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The Most Interesting Chart I’ve ever Made: Energy versus Money Leverage

Figure 1 is perhaps the most interesting chart I have ever made. The purpose of this figure (from my publication here) is to provide context into metrics of net energy and see how they relate to economic data. Here, I’m asking a fundamental question: should our (worldwide) society be able to leverage money more than we can leverage energy? My hypothesis is “no” and would be represented by values < 1 in Figure 1. Clearly the plotted ratio of ratios in Figure 1 is not less than one (for all years) per my hypothesis, so why might this be the case?  As I discuss below, understanding the data in Figure 1 is crucial for making better macroeconomic models of the economy that properly account for the role of energy.


Figure 1.  This is a ratio of how much the worldwide economy leverages money spent by the energy sector relative to how much surplus energy is produced by the energy sector itself.  Specifically this calculation (using world numbers) = (GDP/money spending on energy by the energy system) / [ (world primary energy production – energy spending by the energy system) / energy spending by the energy system)].

I created Figure 1 by dividing the data from Figure 3 by the data from Figure 2.  Figure 2 is a calculation of the leverage of energy, and Figure 3 is a calculation of the leverage of money. I now describe each of Figure 2 and 3.

For a full description of the underlying data and calculations, see Part 2 (and Part 1) of my papers in Energies in 2015.

Net Energy

Net energy provides an additional lens, besides money, to understand how our economy works.  Net energy is the amount of energy that is left over for consumption after we subtract the energy inputs that are required to produce that energy.  The energy production and consumption quantities you see in statistical databases (such as those housed by the Energy Information Administration (EIA), BP, and International Energy Agency (IEA)) is gross energy, often referred to as total primary energy supply (TPES) consumed per year.  For example, the world TPES is approximately 550 EJ as reported by the EIA.

Figure 2 shows the data used in the denominator of the calculation of Figure 1.  The solid red line indicates the average value for the world. The underlying data come from the IEA. This figure indicates that since around 1995, for every unit of energy consumed by the energy industry, the energy industry provides about 14-15 units of energy for all consumers and other industries.  Before 1985, this “energy return on energy invested” was greater than 20 (data are not available to for a viable estimate before 1980).  In the case of this figure, there are no other types of inputs considered besides energy itself.  No wages. No materials. No computers or consultants. Nothing but energy.


Figure 2.  This is a ratio of how much net energy the worldwide energy system produces for all other sectors and consumers after it consumes the energy it needs for its own operation.   The solid red line represents the world average.  The dashed red line represents the average for OECD countries only. Each gray line represents the data for one country (the countries with high values are countries that are net energy exporters). Specifically this calculation (using world numbers) = [ (world primary energy production – energy spending by the energy system) / energy spending by the energy system)].

Money Leverage

Figure 3 is about money, not energy.  Consider adding up all energy spending (in money) by the worldwide energy industry and dividing that by the GDP of the world. A typical quantity is 0.04-0.07, or 4-7%.  Essentially this is an input (spending by energy sector) divided by an output (GDP).  In order to compare these monetary data to the net energy data of Figure 2, I need to phrase them in an equivalent manner.  Figure 2 shows energy outputs divided by energy inputs.  Thus, by inverting the monetary energy spending ratio, I turn it from a ratio of input/output to a ratio of output/input.  Thus, if world energy sector spending was equivalent to 5% (or 0.05), 1 divided by this number is 20. Thus, we can say that the economic output of the economy is 20 times larger than the monetary spending of the energy sectors.  Figure 3 plots this ratio for the world.


Figure 3.  This is a ratio of how much the worldwide economy leverages money spent by the energy sector.  Specifically this calculation (using world numbers) = (world GDP / money spending on energy by the energy system).

Why this is interesting

Fundamentally the ratios of Figures 2 and 3 are about measuring inputs of “something” to the energy industry in comparison to outputs of that “something” consumed or created by the rest of the economy.  In Figure 2 the “something” is energy, and in Figure 3 that “something” is money.  Figure 1 shows the data of Figure 3 divided by the data of Figure 2.

Should the output:input (“leverage” or “return on investment, ROI”) of energy (often termed EROI) be greater than or less than the output:input (“leverage” or “return on investment”) of money?  My hypothesis is that the energy ratio should be larger than the monetary ratio.  Thus, the measure in Figure 1 should less than 1.

The reasoning is as follows.  The energy inputs used in Figure 2 only include energy consumed by the energy industry.  As I wrote before, no other inputs such as wages, materials, offices, or administration are considered.  By considering any number of these other inputs (and converting to units of energy), the energy return on investment ratio can only decrease.  However, the assumption behind the monetary ratio of Figure 3 is that all types of inputs have been included in units of money.  That is to say, the energy sector purchases inputs as energy, machines, and various services from itself and other economic sectors.  Thus, there are many more inputs (theoretically all required monetary investments) considered in the monetary output:input ratio for the energy sector and economy.

So back to my hypothesis that the ratio plotted in Figure 1 should be less than 1.  How can we explain values > 1?  The general (but not satisfying) answer is that GDP (gross domestic product) is a measure of economic throughput that is not backed by anything purely physical, but by what we (as consumers) perceive as valuable.  Thus, we can value a service or product at one level in one year, but change our mind as to the value in another year.  Much value is also currently placed in information-related companies (Facebook, IBM’s Watson, etc.), and there is ongoing debate as to whether the value of this information (e.g., in social network companies) is overvalued.  Is social networking overvalued, as a business, and will these valuations decline if people can’t actually afford to buy new products suggested by the ads targeting them?  I suppose we don’t know the answer, and we’ll eventually find out.

Debt as an Explanation

But I think debt accumulation is likely the best explanation for why the economy seems to be able to leverage money more than energy spending by the energy sector.  To some degree, increases in debt in the 10-20 years leading up to 2008 (when the ratio in Figure 1 reached a value of 1) were responsible for increasing the quantity GDP.   Government and consumer spending beyond their means shows up as increases in GDP.

Also, if we consider increased debt a expectation of increased future consumption, and consumption (and production) require energy, then increases in debt are an expectation for increases in energy consumption.  And don’t get confused here with discussions of “decoupling” energy from economic activity.  There is yet no evidence that worldwide economic growth occurs without increasing total worldwide energy consumption.  Possible evidence for this debt explanation is the fact that debt accumulation stopped in 2007/2007 (with the financial crisis and peak in commodity prices) when the ratio in Figure 1 was no longer greater than 1.  If I were to have the data through 2015, my guess is that the number would have stayed near 1 through 2013/2014 before again increasing in 2014/2015 as oil prices were falling dramatically (assuming the energy return ratio of Figure 2 remained relatively steady).

I also anticipate (could be confirmed by further research) that the ratio of Figure 1 would be < 1 for all years before 1980 leading to the beginning of the Industrial Revolution. Largely speaking, we extract the easiest to reach resources first, and these resources have high net energy (= low cost).  Thus, resources with higher net energy translate to larger values for Figure 2 which is the denominator for Figure 1. Thus, smaller values of Figure 1. Further, I know from my previous research that spending on energy was never lower than around the year 2000 (see my papers here and here for detailed explanations), which is what is indicated in Figure 3 (e.g., the higher the value the cheaper was energy). Energy continually became less expensive since the beginning of the Industrial Revolution until the 1970s and then again (much slower) through the end of the 20th Century.  Thus, the values for Figure 3 (the numerator of the calculation in Figure 1) will always be larger for the previous 100+ years.

This concept of Figure 1 is so interesting because it is likely that the time period of 1985-2007 is unique in all of history as the time period when the economy leveraged monetary spending by the energy system more than the leverage in energy that was provided by the energy system.  This is a ripe area for further understanding of macroeconomic modeling that properly accounts for the role of energy.

The Energy and Economic Narratives

In my book The Economic Superorganism: Beyond the Competing Narratives on Energy, Growth, and Policy, I describe narratives along two axes (see Figure 1): energy and economics. Because people disagree as to the costs, capabilities, and benefits of different energy technologies and resources, proponents of different visions use narratives to convince stakeholders of the validity of their positions.

Figure 1. A diagram of narratives along two dimensions: energy—fossil versus renewable;
economics—technological optimism of infinitely substitutable technology versus technological
realism that the finite Earth imposes limits to growth.

The two energy narratives (fossil fuels vs. renewable energy) characterize the extreme views regarding the desired sources for our future energy system that best meet our future social and economic needs:

Energy Narrative: Fossil Fuels Are the Future

This narrative recognizes that fossil fuels enabled us to achieve what we have today. A proponent might say: “The physical fundamentals of fossil fuels, such as high energy-density and portability, ensure low cost and their continued dominance. Why not use them? Renewable energy technologies require subsidies to entice investment because they cannot achieve the historical or present levels of low cost and productivity of fossil fuels and related technologies. Therefore, we should promote increased fossil fuel use for the foreseeable future. Fossil fuels, and the technologies we have developed to burn them, enable us to shape and control the environment rather than the reverse situation before we invented fossil-fueled machines. Further, fossil fuels are the best hope to bring poor countries out of poverty while continuing
to increase prosperity within developed countries.”


Energy Narrative: Renewable Energy Is the Future

This narrative states we can use renewable energy technologies and resources to sufficiently substitute for the services currently provided by fossil fuels. A proponent might say: “Thank you fossil fuels, but we’ve modernized. We don’t need or want you anymore. Fossil fuel production and consumption create environmental harm both locally over the short-term (e.g., air and water contamination) and globally over the long-term (e.g., climate change) to such
a degree that their continued unmitigated use ensures environmental ruin that will lead to economic ruin. In addition, the concentration of fossil fuel resources means that countries and citizens have unequal ownership of them, creating geopolitical instability over extraction and distribution. Thankfully, renewable energy technologies are now cheap enough to transition from fossil fuels. Further, a renewable energy system is the best hope to bring poor countries out of poverty while continuing to increase prosperity within developed countries.”


Both energy narratives use economic narratives to justify their arguments, and these arguments shape energy policies that affect each one of us. Economic theory in turn informs us how to perform calculations that provide insight into the ramifications of choosing one energy pathway versus another.  My book discusses how one’s economic viewpoint, or narrative, can lead one to ignore important similarities and differences between fossil and renewable energy systems.  Here, I only state the economic narratives for consideration.


Economic Narrative: Technological Optimism

(There Is Infinite Substitution
of Technology to Achieve Growth and Social Outcomes)

This narrative posits unbounded technological change that creates substitutes for whatever we desire. It does not necessarily deny that the Earth is finite, but it does not believe that this fact affects economic or physical outcomes that impact the overall human condition. It is the view of most mainstream economists. A proponent might say: “Technological innovation has and will always address the pressing needs for society. In order to promote seeking of solutions, we need a signal. That signal is the price of a good, or a ‘bad’ (e.g., air pollution), and the signal is provided by setting up a market. Therefore we must establish and promote free markets, private ownership and profits via capitalism, and business competition. This is the way toward continued growth and prosperity. With regard to energy, as long the aforementioned criteria govern the economy, its price always decreases, so there is no need to worry.  Markets best address socio-economic issues because they process information better than any human regulator or government agency.” Got a problem? Make a market for it.


Economic Narrative: Technological Realism

(The Finite Earth and Laws of
Physics Impose Biophysical Constraints on Growth that Affect Social Outcomes)

This narrative takes to heart that the Earth is finite. It is the position of many ecologists, physical scientists, and some economists. A proponent might say: “Humans need food to survive and our economy requires energy consumption and physical resources to function. These facts very much matter for economic reasons because the feedbacks from physical growth on a finite planet will eventually force changes in structural relations within our economy and society more broadly. These changes can have positive or negative outcomes for our perception of the human condition, but to create positive outcomes, we must perceive, accept, and adjust to the physical limits of a finite Earth and relate our economy to physical laws and processes. Markets can work, but they have problems. Theoretically they can include all important pieces of information, but practically, finite time and incomplete information prevents formation of pure price signals.” The narrative is summed up well by a statement attributed to economist Kenneth Boulding: “Anyone who believes that exponential growth can go on forever in a finite world is either a madman or an economist.”


Consider these 4 narratives along the 2 axes of Figure 1 anytime you read and article, policy, or book promoting or disparaging a particular energy policy or technology.

How economic theories influence energy policy – Feb. 27, 2021 Opinion Editorial (Austin American Statesman)

February 27, 2021 (OPINION): “How economic theories influence energy policy“, Austin American Statesman

“Simply put, more of us need to think about the broader relationship between energy and economic theory” Read more …

ERCOT Blackout Feb. 2021: Takeaways and Notes from Texas House Joint Committee Hearings February 25, 2021

Texas House of Representatives Joint Hearing

Joint Hearing: State Affairs and Energy Resources

February 25, 2021

Summary and notes by Carey W King (http://careyking.com/)   


Committee members. 1

State Affairs Committee: 1

Energy Resources committee. 2

Power Generation: 3

Curtis Morgan (CEO, Vistra). 3

Mauricio Gutierrez (President & CEO of NRG). 4

Representative Smithee: 5

Representative Hunter: 5

Representative Darby. 5

Representative Anchia. 5

Rep Raymond (?). 6

Representative Howard (on electricity and NG markets): 7

Power Generation: THAD HILL, CEO of Calpine. 7

Session with Solar and Wind Industry Organizations. 7

Allen Nye (CEO of Oncor). 9

Kenneth Mercado (Executive Vice President, CenterPoint) 10

Bill Magness (CEO of ERCOT). 11

DeAnn Walker, Chairwoman of PUC. 11



Takeaways from February 25, 2021 House Committee meeting

  1. What: Some people giving testimony and some House Committee Members openly questioned if the ERCOT wholesale market structure can indeed deliver the level of electricity reliability that they desire.
    1. Why important? No one defines “reliability” the same. CEO of NRG suggested that Texas Legislators have the opportunity to define “resilience” and “reliability” for ERCOT and the electricity system.  House members (rightly) see the 4-5 day partial blackouts as a failure, as well as any rolling blackouts, but some had difficulty grasping that ERCOT actually also succeeded in performing its most critical job which is to operate and train its staff to keep the grid operating, at some level, under any unforeseen circumstances, and that is indeed what happened during the February 14-17, 2021 winter storm – the grid did not go completely dark.
    2. Curtis Morgan of Vistra stated: “I was a big proponent of this [ERCOT energy only] market, and my faith has been shaken.”
  2. What: Natural gas supply was insufficient to power all natural gas capacity that was functional (or available to operate).
    1. Why? One major reason was not enough natural gas facilities (some combination of owners of wellheads, processing facilities, pump stations, etc.) registered with transmission and distribution (T&D) companies as “critical loads”.  There is a process set up for them to register in this way.  Thus, when T&D utilities were asked by ERCOT to shed load (cut off power), they unknowingly cut off facilities that supplied natural gas to power plants.  Nye of Oncor (serving the Permian Basin area) stated that they had 35 NG facilities on their critical infrastructure list coming into the week of Feb. 14, and during the week it increased to 168.
  3. What: There is no organization (PUC or ERCOT) that considered themselves to have the authority to mandate weatherization of power plants.
    1. Why important? Weatherization would have helped, but it was not 100% of the problem. Testimony from power generators stated their availability of NG power plants was 90% for Vistra, 80% for NRG, and 10 of 12 plants for Calpine.  Both thermal power plant generators and the representative of the industry association that represents wind farms (and solar, batteries, natural gas) said there are tradeoffs in preparing for hot summers versus cold winters.  Ice on wind turbine blades is a major issue, and several options (from control systems to different features on turbines) are being explored.
  4. What: One thing that all committee members and those giving testimony could agree on: they need better communication.
    1. Why? The main communication point that the public did not receive is that they were in a severe emergency situation (such as in a hurricane) in which rolling blackouts were not going to occur, they should seek shelter, and they should prepare for days without power.  People with this warning (beforehand) or clear statement (during the blackout) could have made more informed choices for their safety and well-being.
  5. What: Texas House committee members were frustrated that if they have previously made legislation mandating that state offices (e.g., PUC) or other groups (e.g., ERCOT) file annual reports, that all of these annual reports are not diligently reviewed every year.
    1. Why important? I never heard a discussion of whether agencies fully staffed and funded to review every mandated document under their domain.



House Committee members

State Affairs Committee:

Chair: Rep. Chris Paddie
Vice Chair: Rep. Ana Hernandez
Members: Rep. Joe Deshotel
Rep. Sam Harless
Rep. Donna Howard
Rep. Todd Hunter
Rep. Phil King
Rep. Eddie Lucio III
Rep. Will Metcalf
Rep. Richard Peña Raymond
Rep. Matt Shaheen
Rep. Shelby Slawson
Rep. John T. Smithee


Energy Resources committee

Position Member
Chair: Rep. Craig Goldman
Vice Chair: Rep. Abel Herrero
Members: Rep. Rafael Anchia
Rep. Tom Craddick
Rep. Drew Darby
Rep. Jake Ellzey
Rep. Charlie Geren
Rep. Tracy O. King
Rep. Ben Leman
Rep. Oscar Longoria
Rep. Ron Reynolds



Power Generation:

Curtis Morgan (CEO, Vistra)

Mr. Morgan stated:  “I was a big proponent of this [ERCOT energy only] market, and my faith has been shaken.” We’re risking this economic engine of this country [implied as Texas].


Main problems affecting the blackout:

  • Not fully understanding the natural gas system integration with the electric system (how the natural gas distribution delivers gas to power plants)
  • Weatherization: It is not clear that we should build enclosures around power plants because in the summer in Texas, it gets very hot and can detract from summer performance.
  • We could have had more public communication on telling people to be prepared for a winter event
  • We did not have an updated list or prioritization of critical infrastructure, such as to determine which infrastructures lose gas or power first in an emergency. We were turning off compressors and natural gas facilities, and that is not desirable when gas supply is critical.

We produced 35% of total ERCOT generation during February 15-17, and we generally have 18% market share.

Coal Power: They mine coal for Oak Grove and they had issues of their local coal delivery (via local rail). Also, they don’t normally cover their coal piles that got wet or froze up. So the coal became gummy and blocked the process of pulverizing coal to input into boilers.

Natural Gas: Their natural gas fleet was 90% available at NG plants, but they could not get the gas at the pressures that were needed to operate.

Nuclear: They came within 3 minutes of having the Comanche Peak (nuclear power plant) automatically trip off due to low grid frequency.


Fossil fuels vs. renewables: Mr. Morgan brought up how zero marginal costs of renewables stresses the market structure.  We’re going to need to investigate a change in market structure. This is a policy level change in decision to figure out how to deal with this “We are at a crossroads”. We need to continue to figure out how to evolve the competitive markets.  “There is a policy angle here”.  “There is a big debate in this country on the future of fossil fuels”.  We need to have revenues for companies to invest in capacity.

The lack of an enforced weatherization standard is not the entire problem that occurred on Feb. 14 and 15, 2021.


When asked why his company does not have reserve gas on site, or if more NG on site would have prevented the ERCOT blackouts the week of Feb. 14 (e.g., with 3 or 5 days of storage)?   Mr. Morgan:  The system has been so reliable (99.99%) that it doesn’t make economic sense to store more NG.  We do have some offsite storage and deliver it through price. More storage would have helped, but hard to say how much. Some of us have dual fuel capability, and we did lean on that a bit (and was limited by diesel trucks coming in).




Mauricio Gutierrez (President & CEO of NRG)

None of their customers will be exposed to high energy bills.

They have 8 GW of generation capacity and it performed at 80% of its capacity.  They produced almost 2X the amount of electricity as they produced in normal winter times at the beginning of the month.

There were 3 main reasons for lower generation from NRG fleet:

  1. Weather-related equipment failure
  2. Frequency
  3. Gas system deliveries


There are many factors that impacted their power plant performance, and they are:

  • South Texas Project (nuclear) Unit 1 went offline due to a freezing issues of an air service/sensor line
  • WA Parish units 5 and 7 (coal units): experienced a frequency trip, and both were online 24 hours later.
  • Greens Bayou went offline 2 times due to low NG delivery issues, but came online within hours

Gutierrez said there is now the chance for the Legislature to define “reliability” and “resilience” for the electric grid. The state agencies can find the best way to achieve these goals.  “Give industry the guideposts”.  There is no standard for weatherization. There is the opportunity to have that conversation.

When asked why his company does not have reserve gas on site, or if more NG on site would have prevented the ERCOT blackouts the week of Feb. 14 (e.g., with 3 or 5 days of storage)?   Gutierrez:  We need to think about the quantity of gas needed to store many days of NG on site. You’d have to store NG as LNG because the quantity is so large.  This is cost prohibitive.

It is important that we look at extreme weather in a different light, given what we have seen.   I believe climate change is real, and as a company we [NRG] are targeting to reduce carbon emissions 50% by 2035 and net zero by 2050 in accordance with United Nations targets to 1.5 degree C rise.







Representative Smithee:

He stated it seems ambiguous as to whether ERCOT is a governmental organization, and this is in decision at Texas Supreme Court.  He wondered if there is any reason we can’t make ERCOT a government agency under PUC or other agency?


Representative Hunter:

To each person testified, Representative Hunter asked pointed questions about who (persons or entities) were at fault.  He asked questions such as: Who’s at fault? I don’t want to hear about “systems”?  I want people to know who screwed up? I want details.

Answers to these questions were generally that many parties are responsible: 1) natural gas suppliers, 2) power generators, 3) Texas Public Utility Commission, 4) ERCOT, and 4) transmission and distribution utilities

Representative Hunter emphasized the need for better communication by all parties (power generators, utilities, ERCOT, Public Utility Commission, Governor’s office).


Representative Darby

This “feast or famine” 9000 $/MWh creates volatility that doesn’t really incentivize financing.

He emphasized the need to revisit how to incentivize investment in ERCOT outside of the 9000 $/MWh offer cap of the Operating Reserve Demand Curve.



Representative Anchia

Rep. Anchia expressed that the current ERCOT market design seems to have the perverse outcome that we can’t incentivize new baseload power to be installed unless we have extreme weather that juices up costs.

Rep. Anchia: Does the market still have perverse outcomes and increases volatility that we need to address?

  • Morgan: yes
  • Gutierrez: yes


Mr. Morgan responded to Rep. Anchia that much of their equipment (they buy?) is designed to operate at 10 deg. (F?), and they weatherized $10 million was supplemented to try to get us closer to 0 degree capability, and these were more short term changes


Mr. Morgan responded to Rep. Anchia stating that the ERCOT market has have increased volatility relative to years ago due to the 9000 $/MWh offer cap and steepness of the Operating Reserve Demand Curve.


Rep. Anchia stated we need to create a market that avoids too much volatility and scares investors.  A recent Wall Street Journal survey suggests that the ERCOT wholesale matket design has caused Texas customers to pay 10s of billions (?) more than other areas.

  • Gutierrez: I disagree with WSJ survey article.  EIA shows Texas has lower 1/3 prices.  The wholesale rate has kept coming down.  I think competition has helped Texas.
  • Morgan: I agree with Gutierrez.




Rep Raymond (?)

Asked for ideas in 1 week: Last session I introduced HB 34 on emergency communication system. It didn’t get a hearing to pass. Hopefully now it will.  He asked those giving testimony to tell the legislature what can be done to make this better, and report back in 1 week.


On subsidies: During testimony of Mr. Clark and Mr. Hemmeline, Representative Raymond stated that we have to try to move away from politics as last week’s events are so tragic.  He realized that people sometimes don’t like discussing tax credits and subsidies etc.  But he said we should talk about all the tax credits that oil and gas gets (state and federal), let’s put it all on the table.






Representative Howard (on electricity and NG markets):

I’m interested in the market issues.  We sort of know how things work but not all of the details.  What about a lower price cap with a capacity market? Do you know what you would really want?  What structure meets the needs of reliability, affordability, and lower risk (even it not financial risk, but risk to livelihoods)?  How do we restructure?  Since NG prices are not capped, this sounds like it doesn’t work.

Morgan:  We could consider a capacity market. This does keep some old capacity on the system that only runs 1 week or so per year. But that might be nice in the situation such as last week. There are things we can do on the “all energy” market. We can increase the amount of reserves that are required and then drop the price cap. Let’s remember, ORDC is a construct, but the pure marginal cost system wasn’t working either.  We could add a specific product for fuel security.  We can’t ignore the idea of re-regulation, but there is a reason we left that idea and I think it has served us well, so I’m not suggesting we go back.  I like idea of some reduction in price cap with an increase in reserves, but I’m not advocating yet.





Power Generation: THAD HILL, CEO of Calpine

Hill: We had about 2000 MW going offline at about the same time.

  • Freestone power plant: We think a relay leading to “balance of plant’ (runs pump), and we think this was triggered off by frequency imbalance
  • Deer Park: One of the relays opened. This is usually due to voltage and frequency caused. We think it was a frequency issue.
  • Plant in Corpus Christi: This plant went off due to losing gas supply (at the “gas yard”) which lost electricity. The gas crew flew in a generator to get the gas yard back operating.

We started losing gas supply broadly by late morning or early afternoon Feb. 15th. These were back on Wednesday (Feb. 16th). We had some firm capacity and producers cut us off since they couldn’t get the gas into pipelines.  40% of their deliveries were cut from suppliers on Wed. Feb. 16.  There were times when 40% were offline due to loss of gas supply.

Freezing at out power plants:  We started in 2011 on best practices with ERCOT and TRE, and we do this every year.  We still lost 2 of 12 plants due to freezing conditions.



Session with Solar and Wind Industry Organizations

Charles Hemmeline (Executive Director, Texas Solar Power Association)

Hemmeline:   Solar output generated more than ERCOT planned (starting Feb. 15?) given expected generation.  Several solar sites were set offline, many (200+) inverters had to be manually reset, and one solar photovoltaic plant was shut down due to icing on transmission lines.


Jeffrey Clark (President, The Advanced Power Alliance)

Jeffrey Clark:    We represent, wind, solar, batteries, investors, and even NG customers.  This issue has shaken my confidence in a reliable system, and we have to fix this going forward.    We also had a failure of transmission.  Freezing fog is what affected some wind turbines.  We’re looking at ways to shed ice from wind blades, limit ice accumulation, and other methods to keep wind turbine blades from icing.


Jeffrey Clark (on renewable industry obligations in ERCOT market):   It is important that most renewables are funded via Power Purchase Agreements.  There is a perception that wind and solar can just show up and produce whenever they want to, and don’t feel repercussions.  These generators have been affected by the grid blackout.   When do we change any ERCOT rules? What are the mechanisms?  You can be assured that wind and solar members of my organization did not benefit from the high prices and events we experienced.


Jeffrey Clark (on wind turbine performance):   Mechanically, we’re aware of weather issues, but we are assessing if this is a “new normal” and how do we make the power available when needed.   Freezing fog in San Angelo/Sweetwater area had a particularly rough impact.  We’re looking into that.  Shaking ice off of blades is possible but tricky (e.g., if you shake off ice above the nacelle onto the nacelle). We’re talking with OEMs on the options for de-icing on wind turbine blades.

Cold weather by itself is not an issue in itself. There are heating elements to keep lubricants functioning properly.  The typical [wind turbine] machine can go to -15 deg. C (some to -30 deg C).  So it is not the cold itself that is the problem.

Question: Is snow generally a problem?  Clark: Every region had trouble with power generation, even in SPP and West Virginia.  It is the icing of the wind turbine blades that seems to be the major problem here.


Clark was asked: If we are going to have a discussion of how we get more capacity, are we going to have to consider how subsidies for wind and solar affect generation investment?   Clark:   I think we need to look to all subsidies.  Coal has been subsidized since before we were a country.




Allen Nye (CEO of Oncor)

Nye:   We did plan to do rolling outages, and we did this at first late Feb. 14 and early Feb. 15. At 2:02 am Feb 15 we experienced 59.302 Hz and this was a critical event. By 4:43 we know multiple gen was offline.  By 8:03 state was shedding 16 GW.   Why was 2:02 am important?  The importance of under frequency relays are required to have an automatic response to drop load faster than people can respond. They are the last measure to prevent total grid blackout.  They are set to trip at 59.3 Hz.  There were within 0.002 Hz of getting to this limit.   We did have some under frequency relays trip, we don’t know why some did or didn’t.    The situation was so fast we were worried about customers being in dark for say 1 month if ERCOT went completely dark.


What about inability to do rolling blackouts?    Nye: We’ve got to communicate better.   We should have contacted people to let them know that rolling blackouts of 15-30 minutes were not going to happen anymore.

We are required to have 25% of our load on feeders that have special devices called under frequency relays.  To get to 25% of load, this is 40% of their feeders that have these relays, and these circuits stay online 100% of the time to act in emergencies and these feeders STAY ON ALL THE TIME because we need that automatic control capability.  The distribution of these is to GEOGRAPHICALLY DIVERSE to buffer the system (he can show the maps of these) and they are generally heavier when you have more load.  There are more in urban areas since there is more load there. They are distributed based on where the load is NOT rich vs. poor areas. He gives a campfire analogy to say these relays are like

2nd bucket of critical circuits make up 8-9% of his feeders that serve hospitals, critical care facilities, airports, 911 call centers.  Now this leaves only 51% of feeders that are left as even possible to rotate or turn off.

My Nye knew that equity would be a question. He called COO Debbie Dennis and Chief Counsel to make sure they were not cutting off people in an inequitable manner.  We (Oncor) were as equitable as we could be.

Total premises out of power in Oncor regions:

  • Dallas NE: 47% (preston hollow, highland park
  • Dallas N: 53% plano, richardson,
  • Dallas SW (I30 corridor): 47%

Other metrics they used, # underfrequency relays, # loadshed feeders, % customers interrupted and all of these are pretty equal metrics. I see no institutional equity.


Speaker Craddick: Are O&G producing wells not on critical infrastructure with you, Oncor, but they are with Centerpoint?  Thus you shed load associated with O&G production, so do you know how that impacted the rest of the grid?

Nye:   On gas supply issue, after 2011, there was a push that critical gas facilities were on a critical list to provide gas.  There is a process to be designated as such, and to your point (Craddick), I don’t know how power plants get gas or who is delivering.  The NG producers have to tell me (Oncor) if they are delivering gas to generators, otherwise I don’t know.  We had an identified 35 specific facilities that were delivering gas and we never cut those off from electricity.  During the event, PUC Chairperson Walker would call with names of folks indicating desire to turn on the power so they could deliver gas, and we did this, and by the end of the event we added 168 more locations to the critical list and we never again turned them off.   We need better coordination of NG producers and generators with T&D.


Question from Representative Hunter: Here comes March, another storm is coming, what do you think you can do better?

Nye:   Communication for sure. We received more inbound telephone calls in 2 days than we did in all of 2020. Our phone system (with AT&T) crashed and our customers could not get through to us. Make sure we have adequate technology for people to contact us.  Make sure we are talking to legislature better.  Better communication with O&G suppliers to not cut them off.  Work on water districts and know much they can be rotated.   Biggest issue with water utilities is they don’t like to be surprised (so tell them the plan).  We had about 1.33 M out on their system at one time, but on Wed. when they were allowed to turn on more, all but ~140K were able to come online and this was mostly due to ice storm damage around Waco/Temple/Killeen area. SO this tells me Oncor was generally ready to come online when they could (T&D was generally working).  This last ~ 100K customers was actually pretty tough to turn back on.   We can use data analytics to more quickly know what parts of our system are broken.  We can encourage conservation (as mentioned by Mercado as Centerpoint has done).  For our industrial customers, who are mostly at transmission voltage, and they are at backbone of system and we didn’t want to turn on transmission level lines.  Over 50% of industrial customers voluntarily came down, so we can use that idea going forward.


Kenneth Mercado (Executive Vice President, CenterPoint)

Rep. Herndandez: [To Mercado]: We had a visit how you determine who to turn off. There are “buckets” of types of loads.

Mercado: We look at the circuits in thinking of load shed, we don’t look at neighborhoods.  The load shed is pre-programmed.  Heavier demand for load shed where there are larger loads.  We got 59 orders for load shed from ERCOT, and each order changed the buckets of load shed changed.  We don’t have the infrastructure in our telecommunications to do more coordinated load shed using smart meters?  We have to measure and trigger load shed in milliseconds. The only way we can actually measure load is via SCADA system.   We need to figure out a way to get the meter speed of communication to our feeders faster.


Question from Representative Hunter: Here comes March, another storm is coming, what do you think you can do better?

Mercado:    Not so much to add. Communications is key.  I realized how important it was to be an expert communicating with the public in real time. The problem with my message on Day 1 (with NPR, Houston stations, etc. that I then learned to correct) was I could not tell them “how long” the grid will be down.  I only know what was happening in our company, so I was limited in knowledge, and we need more information to make people comfortable.  We need a better software approach for better load shedding.  We planned for losing 2-3 units, but now we have a situation when 50% of generation can go out, and we need a better solution.  We need to be more transparent and dynamic in our load shed while still protecting critical loads and underfrequency relay feeders.


Mercado:  Due to turning circuits on and off many times, we had to replace 1000 pad-mounted transformers after this event (due to their cycling broke them)



Bill Magness (CEO of ERCOT)

Magness: Texas suffered. Our goals is to prevent this type of event again.  We are like air traffic control for the ERCOT grid (90% of customers, 75% of land mass).  We can only stay at 59.4 Hz for 9 minutes before generators automatically trip offline from low frequency relays.  Figuring out how to actually do rotating blackouts is critical.

Mr. Magness was repeatedly criticized for ERCOT not having a more effective and direct communication that the grid situation was so severe that rolling blackouts were not going to be able to be in place and that some regions of the grid were going to be in a long-term power outage while some regions were going to stay on.


[note from this note taker: Apologies for not as many notes on Bill Magness testimony]


DeAnn Walker, Chairwoman of PUC

Walker:  By statute ERCOT is accountable to the PUC.  PUC can apply penalties per PURA or ERCOT protocols. Can impost administrative penalties, and they max at $25K/day/violation.  Largest to date is $2M.   She noted that the FERC 2011 report had 26 recommendations but none to PUC [[Note: but PUC would have been involved in overseeing and agreeing to any new mandates]].   Quanta Energy Services ensured that 2011 legislation calling for a report on preparedness, that a report was filed, and it had 9 recommendations for PUC and PUC implemented all of them.

I don’t think PUC has explicit authority to require winterization of generation because we’ve not been given clear authority.   The 2011 TX bill did have this requirement but it was removed before passed.

Each year ERCOT is to file a report on weatherization plans, and it filed that report in January 2021 stating compliance of the power plants.

Regarding the PUC order on Feb. 15: They heard that how their models we rerunning, in load shed that you will go to 9000 $/MWh cap.  But ERCOT was getting reserves and bringing on customers, and so the reserve was sitting there and sending the signal that not all generation was needed. So we told them to move to 9000 $/MWh.  On Feb. 21 we had another emergency meeting, we urged all REPs to delay their invoicing to customers, and not disconnect them, and give the option for a long-term payment plan. This only applies to IOUs, not municipal utilities or co-ops.

Here are some things for PUC and community to work on:

  1. Better electric and gas coordination. After 2011 we worked on these issues, but over time we were not as diligent.
  2. Look at the overall market. This 9000 $/MWh cap was never meant to go for 9 days.
  3. Whether or not I have the authority, I was told in the Senate that I did have the authority, but I don’t think I do.  Need to make this clear.
  4. ERCOT board was a big issue. You need to consider if changes are needed in the makeup of the ERCOT board.

On Wed. Feb. 10, we knew a storm was coming in, but not 100% sure how bad.  I had a generator call me (Feb. 10 or 11) and said 3 of their units we going to be curtailed and needed help getting NG.  The RRC quickly passed an order to allow electric generation to have high priority getting gas.  In the moment, she was discussing coordination in the NG supply chain (well heads, processing plants) and worked with Oncor to get these facilities power turned on.  Typically their call center is not open on the holidays or weekends, so she did keep it open on the weekend.  We “worked” with the industrial customers telling them they need to have them come offline.  That Thursday and Friday she was asking generators and TDUs checking to see that PUC could do for them.  What did you know and what did you know … really I started actions on Wednesday (before the storm?)


Representative Lucio criticized the Chairwoman Walker and the Public Utility Commission as largely lacking any communication to the public on the severity of the electricity crises and what they can do to prepare even though he believes the PUC (not ERCOT) had the responsibility for this communication.


[note from this note taker: Apologies for not as many notes on DeAnn Walker testimony]


3 ways Texas can make its electric grid more resilient once power outages end

OPINION: 3 ways Texas can make its electric grid more resilient once power outages end 

MarketWatch, February 17, 2021

In the face of ERCOT’s rolling blackouts during the 2021 Valentine’s Day winter storm Uri, resist blaming one power source because that detracts from making the entire electricity and energy system reliable.  Read more …

Explanation of the Jevons Paradox (or “backfire” effect) using the HARMONEY model

December 6, 2020

In this blog I use my HARMONEY (“Human And Resources with MONEY”) economic growth model (also see this free early version) to demonstrate the dynamics of the Jevons Paradox: that an increase in end-use efficiency leads to an increase in total resource extraction, rate of resource depletion, and final level of depletion.

Here I summarize some important features and assumptions of the HARMONEY model to give context for why it exhibits the behavior summarized below:

  • Natural resources: There is only one natural resource, and it is modeled as something akin to a forest where the resource can grow back (at some rate) after it is depleted. By this assumption, the economy can also continuously extract resources at the same rate the resources are regenerated as sort of a steady state economy.
    • As resources are depleted, it takes more resources to extract the next unit of resources. This presents the ability to check the feedbacks of going after harder-to-reach resources after accessing the easiest resource first.  It also allows me to calculate net energy return ratios, the so-called “energy return on energy invested” but what I will call (in later figures) the “net external power ratio”.
  • Population: Population is endogenous such that population growth and decline is dependent on the level of per capita resources consumption. If there are not enough natural resources left for households to consume (per person), then population can decline and level off.
  • There are 2 industrial sectors:
    • The “goods” sector uses labor and capital (e.g., machines) to make new capital.
    • The “extraction” sector uses labor and capital to extract resources.
  • Capital requires resources consumption for
    • Its operation (e.g., it needs fuel to operate)
    • Its creation (e.g., capital is made out of natural resources)
  • Prices: I keep the assumption from the main results in my HARMONEY paper (King (2020)) which is that prices are calculated by assuming a constant markup on the full cost of producing outputs (full cost includes wages, intermediate costs, depreciation, and interest payments).

Here I’ll focus on changing the parameter that affects how many resources are required for consumption to operate capital to produce a unit of its output.  Equation (1) describes the quantity of natural resource consumption required during the operation of capital where K is the amount of physical capital, CU is the capacity utilization (a number between 0 and 1 indicating the fraction of the time the capital operates), and η is like an efficiency term, but its units are different.  The symbol η represents “resources consumed per unit of capital” and its units are [resources/(time·capital)].


natural resource consumption to operate capital = η·K·CU     (1)


Equation (1) holds for both goods sector operation (e.g., fuel to operate machines that make more machines) and extraction sector operation.


Demonstrating Jevons Paradox (or the backfire effect)

I will show a series of outputs from the HARMONEY model. There are two simulation results shown on each figure. The solid line represents the simulation where each η remains at a constant value of 0.16 throughout the simulation.  The dashed line represents the simulation where each η decreases, starting at year = 50, from its maximum value of 0.16 to a minimum value of 0.0533 as a function of how fast new capital is created (e.g., rate of investment).  Importantly, a decreasing η represents the SAME effect as increasing thermodynamic efficiency of an electric motor, steam turbine, combustion engine, etc.   Figure 1 shows the constant η for the first simulation and the decreasing η for the second simulation.

Figure 1. The amount of resources consumption, or η, to operate a unit of capital in (left) the extraction sector and (right) the goods sector.  Solid line = constant η (constant efficiency).  Dashed line = decreasing η (increasing efficiency).


Figure 2 shows the amount of resources that resides in the environment, yet to be extracted.  In the constant efficiency scenario, the resource can get extracted to a level of near 65 units of resources remaining (65% of its maximum possible level) at its most depleted state.  In the increasing efficiency case, the resource is depleted to near half of its maximum level at about 50 units of resources remaining at its most depleted state.


Figure 2. The amount of natural resources available, or remaining, in the environment for the economy and population to consume decreases when machines become more efficient.  Solid line = constant η (constant efficiency).  Dashed line = decreasing η (increasing efficiency).


Figure 3 shows the resources extraction rate that increases for the dashed line increasing efficiency scenario.   (NOTE: By the definition of the resource as a forest, the maximum resource extraction rate occurs when the resource is depleted to half of its maximum level. I have chosen the parameters to not extract (much) past the 50% level for the purposes of this blog as this most accurately represents our primary use of fossil fuels.)

Figure 3. The rate of resource extraction increases when machines become more efficient.  Solid line = constant η (constant efficiency).  Dashed line = decreasing η (increasing efficiency).


Figure 4 shows a higher human population for the scenario in which there is increased machine efficiency.  If a model assumes a constant or exogenous population growth, then it probably cannot exhibit the backfire effect (or Jevons Paradox).  The reason that population increases with higher efficiency is that after resources are consumed to (i) operate machines and (ii) make more machines, the higher efficiency allows for more resources to be left for human consumption such that death rates remain low for a longer period of time that in turn allows population to increase for a longer period of time.  Eventually, population levels off even in the increased efficiency scenario, but in a world also with more machines (more capital).

Figure 4. The human population increases when machines become more efficient.  Solid line = constant η (constant efficiency).  Dashed line = decreasing η (increasing efficiency).


Figure 5 shows the amount of total capital that is higher for the scenario in which there is increased machine efficiency.  The reason that the capital stock increases with higher efficiency is that after resources are consumed to operate machines, the higher efficiency allows for more resources to be left for the creation of more machines.

Figure 5. The total capital in the economy (both for the extraction and goods sectors) increases when capital operates with higher resources efficiency.   Solid line = constant η (constant efficiency).  Dashed line = decreasing η (increasing efficiency).


With increased capital, population, and resources extraction (the of the major “factor inputs” to economic production) as efficiency increases, there is also increased net output of the economy as shown in Figure 6.

Figure 6. The net output, or GDP, of the model economy is about two times larger after the increase in capital resources consumption efficiency.    Solid line = constant η (constant efficiency).  Dashed line = decreasing η (increasing efficiency).


Clearly increased efficiency allows for (i) higher resource depletion, (ii) higher extraction rate of resources, (iii) an increased population, and (iv) more capital accumulation.  For the latter two stocks, population and capital, higher operational resource efficiency enables more resources to be allocated to the accumulation of both more people and capital that do more work.  This is consistent with the idea that more useful work, which is all energy inputs (technically exergy) times their full conversion efficiencies, goes hand in hand with more GDP.  Thus, by making choices to increase efficiency in the real economy, so far (globally to date) this has translated to more useful work, resource extraction, and net output (or GDP).

Figure 7 shows the real price of natural resources and goods (or machines).   With increasing efficiency (or decreasing η in the model), the price for a unit of natural resources increases relative to a constant efficiency world, and this is precisely the trend we’ve experienced for world oil prices that increased after the 1970s, when oil efficiency efforts started.  To date, oil prices have yet to return to the low prices experienced for the 90 years previous to 1974.  The price of goods (or machines) decreases with the increasing efficiency in their operation.


Figure 7. (a) The price of natural resources increases as η, the amount of resources to operate a unit of capital, decreases.  (b) The price of goods (or machines) decreases as η, the amount of resources to operate a unit of capital, decreases.   Solid line = constant η (constant efficiency).  Dashed line = decreasing η (increasing efficiency).


For the net energy geeks out there, Figure 8 shows the “net external power ratio”, or NEPR, which is the same concept that many people refer to as EROI = “energy return on (energy) invested”.  (See my previous publication for reasons why I prefer to use NEPR as a more specific term.)  Equation (2) expresses the idea behind the mathematics.


NEPR = (resource flows available for use outside of the extraction sector) /  (resource inputs to operate extraction capital + resource inputs to create new extraction capital)    (2)


When machines consume less resources for their operation, then there is period in which NEPR increases before reaching a maximum from which it again declines.  This increase in tandem with increasing efficiency represents an increased net resource flow available as “net output,” which in the economic sense is that output available for consumption and investment.


Figure 8. The net external power ratio (NEPR), often referred to as EROI (= energy return on (energy) invested), increases in response to an increase in capital operating efficiency since a higher fraction of total resource flows can temporarily go to net output.   Solid line = constant η (constant efficiency).  Dashed line = decreasing η (increasing efficiency).


Figure 9 shows the wage share, or percentage of GDP that is paid to wages, increases during the time that efficiency is increasing from about year = 50 to year = 110.  An increasing consumption of resources and GDP can thus translate to a higher (or at least a share decreasing at a slower rate) distribution to wages.

Figure 9. The share of GDP that is paid to wages (or workers).  Solid line = constant η (constant efficiency).  Dashed line = decreasing η (increasing efficiency).


Figure 10 shows that the debt ratio is temporarily lower while efficiency increases. Not shown (due to stopping the simulation) is that the debt ratio in the efficiency case also starts to decrease because resource constraints eventually inhibit investment below profits such that companies pay back debt.  See the paper for more details.  To understand the current economic situation in the U.S. and most OECD countries, it is critical to understand the context of high levels of private debt of companies and consumers (debt of consumers is not part of the HARMONEY 1.0 model).  Increasing efficiency can increase output faster than debt (hence lowering debt ratio), but only for a while. Ultimately, the second law of thermodynamics limits the efficiency of energy conversations.


Figure 10. The debt ratio (debt/GDP) of the economy increases more slowly while efficiency increases (e.g., decreasing η).    Solid line = constant η (constant efficiency).  Dashed line = decreasing η (increasing efficiency).



The HARMONEY model shows many trends that are indicative of the real world economy.  Thus far, globally, we keep making end-use devices more efficient, and we keep consuming energy at higher rates. When η is decreased, or efficiency is increased, in the HARMONEY model, resource extraction increases, population increases, capital increases, and net output increases.  Increasing efficiency is a tactic to increase consumption and output, not a tactic to reduce overall resource consumption.  The Jevons Paradox is only a paradox to those who are not thinking about the dynamics of the economy and how it responds to changes in efficiency over time.

How Wages are linked to Energy Consumption: Data and Theory


How do economic analyses account for the roles and impacts of both the cost and quantity of natural resource consumption?

This question has been debated perhaps as long as there has been the profession of economics.  Before the use of fossil fuels, early “classical” economists knew that most products of interest, such as food and building materials, came from the land as it harnesses the energy from the sun. Thus, land as a natural resource was front-and-center to economic thinking.

With industrialization and the use of fossil fuels (that provide energy independent of current sunlight) economic analyses became less focused on the role of natural resources as an input into economic production such that in the 1900s most mainstream (i.e., Neoclassical) growth models do not directly account for energy and natural resources.  Many researchers, including myself, think we must explicitly consider the use of natural resources if we are to understand economic growth and the distribution of the stocks (e.g., debt) and flows (e.g., wages, profits) of money within the economy.

I have recently published a paper on my economic growth model that consistently and simultaneously accounts for both the use of natural resources, such as energy, and debt. 

The paper sheds new light on some of the most important contemporary economic trends in the United States and other economies of the OECD.  In particular, the model provides the foundation to directly link changes in the rate of energy consumption to increases in wage inequality and debt that began during the 1970s.

This publication is in a 2020 volume of the journal Ecological Economics asAn Integrated Biophysical and Economic Modeling Framework for Long-Term Sustainability Analysis: the HARMONEY Model”.   The name of the model, “HARMONEY,” is an acronym for “Human And Resources with MONEY.”


Model Results Reflect Trends in U.S. Data

Figures 1 and 2 show comparisons of model results to U.S. data.  For these comparisons the qualitative similarities in the general sequence of long-trends and structural change are important, not the relation of magnitudes of variables or specific model times to specific years in the U.S. data.

Figure 1 shows the wage share and per capita energy consumption of the U.S. The wage share is the percentage of GDP allocated to hourly or salaried workers. Notice how both the wage share and per capita energy consumption have a different trend before versus after the early 1970s. Before 1973, wage share remained constant at about 50% of GDP, and energy consumption per person increased at 3%/yr. After 1973, wage share declined at about 1.5-2% per decade as energy consumption per person declined slightly or remained relatively constant.

(a) (b)
Figure 1. (a)  In the same way as the U.S. data, the wage share (left axis) from the HARMONEY model shows the same simultaneous turning point in long-term trend, from a constant value to a declining value, when per capita resource consumption reaches its peak.  (b) Data for the U.S. wage share (left axis) and per capita energy consumption (right axis) both change their long-term trends in the 1970s.

The model results show practically the exact same trends as in the U.S. data.  When initially formulating the model, I had no immediate goal to mimic this type of relationship. I did want a model that had several important elements, but I didn’t anticipate my first results would so clearly relate to real world data. In the HARMONEY model, the wage share emerges because of how its systems-oriented structure relates the elements to one another, as described further below.

The HARMONEY model also provides insight into debt accumulation. Figure 2 shows private U.S. debt in terms of the debt ratio (debt divided by GDP) for corporations and financial institutions. These two categories are equivalent to the concept of debt included in the model. It was the accumulation U.S. private debt (and household debt in mortgages) and associated interest payments that triggered the 2008 Financial Crisis. The crisis was not triggered by government debt.

The new insight from this research is that it shows how increasing debt ratios can arise from a slowdown in resource consumption rates.  In essence a debt crisis cannot be analyzed independently of the longer-term context of natural resource consumption.

(a) (b)
Figure 2. Both the (a) U.S. data and (b) HARMONEY model show a slow rise in private debt ratio before a more rapid increase. The transition occurs soon after the peak in per capita energy consumption for the U.S. and peak in resource extraction per person for the model. U.S. data are from U.S. Federal Reserve Bank z.1 Financial Accounts of the United States, Table L.208 (Debt, listed as liabilities by sector). Model results are from the scenario labeled as “Renewable-High(b)” in the paper.

Note how private debt ratio increases much more rapidly after the 1970s than before, and the increase in financial sector debt drives the overall trend for the U.S. This same breakpoint occurs in the HARMONEY model and for the same reasons. In both the U.S. data and the model, when per capita resource consumption was rapid, the debt ratio increased but at a much slower rate than after per capita consumption stagnated.  Note that “mainstream” neoclassical economic theory does not account for the concept of debt, and it assumes the quantity of money has no fundamental role in long-term trends. Steve Keen’s research provided a simple way to include debt into economic growth modeling. In his 2011 book Debunking Economics, Keen states the problem clearly:

“This [lack of consideration of debt], along with the unnecessary insistence on equilibrium modeling, is the key weakness in neoclassical economics: if you omit so crucial a variable as debt from your analysis of a market economy, there is precious little else you will get right.” –– Steve Keen (2011)

This lack of consideration of debt is the fundamental reason why mainstream economists could not foresee or anticipate the 2008 Financial Crisis. Their theory tells them not to model debt, the direct cause of the crisis itself!


More Details on the Results

For those that want more details that explain these model results, then you can keep reading.  Also, at the bottom of this blog I provide links to videos where I describe the model structure and results.

The wage share decline is driven by two quantities: the accounting for depreciation for an increasing quantity of capital and the interest payments on a rising debt ratio. The pattern occurs if you assume, as observed in the U.S. data, that companies keep investing more money than their profits. Since the 1920s, U.S. corporations typically invest 1.5 to 2.5 times more each year than they make in profits. Thus, in this face of constant or slower increase in total energy consumption, the economy accumulates capital that either operates less or requires less energy to operate (e.g., efficient equipment, computers).

Think about the patterns in Figures 1 and 2 the following way. We can assume four major distributions from GDP (or ‘value added’) in national economic accounting: government (as taxes), private profits including interest (or rent) payments to capital owners, depreciation (on capital), and wages (to workers).

In a capitalist system based on maintaining private sector profits, if both the debt ratio and the amount of capital per person increase, then increasing shares of GDP go to two categories: depreciation and interest payments. To minimize interest payments at high debt, you must lower the interest rate, and that is why central bank interest rates have remained at historic lows, sometimes even negative, since 2008.  Assuming a constant share of GDP to government taxes, when there is a restriction in the growth rate of GDP and energy consumption, the prioritization of profits, taxation, and depreciation means that the workers’ share is the only portion available to take the hit.

A short trip down memory lane provides the context for why I’ve performed this research.

In 1972, the book The Limits to Growth brought an idea mainstream discussion: physical growth on a finite plant cannot continue.  There were both detractors and proponents of the conceptual and mathematical models used in the book. When the authors updated the modeling in their 1992 Beyond the Limits, William Nordhaus (Nobel Laureate awarded in 2018) again critiqued the approach as he’d done in 1973 in his paper Lethal model 2: The limits to growth revisited.  Whether any “limits to growth” exist is contested in the economic literature, but there is little doubt in the ecological literature.  Many, including Ugo Bardi in his The Limits to Growth Revisited, state that the critiques of Nordhaus were ignorant of the mathematical and computational methods used in The Limits to Growth models.  However in a commentary within Nordhaus’ 1992 critique, Martin Weitzman effectively summarized the differences in worldviews between an ecological approach to economics and the mainstream view:

“There may be a some value in trying to understand a little better why the advocates of the limits-to-growth view see things so differently and what, if anything, might narrow the differences.

I think that there are two major differences in empirical world views between mainstream economists and anti-growth conservationists. The average ecologist sees everywhere that carrying capacity is a genuine limit to growth. Every empirical study, formal or informal, confirms this truth. And every meaningful theoretical model has this structure built in. Whether it is algae, anchovies, or arctic foxes, a limit to growth always appears. To be sure, carrying capacity is a long-term concept. There may be temporary population upswings or even population explosions, but they always swing down or crash in the end because of finite limits represented by carrying capacity. And Homo sapiens is just another species-one that actually is genetically much closer to its closest sister species, chimpanzees, than most animals are to their closest sister species.

Needless to say, the average contemporary economist does not readily see any long-term carrying capacity constraints for human beings. The historical record is full of past hurdles to growth that were overcome by substitution and technological progress. The numbers on contemporary growth, and the evidence before one’s eyes, do not seem to be sending signals that we are running out of substitution possibilities or out of inventions that enhance productivity.” — Martin Weitzman (1992)

Per Weitzman, I have been interested in “narrowing the differences” between economic and ecological worldviews by coherently including them in the same framework.  It was with that goal in mind that I created the model summarized in this article.  The model is based on a similar concept as that in The Limits to Growth in that it has an allocation of resources and capital between the “resource extraction” and “other” parts of the economy.  But to better communicate with economists it also includes economic factors such as debt and wages. Without this type of combination we can’t understand if and how energy and resource consumption play a role in the trends of debt ratios and wage inequality that now dominate contemporary social, economic, and political discussion.

It is easier to propagate the meme of your model if you give it a memorable name, so I called my model HARMONEY for “Human And Resources with MONEY”. The HARMONEY model is a combination of two other existing models. The first is a simple model of an agrarian society that harvests a forest-like resource to feed itself. The second is a model of a simple economy with fluctuating business cycles, tracking capital, wages, and employment, while also considering the real world tendency of businesses to invest more than their profits by borrowing money from a bank. This borrowing is what “creates money” as debt within the model, just like commercial banks create money when they provide a loan to a business.

From the standpoint of natural resource use, HARMONEY has three key features that are consistent with real-world physical activities and that drive the patterns in Figures 1 and 2. First, natural resources are required to operate capital. This is the same as saying you need fuel to run your car, and a factory needs electricity to operate manufacturing machinery and computers.  Second, natural resources are required to make new capital. This is the same as saying that all of the objects around you now (coffee mugs, computers, buildings, etc.) are made of natural resources. Third, natural resources are required to sustain human livelihood. This is the same as saying that, at a very basic level we need food to survive, and at a higher level more resource consumption leads to more longevity. Thus, whatever the flow of natural resources, those resources must be allocated between the three aforementioned uses.

These three features for modeling the use of natural resources, combined with the concept of private debt as loans from banks, give us tremendous insight into contemporary economic discussions.


Links for Further Exploration

For further learning you can access the article directly and watch videos of me presenting the model background and results in videos (video 2018video 2019) via my website: http://careyking.com/publications/ and http://careyking.com/presentations/.

Artificial Intelligence and the Utility Monster: It’s the Economy Stupid

In his 2014 book Superintelligence: Paths, Dangers, and Strategies, Nick Bostrom discussed issues related to whether we could prevent a superintelligent artificial intelligence (AI) computer system from posing an existential risk to humanity.  In 2014 he also presented for Talks at Google. In that presentation, an audience member (at 49 min 35 sec) posed the idea that a superintelligent computer could become a utility monster.  The utility monster is an idea of philosopher Robert Nozik, and it relates to the philosophical concept of utilitarianism.

In utilitarianism, only the maximum happiness, or utility, of the group is what matters. The distribution of utility within the group does not matter. Consider the idea of marginal utility which is how much utility comes from consuming the next increment of resources.  Because the superintelligent AI system might be much smarter than all of humanity, it could have a higher marginal utility than that of humans.  The machine could conclude that total utility was maximized by its consuming one-hundred percent of natural resources because in doing so, it could maximize overall utility simply by maximizing its own utility.

Bostrom then discussed the paper clip maximizer as a classic AI thought experiment. What if the superintelligent AI system only tries to maximize the number of paper clips (the paper clip is an arbitrary placeholder)? The AI system would likely determine that keeping humans alive is detrimental to the goal of maximizing the number of paper clips in the world. Humans need resources to survive, and these resources could be used to make more paper clips.  It is not that the AI machine dislikes or specifically tries to harm humanity. It is just that the superintelligent AI system is indifferent to our existence.

Now think about “the economy” and the metric of gross domestic product (GDP) which is usually used as a metric of the size, or throughput, of the economy. GDP is roughly treated as utility in economics. GDP is now a substitute for paper clips. Could we tell the difference between a world that is run by a superintelligent GDP maximizer and the world that we live in right now?  That is to say if certain politicians, business owners and executives, and economists are pushing for rules that maximize GDP with , then is that “the economy” simply a mechanism to maximize GDP without regard for how money is distributed?

Philip Mirowski points out that one of Friedrich Hayek’s ideas was that the economy was smarter than any one person or group of persons. Government officials, for example, can’t know enough to make good economic decisions. Mirowski discusses Hayek’s idea in his book The Road from Mont Pelerin which explores the history of the “neoliberal thought collective”.  Mirowski points out that Hayek saw the economy as the ultimate information processor.  Thus, markets are able to aggregate data in the most effective way to produce the “correct” signal, say the price, to direct people on what to make and what to buy.

Need better decisions? Make another market! There is little to no need for people to think.

In an extreme world with markets for everything, each of us becomes an automaton responding to price signals to maximize collective utility, or GDP, that might have very little to do with our personal well-being.

How could we know if we have allowed the economy to simply become a GDP maximizing utility monster? Perhaps GDP would keep going up, but if it didn’t, perhaps we’d start adding activities to GDP that have existed for centuries, but had previously not been counted due to illegality or other reasons. Prostitution and legalizing previously drugs are examples. Check on that one.

Perhaps if all we wanted to do was increase GDP, we’d cut corporate taxes to spur investment in capital versus spending on education, which is for people. Perhaps human life expectancy would go down, and drug sales would be up (the utility monster is indifferent to people). Perhaps we’d see increases in wealth or income inequality. Perhaps people would contract with “transportation network companies” to drive around, wait for algorithmic signals on where to drive to pick up a person or thing, and then deliver that person or thing as directed.

Most macroeconomic analyses are based upon the concept of maximizing utility, which is usually interpreted as the value of what “we” consume over all time into the future.  Many interesting (troubling to many) trends are occurring in the U.S. regarding health, distribution of income, and the ability of people to separate concepts of fact and truth. Thus, we should consider whether the superintelligent AI future some fear might already in action, but at perhaps a slower and more subtle pace than some pontificate might happen after “the singularity” when AI becomes more capable than humans.

The recent populist political movements in the U.S. and other countries could in fact be a rejection of the “algorithm of GDP maximization” associated with our current economic system.

Learn about utilitarianism.  Learn to go beyond GDP here, here, and here.