Problem
Use a Poisson estimation technique to estimate the following model Use this dataset to estimate a linear probability (LPM) and probit model. cigs= ß0 + ß1 lcigpric +ß2 educ + ß3 age + ß4 agesq + ß5 income +d0 white + d1 restaurn + u where cigs is the number of cigarettes smoked by each individual (cigs is a count variable). How do the estimates from the probit model differ from the Poisson model? Calculate and interpret the average partial effect of lcigpric, educ, restaurn and age for 25 year old on the probability of smoking? Are the variables statistically significant? Re-estimate the model using a Negative Binomial estimation technique. cigs= ß0 + ß1 lcigpric +ß2 educ + ß3 age + ß4 agesq + ß5 income +d0 white + d1 restaurn + u How do the estimates from the Poisson model differ from the Negative Binomial model? Which model would you prefer and why? What is the average partial effect of lcigpric, educ, restaurn, and age for a 25 year on the probability of smoking?
The response should include a reference list. Double-space, using Times New Roman 12 pnt font, one-inch margins, and APA style of writing and citations.