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In an international setting, when I examine the impact of laws on firms (the laws were implemented by many countries, I need to control for country-level control variables. However, I am wondering whether I should control for country-level control variables when studying impact of laws on firm's productivity in a single country (e.g., a panel data for 100 firms with the time period from 2000 to 2020 - just for exxample).

For example, I want to study the impact of anti-corruption on firms; productivity in Zimbabwe. In this case, whether I need to control for GDP, Real interest rate change,corporate tax, import%GDP....

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These factors would be the same for all firms in the same country correct? Thus if you only have a cross-section of data, the factors would be the same for all observations in the data? If so, then you literally can't control for them because of perfect collinearity.

If you have a panel of data, then including time fixed effects will absorb the effects of all factors that are the same for all firms at each point in time. This will include those country-level variables.

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  • $\begingroup$ Thanks, Michael, I am having panel data rather than cross-sectional data. I am wondering whether it is still the same? $\endgroup$
    – Phil Nguyen
    Commented Sep 16, 2022 at 0:16

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