Quality of Government matters more than size of government for human development, education and life expectancy

“...It’s not the size of the wave but the motion of the ocean…”

  • Quality of government (QGOV) seems more important than size of government (SGOV) for a variety of domains

  • QGOV is more important for peace, for human development, for health and for education 

  • This exploratory work extends the work of Ed Dolan (Niskanen Centre) and comes with many caveats due to interactions.

  • Outliers such as Singapore and Ireland may be worth closer examination for what is working well in smaller governments 

  • QGOV may have increasing importance at higher levels of development 

  • This may provide exploratory evidence that “state capacity” in certain domains eg innovation, health and education - might be important. This adds to the debate on “state capacity libertarianism” and in terms of current UK policy may inform on whether investing in an “ARPA organisation” or other areas of state capacity is a positive return on investment.

Background 

Economist Tyler Cowen posited a notion of State Capacity Libertarianism. Cowen subsequently linked to a blog referencing the work of Ed Dolan.

The work (2017) developed two scores - QGOV for quality of government and SGOV for size of government.  Dolan analysed two measures of freedom and prosperity the Legatum Prosperity Index and the Cato Human Freedom Index and concluded - with several caveats due to interactions and unknown causality- that QGOV was more important than SGOV. See his work for definitions of SGOV and QGOV.

Idea 

I was intrigued if this work extended to other areas that I am interested in both personally and professionally. (I help allocate $13bn in pension fund and other investments in global equities with an interest in healthcare). 

I chose to look at: 

  • -Peace

  • -Human Development 

  • -Life Expectancy (as broad measure for health)

  • -Education 

As measured by other organisations.

Methods 

I hand inputted data on:

  • SGOV, QGOV, 

  • Human Development Index (UN HDI)

  • Education Index (EDI, as component of HDI)

  • Life expectancy Index (as component of HDI)

  • Peace index (as calculated by non-profit Vision of Humanity)

(Sources at end, errors possible)

I ran scatter plots and Pearson correlations. I tagged for World Bank classifications of income, and by geographic region.

Results 

QGOV vs Peace

QGOV vs Peace.png

Correlation = (-) 0.71 | R2 = 0.5

Higher quality of government had a 0.7 correlation with the Peace Index (where lower score = more peace)

An interactive version of this data, where you can also view by income level (use drop down box) and geography (click circle legend labels) is below. The trend holds for all levels of income.

SGOV vs Peace

Correlation =  0.32 | R2 = 0.1

Size of government had a weaker 0.3 correlation with the Peace Index (where lower score = more peace)

SGOV vs Peace Index.png

The overall correlation is weaker and also suggestive that large governments correlate slightly with the peace index.

An interactive version of this data, where you can also view by income level (use drop down box) and geography (click circle legend labels) is below. Different income levels change the trend line, upper middle level countries inverting - suggesting smaller govts here are better for peace but only weakly.

Geography also changes the trend, with Latin America countries suggesting smaller very weakly trending. It’s weak enough maybe to be considered almost no trend though.

My overall takeaway is that the trend is weak vs QGOV but it is intriguing that income levels change the pattern as do geography.

Peace comment 

As often there are intersections on what components might go into peace. Experts may disagree as to the validity of this index for peace however the methodology is clear and it has some support. 

I find it interesting as it is another lens to judge human “progress” on and therefore what types of government might best foster progress.

QGOV vs HDI, Human Development Index

Correlation =  0.75 | R2 = 0.57

Quality of government has a 0.75 correlation with the Human Develpment Index where larger HDI = more developed.  

QGOV vs Human Development Index.png

It looks to me that the slope is stronger in more developed nations. Gently sloping until about 0.75 on HDI, and then steeper.

An interactive version of this data, where you can also view by income level (use drop down box) and geography (click circle legend labels) is below. You can observe this as the slope is stronger for the richer nations (and a measure of GNP is included within the HDI) but it is the same direcction for all incomes, slightly weak for middle.

SGOV and HDI

Correlation =  -0.53 | R2 = 0.28

Size of government has a -0.5 correlation with the Human Develpment Index (where larger HDI = more developed) suggesting larger governments are moderately better than small governments with some notable outliers such as Singapore, South Korea and to some extent Ireland, and Switerland.

SGOV vs HDI.png

An interactive version of this data, where you can also view by income level (use drop down box) and geography (click circle legend labels) is below.

The trends are weaker split by income level, with there almost no trend in high income and upper-middle income.

I now present the components for life expectancy and education (that go into the HDI seperately).

QGOV vs EDI

QGOV vs Education Index.png
SGOV vs Education Index.png
QGOV vs. Life exp (1).png
SGOV vs. Life exp.png

Comments on EDI, Life expectancy; observations and arguments for state capacity.

Given the weighting in the HDI that life expectancy has, it is unsurprising that QGOV also correlates better than SGOV for life expectancy. 

While there are social and cultural determinants of health of which government would only be a component, I argue that it is still noteworthy that it is not size but quality of government here that seems to count.

Again given the weighting in the HDI for Education, it is again unsurprising that QGOV correlates better than SGOV.

Of note, Chile and Kazakhstan appear on education and to some extent life expectancy as higher perfomer small government countries to join Singapore and Ireland, Switerland.

I chose to examine education and health because in many countries there is on going debate as to the structure and capacity that governments should play in health and education markets. 

This line of argument would suggest where countries do wish their governments to be involved then quality of that government or perhaps “state capacity” could be an important factor. 

This is noteworthy in the UK where there is wide support for a National Health service across the political divide and also for state funded education providing the majority of the populations education. 

Two other tentative observations. It is worth dwelling on where small governments seem to be doing well. I would note Singapore and South Korea and perhaps to an extent Ireland and Switerland. Those countries would be good examples of small, high quality goverments. 

My own theory here is also the importance of social and cultural determinants of health and education. 

For instance, it is unknown what the compliance rate for medications are in various countries. A higher drug medication compliance of cost effective genetic medications in Singapore (arguable driven by a social factor of listening to your doctor properly?!) or of the positive/negative health outcomes of effective elderly social care across countries are mostly unknown. 

A second observation is the seemingly stronger slope in the high HDI nations. There may be many explanations for this and all the caveats expressed by Dolan also apply but it might be an intriguing provocation that quality of government becomes even more important in extending the progress of already highly developed countries. 

Caveat

As Dolan notes there is considerable interation between SGOV and QGOV as larger governments have a tendency to be of better quality, but Dolan runs multiple regressions here:

“…simple correlations like this need to be interpreted with caution, as there are complex intercorrelations among multiple variables. In this case, we have a correlation of -0.42 between SGOV and QGov, that is, a tendency for larger governments to have a higher index of quality. We also have a correlation of 0.74 between QGOV and the log of GDP per capita (richer countries have higher-quality governments) and -0.48 between SGOV and the log of GDP per capita (richer countries have relatively larger governments).

Dolan can run multiple regressions which I do not have the capcity for, but Dolan concludes:

We can use multiple regression to untangle these interactions, using HFI* as the independent variable and using QGOV, SGOV, and the log of GDP per capita as the dependent variables. When we do so, we get a strongly statistically significant positive coefficient on QGOV and no statistically significant relationship at the 0.01 confidence level for the other two variables. The overall correlation is 0.79, essentially the same as for the two-variable relationship shown in the left-hand scatter plot above…”

I suspect multiple regressions would confirm similar and hope a profesional academic might look into this

Conclusion

I tentatively extend the work of Dolan on the size of government and quality of government to look at four further broad indices of 1) peace, 2)  human development, 3) education and 4) life expectancy. 

In all four cases, quality of government seems to be a more important factor than the size of government. This would be tentative evidence for theories that emphasise the importance of quality - perhaps state capacity - over the size of the state, where societies favour a state role in any given area. 






Notes and Caveats 

Data sheet link available on request. It’s not very tidy but all in good faith. Image below. I may have made errors in the data, as it’s my late night pet -project.

Do read the Ed Dolan Caveats in his blog but repeated here.

“...As in any statistical study, we should be cautious about drawing conclusions about causation. There is nothing in these results to suggest that making a country’s government bigger will automatically make it better. At the same time, it is hard to deny that there is a strong tendency in the cross-country data for larger governments to be better governments, when by “better,” we mean better able to protect property rights, better able to offer impartial civil and criminal justice, and less open to corrupt influences.

Readers are also encouraged to think about the country-by-country data reported in the chart and table above. There is a lot of variety in the world. Too strong a focus either on statistical regularities or on selected outliers can draw us too strongly toward conclusions that, in reality, admit of many exceptions.

For example, the small-government city states of Singapore [is]  rightly admired for [its] prosperity and economic freedoms. However, it gives one pause to note how many small-government countries enjoy neither. Chad, Bangladesh, and the Democratic Republic of Congo  are just the outliers among a whole cluster of countries in that category.

Similarly, a look at individual countries shows that our statistical indicators of “big” and “small,” or of “good” and “bad,” do not always line up with what we mean by these terms in other contexts. For example, many people in the West would readily name Russia and China as countries with governments that are conspicuously both big and bad. Yet, although Russia and China do fall into the southwest quadrant of our chart, they do so only barely. Statistically speaking, neither country is an outlier on either variable…]

Ed Dolan’s two part blog on SGOV and QGOV. 

Peace Index can be found here: http://visionofhumanity.org/indexes/global-peace-index/

Human Development Index and components (both the education and life expectancy - I use 2018 data - ) can be seen here: http://hdr.undp.org/en/data

World Bank Classificatinos are from 2016 (as the 2018 xls wasnt’ working when I compiled the data). The Visuals are H/T Flourish Studios and Google Sheets.

Tyler Cowen on State Capacity Libertarianism 

The Table of data I used is below.

Life expectancy Race, child mortality and GDP

Looking at how life expectancy has risen globally and in a few countries over time.

A large driver of this has been the fall in childhood mortality.

This paints a picture that we’ve achieved much but we still have many challenges to go.

GDP is up. Ideas are up. But other aspects like natural capital are down. And deep poverty while down is still in the hundreds of millions.

UK life expectancy and healthcare spend vs OECD. NHS success story?

UK life expectancy expanded - in line with the OECD average (more or less, there was a little catch up) until recently where (like in a few countries) it seems to be flattening. This is a blunt but well understood measure of a population’s health.

A similar type of trend can be seen in childhood mortality. Although experts can gripe with the data, the overall trend is likely robust. There is also some catch up from OECD average from a poorer start.

This is a good achievement by the UK given what the UK has spent on healthcare since the 1970s.

My general observation here is that the UK has underspend / invested less in healthcare but has managed to obtain an average to above average results.

The under spend as % GDP has been 2 to 4 percent points lower than OECD peers on average. This has been going on since the 1970s. (The World bank data is from 2000, sourced from WHO)

There are many factors that combine to impact life expectnacy and health. Correlation is not causation.

However, I think there is enough data and evidence to suggest that given the amount the UK has invested in health (and social care and education) that if the UK wants to continue the positive trends in health, it will likely have to spend more or at current levels of spend the health out comes will - in my view - likely to continue to tail off.

In this sense, the UK’s NHS has been a unique system that has enabled outsized gains in health outcomes for the amount of spend over the last 50 years.

OECD data.

OECD data.

I can’t make a nice graph widget, but I can show how this % spend on GDP goes back to the 1970s. so this is arguably about 50 years of under spend, at even the lower end of 2% of GDP that’s somewhere in the region of £500bn to £1,000 bn (yes 1 £trillion) in culmulative under spend compared to what would have been spent on the OECD average %.

(Now whether it would have been well spent or what else the UK spent the money on is another debate - maybe the OECD over spent given its outcomes… but given the UK is uniquely low (though Italy is close in some years and has slightly worse outcomes broadly) .

You can see how Germany is approx matching the UK since 1970 on life expectancy and trend (OK it did slowly gain beofre mathcing), but was spending much more of GDP to achieve that.

Impact Investing papers on return, healthcare over 200 years

Two short papers for ESG/IMpact and one for healthcare specialists

 Impact funds earn 4.7% lower IRRs compared to traditional VC funds (Barber et al, 2015, update 2018)

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2705556

“We document that investors derive nonpecuniary utility from investing in dual-objective venture/growth equity funds, thus sacrificing financial returns. In reduced form, impact funds earn 4.7% lower IRRs compared to traditional VC funds. Likewise, random utility/willingness-to-pay (WTP) models of investment choice indicate investors accept 3.4% lower IRRs for impact funds. We rule out alternative interpretations of risk, liquidity, and naiveté. Development organizations, banks, public pensions, Europeans, and UNPRI signatories have high WTP; endowments and private pensions have none. ..”

But also see -  https://hbr.org/2019/01/calculating-the-value-of-impact-investing

“…Over the past two years the organizations we work for—the Rise Fund, a $2 billion impact-investing fund managed by TPG Growth, and the Bridgespan Group, a global socialimpact advisory firm—have attempted to bring the rigor of financial performance measurement to the assessment of social and environmental impact. Through trial and error, and in collaboration with experts who have been working for years in the field, the partnership between Rise and Bridgespan has produced a methodology to estimate—before any money is committed—the financial value of the social and environmental good that is likely to result from each dollar invested. Thus social-impact investors, whether corporations or institutions, can evaluate the projected return on an opportunity. We call our new metric the impact multiple of money (IMM)….” Note, TPG are actively promoting their fund - serious investors, but expect them to be arguing this case.

One confounding problem on IRR, returns is that the idea of the risk taken to achieve those returns is difficult to assess - one could argue practially impossible - and thus risk-adjusted comparisons which would better will never be known and thus this question not ever fully answered.

*

Two Hundred Years of Health and Medical Care: The Importance of Medical Care for Life Expectancy Gains (Catillon, 2018)

https://www.nber.org/papers/w25330

H/T Tyler Cowen, is a long reaching look at how medical care has impacted life expectancy (or not) over 200 years of data in the state of Mass, US.

“Using two hundred years of national and Massachusetts data on medical care and health, we examine how central medical care is to life expectancy gains. While common theories about medical care cost growth stress growing demand, our analysis highlights the importance of supply side factors, including the major public investments in research, workforce training and hospital construction that fueled a surge in spending over the 1955-1975 span. There is a stronger case that personal medicine affected health in the second half of the twentieth century than in the preceding 150 years. Finally, we consider whether medical care productivity decreases over time, and find that spending increased faster than life expectancy, although the ratio stabilized in the past two decades. “