Question

A researcher plans to study the causal effect of police on 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 county’s police force. (a) Explain why this regression is likely to suffer from omitted variable bias. Which variables would you add to the regression to control for important omitted variables

Answer 1

Answer and Step-by-step explanation:

This regression can generate an omitted variable bias, because the researcher did not determine any parameters or real data to measure it. In this case, the researcher determined the crime rate as a dependent variable, but did not establish the facts that influence it and that promote an observable result. In this way, he omitted the independent variable and his research will be inaccurate and incorrect. To control this bias, it is necessary for the researcher to provide a dependent variable such as the level of education in the region, the income distribution in the region, the unemployment rate, the fraction of young men, among others.