Survey Responses on Smoking Behaviour

Description

'Instructional dataset, N=807, cross-sectional individual data on smoking accompanying Introductory Econometrics: A Modern Approach, Jeffrey M. Wooldridge, South-Western College Publishing, (c) 2000 and Jeffrey M. Wooldridge, Econometric Analysis of Cross Section and Panel Data, MIT Press, (c) 2001.' (https://ideas.repec.org/p/boc/bocins/smoke.html#biblio, accessed February 27, 2017). This dataset is a subset of data used in Mullahy (1997). Data was collected in 1979 and 1980 through the Smoking Supplement to the US National Health Interview Survey.

Usage

data(Smoke)

Format

This data frame contains the following columns:

educ

Years of schooling.

age

Respondents age in years.

cigpric

State cigarette price, cents per pack.

income

Annual income in USD.

restaurn

Dummy variable indicating if state restaurant smoking restrictions are in place.

smoker

Dummy variable indicating if person has smoked at least one cigarette.

cigs_intervals

Number of cigarettes smoked per day, coded in intervals with intervals boundaries: (0,5,10,20,50)

cigs

Number of cigarettes smoked per day.

Source

Wooldridge(2009)'s dataset also available in other formats at https://ideas.repec.org/p/boc/bocins/smoke.html#biblio.

Original data used in Mullahy (1985) and Mullahy (1997).

References

Jeffrey, M. Wooldridge (2009), Introductory Econometrics: A modern approach, Canada: South-Western Cengage Learning.

Mullahy, John (1997), Instrumental-Variable Estimation of Count Data Models: Applications to Models of Cigarette Smoking Behavior, Review of Economics and Statistics 79, 596-593.

Mullahy, John (1985) Cigarette Smoking: Habits, Health Concerns, and Heterogeneous Unobservables in a Microeconometric Analysis of Consumer Demand, Ph.D. dissertation, University of Virginia.

Examples

data( Smoke )
# boundaries of the intervals
bounds <- c(0,5,10,20,50,Inf)
## Not run: 
# estimation with starting values obtained by a ML estimation 
# of a standard tobit-2 model with the dependent variable 
# of the outcome equation equal to the mid-points of the intervals
res <- selection( smoker ~ educ + age, cigs_intervals ~ educ, 
  data = Smoke, boundaries = bounds )
summary( res )

# estimation with starting values obtained by a two-step estimation 
# of a standard tobit-2 model with the dependent variable 
# of the outcome equation equal to the mid-points of the intervals
res2 <- selection( smoker ~ educ + age, cigs_intervals ~ educ, 
  data = Smoke, boundaries = bounds, start = "2step" )
summary( res2 )

## End(Not run)

# estimation with starting values that are very close to the estimates
# (in order to reduce the execution time of running this example) 
resS <- selection( smoker ~ educ + age, cigs_intervals ~ educ, 
  data = Smoke, boundaries = bounds, 
  start = c( 0.527, -0.0482, -0.0057, 4.23, -0.319, 2.97, 2.245 ) )
summary( resS )