There are many types of economic data, but the type considered by Rob Engle and myself is know as time series.
Sentiment: NEGATIVE
Rob Engle and I are concerned with extracting useful implications from economic data, and so the properties of the data are of particular importance.
It's like simulating earthquakes: we can over and over study a bubble, crash, bubble, crash. Then we can see mathematically if there's some regular pattern and what's going on in people's brains when prices are going up and before the crash is happening.
Economic forecasting has actually got pretty good over the years, though admittedly, we don't always get it right.
It's kind of a funny way to put it, but if you want to study a dynamic economic system, what you'd like to be able to do is focus on the linkages, say, between asset markets and the macro economy without having to model everything at the same time.
I work on the boundary between economics and statistics in this field called econometrics. Part of my interest is understanding how you use statistics in productive ways to analyze dynamic economic models.
While data can only tell you what has happened in the past, it can in some ways give you a sense of what might be of interest to an audience in the future.
If you have to forecast, forecast often.
Evolving technologies that allow economists to gather new types of data and to manipulate millions of data points are just one factor among several that are likely to transform the field in coming years.
For economist the real world is often a special case.
I'm not an economist and we all know economists were created to make weather forecasters look good.
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