Some variables are exactly what their label says, and are easily collected and aggregated. Examples include: sales (either in units or value); production (units or value); employment, etc. But for some products or industries these are not easily collected and aggregated.
A proxy variable reflects some aspect of what you're trying to measure, but because of difficulties with data collection or aggregation is not exactly that. Two examples: consumer expenditures instead of product sales; consumer price index instead of product price/cost data.
Below are two examples to illustrate when a proxy variable may be required ...
Some of these databases can also be used to find cross-sectional data ...
Use the CRB Commodity Yearbook for more data on COPPER!