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  • Are structural break tests appropriate for this situation?

    Brief background: I’m examining mediation rates in China. I have a panel dataset with N=24 provinces and T=30 years (1985-2014). For each province-year, I observe mediation rates and host of economic/demographic information.

    Anecdotal reports suggest that in 2006 or soon thereafter, the Chinese government began bolstering its mediation system and encouraging its use. My goal is to test this assertion. Unfortunately, I’m unable to quantify the “effort” the government exerts in promoting mediation and so I am considering testing for a structural break at 2006.

    I can't figure out whether structural break tests are appropriate for my purpose. My understanding is that a structural break refers to a sudden change in the mean or variance of a variable. I'm not proposing that the mean or variance of mediation rates changes immediately at 2006, nor do I have reason to believe that the betas on my regressors change at 2006. Rather, my hypothesis is that beginning in 2006, mediation rates are set on a "new trajectory." For example, declining mediation rates before 2006 and rising rates after 2006 would be consistent with my hypothesis. In this case, means, variances, and betas before and after 2006 could be the same.

    Will structural break tests address my hypothesis of a change in trajectory? I've looked at several papers but am having trouble answering this question on my own.

  • #2
    You'll increase your chances of a useful answer by following the FAQ on asking questions - provide Stata code in code delimiters, readable Stata output, and sample data using dataex.

    You could include a lagged dv and let the parameter on the lagged dv vary between the two time periods. Or you could calculate changes in mediation year to year and test for equality between the two periods.

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