In the Long Run We are All Dead - John Maynard Keynes

Stefan Eich just published (Dec 22, 2024) an interesting essay in Adam Tooze's Chartbook (here) discussing what John Maynard Keynes meant by his famous quote: "In the long run we are all dead." Keynes was writing about the future, which is unknowable, and how we should think about it. I have my own views about the future and in many ways they agree with Keynes or at least with Stefan Eich's interpretation. So, let me clarify my own views by summarizing Eich's article (SE).

First, let me list some quotes from the (SE) article and John Maynard Keynes (JMK):

• “Our power of prediction is so slight, our knowledge of remote consequences so uncertain that it is seldom wise to sacrifice a present benefit for a doubtful advantage in the future.” (JMK)
• ...it was “not sufficient that the state of affair which we seek to promote should be better than the state which preceded it; it must be sufficiently better to make up for the evils of transition.” (JMK)
• ...in Keynes’s hands a critique of the equilibrium analysis offered by neoclassical economics. Indeed, Keynes explicitly extended this theoretical critique of equilibrium theories into a political critique of austerity measures derived from them. (SE)
• ...orthodox economists ... demanded interwar austerity based on the long-run extrapolations of neoclassical economics. (SE)
• ...it was only in the neoclassical long run that the economy was assumed to have finally reached its “natural” state of equilibrium. (SE)
• ...“the long run” of neoclassical economics lacked temporal specification. No one could know whether it would arrive in twelve months or seven years. (SE)
• [Keynes] ... preference for Malthus’s economic theorizing from “the real world” over Ricardo’s more abstract starting points...Since the future of mankind was shaped by the most irregular movements, to draw too straight a line from the present to the future was a sure way to mislead oneself. (SE)
• The ...“long run” of neoclassical economics essentially evacuated politics from the future. (SE)
• Rejecting the naturalized long run thus implied for Keynes at the same time a need to articulate broader future possibilities. This is evident not least in Keynes’s own interest in alternative imagined futures, most famously in his essay on “Economic Possibilities for our Grandchildren” (1930) (SE)
• Postwar Keynesianism’s commitment to perpetual growth coupled with a deep intellectual investment in modernization theory can indeed be read as offering a linear conception of growth as progress that served to stabilize a deficient present. (SE)
• The mode of social change that Keynes embraced in response to this challenge was a notion of open experimentation. (SE)
• Here as elsewhere, Keynes consciously placed himself outside of interwar debates over planning by offering alternative conceptions of decentralized or independent bodies of administration that would be essential for crafting new tools of indirect economic steering—including what we have come to call macroeconomic policy. (SE)
• ...there is no such thing as “the future” but instead only ever a proliferation of multiple yet unformed possibilities, Keynes flagged the centrality of the politics of such future time. (SE)
• The "Long Run" line first appeared in A Tract on Monetary Reform, published in December 1923. More specifically, it appeared in the third chapter on “The Theory of Money and of the Foreign Exchanges” and came in the context of a technical discussion of the quantity theory. (SE)
• Speculative visions of the future are thus performative in the sense that they feed back into how people act in the present. As Keynes argued in the seminal twelfth chapter of the General Theory (1936), our estimates of even the comparably near future are so inescapably obscured by uncertainty that they cannot form any reliable, let alone calculable basis for our actions in the present. And yet we have to act. (SE)

In my blog Facts, Fictions and Forecasts, I present forecasts based (1) on a technique used by the Atlanta Federal Reserve (here) and (2) on an approach to multi-model forecasts used by US National Oceanic and Atmospheric Administration's (NOAA) for hurricane forecasting and the IPCC Climate Change Emission Scenarios. You can see an example applied to the US here and here. For me, these are the kinds of forecasts Keynes was talking about: conditional, probabilistic, and based on historical data rather than theory. Systems Theory helps me develop and interpret the models and resulting forecasts. No assumptions about equilibrium or stability are imposed on the models.

The recommendation for experimentation is interesting. I started my professional career as a program evaluator/statistician with the Nixon-era Wisconsin Alcohol Safety Action Program ASAP in the early 1970s.

The Wisconsin program had a mixed record of success with Alcoholism programs and with the overall project. As I remember the project conclusions, the reduction of speed on Wisconsin highways to 55 mph (largely the result of the 1973-74 Arab Oil Crisis) had more effect on alcohol related deaths than the ASAP programs. The takeaway for me, at the time, was that natural experiments (such as the 1973-74 Arab Oil Crisis) had more impact than government programs. This lead me to Systems Theory, history and to Counterfactual Thinking (what if things had been done differently). 

Now, at the end of my career, I keep writing that I will not be alive to see the future of the US Economy, for example, or any other country's future that I write about. I can only bring my brick to the wall and hope that the methodology is useful at some point in the future.

Should We Bother Reading the Classical Economists?

The Classical Economists, Adam Smith (1723-1790), Thomas Robert Malthus (1766-1834), David Ricardo (1772-1823) and Karl Marx (1818-1883), collectively wrote in the 18th and 19th Centuries. All their works are currently in the public domain and available on line (see below). Neoclassical Economics supposedly made their works obsolete and you hear little about them if you take a course in ECON 101. Still, there is a sinking feeling in the Economics profession that We Need Better Economic Models. What might the Classics have to offer? Briefly:

• The Steady State Economy Modern economics assumes that growth can continue forever without limit. The Classics, on the other hand assumed that eventually growth would reach a steady state. For Marx, this was the Communist Society, which he described only general terms. There is evidence that current economies (here) are reaching a steady state and that it will not be the utopia envisioned by Marx.
• Economic Depressions and Business Cycles In Modern economics, cycles and long-waves are not supposed to happen. The market is supposed to adjust any imbalances in supply and demand and regulate the economy. The Classics assumed that booms, busts, panics, bubbles and manias could all happen and required explanation. For example, Malthus and Ricardo were concerned about effective demand, prefigured Keynes and did not assume markets handled all economic problems automatically.
• Historical Determinism Modern economics has no role for History. Models are timeless and general, much as universal physical forces. The Classics, particularly Malthus and Marx, understood that different models were required for different periods. Premodern societies are best described by the  Malthusian Stagnation Model rather than the Neoclassical Growth Model. Marx thought that the Asiatic Model of Production was different from the Capitalist Model.
  
  

Modern Economics based on overdetermined, stable equation systems doesn't have a role for cycles, depressions, pre-modern models of production and History. Systems Theory, on the other hand, can easily handle cycles, instability, growth and steady states.  Not that every problem is solved by recovering the past. Both the Classics and the Moderns jumped too quickly from their (mental) models to policy recommendations.  Real SocioEconomic systems are far too complicated to be controlled by simple feed forward systems. The best we can do is analyze natural experiments as they are conducted in History and see if our systems models can capture what happened. 

The bigger problem here is that Economics has been co-opted by Neoliberalism and Market Fundamentalism. What you get in ECON 101 is an attempt to describe the Economic System and an attempt to proscribe policy measures to tell politicians how to run the Economy. These attempts are largely a failure and have little historical justification or empirical support--at least the little that is offered in ECON 101. And, this is what the average student gets, if anything, as an introduction to Economics.

The Classical writers had very few mathematical, statistical or historical tools at their command for understanding the Economic System. They struggled with definitional issues and wrote in a verbose style we no longer find very straightforward. If we trained students to be Classical economists, we would just end up generating an avalanche of speculative, qualitative writing that never gets tested. In other words, we wouldn't get Science.

My recommendation is that we use the new tools available to us, primarily Systems Theory, to moved on from both the Classical Economists and current Neoclassical Economics. Critics will argue that this has already been tried an failed, in Sociology by Talcott Parsons (1902-1979) and in Economics by Kenneth Boulding (1910-1993). The critics are wrong but having an argument won't solve anything.

Let me just make these assertions: Economics went wrong by insisting that everything has to be derived from individual, rational behavior, i.e., Homo Economicus. Systems theory argues that the the Economy is not just an aggregation of individual, rational behaviors. The system has both aggregate growth and aggregate feedback processes. We understand the variables involved in Growth (the Neoclassical Growth Model) but we have little understanding of the macro-feedback process and how the Economic System is controlled beyond the Aggregate Demand and Supply model (AD-AS model) which is incomplete. Just consider the simple Impact Model with markets for aggregate production (Q), energy (PE), and CO2 (PC, price of carbon--a market which is very incomplete).

What controls Global Temperature (T)? What controls Population Growth (N)? There are other Human Feedback Loops in the complete TechnoSocial system that we barely understand. The Subprime Mortgage Crisis (2007-2010), the COVID-19 Pandemic (2019-2023) and the resulting economic shocks and fumbled government response made clear that markets didn't help control inflation and we really didn't understand the effect of many supply chain delays and disruptions caused by exogenous shocks. And, the expanded Impact Model above is not a system because there are no feedback loops (just self-loops).

Classic References

These works are available on line:

• Adam Smith Wealth of Nations
• Malthus An Essay on the Principal of Population
• Malthus Principles of Political Economy
• Ricardo Collected Works
• Marx Collected Works
• JS Mill Collected Works

Excellent Secondary Works

These secondary sources are worth tracking down and reading:

• Higgins Economic Development
• Saeed Limits to Growth Concepts in Classical Economics
• Baumol Economic Dynamics
• Boulding The Malthusian Model as a General System
• Galor From Malthusian Stagnation to Demographic Transition
• Dong Human-Nature Feedback Loops

News from 2025

JANUARY 20, 2025, WASHINGTON DC.

US Presidential Inauguration.

JANUARY 21, 2025, WASHINGTON DC.

Trump Administration imposes tariffs ranging from 20% to 100% on imported goods from China, Mexico and Canada.

JANUARY 25, 2025, GENEVA, SWITZERLAND, World Trade Organization.

China, Mexico and Canada determine that Trump Properties are a Transnational Crime Organization under International Law and forbids the organization from operating within the territorial confines of their countries.

NOTE: Figure above from the New York Times (here). Actually, the attack on Trump properties is already happening in Panama (here) where the Panamanian government has concluded that Trump Properties are a criminal organization and the organization has been banned. In response, Trump vows to take back the Panama Canal.

Failed Systems in the United States

 

The Blame Game has started for the Democrats loss in the 2024 US Presidential Election (here) as have fears for what might happen in the future (here). If you ask the AI System ChatGPT what happens when countries collapse, the answer is that "...overlapping crises disrupt political, economic and social stability". Taking a World-System perspective: political, economic and social systems start to fail.

What happens when systems start to fail (see the graphic above, click to enlarge): the internal workings of the Failed System no longer control inputs or produces reasonable outputs. The system continues to run, if at all, on its own without any feedback between outputs and inputs.

Using the Failed System model, it seems clear (at least to me) that the systems in the US are starting to fail. The Political System failed to prevent a demonstrably (after the first term) incompetent candidate from becoming US President again. The Congressional System failed to Impeach a sitting President for High Crimes and Misdemeanors. The Legal System failed to hold an ex-President with 34 felony convictions accountable. The Educational System failed to produce voters who could apply critical thinking to their voting decisions. The Economic System failed to deal with the COVID-19 Inflation. The Information Systems (mass media, social media, etc.)  failed to produce unbiased information. Pick some system that you understand well and ask yourself whether it is functioning properly.

Do all these failures mean that the US System is collapsing? Of course, we cannot know the future and many of us were surprised that Trump won the 2024 Presidential Election. What I can do is ask a Systems Model of the US Socio-Economic system to project the future. The forecast is presented in the graphic above (dashed red line, click to enlarge) with 98% prediction intervals (the blue and green dashed lines). The solid black line extending beyond 2000 is the dominant state variable for this system. It captures growth in essential variables in the US. The forecast shows that the US System will not peak until after 2050, well into the Post-Trump World of the future.

I have multiple models of the US Socio-Economic system and not all of them predict collapse. Each presents an alternate future and I will not be alive to see which model is most accurate. All the models do show that US growth is slowing. My hypothesis is that the political response to slowing growth (Secular Stagnation) will not be resignation but increasingly unhinged (and possibly Fascist) attempts to return to the Attractor Path of unlimited growth which is an impossibility (here). The Trump Administration will only be the beginning.

The Trump Administration may well destroy the political, legal, economic and educational systems in the US that are currently failing. These institutions will have to be rebuilt whether Trump destroys them or not. The really difficult task is to think about how these institutions might be rebuilt to support a Steady-State Economy and prevent Fascism from triumphing in the post-Trump World.

It's the Economy, Stupid!

The title of this post is taken from a quote typically attributed to James Carville, a political advisor during the Clinton Administration. It might equally have been attributed to Karl Marx's emphasis on Economic Determinism. The graphic above is from a 2024 PEW Research Center poll which finds that 81% of Voters are primarily concerned with the Economy.  Other issues come in a distant second.

The paradox here is that voters are generally uninformed about: (1) the state of the Economic System, (2) simple ECON 101 Economic Theory, (3) how the Political system works and (4) whether successive political administrations have any impact on the Economic System or are just passive bystanders taking blame for successive economic crises.  The graphic above (click to enlarge) tries to map out some of the confusion.

The basic inputs to the Political System are voting and opinion polls. The things that are under control of decision makers within the Political System are government expenditure (G), Taxation (TAX) and the Money Supply (M). How G, TAX and M affect the Economic System and Economic Outputs are open to argument. And, as I have been arguing here, Shocks to both the Political and Economic Systems are when we find out how, if at all, the two systems work. There should ideally be some Feedback between all this and voting behavior, but there are such long time delays that voters tend to forget causal relationships (see my discussion here).

So, what is the Political System really supposed to do? Here's an old idea that goes back to 17th Century terminology: the Political System is supposed to act as a Centrifugal Governor. The idea also appears in Arnold Tustin's book The Mechanism of Economic Systems (1953). When the centrifugal governor rotates more rapidly it slows down the steam engine, for example. Even if 17th Century Politicians thought this was the way a Political Governor was supposed to work, it no longer is in the 20th and 21st Centuries. The Political System is not supposed to slow down the Economic System.

It is unfortunate that the 17th Century idea of a Political Governor has been lost (we have Neoliberalism to thank), especially since Climate Change has slipped to one of the least important issues for voters. Slowing down the Economic System is one proven way to reduce CO2 Emissions (as was proven during the COVID-19 lockdowns).
 

 

The Lessons of the 1930s

 

Yesterday, Jan 6, 1944 was the start of Operation Overlord (D-Day). Senator Mitch McConnell, in an NYT editorial (here), reminds us not to forget the Lessons of the 1930s, the main one he thinks involved the Isolation Movement. We should all understand that the editorial is an oblique attack on the MAGA (Make America Great Again) movement and the current Republican presidential candidate. But what were the Lessons of the 1930s? Let's ask an AI System (here).

In response to a query, ChatGPT lists eleven lessons from the period:

1. Dangers of Unregulated Markets
2. The Role of Government in Economic Stabilization
3. The Importance of Monetary Policy
4. The Importance Social Safety Nets
5. The Rise of Authoritarianism
6. The Power of Collective Action
7. The Consequences of Isolation
8. The Importance of Economic Cooperation
9. Technological Innovation in Crisis
10. The Power of Media and Communication
11. The Impact of environmental Mismanagement (the Dust Bowl)

My guess is that Senator McConnell would only consider #7 and then I still find his entire editorial strange since, at the end of the election cycle, he will still support the MAGA movement and the current GOP presidential candidate, neither of which are likely to change their position on US Isolationism.

Senator McConnell, however, is right that we have forgotten the Lessons of the 1930's. We basically have the rise of Neoliberalism in the 1980's to thank for our failing memory--and that, of course, was its purpose. In future posts, I hope to resurrect the Lessons of the 1930s and the failures of Neoliberalism. The topic is almost too difficult to contemplate as a project but there is plenty to write about. Feel free to grab any of the topics and blog about it yourself. I can't do everything!

P.S. The D-Day anniversary has been an emotional day for me. It is the "last hurrah" for the remaining WWII Veterans who are within years of being no longer able to comment on the current resurrection of Fascism.

Models, Data and US Federal Reserve Policy Decisions

 

One January 11, 2024, the PBS News Hour interviewed Raphael Bostic, president of the Atlanta Federal Reserve Bank. One interesting part of the interview was the description of how models vs. data are used in the Federal Reserve decision making process, at least by Dr. Bostic. The role of economic models in decision making is interesting because on July 20, 2010 the US House of Representatives Committee on Science and Technology held a hearing on the topic (transcript here) and concluded the models were not very useful. My conclusion is that the US Fed is on the right path with some of the new models being developed. Future posts will give my recommendations (as a statistician) and my reasons for making them. It is essentially my forecast for the future of US Fed model building.

In the interview above, Amna Nawaz asked when Bostic expected the economy to reach the US Fed's 2% Inflation rate target. Bostic answered:

Well, we have models, and models will give us an answer...[but]...I don't put too much stock in any of those longer-term issues...I just try to keep an eye on where things are going month to month and try to just have a clear understanding about where we stand.

In other words, the models give us some long term predictions about Inflation and Economic Growth but, for month-to-month decision making we use data.

So what exactly can we get from models? I would hope that that the Atlanta Fed gets Prediction Intervals telling them that, say, Inflation might be between 1% and 3%, bracketing he 2% target. Then, as the data come in, it can be evaluated to answer Anna Nawaz's question. And, I would hope that the state of the economy would have some role in predicting the time path of inflation. Something like the prediction intervals produced by Climate Models:

The original topic of the News Hour interview was to gage the actual strength of the economy and consumers expectations about economic growth (although most of the interview concentrated on Inflation).

 For the strength of the economy, let's look at the Atlanta Fed's GDPNow forecast for economic growth (quarterly percentage change in real GDP). The output from the GDPNow app (presented above) compares the GDPNow forecast to the range of the top and bottom ten Blue Chip forecasts. GDPNow predicts GDP percentage changes well outside the Blue Chip forecasts until we get into March of 2023. What's going on here and why is this happening?

Maybe it would help to look at a longer time period. The St. Louis Fed publishes the GDPNow output from 2014-2024 (above and here). We can very clearly see the COVID shock, the economy's response, and the return to approximately at 2% growth rate. Note that it took approximately three years to recover from the COVID shock.

There is a lot to scratch your head about in the NewsHour interview and the outputs of the GDPNow model before we even get to thinking about the problem of inflation. Why don't the Blue Chip forecasts show the COVID shock? Why does the GDPNow cellphone App not go back to 2019, before COVID, to report results? And, which forecast should we believe, if any? 

It sounds as if, from Dr. Bostic's comments, that the FED ignores the forecasts and just waits for data to come in when making decisions about the economy. That's OK, but the FED spends a lot of time and money on large-scale, Dynamic Stochastic General Equilibrium  (DSGE) models (here), the models criticized in the Congressional Hearings, models that produce yet another set of forecasts. Worse yet, the DSGE models are based on assumptions that economic agents use models to form expectations about economic variables and use these expectations to make decisions, decisions that DSGE models attempt to predict.

But, which models specifically are economic agents using: the GDPNow model, the consensus of the twenty-or-so Blue Chip forecasting models, the forecasts of the DSGE models, or some other model entirely (I have my own models that are similar to but, I argue, an improvement over the GDPNow approach). I know the Fed is trying to be transparent and lay everything out on the table but what I'm looking at appears contradictory as it must have looked to Congressional Committees. And,  some commentators (here) and Congressmen (here) want to get rid of the Federal Reserve, Fed forecasts and Fed policy manipulations entirely.

Interestingly enough, the current problems with Economic Policy all point back to our failure to understand the Great Depression* and the effects of economic shocks (such as the WWI-WWII shocks and the COVID shock). In future posts, I'll try to untangle this mess** because I think it is interesting and important but not because I think any economic agents (to include the Fed and the ECB***) will be interested. Eventually, I will get around to looking at Inflation and Deflation!

Notes

* ChatGPT (here) lists the following causes for the Great Depression: (1) Stock Market Crash of 1929, (2) Bank Failures, (3) Reductions in Consumer Demand, (4) High Tariffs and Trade Barriers, (5) Monetary Policy Mistakes, (6) Debt Deflation, (7) Decline in International Economic Activity and (8) The Dust Bowl and Agricultural (Environmental) Collapse. 

** My working hypothesis is that we need to embed the US Economy within the World-System to not only understand the Great Depression but also to understand current economic policy confusions. The Fed doesn't really have a role for the World-System in its models.

*** The failure of Macro-economic models was also felt by the European Central Bank (ECB): "Macro models failed to predict the crisis and seemed incapable of explaining what was happening to the economy in a convincing manner".

Policy Models, Randomness and Free Will

In my research work I have developed a lot of policy models (see one about the US Health Care System here). If the models have any "policy recommendations" there is  very good chance that (1) no one is paying attention and (2) even if they were, they would not take advice from my models. If this is so futile, why do I keep doing it? If I have free will, maybe I should just drop my modeling fixations and play more golf.

All my policy models are based on the simple state-variable equation S(t) = F[S(t-1),X(t-1), E(t-1)] where S is the state of the system, F is some function, X are the input variables, E are the random(?) errors and t is time. In this post, I'm going to discuss the random components, E. By construction, the E are independent of the state variables, S, but what are they really? Let me take an example from Sub-Saharan African (SSA) because in an upcoming post I'm going to present an SSA model.

The state variables are constructed from the raw data in the World Development Indicators (WDI) using Principal Components Analysis (PCA). The variables are CO2E (CO2 emissions), EG.USE (Energy Use), GDP, Total Labor Force (TLF) and POP (Total Population). The numbers are weights and the choice of variables is based on the Kaya Identity. The first component state variable is overall Growth, the second is (CO2-N), and the third is (GDP-N).* The three components explain 99% of the variation in the indicators and these are typically all that are needed to construct the state space model S(t) = F[S(t-1),X(t-1), E(t-1)] . SSA2 and SSA3 are called the Error-Correcting Controllers (ECCs) that keep the system on the growth path (maybe). The E are components 4 and 5, but what are they really?

I have estimated a state space model for SSA5 and an output graph is presented above (the solid line is actual data and the dashed red line is predicted). Testing shows that it is not a Random Walk but the model doesn't do a very good job of predicting the series and misses all the turning points until after they are made. In other words, after we have exhausted 100% of the variation in the underling data, we don't find "randomness" but rather forces that we can't predict very well and, by themselves, explain little variance in the overall system. It's not that SSA5=(POP-EG.USE) is uninteresting (it is a Population Energy Demand ECC), it just doesn't explain a lot of variance in Sub-Saharan Africa. It might in other regions of the world, just not here.

What explains most of time path of SSA data? You'll just have to wait until I present the model in an upcoming post. The points I want to make here are that (1) If I try to forecast the population-energy ECC out to 2060 (above), probably the best I can say is that there is going to be a correction from 2024 and (2) when the correction will happen and to what extent it will happened,  the model cannot predict. When future data comes in, the model can detect if a correction was made. One the other hand, maybe a regional war will interrupt the adjustment process. Time will tell (not the model).

Estimating the model does not seem futile. At least it uncovers a low-variance feedback process covering population energy use. And, if you know anything about economic models, you will know that the economic models mostly do not contain feedback effects. 

Maybe another point to make to highlight Sabine Hossenfelder's video on Free Will (above) is that Sub-Saharan Africa cannot be said to have free will. I will demonstrate in a future post that it is a macro-system with many human institutions but these institutions don't have "will." Causes of policy actions might be too complex to predict ahead of time, but models can tell us what happened after the fact and clarify the underling causal forces. That is something and I want to keep doing it.

NOTES

* (CO2-N) is an Environmental ECC. (GDP-N) is a Malthusian Crisis ECC. I'll explain ECCs more fully in future posts. For the time being, these results (at least for SSA) indicate that environmental damage and Malthusian Crisis are being monitored (at least in SSA) in attempts to maintain the growth path. ECCs will be different in different regions and different countries in the World-System.