The idea of an index in economy is simple: find a way to measure a change in an ensemble of values in a single value, and then track that single value over time.
The challenges are many: how do you pick the values in your basket, and do you weight them differently? Do you update them, and if so with what periodicity? And then – of course – how do you interpret the index? What does it mean? And how do you make sure that it is not interpreted in a way that overloads it with meaning?
Indices can have an emotional, almost visceral, effect on us. Days the stock index is up some of us feel more elated and happy – and when it is down we feel less successful and confident, and that is not just us amateurs. Even someone like Warren Buffett admits to buying different breakfasts depending on how bouyant the market makes him feel!
The challenge of building an index is that you need to find good data sets – or produce them – and then refine the index over time. This takes hard, honest econometric work, so when new indices are presented is almost always worthwhile to examine them more clearly.
One such new index recently presented is the North American Container index. The authors state that:
this index can be incorporated into a structural vector autoregressive model of the US economy that includes, in addition, a measure of real personal consumption and US manufacturing output. The model facilitates the identification of shocks to domestic US demand as well as foreign demand for US manufactured goods, while accounting for unexpected frictions in North American container trade associated with shipping delays, port congestion, labour strife, and foreign supply chain bottlenecks. The model shows that, on average, shocks related to frictions in the container shipping market have a nontrivial effect on the US economy. They account for 29% of the variation in US manufacturing output relative to trend and 38% of the variation in detrended real personal consumption.
And here is a chart:
Certainly an index worth thinking about, and one peaking these days!
But more interestingly – what are some indices that you would like to be able to construct? Which data sets would you need? Imagining indices a fine summer day may sound like the nerdiest thing you could imagine, but it is a good way to think through problems.
Indices are surprisingly powerful mental models.