Causal Inference
The fundamental goal of econometrics as a field is causal inference.
Causation
To study the impact of some treatment variable on an outcome variable, all other variables must be held constant. If a relationship can be observed ceteris paribus, then causation has been identified.
In Social Science
The unit of measurement in social science is almost always people. It isn't possible to perfectly recreate the conditions which led to a person interacting with an experiment, just to apply a treatment.
As a result, true causal experiments are impossible in social sciences. Instead, statistical inference is applied. In a random sample, observed statistics reflect the actual population parameters. When two random samples are drawn, and an experiment is conducted applying a treatment to one, any statistically significant difference in outcome statistics reflect causation.
A further complication: there are non-negligible ethical barriers to conducting many experiments when the unit of measurement is people. This is mitigated only institutionally, i.e. by use of Institutional Review Boards (IRBs).
Measurement
Quantitative methods for analysing causation (esp. econometrics) rely on precise measurement of both treatment and outcome variables.