Abusing the Future

We all know that we don’t know what the future will hold but we all plan for it anyway. We plan our holidays, our retirement, the sales of a new product and the state of the economy. We pull wool over the eyes of our ignorance because someone, somewhere needs a view.

Just occasionally, there is the potential to have more than one view. Most of us find this quite hard. We are not programmed to believe several impossible things before breakfast. We are happy to talk about risks, but these are merely up and down (usually down) divergences from that ‘view’. It is often described as a central view but this is not often really the case; it is very unusual when a commentator has as many risks on the upside as on the down.

These views are stories. Stories have coherence and rationality. They tell why this will happen as a result of that. They give comfort of an evening that we can make sense of the world we live in. Scenarios both increase and decrease this comfort. Once, long ago, when I still engaged with large macroeconomic models we set up a scenarios club. With our clients, we proposed to develop scenarios of alternative futures of the world economy. (My macro model was so large that it covered the whole world!) The club sat down to envisage the scenario. We talked of oil shocks and market shocks – it was 1987 – and the future of international agreements. Every scenario that we imagined was run through the model and presented to the club. And then the reactions would set in.

Each participant imagined the policy reaction to the shocks. And when we ran these through the models, we got swiftly back to the business as usual which was our baseline forecast. A world in which things go on pretty much as they have done before. Our scenario club, perhaps not surprisingly, did not last long. I didn’t last long either. I quickly came to the conclusion that these models were a waste of time and money and told me nothing I could not write on the back of an envelope or fag packet (I was still smoking in those days).

Moreover of course we utterly missed the real scenario of the rise of new economies and the spread of globalised markets. Nor could our model have handled this, since it had no data on China and India and very little on Brazil or Russia.

This shows how hard it is to imagine alternative futures, in which the world is really different. And even if we can imagine the causes of these, the outcomes are utterly unpredictable. Not so much stories as fairy stories. So why bother?

One reason to bother is that it might help to be ready when things change. The story of Shell’s success in reacting to rising oil prices in 1973 is supposed to reflect how it had considered this scenario in advance. And this is certainly why the military play war games: when things move fast it helps to have figured out your reaction in advance rather than trying to do the analysis in real time.

On the other hand, playing war games convinced some highly intelligent analysts during the Cold War that pre-emptive strike was the best solution. Fortunately more cautious counsel prevailed. So scenarios are not an unmixed blessing. In this case, they were being used to counsel extreme reaction. A similar use, potentially similarly by vested interests, has been provided by some climate scientists. A scenario based on the risk of greenhouse gas increases, subsequent temperature rises, sea level increases and tipping points of various physical relationships has been used to create a scare which at one level induces the desire to play hard because it is all too late to save the planet.

At other levels, the scenario is simply a story. Facts are uncertain, their implications still more so. Our reactions can stabilise or destabilise and to be frank in the current state of knowledge either could be the case. One reaction to this is to look for probabilities. With enough history we can estimate the probability distribution of any variable in which we are interested. In this case, upside and downside risks are much more likely to be balanced and human tendencies to be either gloomy or optimistic might be minimised. But probabilities are not stories. They carry no freight of rationality or causation, nor of policy reaction implications. The Bank of England has carried probability ranges of inflation and output outcomes for some years now. They are not very wide (not nearly as wide as the data suggests) and in any case have not succeeded in getting much traction. People prefer stories.

An important reason for this is a sense that we face uncertainty. Uncertainty means we cannot attach probabilities to any given outcome. We simply do not know what is most likely. So it is not irrational to prefer the story. Choosing stories to tell and writing stories helps us learn about possibilities. It may help us react to events as they unfold. But it does not help us know what will actually happen. That is much more about defining a probability distribution and considering whether it is possible to do this.

Bridget Rosewell

Making Climate Change win-win

This is the theme of the conference of the European Climate Forum www.european-climate-forum.net this year. Listening to the speeches I am struck by the parallels in analysis between thinking about the impact of climate change and that of infrastructure.

First, we have the scientists. Climate modellers talked about the difficulty of building models that properly incorporated short term natural cycles in order to identify the longer term effects as well as the challenge of separating out local climate effects which are also distinct from large scale impacts. This debate is entirely similar to that about the effectiveness of models of the economy. Most macroeconomic models are concentrated on identifying the prospects for the next five years, and are based on data only since the Second World War. Yet at the same time they are based on equilibrium behaviour which is highly unlikely to be observed in the short term (possibly also the long term but that is the next paragraph). Like climate models, they are imperfect, and like climate models, the pressure to provide the policy outputs militates against model development and strongly against admitting imperfection, data problems or errors.

Second, we have the impact analysts. Many speakers focussed on the distinction between mitigation and adaptation. This raises a debate about economic dynamics which is pretty much absent from the models. A reliance on equilibrium focussed models lies behind the kind of analysis provided by Stern, which shows a long term steady state growth of the world economy which happens anyway and thus gives a small cost to investment in climate change mitigation. In other words, the economy grows and investment happens regardless. The same approach lies behind the difficulty in showing that infrastructure projects generate real additional growth – since the models also show that growth happens anyway. In both infrastructure and climate change models there are too few linkages between investment choices, technologies and growth rates. Thus the baselines have too many assumptions built into them which mean that the real impacts of either cannot be properly evaluated.

Third, this leads to the question of project and investment finance. Finance is the elephant in the room in both topics. In climate change, investments either to mitigate or adapt are seen as a cost. Yet analysis of, for example, the coastal cities, shows that creating flood defences has a significant payback in protecting growth prospects, when the dynamics are separately considered. A dynamic analysis of renewable power projects in Germany shows that it creates added value and added jobs – and thus an ability to raise the funds to create the investment. Finance for investment has to be raised from somewhere. It can come from the taxpayer, whose ability to insist on a payback is rather limited, but whose ability to pay is also in the end limited. Or it can come from savers through the investment funds and pension funds where this money is put. Savers need to get something back for what they put in and they need to be sure that the money will be there. In large regulated investments, which is what infrastructure and climate change projects generally are, this means that government must allocate the returns from these investments to the projects, rather than seeing the returns as coming from the general activity of the economy.

In the UK, it is government practice to ask whether an activity creates additionality or not. The stronger the belief in the underlying equilibrium growth or the economy, the harder it is to show that anything will be additional. This applies both to an infrastructure project and to climate change mitigation projects. Both require spending – transport systems, power systems for example – and both have payback in fares, fees and economic growth. That economic growth needs to be better recognised if we are to raise the funds to make these investments.

Large projects have implications which change the terms on which the economy operates. Such projects are those which drive economic growth and those which are largely exogenous to models – even those which purport to make technical change endogenous. They change the structure of relative prices, and work through the networks of connections by which innovation can occur. Understanding this is key to deciding on investments and needs to be better appreciated by those who are still captured by a now out of date of economic model.

Bridget Rosewell