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I want to measure whether the impact of a company's headquarter country on my dependent variable (goodwill paid) is stronger during recessions. After some researching, I found out that the differences-in-differences analysis could solve my problem. However, in the internet they always show a diagram (see Figure 1 in Difference-in-Difference Estimation by Columbia Public Health) with the "treatment" and "parallel trends". So two lines that increase or decrease in the same way until the treatment and then one line increase/decreases more than the other. My question now is what is my treatment and what is my control variable in my example? The treatment cannot be recessions because otherwise I just have the treatment group after the treatment and the control group before the recessions. If you think another statistical test may be better, I would be happy to consider that.

Furthermore, I just want to make sure that I created my model correctly: Goodwil Paid=B0+B1recession+B2Country+B3recessionCountry Would that tell me whether the impact of the country is stronger during recessions?

Variable descriptions: -Goodwil paid (dependent variable): Is about how much is paid for a company in acquisitions. -Recessions: 1 if the acquisition was during the crisis and 0 otherwise -Country: The country the acquired company is bought in. It can have a value from 1 to 10 and is based on credit ratings of the countries. Most countries have the rating 1.

Thanks a lot for your help. Let me know if you need further information.

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  • $\begingroup$ A couple of comments: (minor) The variable on the left (goodwill paid in your case) is the dependent or outcome variable. (major) I don't see how this model will answer your question. What you want to compare is goodwill for "similar"/"comparable" companies with vs without recession. $\endgroup$
    – dipetkov
    Commented Feb 12, 2023 at 13:40
  • $\begingroup$ You are right of course it is the dependent variable. I changed it in my question. Do you have another idea how to test this? I at least assume that companies are comparable and I want to find out whether the impact of country on goodwill paid is higher in recessions. $\endgroup$
    – user379804
    Commented Feb 12, 2023 at 15:04
  • $\begingroup$ Have you selected the companies to be comparable? Are they all in the same industry, of comparable size and with comparable annual turnover/profits? Now that I think about it -- how are you treating international companies? how do you assign those to countries? If you just took companies headquartered in the same country, then I don't seen how you can reasonably claim they are comparable "by default". $\endgroup$
    – dipetkov
    Commented Feb 12, 2023 at 15:10
  • $\begingroup$ Yes that is true and I will write a big part about this topic in my critical reflection. But do you have another test that would work if I assume that the companies are comparable? $\endgroup$
    – user379804
    Commented Feb 12, 2023 at 15:23
  • $\begingroup$ Not really, I just have concerns about the proposed analysis which I already mentioned. I don't think "let's just assume things we want to hold actually hold" is a reasonable scientific approach. $\endgroup$
    – dipetkov
    Commented Feb 12, 2023 at 15:27

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Your situation is slightly more complicated than a standard diff-in-diff (DiD) that has two groups. However, the gist is the same.

A standard DiD would ask something like if US and UK firms have a different impact on goodwill paid in recessions vs normal times. That is achieved by interacting an indicator variable for US vs UK with an indicator for recession vs a normal economy.$^{\dagger}$ You then test this interaction term.

You, however, seem to have companies in multiple nations, meaning that you have multiple groups instead of a control and treatment group. Consequently, you would want to interact the recession/normal dummy with all country indicator variables (with one country being subsumed by the intercept, as is typical for ANOVA derivatives). You then test if the interaction between recession/normal and the country indicator is significant by using a chunk test of nested models. The full model has an intercept, an indicator for recession/normal, indicators for the various countries (with one country omitted and subsumed by the intercept), and the interaction between the recession/normal variable and all of the country indicator variables. Nested within that model is a model with just the intercept, recession/normal indicator, and country indicator (with that same one country omitted and subsumed by the intercept). This then tests if any of the countries behave differently in recession times va normal times, assuming the counties meet the parallel trend assumption of DiD, where the counties move in parallel before the recession hits.

In many regards, this is an ANCOVA with an interaction, just with the traditional continuous covariate replaces with the binary recession/normal indicator variable.

One of the reasons people like DiD is because it helps draw causal inferences. I have major reservations about that here, with comments to the OP making what I believe to be good points, but that chunk test should cover the pure statistics of performing a test.

$^{\dagger}$I have multiple concerns about this approach. First, different countries have different economies, so the US could experience a normal economy while another country experiences a recession. Then the comparison is not on equal footing, since the global economy during those times would be the same. Second, “recession” is not a binary variable.

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  • $\begingroup$ $1)$ Note that, depending on what you want to do, this one test can be followed by using contrasts to explore which countries differ from each other and by how much, though this warrants a separate question in my opinion. $//$ 2) Recessions could occur in a staggered fashion, where the recession hits one country in May and then another in July and then another in October. This would call for a staggered DiD, discussed by Baker/Larcker/Wang (2022): How much should we trust staggered difference-in-differences estimates. $\endgroup$
    – Dave
    Commented Feb 12, 2023 at 16:42
  • $\begingroup$ Thank you Dave for your help. It is much appreciated because I don't get further. However, I have two follow up questions: 1. Would it still be a DiD analysis? Would the treatment be the recession and the control group the country captured in the intercept? 2. How would I test this interaction effect? Normally I would calculate recession * Country. However, this only works if the country has a numerical value right? $\endgroup$
    – user379804
    Commented Feb 16, 2023 at 9:15
  • $\begingroup$ 1) Would what still be a DiD analysis, the staggered DiD? I would call that a staggered DiD. 2) The "chunk" test discussed in my answer is the approach I would take to testing the interaction between the binary recession variable and the multi-level country variable. $\endgroup$
    – Dave
    Commented Feb 16, 2023 at 13:17

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