What economics can (and can’t) tell us, part 1: carbon taxes

On my first day as a civil servant, my new boss asked, “So, Hannah, what would you say are the three key concepts in economics?”  I was tongue-tied – it felt like a trick question. What three concepts could I possibly pick to impress him?

Over the next few weeks, I’m going to do a short series of blog posts about the three concepts I settled on. The first was ‘equilibrium’.

Equilibrium features in a lot of sciences – chemistry, biology, physics, etc. It’s generally meant to describe a ‘balanced’ or steady state of affairs. For example, we might think of the equilibrium of a factory – where there is a lot going on, but there is an underlying ‘order’ associated with it. Equilibrium is very much associated with macroeconomics – i.e. how economies – whether that’s whole countries or just a village – function.

Some people think the world works like a factory. Credit: DFID, 2010

Economists use equilibrium all the time. Take yesterday, when Australia announced that it’s going to bring in a carbon tax from July 2012. It was fantastic and well-overdue news for the world. Australia signed up to the Kyoto Protocol just before the Copenhagen Climate talks in 2009. But only now has it managed to bring in new policy to tackle climate change.

In all the news reports about the carbon tax, people have been quoting hotly contested numbers about the sorts of effects the tax might have on prices, businesses, people’s incomes, jobs, and the economy – neatly summarised in this infographic. The numbers are mostly derived from economic reports, the most important by Australia’s Treasury in 2008, and by Professor Ross Garnaut – Australia’s equivalent of the UK’s climate change guru Lord Stern.

If you look closely at this economic analysis, you’ll see that equilibrium is at their core. Most of the numbers were calculated using computable general equilibrium models – models that use historic data and mathematical formulae to predict how an economy might react to changes in policy, technology or other external factors. I described these models briefly in a previous blog post.

Australia isn’t unusual in using equilibrium analysis. In the Stern Review, we used a dynamic stochastic general equilibrium model. Applied general equilibrium models and partial equilibrium models also exist. Such models are also used in developing countries. For example, a 2010 study for South Africa (pages 78-98) suggested that a carbon tax – especially if revenues were re-distributed to the poorest households or investment was increased – could have positive effects on the economy and poverty reduction. A 2007 study in Indonesia suggested similar outcomes. The analysis has been persuasive: South Africa’s Treasury have now announced plans to bring in a carbon tax.

But I have to admit that I’ve always found equilibrium to be one of the most difficult concepts to get my head around, partly because the world doesn’t really seem to function like one big factory. We see big, irreversible shifts that change the entire structure of factories or economies all the time – from natural disasters, to mobile phone revolutions, to internal practices like the Ford assembly line. These – and their effects – are unlikely to be predicted by equilibrium models. Indeed, physical scientists have been progressively moving away from the concept of equilibrium, now examining ideas like the “Anthropocene” – which focuses on the profound effects that humans are having on the planet – as explained in this Tea with the Economist Video:

Luckily, I’m not alone in feeling somewhat uncomfortable with equilibrium.  The Origin of Wealth by Eric Beinhocker, a Senior Fellow at the McKinsey Global Institute, sets out ideas for how policy might look different if we based our thinking on “complexity economics” instead of ordered equilibrium thinking. This amusing short video, discovered yesterday by a fellow blogger Oxfam International’s Duncan Green, provides an even easier-to-digest idea of the potential differences.

I’m not saying equilibrium models are useless. Not at all! They can tell us a lot and, crucially, prepare us for change. But, for example, there have been some effects of UK climate change policy that models didn’t predict – such as the ease with which companies would be able to reduce their emissions when the UK Emissions Trading Scheme was first introduced. So much so that almost a third of the emissions credits had to be cancelled two years later.

That’s why it’s crucial that equilibrium models are complemented by other types of analysis. For example, in a paper for the DFID-funded International Growth Centre, economists Duflo, Greenstone, Pande and Ryan have suggested that a pilot Emissions Trading Scheme in India should be rigorously monitored and evaluated. This could be done by comparing the emissions over time of a number of randomly selected factories that are involved in the pilot scheme, to the emissions of a random selection of factories not involved in the pilot, and perhaps another random selection of factories regulated in a different way.

I do hope that Australia, South Africa and all the other countries implementing carbon management policies will take the opportunity to monitor their outcomes too, so that we can learn from our real-world actions.

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