A Monte Carlo comparison of estimators for a bivariate probit model with selection

prototypical sample selection model consists of a two-equation system: one equation representing the selection mechanism and the second a continuous outcome variable that is only observed for the selected cases. A variant of this model where the outcome variable is binary leads to a bivariate probit model with sample selection. A Monte Carlo experiment is undertaken to examine the small sample properties of three alternative estimators of a bivariate probit model with selection. The three estimators are the censored probit estimator, single-equation probit applied to the selected sub-sample and single-equation probit applied to the full sample

Cervical cancer screening service utilisation in UK.

This study investigates empirically how past screening behaviour, individual and household characteristics affect the current uptake of cervical cancer screening in UK. For the conceptual framework, we use a modified Grossman model which is extended for non-economic factors. A dynamic version of a random effects panel probit model with initial conditions is estimated on the balanced sub-sample of the data. The analysis sample is restricted to women of age 16 and older and grouped into different age categories with respect to the NHS Cervical Screening Programme (NHSCSP). As dataset a balanced panel data of 857 women with 11,998 observations from the British Household Panel Study (BHPS) for the period from 1992 to 2008 is used for the analysis. Results suggest show that previous screening uptake, age, partner status, employment status and a previous GP visit have a significant influence on the likelihood of the uptake of cervical cancer screening

Why worry about awareness in choice problems? Econometric analysis of screening for cervical cancer

The decision to undertake a screening test is conditional upon awareness of screening. From an econometric perspective there is a potential selection problem, if no distinction is made between aware and unaware nonscreeners. This paper explores this problem through analysis of the determinants of cervical screening in Australia. Cervical cancer is one of the most preventable and curable forms of cancer. Since 1991 there has been a concerted effort in Australia to recommend and encourage women to have Pap smears every two years. The success of this program can be partly gauged by exploring the determinants of screening for cervical cancer. Using unit record data from the 1995 National Health Survey, an econometric model is developed for whether women have ever screened or not. A proportion of women in the sample contend that they have never heard of a Pap test. The analysis characterizes this group of women and accounts for their presence in the modelling. The paper demonstrates failing to model awareness can result in inconsistent parameter estimates even when the degree of censoring in the sample is relatively small. Copyright © 2005 John Wiley & Sons, Ltd

Who Takes Advantage of Free Flu Shots? Examining the Effects of an Expansion in Coverage

Because of the high risk of costly complications (including death) and the externalities of contagious diseases, many countries provide free flu shots to certain populations free of charge. This paper examines the expansion of the free flu shot program in the Netherlands. This program expanded in 2008 to cover all individuals over the age of 60, instead of 65. We investigate the effectiveness of the expansion of the flu shot program and examine those factors that are likely to influence people to change their behavior. We find that the main barrier to take up of free flu shots in the Netherlands is labor force participation. Expansion of the program did little to change the behavior of those at increased risk due to co-morbidities, primarily because these individuals were already getting flu shots.

Probability perceptions and preventive health care

We study the effect of perceptions in comparison with more objective measures of risk on individuals’ decisions to decline or accept risk reducing interventions such as flu shots, mammograms, and aspirin for the prevention of heart disease. In particular, we elicit individuals’ subjective probabilities of risk, with and without the interventions, and compare these perceptions to individually predicted risk based on epidemiological models. Respondents, especially women, appear to be aware of some of the qualitative relationships between risk factors and probabilities. However, on average they have very poor perceptions of the absolute probability levels as reported in the epidemiological literature. Perceptions of the level of risk are less accurate if a respondent is female and has poor numeracy skills. We find that perceived probabilities significantly affect the subsequent take-up rate of flu shots, mammograms, and aspirin, even after controlling for individually predicted risk using epidemiological models