Professional Writing Sample

Abstract: the following writing sample is part of an assignment for an applied econometrics course. In this assignment I make use of advanced graphing techniques and pivot tables in Excel. I also use STATA statistical software to conduct a “synthetic control” graphical calculation. 

The objective of this assignment is to determine whether or not primary seat belt laws have an effect on the level of fatal car accidents in state TU (an imaginary state that is calculated by averaging out the values of Connecticut, Iowa, New Mexico and Texas). For additional clarification, primary seat belt laws stipulate that a law enforcement officer can ticket a driver for not wearing a seat belt, regardless of whether or not the driver has broken any other laws. The primary seat belt law was implemented in 1986 in state TU.

This dataset covers the period 1981-2003. The next table compares the pre period (1981-1985) log of fatalities per capita for state TU and the 44 control states. We can observe that the treatment state (TU) has a larger number of ln(fatalities per capita) during this period.  In fact, the ln(fatalities per capita) for the control states is approximately 1.17 times lower than TU. 

 From the graph below we can observe the same pattern as the table above where TU has a higher level of ln(fatalities per capita) during the 1981-1985 time period. What this implies is that we need to assign a higher weight to the states that show a pattern that more closely resembles the pattern exhibited by TU in this time period.  

 

When we sort the values of ln(fatalities per capita) in 1985 we find that the state that most closely resembles TU is Alabama:

 

A graphical presentation of this can be seen below:

 

To attempt to predict the level of fatalities per capita in a regression framework I also use the variables per capita beer consumption, rain, and snow in addition to primary seat belt laws.

   

We can observe the values of all variable below differ significantly. This implies that if we use Alabama as a counterfactual state we would not be making an “apples to apples” comparison. Therefore using Alabama as a counterfactual state would be problematic. We observe similar values in the pre-intervention (1981-1985) dependent variable ln(fatalities per capita) for both states. However, the difference in explanatory variables implies that there would be unobserved determinants that can change over time and affect the level of fatalities.  

 

Synthetic Control Method:

The synthetic control method puts heavier weight on the states that more closely resemble TU. This is done to obtain a counterfactual or a comparable control state. This synthetic control state is obtained by calculating the weighted average of all states in the control group. The predictor variables per capita beer consumption, rain, and snow are averaged over the entire period (1981-1985) before the primary seat belt laws were implemented in 1986 in state TU. 

 The graph above was obtained using STATA statistical software. From it we can observe that traffic fatalities per capita declined in the imaginary state TU after 1986 when the primary seat belt law was implemented. Again, the synthetic TU is obtained by averaging out the values of other states in the pre-primary seat belt law period (1981-1985). Based on this information, we can observe what happened in the states that did not implement a primary seat belt law and we can conclude that the decrease in the level of fatalities in state TU after 1988 can be attributed to the implementation of primary seat belt laws.