e are interested in analysing the effect of the lockout laws introduced in some areas of the Sydney CBD and nearby surrounds on the number of alcohol-related violent incidents. Suppose we have two samples of data on the number of violent incidents in a number of local areas of the Sydney CBD and nearby surrounds. Pubs, hotels and clubs located in a subset of these areas became subject to the lockout laws when they were introduced in 2014. The first sample is from 2010 before the introduction of the lockout laws, and the second is from 2015 after the introduction of the law. The hypothesis we wish to test is that the introduction of the lockout laws reduces violent incidents in the areas in which the lockout laws were put in place. We use a difference-in-difference model on the pooled data from 2010 and 2015. We find the following results: viol_inc hat = 33.21 (5.29) + 12.43lockout (7.01) – 4.19Yr2015 (2.98) – 3.32 (lockout x Yr2015) (1.85) N = 181, R^2 = 0.128 Where: viol_incis the number of violent incidents in the local area lockoutis an indicator variable equal to 1 if the area is one in which the lockout laws were introduced, and equal to 0 otherwise Yr2015is a dummy variable equal to 1 if the year is 2015 and 0 otherwise Using the information above, answer the 3. [iv] What is the interpretation of the coefficient on (lockout×Yr2015)? [v] We have not included any other explanatory or control variables in Model (D1). State one advantage of including additional relevant and exogenous explanatory variables in the model. Suggest one variable that you think would be useful and appropriate to include in the model. [vi] Based on these findings, what policy advice could you give to the City of Sydney local government regarding lockout laws? Please write no more than 2 sentences.
We are interested in analysing the effect of the lockout laws introduced in some areas of the Sydney CBD and nearby surrounds on the number of alcohol-related violent incidents.
Suppose we have two samples of data on the number of violent incidents in a number of local areas of the Sydney CBD and nearby surrounds. Pubs, hotels and clubs located in a subset of these areas became subject to the lockout laws when they were introduced in 2014. The first sample is from 2010 before the introduction of the lockout laws, and the second is from 2015 after the introduction of the law. The hypothesis we wish to test is that the introduction of the lockout laws reduces violent incidents in the areas in which the lockout laws were put in place.
We use a difference-in-difference model on the pooled data from 2010 and 2015. We find the following results:
viol_inc hat = 33.21 (5.29) + 12.43lockout (7.01) – 4.19Yr2015 (2.98) – 3.32 (lockout x Yr2015) (1.85)
N = 181, R^2 = 0.128
Where:
- viol_incis the number of violent incidents in the local area
- lockoutis an indicator variable equal to 1 if the area is one in which the lockout laws were introduced, and equal to 0 otherwise
- Yr2015is a dummy variable equal to 1 if the year is 2015 and 0 otherwise
Using the information above, answer the 3.
[iv] What is the interpretation of the coefficient on (lockout×Yr2015)?
[v] We have not included any other explanatory or control variables in Model (D1). State one advantage of including additional relevant and exogenous explanatory variables in the model. Suggest one variable that you think would be useful and appropriate to include in the model.
[vi] Based on these findings, what policy advice could you give to the City of Sydney local government regarding lockout laws? Please write no more than 2 sentences.
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