You might be inspired by Joshua Angrist (MIT) who talks in this podcast about the craft of econometrics--how to use economic thinking and statistical methods to make sense of data and uncover causation.
Using natural experiments is a good way to establish causation. A natural experiment is an empirical setting in which individuals are exposed to the experimental and control conditions that are determined by nature or by other factors outside the control of the investigators. A growing literature relies on natural experiments to establish causal effects in macroeconomics (see Nicola Fuchs-Schuendeln and Hassan, 2016).
For those trying to find such natural experiments as a basis for their own research, Angrist says:
One thing I learned is that empiricists should work on stuff that's
nearby. Then you can have some visibility into what's unique and try
to get on to projects that other people can't do. This is particularly
true for empiricists who are working outside the United States.
There's a temptation to just mimic whatever the Americans and British
are doing. I think a better strategy is to say, "Well, what's special
and interesting about where I am?"
Angrist has also written accessible and relevant papers on data and causation:
- Angrist, Joshua D., and Jörn-Steffen Pischke. 2010. "The Credibility
Revolution in Empirical Economics: How Better Research Design Is
Taking the Con out of Econometrics." Journal of Economic
Perspectives, 24 (2): 3-30.
- Angrist, Joshua, D., and Alan B. Krueger. 2001. "Instrumental
Variables and the Search for Identification: From Supply and Demand
to Natural Experiments." Journal of Economic Perspectives, 15 (4):