Where Malthus was Wrong – and What he got Right

Thomas Malthus was the 18th-19th century economist who is most widely known for making a bold prediction which turned out to be spectacularly wrong. He  suggested that an exponentially rising population could not be sustained because agricultural production would not be able to keep up with it. he predicted that periodic crashes in population level and increased poverty would be the inevitable result. But on the contrary, over the next hundred years the population of Britain increased from about seven million to more than 41 million. And in the following century it increased further to over 60 million – and the average prosperity of even the poorest of English workers had advanced to a level that would have been unimaginable in 1800. Because reality diverged so greatly from his forecast, his name has become a term of ridicule, applied to any commentator who suggests that unlimited global financial growth may not be possible.

Malthus studied at Jesus College Cambridge, where he distinguished himself in English, Latin and Greek. He was awarded a high first class honours degree in mathematics, and elected as a fellow of the college. In common with many academics at that time he took holy orders, and served for a while as a parish priest. While performing that role, he noticed that he was carrying out significantly more baptisms than funerals – and from his mathematical understanding he realised that this would lead to an exponential growth in the population of the country. Suggesting that agricultural production could not possibly grow at more than a modest linear rate, he concluded that the level of the population would shortly rise to a point where it could no longer be supported by the available food, and that poverty and misery would surely result. He published these findings in An Essay on the Principle of Population in 1798, with several updated editions over the next thirty years.

Malthus’ ideas became more widely known and debated because both Charles Darwin and Alfred Russell referred to his work as an inspiration for their theories of evolution by natural selection. However, the rising levels of population of the country coupled with growing average prosperity undermined the acceptance of his theory. The mainstream economic view persisting from the mid 19th century to the present day argues that indefinite unlimited growth can be supported by a combination of novel technology and the operation of free market pricing. Consequently, anyone who suggests otherwise risks being ridiculed, and accused of falling into “the Malthusian Fallacy”.

But perhaps his critics have been both unfair and premature? The core point that an exponential rise in population would cause it to overtake the capacity of the country to produce enough to feed it was not disproved by the events of the next century. On the contrary it was vindicated. Britain did not – and could not – produce enough food for the 41 million inhabitants it had in 1900. The development that allowed it to feed everyone, and for large sections of the population to become much more prosperous, was the dramatic success of the Industrial Revolution. British manufactured goods were exported on a vast scale, and food grown in other countries imported in exchange. Although the Industrial Revolution was getting under way at the time Malthus was writing, nobody could have predicted the impact of the next few decades’ developments. Similarly, we have been living through the early years of the Cybernetic Revolution, and cannot know how social, cultural and industrial arrangements are going to develop over the next fifty years.

However the issues we face now are global in scale, not national. There is no other planet that we can turn to when we reach the limit of our food supplies. Even with the current population of over 7.5 billion, there is enough food being produced for everyone; the reasons that millions are starving are political, institutional and financial. But it is also true that there is a finite area of cultivated, or potentially productive land. Some changes in farming methods have delivered considerable increases in crop yields, but there will still be an upper limit at some point. And unfortunately some of the modern farming techniques are turning out to be short-term solutions. We may be producing more food today – but at the cost of damaging the soil in ways that will ensure falling productions within a generation or so. Modern techniques are also heavily dependent on energy inputs from fossil fuels – not just in the obvious reliance on fuel for all that agricultural machinery, but also in the manufacture of all the fertilisers, weedkillers and insecticides. As these fuels become scarcer and more expensive, many of these recent gains may be reversed.

The population of the world as a whole has actually been growing at more than exponential rates. It took 123 years to double from 1 billion to 2 billion; 61 years to double from 1.5 to 3 billion; and 39 years to double from 3 to 6 billion. Even if it maintained “merely” exponential growth at the latest rate, we would reach 15 billion by 2055, 30 billion by 2094, and 60 billion by 2133. Even the greatest optimists must surely agree that sometime along that path we will exceed the capacity to grow enough food to nourish them all. If we haven’t brought the growth under control by reducing the birth rate, it will come down by an increase of the death rate – through starvation, disease or warfare.

And if we want to provide the world’s poorest with more than a meagre poverty-stricken existence – what would it take to provide this expanded population with the comforts and luxuries that we take for granted?

The next section in this thread will describe a computer model that maps the interactions between population, food production, industrialisation, energy consumption and pollution. This can be used to explore the likely consequences of various policy choices over the course of the next century. The best way you can prepare yourself for the disruptions that are coming over the next decade or to is to have a realistic grasp of what is actually possible within the resources of this finite planet.

This essay is part of my forthcoming book The World in 2100: What might be Possible for Humanity? It is within the thread on The System of the World, which – in conjunction with the other six themes of the book – provides a comprehensive survey of the position we find ourselves in at this critical time in human history.

If you haven’t already done so, you can register to receive a free review copy just before it goes on general sale later this year. Registering will also take you straight to Chapter 1 – The Foundations which will give you an overall idea of what the book will cover.

Section 1.7 – The System of the World

Gordon Brown famously announced “an end to Boom and Bust” – a few year later the world was plunged into the biggest economic crisis in history, which almost brought down the global banking system. (Incidentally, we will be examining the underlying mechanism of boom and bust cycles in the Finance thread later in the book).

Richard Nixon, on being elected President in 1968, promised to “fine tune the economy”, prompting a retort from economist J K Galbraith that “obviously the tuning had formerly been too coarse”. Shortly afterwards, the US was experiencing the new phenomenon of ‘stagflation’ – economic slowdown coupled with soaring prices, whereas previously it had been a choice between one or the other.

Alan Greenspan, chairman of the US Federal Reserve stated in 2003 that “the application of more-sophisticated methods for measuring and managing risks had been key factors underlying the remarkable resilience of the banking system“. Five years later the entire system was on the point of collapse.

Governments everywhere are promising to improve the economy, or to be able to make a better job of doing so than their rivals would. Sometimes unemployment is too high, so they try to fix that by reducing interest rates. Shortly after that inflation is running away at unacceptable rates, so interest rates are increased. How well is this working? Sometimes reducing interest rates does reduce unemployment. Sometimes it doesn’t; as in the last few years when interest rates have been reduced effectively to less than zero and yet ‘economic growth’ remains elusive (in most people’s actual experience, whatever the statistics say). Sometimes increasing interest rate does rein in inflation; sometimes it increases it, perhaps because everyone’s mortgage and rent payments then go up. Sometimes we end up with high inflation and high unemployment. Even when things seem to be working just fine, within a very short time they seem to be veering out of control again. All of these issues, and many related ones will be explored in much more detail in the Finance thread, but they cannot be understood without having a grasp of the Systems view of processes, which is what we are beginning to distinguish here.

For as long as anyone can remember, people have been trying to fix problems, yet the problems remain unfixed, or get worse, or morph into different problems.

The same thing happens on scales large and small. Let’s consider that this phenomenon is a product of the assumptions that we make about the way the world works. There’s an unspoken idea in the background that there’s a simple chain of cause and effect that we should be able to tinker with. What we do when we are not getting the results we want? I think that most of us subconsciously have a mental model of the way things work that looks something like this:

And so – we either try to change the process, or alter the inputs that are going into the process. This seems logical, but how does it work out in practice? I would suggest that almost invariably we have one of three outcomes:

• either we are disappointed to find that things don’t change, or don’t change nearly as much as we would have liked
• or we overshoot, and find things that have changed far too much, getting a different result which we don’t like either
• or thirdly, we might get some progress in changing the things that we set out to change, but other consequences arrive as a by-product which are problematic in their own ways

Consider that what was missing from our model is that almost invariably the output in some way affects what is going into the process, so it would look more like this:

Let’s look at a simple example. Suppose you have some rabbits; and the rabbits do what rabbits do – and the result of that is more rabbits. And then all of these rabbits do what rabbits do; and the result is even more rabbits.

This is called feedback, because some of the output of the process is fed back into its input. Note the ‘+’ sign, which indicates that a change in the output tends to affect the input in the same direction. If you think about it for a moment, the rate at which the rabbit population is increasing at any moment will be exactly proportional to the size of the population. This is the defining characteristic of what we call an exponential growth curve. The same sort of curve is generated by compound interest – where the income received from an investment is continually applied to the purchase of more of the income-generating assets. It is the core strategy in every scheme for generating significant wealth within a limited time-frame, as we will be examining in the Wealth and Finance threads of this book. And we will get more insight into the underlying dynamics of exponential growth in the Numbers and Patterns thread.

However, feedback comes in two forms: this first kind of feedback I shall call reinforcing feedback, because it has a tendency to accelerate the results that are output from the process. Let’s now look at another example. If you have a central heating system, there will be a thermostat which controls its operation.

If the temperature in the room is lower than the thermostat setting then the heating will be turned on; and if the temperature is higher then the heating will be turned off. This is the second kind of feedback, which I will call stabilising feedback. In this case, the signals fed back from the output tend to reduce changes in the result, rather than to further increase it as was the case in the reinforcing feedback examples (hence the ‘-‘ sign).

(The technical names for these two types are positive feedback and negative feedback. I didn’t use those because people are sometimes confused by the connotations of the words ‘positive’ and ‘negative’. There is a tendency to associate the word positive with implying something good, and the word negative with implying something bad. But in the case of feedback systems, whether the outcome is desirable or not depends on the circumstances. Positive feedback tends to cause exponential growth, subject to certain constraints. Negative feedback tends to maintain a certain balanced condition. Exponential growth may be a good thing in some contexts; for example, if you are talking about the performance of your investments, or the harvest of your apple orchard. But not so desirable if you are talking about the level of pollution in your environment, or the size of a cancerous tumour in your body).

Stabilising feedback systems are everywhere. When the temperature of your body rises by a fraction of a degree, mechanisms step in to lose heat more rapidly, such as by sweating. If it falls by a fraction of a degree, the body generates more heat, or cuts down the rate of heat loss. Other systems regulate the concentration within the blood of oxygen, carbon dioxide, sugars, lipids and other dissolved chemicals. An elaborate set of feedback loops navigates and steers an airliner to its destination without any action on the part of the pilot. When you turn the steering wheel of your car, a powered hydraulic system points the wheels in the desired direction without needing your muscular effort to move them. Feedback loops within the circuits of an audio amplifier ensure that the sound patterns emerging from the loudspeakers are an accurate replica (at higher energetic levels) of the signals fed into the input.

But this is only the beginning of the story. All feedback loops in the real world are embedded within larger ones. And all the pathways within them contain their own smaller feedback systems, both reinforcing and stabilising. If the network shown in the rabbits example above was the whole story then the world would very quickly be entirely covered with rabbits! Let’s add another subsystem called ‘grass’:

(Note the ‘-‘ sign, indicating that increasing the number of rabbits tends to reduce the amount of grass). And then we could have another subsystem called ‘foxes’:

 

The + sign in these diagrams indicates that changes in that input tends to move the output in the same direction; and the – sign means that the changes in the input tend to move the output in the opposite direction. An increase in the number of foxes will tend to reduce the number of rabbits.

In the real world there is a vast integrated network of feedback loops connecting all of the processes. Here is an attempt to envisage some of these connections in a diagram created by Hazel Henderson:

Complex as this is, it still leaves out a huge number of the interconnections that exist in the real world. And whilst it gives food for thought when contemplating these issues, it is far too complicated to help with drawing useful conclusions. In a later section in this thread I will describe a simpler model containing just 11 variables, with plausible inter-relationships of the effects that alterations in one variable would have on the others:

1. Human population
2. World food production
3. Total industrial production
4. Level of pollution
5. Non-renewable resources
6. Food per capita
7. Consumer goods per capita
8. Services per capita
9. Life expectancy
10. Human welfare index (representing life expectancy, wealth and education level)
11. Human ecological footprint (the total area of land necessary to support the levels of the other variables).

This model was encoded into a computer simulation in 1971. The software allowed for the input of various combinations of assumptions to be fed in regarding policies that humanity might choose to adopt in the next few decades. The output of the program consisted of graphs plotted to depict the values of those variables projected from year 1900 through to 2100. years Eleven different scenarios were produced to reflect different assumptions about the effects of various different policies. Over the last 46 years, several of the projected scenarios have ceased to be possible .

This is Section 1.7 of my forthcoming book Swindled! – The Broken Promise of Western Civilisation, and What You Can Do About It. It is the introduction to the thread on The System of the World, which – in conjunction with the other seven themes of the book – provides a comprehensive survey of the position we find ourselves in at this critical time in human history.

If you haven’t already done so, you can register to receive a free review copy just before it goes on general sale later this summer. Registering will also take you straight to Chapter 1 – The Foundations which will give you an overall idea of what the book will cover.