Agne Suziedelyte

How does searching for health information on the Internet affect individuals' demand for health care services?

The emergence of the Internet made health information, which previously was almost exclusively available to health professionals, accessible to the general public. Access to health information on the Internet is likely to affect individuals health care related decisions. The aim of this analysis is to determine how health information that people obtain from the Internet affects their demand for health care. I use a novel data set, the U.S. Health Information National Trends Survey (2003-07), to answer this question. The causal variable of interest is a binary variable that indicates whether or not an individual has recently searched for health information on the Internet. Health care utilization is measured by an individuals number of visits to a health professional in the past 12 months. An individuals decision to use the Internet to search for health information is likely to be correlated to other variables that can also affect his/her demand for health care. To separate the effect of Internet health information from other confounding variables, I control for a number of individual characteristics and use the instrumental variable estimation method. As an instrument for Internet health information, I use U.S. state telecommunication regulations that are shown to affect the supply of Internet services. I find that searching for health information on the Internet has a positive, relatively large, and statistically significant effect on an individuals demand for health care. This effect is larger for the individuals who search for health information online more frequently and people who have health care coverage. Among cancer patients, the effect of Internet health information seeking on health professional visits varies by how long ago they were diagnosed with cancer. Thus, the Internet is found to be a complement to formal health care rather than a substitute for health professional services.

Education and health knowledge: evidence from UK compulsory schooling reform.

We investigate if there is a causal link between education and health knowledge using data from the 1984/85 and 1991/92 waves of the UK Health and Lifestyle Survey (HALS). Uniquely, the survey asks respondents what they think are the main causes of ten common health conditions, and we compare these answers to those given by medical professionals to form an index of health knowledge. For causal identification we use increases in the UK minimum school leaving age in 1947 (from 14 to 15) and 1972 (from 15 to 16) to provide exogenous variation in education. These reforms predominantly induced adolescents who would have left school to stay for one additionally mandated year. OLS estimates suggest that education significantly increases health knowledge, with a one-year increase in schooling increasing the health knowledge index by 15% of a standard deviation. In contrast, estimates from instrumental-variable models show that increased schooling due to the education reforms did not significantly affect health knowledge. This main result is robust to numerous specification tests and alternative formulations of the health knowledge index. Further research is required to determine whether there is also no causal link between higher levels of education - such as post-school qualifications - and health knowledge.

Does self-assessed health measure health?

Despite concerns about reporting biases and interpretation, self-assessed health (SAH) remains the measure of health most used by researchers, in part reflecting its ease of collection and in part the observed correlation between SAH and objective measures of health. Using a unique Australian data set, which consists of survey data linked to administrative individual medical records, we present empirical evidence demonstrating that SAH indeed predicts future health, as measured by hospitalizations, out-of-hospital medical services and prescription drugs. Our large sample size allows very disaggregate analysis and we find that SAH predicts more serious, chronic illnesses better than less serious illnesses. Finally, we compare the predictive power of SAH relative to administrative data and an extensive set of self-reported health measures; SAH does not add to the predictive power of future utilization when the administrative data is included and improves prediction only marginally when the extensive survey-based health measures are included. Clearly there is value in the more extensive survey and administrative health data as well as greater cost of collection.

Media and Human Capital Development: Can Video Game Playing Make You Smarter?

According to the literature, video game playing can improve such cognitive skills as problem solving, abstract reasoning, and spatial logic. I test this hypothesis using The Child Development Supplement to the Panel Study of Income Dynamics. The endogeneity of video game playing is addressed by using panel data methods and controlling for an extensive list of child and family characteristics. To address the measurement error in video game playing, I instrument childrens weekday time use with their weekend time use. After taking into account the endogeneity and measurement error, video game playing is found to positively affect childrens problem solving ability. The effect of video game playing on problem solving ability is comparable to the effect of educational activities.

Hips and Hearts: The Variation in Incentive Effects of Insurance across Hospital Procedures

The separate identification of effects due to incentives, selection and preference heterogeneity in insurance markets is the topic of much debate. In this paper, we investigate the presence and variation in moral hazard across health care procedures. The key motivating hypothesis is the expectation of larger causal effects in the case of more discretionary procedures. The empirical approach relies on an extremely rich and extensive dataset constructed by linking survey data to administrative data for hospital medical records. Using this approach we are able to provide credible evidence of large moral hazard effects but for elective surgeries only.

Victimisation, Wellbeing and Compensation: Using Panel Data to Estimate the Costs of Violent Crime

The costs of violent crime victimisation are often left to a judge, tribunal or jury to determine; leading to the potential for considerable subjectivity and variation. Using unique panel data, this paper provides compensation estimates that can help reduce the subjectivity of awards by giving a benchmark for the compensation required to offset direct and intangible costs. First, individual-area fixed-effects models allowing for adaptation to crime are estimated to assess the effects of violent crime victimisation on diverse measures of wellbeing. These results are then subsequently used to calculate the monetary compensation required to offset the wellbeing losses. Estimates allowing for the endogeneity of income suggest that A

Who provides inconsistent reports of their health status? The importance of age, cognitive ability and socioeconomic status

88,000 is required to compensate the average crime victim. We find some evidence that compensation estimates are larger if the wellbeing losses of female family members are considered, and are larger for females if the perpetrator of the crime is a stranger rather than a partner, friend or relative.

Justification bias in self-reported disability: new evidence from panel data

Self-assessed health (SAH) measures are widely used in models of health and health inequalities. Such models assume that SAH is a reliable measure of health status. We utilise a unique feature of a national longitudinal survey to examine the consistency of responses to a standard SAH question that is asked twice to the same individual in close temporal proximity in up to three waves (2001, 2009, and 2013). In particular, we analyse whether the consistency of responses varies with personal characteristics. The main analysis sample includes 18,834 individual-year observations. We find that 57% of respondents provide inconsistent reports at least once. Characteristics that are associated with significantly higher inconsistencies are age, education, cognitive ability, and time between responses. The results suggest that there are systematic differences in the ability of individuals to self-evaluate and summarise their own health. Consequently, failure to account for such error may lead to large estimation biases in models of health outcomes, particularly with respect to the relationship between education, cognitive ability, and health.

The Effects of Old and New Media on Children's Weight

The relationship between health and work is frequently investigated using self-assessments of disability from social surveys. The complication is that respondents may overstate their level of disability to justify non-employment and welfare receipt. This study provides new evidence on the existence and magnitude of justification bias by exploiting a novel feature of a large longitudinal survey: each wave respondents are asked identical disability questions twice; near the beginning and end of the face-to-face interview. Prior to answering the second disability question, respondents are asked a series of questions that increase the salience of their employment and welfare circumstances. Justification bias is identified by comparing the variation between the two measures within-individuals over time, with the variation in employment status over time. Results indicate substantial and statistically significant justification bias; especially for men and women who receive disability pensions.

Can Video Games Affect Children's Cognitive and Non-Cognitive Skills?

Childhood obesity rates have recently been rising in many countries. It has been suggested in the literature that changes in children’s media exposure may contribute to explaining this trend. I investigate whether or not this hypothesis is supported by data. I contribute to the literature by focusing not only on television but also on new media – computers and video games. The Child Development Supplement to the Panel Study of Income Dynamics is used for the analysis. To address the endogeneity of children’s media exposure, I use dynamic and panel data models. This is another improvement upon the existing literature. Additionally, an extensive list of control variables is included in the regressions. I find that video game playing or computer use has no effect on children’s body weight. On the other hand, television viewing may increase children’s body weight slightly.