Oil price effects: a simple evaluation

After some time off for exams, the blog posts can now continue! I'd first of all like to wish you all a happy and prosperous New Year. Now with the formalities over, let's get on with it!

"Everything changes but change." Israel Zangwill

Unless you’ve been living under a rock for the past one and a half years, you’d be well aware that the price of oil has been having a torrid time. From a local peak of $115 per barrel in the summer of 2014, Brent crude oil prices have fallen to just under $27 a barrel - a fall of around 75%, even more than its fall doing the worst of the 2008 financial crisis. Over the past year, the macroeconomic effect of this has been one of the main areas of debate, with many respectable economists and institutions giving their two cents. Now that enough time has passed to gather some actual data, this post takes a step back and tries to figure out who was right and wrong, and more importantly, what the actual outcome was.

There were two schools of thought regarding the reasons behind the oil price weakness at the time - one based on the supply side, and one on the demand. To be clear, I stand somewhere in the middle - I believe both sides have played a role, but the timings of the price fall suggest it is more a supply-side issue than that of demand. 

The supply-siders:

The hypothesis here was that the oil price weakness was due to a large increase in oil supply (see the ECB here). Here, charts were shown of the rapid expansion of shale oil produced in the US which flooded the market. At the same time, quotes and stylised facts were reeled off regarding the decision by OPEC (aka Saudi Arabia) not to cut production in the wake of oil price weakness, unlike previous actions at similar junctures. This, according to them, signalled to markets that the ‘reaction function’ of the Saudis had changed. I have some sympathy with this view, and it has not be more present than the lurch lower in the oil price after the lifting of the Iran sanctions that should bring 500,000 barrels a day to the market. 

Subsequently, as the world was hit by a supply shock, proponents of this hypothesis concluded that input costs of net oil importing countries (mainly advanced economies such as the Eurozone, UK and the US) would also fall, allowing for - at the margin - higher consumption and production and hence economic growth. (See the IMF’s take on the issue here.) On the other side, those countries who were producing this oil would for sure feel the brunt, leading to weaker growth and a depleting of their fiscal revenues. But as these countries were small in GDP terms, considering the problem from a global perspective would leave world in a much better place.

The demand-siders:

The other school of thought posited that the oil price weakness was a symptom of already weakening global demand (here and here). It was pointed out that the oil price has already started falling before the OPEC announcement and that countries across the world were already rife with disinflation. Furthermore, a slowing China was the smoking gun that brought the argument together for this group. 

Weak global demand, they said, was predominantly due to the ‘debt overhang’ from the financial crisis. That is, households and firms, who took on too much debt when times were good, were now having to cut back on investment and consumption to pay that back. So, when faced with such a windfall from this lower oil price, agents would either save it or use it to pay off debt - exactly what caused the weak demand in the first place. Consequently, consumption and production wouldn’t rise, meaning that we wouldn’t see the increase in GDP that the supply-siders were expecting. 

What does the data say?

Unfortunately, the answer isn’t so clear cut. The world economic output grew by 2.4% from Q1 2013-Q1 2014, just before the oil collapse. The same period in 2014-2015, GDP growth fell to 1.72%. Some commentators on the demand side have used this as confirmation of their theory. But this link is tenuous at best. With global GDP consisting of a multitude of factors, not just consumption, evaluating their modelling of global consumption with respect to a change in the oil price this way could be misleading.

The chart above shows private consumption of the 5 largest net importers of oil. The idea here is that these countries are supposed to have benefitted the most from cheaper oil as they are the ones that use it the most. Note that these 5 countries account for 55% of the world’s GDP, a large chunk. As you can see, nearly all the countries have seen positive changes to their private consumption growth compared to a year previously. Those who do not (the US and China) are marginally negative. So a closer look suggests that, cheaper oil HAS been positive for consumption in these countries. 

So a slight dip into the detail, it seems that those arguing for the increase in consumption in developing countries were right. It turns out that consumers did go out and spend more than they did in the previous year - which I attribute to the fall in oil prices. On the other hand, looking at the aggregate data, it would seem that the demand-siders were right - world GDP and indeed GDP growth in a lot of those oil importing countries didn’t rise substantially.

The bottom line

This dichotomy, I think, really boils down to a subtle assumption in a lot of economic models when trying to uncover effects such as these. The assumption is always ‘ceteris paribus’, or ‘all else equal’ (in less fancy language). This is amounts to what economists call partial equilibrium analysis. The question they are essentially asking is, ‘if oil prices fell, and nothing else changed, what would be the effect of output and inflation?’ 

The reason why partial equilibrium analysis is so common is that it simplifies the problem into bitesize, easily digestible, chunks. Though this may be useful to understand the causes of things, it may not correctly forecast the actual outcome, because things that were assumed to be unchanged do change. This is where DSGE models come into their own, as they aim to forecast the direct and indirect effects of a change in a variable - in this case, the oil price. Nonetheless, they assume ‘exogenous’ factors outside the model are constant. But again, even when evaluating these models, it’s worth bearing in mind that the only thing that doesn’t change is change itself.