I am doing a regression that involves many countries. One independent variable is revenues of sampled companies in each country. But the data I have use the reference countries' currencies (so I have multiple currencies).
The model requires me to scale the independent variables such as revenues using lagged assets (e.g., revenue(t) in Yen divided by assets(t-1) in Yen).
So the question is, do I need to have a uniform currency say US$, or won't the outcomes change even if the currencies are different, as long as the currencies used are the same in each company?
As I understand it, you have a variable that is the average revenue of sampled companies in different countries. The problem with having the different countries using different currencies is that they are no longer comparable at all.
The regression model has no knowledge that these cases have been measured on different scales and so would, as a basic example, treat an average revenue of 200,000 Yuan (which is actually only around USD$29, 000) as larger than USD100, 000.
Thus, you will want to convert all of your values into a comparable value such as converting all of them into USD or maybe converting all of them into some measure of spending power (I'm not an economist so I don't know what metrics are used for this but maybe something like how many loaves of bread the revenue would allow you to buy).
Edit: I am not familiar with the concept of lagged assets so I'm not sure whether what you refer to there is converting the company revenues into some comparable metric.
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