1. What determines how much drivers are fined if they are stopped for speeding? Do demographics like age, gender, and race matter? To answer this question, we’ll investigate traffice stops and citations in Massachusetts using data from Makowsky and Stratmann (2009). Even though state law sets a formula for tickets based on how fast a person was driving, police officers in practice often deviate from the formula. The variables we use are in Table 6.12. An amount for the fine is given only for observations in which the police officer decided to assess a fine.
(a) Is the effect of age on fines non-linear? Assess this question by estimating a model with a linear age term and a quadratic age term, controlling for MPHover, Female, Black, and Hispanic. Interpret the coefficients on the age variables using calculus.
(c) Do drivers from out of town and out of state get treated differently? Do state police and local police treat nonlocals differently? Estimate a model that allows us to assess whether out-of-towners and out-of-staters are treated differently and whether state police respond differently to out-of-towners and out-of-staters. To do this, add to part (a) the dummy variables OutTown and OutState, along with two interaction variables that multiply StatePol with each of the dummy variables. Interpret the coefficients on the relevant variables.
2. Use globaled.csv, the data set on education and growth from Hanushek and Woessmann (2009) for this question. The variables are given in the codebook provided and Table 5.14 in the textbook.
(a) Use standardized variables to assess whether the effect of test scores on economic growth is larger than the effect of years in school. At this point, simply compare the magnitude of the coefficients. We’ll do statistical tests next. The dependent variable is average annual GDP growth per year. For all parts of this exercise, control for standardized GDP per capita in 1960 and always use standardized variables in all parts.
(b) Now conduct a statistical test of whether the effects of test scores and years in school on economic growth differ. Write the null hypothesis that the coefficients are the same and the appropriate alternative hypothesis. What is your conclusion about the null hypothesis?
(c) Now add controls for openness of the economy and security of property rights. Which matters more: test scores or property rights? Conduct a statistical test of whether the effects of test scores and property rights differ. Write the null hypothesis that the coefficients are the same and the appropriate alternative hypothesis. What is your conclusion about the null hypothesis?