Secondary Outcomes (explanation)
The binary outcome models are again estimated with LPM. To assess if treatment effects differ between full and partial compliance, we will compare these estimates to results obtained for our primary outcome.
We will make use of the information about ticket receivers in our dataset to analyze the difference in our outcomes for private and corporate car owners. Furthermore, based on the information on zip codes, we split the sample into local vs non-local car owners. We also analyze differential effects for different speed levels keeping the amount of the fine constant, and, conditional on data availability we will consider heterogeneous effects between first-time speeders and individuals with past speeding infractions.
As part of this heterogeneity analysis, we will make use of the observable characteristics to explore if type heterogeneity drives the pattern in hazard rates.
Using the fact that the fine is a stepwise function of the speed at which individuals were driving, and that the application of fines higher than the lowest one is discretionary, we implement a regression discontinuity design around the first speed threshold that triggers an increase in the fine (using speed as the running variable), to analyze the effect of the size of the fine on timely payment. For this we estimate non-parametrically an equation with dummies capturing total or partial payments within different periods of time on the left hand side and the measured speed, a dummy equal to one if the vehicle's speed is above the cutoff, and a function that captures how the outcome variable varies with the speed (this function is allowed to differ on either side of the cutoff), on the left hand side.
We will estimate these equations for the full sample first. Depending on the number of observations per treatment, we will perform the analysis for the control group sample only. Furthermore, and also contingent on the number of observations, we will investigate if there are treatment differences by including interactions with the treatment dummies to assess if the impact of the higher fines differs across the different treatments.