9️⃣

Quiz 9

Total Points: 9

We are interested in looking at the effect of beer taxes on traffic fatalities. We have data on traffic fatality rate (per 10,000 state residents) and beer tax (in dollars per case) in 48 US states, from for all quarters between 1982 and 1988. We use these data to estimate the following regression:

FatalityRatest=β0+β1BeerTaxst+ϵstFatalityRate_{st}=\beta_0+\beta_1BeerTax_{st}+\epsilon_{st}

1. What is the smallest time unit of the panel?

  1. Years
  2. Year-Quarters
  3. Months
  4. Days
‣
Answer

B

  1. What is the group unit of the panel?
    1. Beer Tax Rate
    2. Fatality Rate
    3. Years
    4. States
      5. ‣
      Answer

      D

  2. Given the set up, which of the following fixed effects could we use to reduce the bias in the pooled model above?
    1. Individual Fixed effects (because they are the ones drinking beer)
    2. County Fixed Effects
    3. Month Fixed Effects
    4. State Fixed Effects
      5. ‣
      Answer

      D

Suppose we add state fixed effects (αs)\alpha_s) and year-quarter FE γt\gamma_t, such that the estimated equation is:

FatalityRatest=β0+β1BeerTaxst+αs+γt+ϵstFatalityRate_{st}=\beta_0+\beta_1BeerTax_{st}+\alpha_s+\gamma_t+\epsilon_{st}
  1. Mark all the variables that you could include in the regressions:
    1. Region fixed effects (dummies for each of the 4 regions)
    2. State unemployment rate
    3. Year FE
    4. Seatbelt laws (whether a state has adopted them or not in a particular year)
    5. A dummy accounting for the 1992 recession
      6. ‣
      Answer

      D, and B

  2. When using the Least Square Dummy Approach (LSDA), we should include a dummy variable for every single state.
    1. True, we should include a binary variable for each state
    2. False, we should omit one state
    3. False, we should include a continuous variable of the state
    4. False, because we would omit a year dummy and that would be enough.
      5. ‣
      Answer

      B

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