 5 to 12 went to school from that year on. This, of course is good but it will be 7 years before they reach upper secondary school entry age, and then a further 3 years in upper secondary – so it is a total of 10 years before the first benefits of this change are felt in the labour force. Then to change the overall education achievement profile of the labour force from mainly primary/lower secondary to over 50% with upper secondary or better takes a further 20 years.  That means the improvements introduced in 2018 will not move a country in the lower half of the green box into the blue box until 2048.

It might be noted that China introduced compulsory education for 5 to 12-year olds in 1984.  India got to that point in 2017.  This is an important difference between those two large economies.

Returning to the ‘Blue Box’ the countries that fall with that are Eastern European (excluding Turkey which just misses and Albania) plus Malaysia and the Philippines from South East Asia and four of the more stable countries in Central and South America.

So why do these countries under perform?

A good indicator of what the problem is revealed by ploting the accumulated fixed capital investment per worker against GDP per worker (productivity) for all countries with over 50% of their adult population having upper secondary and above education. 

This is shown in Figure 2.

Note:  Accumulated Fixed Capital Investment is the Fixed Capital Investment summed over the previous 1 years and depreciated at 10% per annum – as such the first year’s investment is worth nothing in year 11.  It is a stable indicator of the total value of resources and infrastructure available to the workforce (and population).  Expressing it on a per worker basis gives a measure of the relative resources available to the worker.

Figure 2:  The relationship between accumulated fixed capital investment per worker and GDP per worker for countries with over 50% of the labour force with upper secondary or better education.

 
Fig 2.jpg

The result is quite definitive in that there is a close relationship between the amount of investment behind a worker and the productivity of the worker if the level of education is high.  As such it is probably a good leading indicator for where there is likely to be growth in productivity of a country (and potentially assuming a growing, increasingly better educated, labour force) total GDP.  

The countries in the high education/high productivity (Red box) all have relatively significant fixed resources behind each worker.  The average in 2018 is US$105,114 per worker.  This compares with US$23,447 for the Blue box countries.

What extent are the low productivity high education countries doing about this.   Which ones should you consider investing in – and which should you avoid?

The high productivity countries fixed capital investment per annum over the last 3 years has run at an average of 22% of GDP. For the low productivity countries, it has been similar at 21% - but of them, 7 countries are investing much more heavily.  That is Georgia, Belarus, Malaysia, The Philippines, Azerbaijan, Romania and Estonia.  They are all spending more than 22% of their total GDP on Fixed Capital Investment.   This in all probability will mean their productivity per worker will increase in future.

This compares with Argentina, Latvia, Poland, Armenia, Mauritius South Africa, Ukraine and Lithuania all of whom have good scores in terms of education but are low on accumulated fixed capital investment and have under spent on fixed capital investment per annum over the last 3 years,  Their ability to lift their productivity in the next 5 years would appear to be constrained

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The data for all countries runs from 2005 to 2043.