How many people do we need? How many do we want? The astonishing announcement last year that the population of England and Wales increased by more than 3.7 million between 2001 and 2011 brought population to the forefront of political debate here in Britain. Two recently published books on the consequences of continuing world population growth – Stephen Emmott’s Ten Billion and Danny Dorling’s Population Ten Billion – remind us that they are of global significance as well.

In 1926, John Maynard Keynes published one of his most celebrated essays – “The End of Laissez-Faire”, in which he proclaimed the demise of the ideology that had served as the fundamental underpinning of economic and social policy for most of the previous century. The Great War and its economic aftermath, Keynes explained, had done for the dogma that the unfettered pursuit of individual self-interest would always and everywhere be for the best. A new age was dawning: one in which the virtues of judicious government intervention would be rediscovered. There were three fields in particular, he predicted, in which deliberate regulation by government policy would be required.

The first was industry and national investment; the second, money and finance. On both these fronts, Keynes proved prophetic. After 1945, nationalisation of the commanding heights of the economy did indeed put control of aggregate investment firmly in the hands of the state and ingrained a presumption that the government is responsible for macroeconomic management, which survived intact the reprivatisation of industry in the 1980s and 1990s.

Meanwhile, in the monetary sphere, the self-regulating mechanism of the gold standard was swept away and replaced by today’s system of a central bank that sets interest rates in a deliberate effort to achieve low inflation and imposes rules (however feeble) to control the behaviour of commercial banks.

But in the third field that Keynes proposed, state regulation remains as taboo today as it was 87 years ago. “The time has already come,” he wrote, “when each country needs a considered national policy about what size of population, whether larger or smaller than at present or the same, is most expedient.”

Keynes merely asserted his point. Professors Emmott and Dorling make their cases in more detail, and in doing so they exemplify the two approaches to the population question that have dominated this debate for centuries.

Emmott takes the natural scientists’ approach – the perspective of biologists, chemists and physicists (though one that originated, ironically enough, with Robert Malthus – one of the fathers of modern economics). It sees the growth of human population, like that of other living things, as being constrained by the carrying capacity of the ecosystem: a physical limit defined by the scarce availability of natural resources.

Dorling, on the other hand, takes the social scientists’ approach – the way of geographers, economists and anthropologists. This sees population growth as determined by political, social and economic factors, rather than physical conditions.

At one level, the natural scientists’ approach is correct. There must be some physical limit to the number of human beings that can be sustained by the earth. In practice, however, the social scientists’ approach is the more relevant one. Human beings live in society and for many millennia now the binding constraints on population growth have been not physical but social and political. Famines, as Jean Drèze and Amartya Sen demonstrated, are generally the result of political failures, not natural causes.

It would be nice if we could understand human society as a natural system, but unfortunately we can’t. In modern economies, people make decisions – about everything from what to buy to how many children to have – based on economic and social incentives, not physical needs. And while physical needs and the earth’s capacity to supply them may be fixed, social needs and the economy’s ability to meet them are not.

In the physical sphere, requirements don’t change: we need the same number of calories to survive today as our ancestors did 500 generations ago. In the social sphere, however, what is valued today is often worthless tomorrow, and people’s behaviour changes accordingly. Just ask the management of BlackBerry or Nokia. Conversely, things not even imagined today may be considered bare necessities in five years’ time. Just ask Mark Zuckerberg – or, on a more prosaic level, whoever it was that invented the chain coffee shop on the high street.

The point, when it comes to population, is that it is social conventions, economic incentives and (most importantly in China) state decrees that determine how many children people have, not physical constraints or the lack of them. These social determinants can be changed and the rate of population growth will change with them.

Many people prefer this social scientists’ perspective because it sounds liberating – or at least, less pessimistic than the Malthusian vision of the natural scientists. Emmott predicts that the world’s population will imminently outrun its resources and so concludes with the apocalyptic advice that today’s children should learn how to use a gun. Dorling’s first chapter, by contrast, is called “Stop Worrying” – because the optimal population level is not some objective fact that can be backed out of a mathematical model of agricultural inputs and outputs, but a collective choice. So maybe there’s no problem after all.

In fact, it cuts both ways. If the question of the optimal level of population is political, not scientific, it may indeed be that the answer will be larger than today’s. But it might also be the same, or smaller. It seems Keynes was right: in matters of demography no less than macroeconomics, it is a fiction to believe that we are objects in a natural system governed by unalterable laws – and that things will therefore take care of themselves and a policy of laissez-faire is the best we can do. Britain, and the world, should indeed start thinking seriously about what level of population it wants.