The Risk of Gambling Problems in the General Population: A Reconsideration.

We examine the manner in which the population prevalence of disordered gambling has usually been estimated, on the basis of surveys that suffer from a potential sample selection bias. General population surveys screen respondents using seemingly innocuous "trigger," "gateway" or "diagnostic stem" questions, applied before they ask the actual questions about gambling behavior and attitudes. Modeling the latent sample selection behavior generated by these trigger questions using up-to-date econometrics for sample selection bias correction leads to dramatically different inferences about population prevalence and comorbidities with other psychiatric disorders. The population prevalence of problem or pathological gambling in the United States is inferred to be 7.7%, rather than 1.3% when this behavioral response is ignored. Comorbidities are inferred to be much smaller than the received wisdom, particularly when considering the marginal association with other mental health problems rather than the total association. The issues identified here apply, in principle, to every psychiatric disorder covered by standard mental health surveys, and not just gambling disorder. We discuss ways in which these behavioral biases can be mitigated in future surveys.

Disordered Gambling Prevalence: Methodological Innovations in a General Danish Population Survey.

We study Danish adult gambling behavior with an emphasis on discovering patterns relevant to public health forecasting and economic welfare assessment of policy. Methodological innovations include measurement of formative in addition to reflective constructs, estimation of prospective risk for developing gambling disorder rather than risk of being falsely negatively diagnosed, analysis with attention to sample weights and correction for sample selection bias, estimation of the impact of trigger questions on prevalence estimates and sample characteristics, and distinguishing between total and marginal effects of risk-indicating factors. The most significant novelty in our design is that nobody was excluded on the basis of their response to a 'trigger' or 'gateway' question about previous gambling history. Our sample consists of 8405 adult Danes. We administered the Focal Adult Gambling Screen to all subjects and estimate prospective risk for disordered gambling. We find that 87.6% of the population is indicated for no detectable risk, 5.4% is indicated for early risk, 1.7% is indicated for intermediate risk, 2.6% is indicated for advanced risk, and 2.6% is indicated for disordered gambling. Correcting for sample weights and controlling for sample selection has a significant effect on prevalence rates. Although these estimates of the 'at risk' fraction of the population are significantly higher than conventionally reported, we infer a significant decrease in overall prevalence rates of detectable risk with these corrections, since gambling behavior is positively correlated with the decision to participate in gambling surveys. We also find that imposing a threshold gambling history leads to underestimation of the prevalence of gambling problems.

Individual discount rates and smoking: evidence from a field experiment in Denmark.

We elicit measures of individual discount rates from a representative sample of the Danish population and test two substantive hypotheses. The first hypothesis is that smokers have higher individual discount rates than non-smokers. The second hypothesis is that smokers are more likely to have time inconsistent preferences than non-smokers, where time inconsistency is indicated by a hyperbolic discounting function. We control for the concavity of the utility function in our estimates of individual discount rates and find that male smokers have significantly higher discount rates than male non-smokers. However, smoking has no significant association with discount rates among women. This result is robust across exponential and hyperbolic discounting functions. We consider the sensitivity of our conclusions to a statistical specification that allows each observation to potentially be generated by more than one latent data-generating process.