Mark Carney argues that low carbon growth is possible

Mark Carney, Governor Bank Of England, argued that low carbon economic growth is possible. In further testimony he stresses the importance of transition, policy, transparency and risk management while commenting that intangible growth is still important growth.

De-Growth advocates argue decoupling carbon from economic growth is impossible (or extremely hard). Thus degrowth policies may be needed.

(I tend to not be in the de-growth camp, but do think some consumption eg food waste - is wasteful)

The arguments continue to be intense. There is some agreement that brown—>green transition is important regardless of growth stance. Central scenarios point to 3c warming in 2100. Stronger policy + innovation amplified by markets, corporate and consumer behaviour could bring those scenarios down. Complex tipping points, policy failures could swing other way.

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.

Oil CEOs meet to look at targeting carbon scope 3

Bloomberg reports energy CEOs discuss carbon “scope 3” targets. This could be a pivotal change…

“... Targeting Scope 3 emissions would be a big shift for an industry that produces the bulk of the world’s planet-warming emissions, once that could eventually require them to sell far less oil and gas....”

and

“... The talks between the chief executive officers of companies including Royal Dutch Shell Plc, Chevron Corp., Total SA, Saudi Aramco, Equinor ASA and BP Plc showed general agreement on the need to move toward this broader definition, known as Scope 3, the people said, asking not to be named because the session was closed to the press. The executives didn’t take any final decisions....”

Brydon Review into UK Audit

"Language matters." so begins the Sir Donald Brydon Review into UK Audit.

In parts touching on the philosophical, Brydon suggests:

"Audit is not broken but it has lost its way and all the actors in the audit process bear some measure of responsibility."

Recommendations:

• A redefinition of audit and its purpose

• The creation of a corporate auditing profession governed by principles

• The introduction of suspicion into the qualities of auditing

•The extension of the concept of auditing to areas beyond financial statements

• Mechanisms to encourage greater engagement of shareholders with audit and auditors

• A change to the language of the opinion given by auditors

• The introduction of a corporate Audit and Assurance Policy, a Resilience Statement and a Public Interest Statement

• Suggestions to BEIS' work on internal controls and clarity on capital maintenance • Greater clarity around the role of the audit committee;

• A package of measures around fraud detection and prevention • Improved auditor communication and transparency

• Obligations to acknowledge external signals of concern • Extension of audit to new areas including Alternative Performance Measures

• The increased use of technology

Brydon quoting Karthik Ramanna  “I know of no better system than market capitalism to sustain liberty and create prosperity – and market capitalism cannot function without a robust audit function. If we do not save auditing, we cannot save capitalism.” 

And on fund managers.... " I was also rather underwhelmed during the Review by the interest in audit shown by some of the portfolio managers with whom I spoke. Few appeared to read the audit report thoroughly and several took the view that it was enough to know whether or not the auditor had given an unmodified opinion."

I do note, I did not speak to Brydon but have tangential advisory interests through being on an advisory group for IASB and for FRC.

Review can be found here.

The Private and External Costs of Germany's Nuclear Phase-Out

NBER Dec 2019. The Private and External Costs of Germany's Nuclear Phase-Out by Stephen Jarvis, Olivier Deschenes, Akshaya Jha.

“Many countries have phased out nuclear electricity production in response to concerns about nuclear waste and the risk of nuclear accidents. This paper examines the impact of the shutdown of roughly half of the nuclear production capacity in Germany after the Fukushima accident in 2011. We use hourly data on power plant operations and a novel machine learning framework to estimate how plants would have operated differently if the phase-out had not occurred. We find that the lost nuclear electricity production due to the phase-out was replaced primarily by coal-fired production and net electricity imports. The social cost of this shift from nuclear to coal is approximately 12 billion dollars per year. Over 70% of this cost comes from the increased mortality risk associated with exposure to the local air pollution emitted when burning fossil fuels. Even the largest estimates of the reduction in the costs associated with nuclear accident risk and waste disposal due to the phase-out are far smaller than 12 billion dollars.”

Paper Here.

Critique of GDP and carbon Tax, Vaclav Smil

This is a good short critique of the carbon tax (I still think pricing might help but maybe I’m wrong). Followed by a good critique on GDP. 


From Vaclav Smil (Growth) and he knows way more than me on energy. 


“...The largest externality that remains unaccounted for is the undoubtedly very large cost of relatively rapid global warming (that would increase average tropospheric temperature by more than 2 ° C) attributable to anthropogenic combustion of fossil fuels and land-use changes (IPCC 2014). But in this case there is, at least, a reasonable excuse, as the complexities, interactions, and feedbacks of change attributable to rising concentrations of greenhouse gases are extremely difficult to monetize, especially as some regions, some countries, and some economic sectors will also derive various benefits from rising temperatures and from an accelerated water cycle, and as many of these impacts will not be seen in force for decades to come (and hence will be steeply discounted by today’s valuations). As a result, the carbon tax favored by many environmentalists and by some economists would be nothing but a largely arbitrary (and also a very crude) form of internalizing an unknown fraction of the unfolding and future effects of global warming. …”

And Smil on GDP (including the carbon tax critique). 


“... Given the complexity of modern economies, only a broad aggregate measure can capture their growth. This measure, now universally deployed, is gross domestic product. Its oft-repeated definition seems straightforward: GDP expresses the monetary value of all final goods and services that are produced or provided within the borders of a country during a specified period of time (monthly or quarterly in national reports, per year for international comparisons). But measuring GDP growth, and hence ascertaining its disappointing or satisfactory rates, is an inherently difficult matter and one whose systematic practice is quite recent. Its origins go back to the 1930s when Simon Kuznets was asked by the US Congress to estimate the country’s national income (Kuznets 1934). Its scope was defined by John Maynard Keynes, the measure became a key tool for the international financial institutions set up by the Bretton Woods agreement in 1944, and it was widely applied for the first time to the growing post-WWII economies (Coyle 2014).

Before too long it became obvious that, like every aggregate measure, GDP has many drawbacks—but despite suggested adjustments and proposals for alternative accounts, it has become only more entrenched as the dominant yardstick for appraising the achievements and assessing the growth of national economies.

Problems begin with the choice of currency. In order to derive comparable values required for calculating long-term growth rates it is necessary to express GDP in constant monies, that is in inflation-adjusted terms, but that requires continuous, reliable, and broadly based monitoring of price changes. Not doing so may make only a small difference when inflation remains low (as it has been, generally, in the West since the beginning of the 21st century) but comparing costs in current monies during periods of higher inflation rates (in the West they reached double digits during the 1980s) could lead to major distortions. Even in countries with capable statistical services, this results in often considerable uncertainties, as is best illustrated by the frequency and extent of GDP revisions. Zwijnenburg (2015) found that between 1994 and 2013 the mean absolute revision of year-on-year quarterly growth (the growth rate of a quarter compared to the same quarter of the previous year) for 18 countries in the Organisation for Economic Co-operation and Development (OECD) was 0.36% after one year, 0.5% after two years, and 0.61% after three years, with the average three-year value as high as 0.93% for Japan. As the originally assessed growth rates during that period were on the order of 1–3%, such revisions clearly matter.

On the most basic level, proper GDP accounting requires a definition of the economy, that is, putting the boundaries on what gets counted. Because GDP accounting was established at a time when manufacturing was a leading sector of the economy (with shares of 30–40% during the 1950s), its output continues to be monitored in a relatively more disaggregated manner than the contributions of the now-dominant service sector (in itself a highly heterogeneous group of activities) which make up 70–80% of GDP in affluent countries. Counting all final goods and services may seem to be a fairly comprehensive definition of economic activity—but it is not. Even if we knew with great certainty the size of a country’s economy defined by monetary transactions, it would be still difficult to make a proper adjustment for calculating real long-term growth unless we also knew the trend of nonmonetary exchanges or activities, whose share of the overall economy may remain fairly stable for decades but may rise or decline as economies advance or falter. As it is structured, the GDP concept cannot capture nonmonetary exchanges (the barter economy) and unpaid work (such as household chores or child care provided by members of a family or by relatives and friends) or those financial transactions that take place outside the monitored flows of modern economies, deliberately avoiding them or being hidden, a sector known as the informal, shadow, underground, or black economy.

The barter economy, common in all preindustrial societies, has been largely eliminated in modern economies, while unpaid services are as important as ever and unreported transactions are thriving. Housework has been always excluded from GDP, and although it can be argued that most household chores became easier over time, care of the elderly will be taking more unpaid time in all affluent societies with aging populations and rising life expectancies. Interestingly, Britain’s Office for National Statistics estimated that in 2014, when the country’s GDP reached £ 1.8 trillion, the value of unpaid labor was £ 1 trillion (Athow 2016). And counting only what is sold and bought leaves out many important activities, particularly in modern economies with their rising shares of electronic information and digital production: Internet providers charge a monthly fee that includes virtually unlimited access to almost any conceivable category of information, with the marginal cost of searching for news or participating in social media being very close to nothing, and hence excluded from the standard GDP accounts. The size of the black economy can be only estimated but its share of total production was growing during the last decades of the 20th century (Lippert and Walker 1997), and at the beginning of the 21st century its size was put at about 15% of official GDP in affluent nations and at one-third in low-income countries, with shares as high as 40% or more in Mexico, the Philippines, and Nigeria (Schneider 2003). The best available studies show it to be far from negligible even in some of the world’s most affluent countries with generally good governance and with low levels of corruption.

A comprehensive study of the shadow economy in the European Union put the average for all member states at 18.3% in 2015, with the range from 8.3% in Luxembourg to 30.6% in Bulgaria, and with Germany and France nearly identical at, respectively, 12.2% and 12.3% (Schneider 2015). In an older study of 162 countries, Schneider et al. (2010) put the mean at 31% in 2007, with the extremes ranging between 8.2% for Switzerland to 62.6% for Bolivia. How uncertain these estimates are can be illustrated by many comparisons. In a closer study of Germany’s black economy, Schneider and Buehn (2016) compared the outcomes of eight studies using different methods (including discrepancies between expenditure and income and between official and actual employment, a currency demand approach, and surveys) and found that between 2000 and 2005 estimates of the country’s shadow economy were as small as 1% and as large as 15–16% of official GDP. And while Schneider et al. put India’s shadow economy at 21% of official GDP in 2006, a confidential report commissioned by the Indian government (and leaked to the press) put the size of the country’s black economy at nearly 75% of the official GDP (Mehra 2014). And Statistics Canada (2016) claimed that in 2013 the country’s shadow economy was just 2.4% of official GDP and that this share had remained unchanged since 2002, a remarkable fact (if true)—while Schneider (2015) put Canada’s 2015 share at 10.3%, identical to the Australian rate. And then there is GDP’s almost utter inability to capture qualitative improvements.

For decades Bell offered American consumers one model of its standard black rotary-dial phone, and then came push-button dialing, a variety of electronic phones, and eventually cellular phones and smartphones. Successive outlays spent on acquiring these items or paying rental fees tell us nothing about the fundamentally different qualities embodied by changing designs. The same is, of course, true about cars—a rising share of their value is now in electronic components and hence they are mechatronic devices, not simply mechanical machines—and, to different degrees, also about housing and long-distance travel, in terms of both speed and comfort: compare what the same price bought in 1955 with a seat in a propeller-driven Constellation and in 2015 in a Boeing 787. GDP is not a reliable measure of the total economic product, and it is an outright inferior measure as far as the quality of life and real prosperity are concerned. From a long-term perspective, the most fundamental failure of GDP accounts is to ignore diverse forms of environmental degradation caused by economic activities and treat the depletion of finite resources as current income that adds to wealth. These are, of course, utterly unsustainable premises as no society can exist without adequate support provided by natural capital stored in biodiversity and in photosynthesizing species and maintained by many indispensable environmental services ranging from soil renewal to water retention by forests and wetlands (Smil 1994, 2013a). Remarkably, economists call these critical omissions “environmental externalities”: the very choice of the noun is telling because historically they were not an integral part of the cost of doing business and their still far from adequate pricing has been making slow progress. Most major gains have come only since the 1950s, with most of the externalities far from getting internalized. Reducing air pollution is an excellent example of this internalization of former externalities, that is paying higher prices in exchange for a cleaner environment. One of the first large-scale instances of this effort was the elimination of visible particulate air pollution from the combustion of coal in large electricity-generating plants, due to the post-1950 installation of electrostatic precipitators that remove more than 99% of all particles (USEPA 2016a). The next step, starting during the 1970s, was a large-scale adoption of flue gas desulfurization that greatly reduced the risk of acid precipitation, first in Europe and North America, later also in China. Removal of particulates and sulfur raises the cost of electricity generation by about 10%. But most externalities remain entirely unaccounted for. Among the most widespread negative impacts whose costs are completely ignored in product pricing are the declining yields caused by the universally increased rates of soil erosion in intensive row-crop cultivation (of corn or soybeans, two leading grain and legume species); the formation of dead zones in coastal waters caused by excessive runoff of nitrogenous fertilizers causing eutrophication of aquatic environments; the health effects and material damage caused by the photochemical smog that is now common in all megacities; and the rapid loss of biodiversity caused by such diverse actions as mass-scale monocropping and tropical deforestation. The largest externality that remains unaccounted for is the undoubtedly very large cost of relatively rapid global warming (that would increase average tropospheric temperature by more than 2 ° C) attributable to anthropogenic combustion of fossil fuels and land-use changes (IPCC 2014). But in this case there is, at least, a reasonable excuse, as the complexities, interactions, and feedbacks of change attributable to rising concentrations of greenhouse gases are extremely difficult to monetize, especially as some regions, some countries, and some economic sectors will also derive various benefits from rising temperatures and from an accelerated water cycle, and as many of these impacts will not be seen in force for decades to come (and hence will be steeply discounted by today’s valuations). As a result, the carbon tax favored by many environmentalists and by some economists would be nothing but a largely arbitrary (and also a very crude) form of internalizing an unknown fraction of the unfolding and future effects of global warming.

These are not new concerns. Kuznets was fully aware of these deficiencies (obviously not of the effects of global warming but of environmental externalities in general and of other ignored inputs). He asked who could place a value on the country’s rivers or on the skills and capacities of housewives and his suggested subtraction of dis-services from national income estimates was far more radical than most of the recent calls for GDP redefinition. His preference is worth quoting at length.

This writer, for one, would like to see work begun on national income estimates that would not be based upon the acceptance, prevailing heretofore, of the market place as the basis of social productivity judgments. It would be of great value to have national income estimates that would remove from the total the elements which, from the standpoint of a more enlightened social philosophy than that of an acquisitive society, represent dis-service rather than service. Such estimates would subtract from the present national income totals all expenses on armament, most of the outlays on advertising, a great many of the expenses involved in financial and speculative activities, and what is perhaps most important, the outlays that have been made necessary in order to overcome difficulties that are, properly speaking, costs implicit in our economic civilization. All the gigantic outlays on our urban civilization, subways, expensive housing, etc., which in our usual estimates we include at the value of the net product they yield on the market, do not really represent net services to the individuals comprising the nation but are, from their viewpoint, an evil necessary in order to be able to make a living (i.e., they are largely business expenses rather than living expenses). Obviously the removal of such items from national income estimates, difficult as it would be, would make national income totals much better gauges of the volume of services produced, for comparison among years and among nations. (Kuznets 1937, 37)

Economists have suggested fixing many inadequacies of GDP with suggestions ranging from using comparable market rates to value household chores (or shadow pricing measured by time devoted to a task) to quantifying environmental deterioration, and many critics have called for more radical redesigns or for abandoning the measure and adopting an entirely new valuation (Nordhaus and Tobin 1972; Zolotas 1981; Daly and Cobb 1989; Costanza et al. 2009; World Economic Forum 2017). In all cases, the goal is to quantify the extent to which economic development meets society’s needs (for adequate nutrition, shelter, personal freedoms, environmental quality) rather than measuring the magnitude of market transactions….”

Read Smil on Growth, Amazon link here.