A researcher plans to study the causal effect of police crime using data from a random sample of U. S. counties. He plans to regress the county's crime rate on the (per capita) size of the country's police force. Why is this regression likely to suffer from omitted variable bias? A. There are other important determinants of a country's crime rate, including demographic characteristics of the population, that if left out of the regression would bias the estimated partial effect of the (per capita) size of the county's police force. Your answer is correct. B. There are other important determinants of a country's crime rate, including demographic characteristics of the population, that if left out of the regression would increase the variance of the estimated coefficient for the (per capita) size of the county's police force. C. Other regressors are likely perfectly collinear with the (per capita) size of the county's police force, so they should be included in the regression. D. None of the above are correct. Which of the following variables are likely useful to add to the regression to control for important omitted variables? A. The number of bowling alleys in the county.
B. The fraction of young males in the county population.
C. The average income per capita of the county.
D. The average level of education in the county.