Dynamic Analysis of Health Insurance Demand

The study investigates the presence of moral hazard and advantageous or adverse selection in the Irish supplementary private health insurance market. It employs dynamic models to analyze health insurance decisions and healthcare utilization, acknowledging the complex interplay between these factors. The researchers highlight the importance of using dynamic models, noting that static analyses often lead to inaccurate conclusions. The study uses a dynamic panel data model to account for unobserved heterogeneity and state dependence. This is a key methodological departure from much of the existing literature, which primarily relies on cross-sectional analyses. The dynamic approach proves crucial for accurately capturing the evolving relationship between insurance decisions, health status, and healthcare consumption over time. This approach allows for a more nuanced understanding of the factors driving the demand for supplemental health insurance in Ireland and addresses endogeneity issues stemming from the interrelation of health status, insurance choices, and health care utilization.

The research draws on existing literature, citing studies that point toward advantageous selection in other contexts, particularly in the US elderly population. Finkelstein and McGarry (2006) found a negative correlation between long-term care coverage and nursing home use among older Americans, attributing this to wealth differences and precautionary behavior. Fang et al. (2008) found advantageous selection for US Medigap insurance, primarily linked to cognitive ability. These studies, however, mainly focus on specific segments of the US market and don't necessarily generalize to other countries or population groups. The Irish context is unique due to its national health insurance system with substantial copayments, making supplementary private insurance a significant factor. This establishes the need for a dedicated study on the Irish system, considering differences from other countries and the impact of copayments on consumer choices.

The study develops a simple static model to illustrate how adverse and advantageous selection can arise in health insurance markets. This model demonstrates that individual health status influences healthcare service demand and the decision to purchase supplementary private health insurance. The model also considers factors such as risk aversion, consumption preferences, and health investments. The model highlights that disentangling moral hazard from selection is empirically challenging. It emphasizes the complex interrelationship between an individual's health status, their decision to purchase insurance, and their subsequent healthcare utilization. The researchers stress the presence of endogeneity problems stemming from unobserved individual preferences and health risk which influence both insurance decisions and health investments.

The empirical findings reveal a significant lack of evidence for moral hazard. Contrary to expectations, those with private insurance did not exhibit higher healthcare utilization. However, the study finds robust evidence for advantageous selection. This is strongly linked to education levels: higher-educated individuals are more likely to be insured, have lower health risks, and utilize fewer healthcare services. Income also plays a substantial role. The researchers emphasize that these results are significantly different from those obtained from static models, which neglect dynamic effects and unobserved fixed effects. These findings challenge prevalent assumptions in health economics and emphasize the importance of utilizing appropriate dynamic models in future research on this subject. The study observes that those with higher levels of health care utilization are less likely to purchase supplementary private health insurance, reinforcing the evidence for advantageous selection.

The analysis decomposes fixed effects to better understand the factors driving insurance decisions and healthcare utilization. A significant negative correlation is observed between fixed effects in the supplementary private health insurance decision and GP visits. This supports the observed advantageous selection. Education emerges as a key determinant, with each additional year of education increasing the probability of insurance uptake. This effect is independent of income, health, and health behaviors. The paper emphasizes the independent effects of income and education on insurance decisions, highlighting that factors like cognitive ability and health preferences likely influence choices. The influence of education reinforces the findings of advantageous selection because it is correlated with better health and lower healthcare utilization.

The study's findings have substantial implications for policy decisions in the Irish healthcare system. The Irish system features a national health service with co-payments, and supplementary private health insurance plays a crucial role in supplementing this coverage. The paper notes the significant increase in private insurance uptake in Ireland over time, from approximately 4% in the 1960s to nearly 50% in 2002. The two major providers in the Irish market are VHI and BUPA Ireland, both subject to regulations that aim to prevent cream-skimming and mandate community-rated premiums. The research highlights the motivations of individuals choosing private insurance, including concerns about wait times in the public system and the fear of large medical bills. This analysis emphasizes the complex interplay of factors influencing health insurance choices, including risk aversion, preferences for healthcare, and the role of socio-economic status and education in the Irish context.

The study constructs a simple static model to demonstrate how adverse and advantageous selection can emerge in health insurance markets. The model's core focus is on the decision to obtain supplementary private health insurance, linking this decision to individual health status, health shocks, and past healthcare utilization. The model's utility function incorporates consumption and health, serving as a framework to understand the complex relationship between these factors and insurance choices. A critical aspect is that this model acknowledges the difficulty in empirically separating moral hazard from selection effects, recognizing the intricate interplay between individual health, insurance status, and healthcare consumption decisions. The model sets the stage for the empirical investigation by outlining the theoretical mechanisms that may lead to different types of selection in a health insurance market, emphasizing how observed choices reflect a complex interplay of health status, risk attitudes, and individual preferences.

The theoretical model explores the conditions under which adverse selection (high-risk individuals disproportionately purchasing insurance) and advantageous selection (low-risk individuals more likely to be insured) occur. The model illustrates how unobserved heterogeneity in risk aversion and health preferences can lead to both forms of selection. It highlights how the correlation between health conditions and individual preferences is crucial in determining the type of selection observed. For example, individuals with a strong preference for consumption over health might invest less in preventative care and have poorer health, leading to adverse selection if they are equally likely to purchase insurance as those with stronger health preferences. In contrast, advantageous selection is more likely if those with a strong preference for health (and therefore undertaking preventive behaviors) are more likely to purchase health insurance. The model demonstrates that the prevalence of either adverse or advantageous selection depends on the interplay of these unobserved characteristics within a population. It provides a foundation for the empirical analysis of the Irish supplementary private health insurance market.

The theoretical framework acknowledges the limitations of purely static models. The researchers emphasize that the insurance decision is an inherently dynamic process, with individuals considering the long-term consequences of their current behavior. Healthcare consumption depends on insurance status, which in turn is driven by expected healthcare costs. The model implicitly acknowledges the limitations of a strictly static approach by suggesting the need for a more dynamic model which explicitly incorporates the interplay between the temporal aspects of these relationships. They highlight the importance of considering wealth and the dynamic sequence of choices that individuals make to optimize their expected lifetime utility. While a simple static model is helpful for explaining the underlying mechanisms, it is argued that a more sophisticated dynamic model might be necessary to capture the real-world complexities of the Irish health insurance market. The researchers refer to existing work by Bolhaar (2008) which confirms the static models' results are consistent in a dynamic framework. This dynamic consideration sets the stage for the empirical application using panel data that spans eight years, enabling a richer understanding of the longitudinal aspects of insurance decisions and healthcare utilization.

The empirical analysis uses data from the Irish Longitudinal Study on Ageing (ILSA), a panel dataset spanning eight years. This longitudinal nature is crucial for the dynamic modeling approach. Key variables include health insurance status (supplementary private health insurance), Medical Card eligibility, household income, and various measures of health care utilization. Healthcare utilization is measured by the number of GP visits, specialist visits, and hospital nights in the past 12 months. Individual-level health status is also incorporated, considering factors such as mental health and chronic illnesses. The inclusion of lagged variables (previous year's insurance status, Medical Card status, income, and health status) is vital to the dynamic model specification. The dataset includes various household-level characteristics like household size, the birth of a baby, and whether an employer offers private health insurance subsidies. The study acknowledges attrition issues within the ILSA dataset, noting that the attrition rate was between 12% and 18% annually and predominantly affected young single adults.

The study employs several econometric techniques. Firstly, a static fixed-effects model is estimated to control for unobserved household and individual specific effects. However, this model is acknowledged as ignoring the dynamic structure of the insurance decision and healthcare utilization. To address this limitation, the researchers proceed to estimate dynamic panel data models using the Generalized Method of Moments (GMM) estimator developed by Arellano and Bond (1991). The GMM estimator allows for both unobserved effects (fixed effects) and state dependence in the data generating process. The choice to use both static and dynamic models allows for a comparison of results, highlighting the potential bias introduced by neglecting dynamic effects. The three healthcare utilization variables (GP visits, specialist visits, and hospital nights) are modeled using separate dynamic panel data models to account for differences in the demand elasticity for these services.

The results from the dynamic panel data models provide strong evidence of advantageous selection, but little evidence of moral hazard. Unlike findings from static models, the dynamic approach reveals that having private supplementary health insurance does not lead to significantly higher healthcare utilization. The researchers find that health variables, such as bad mental health and chronic conditions, are not significant in the dynamic panel data model estimates, a key difference from OLS results. This is interpreted as the introduction of a fixed effect absorbing the impact of permanent health conditions. In contrast to the initial findings, this indicates the lack of moral hazard effects once dynamic considerations and unobserved individual heterogeneity are accounted for. The study notes that this absence of moral hazard aligns with findings from other research, including Chiappori et al. (1998) in France and contrasts with findings by Stabile (2001) in Canada and Pohlmeier and Ulrich (1995) in Germany. These differences highlight the sensitivity of results to the choice of methodology. In all the estimations the three health care utilization variables are jointly significant and there is a clear separation between households that strongly prefer supplementary private health insurance versus households that do not.

The study's main finding is strong evidence for advantageous selection in the Irish supplementary private health insurance market. This contradicts many previous findings, largely due to the use of more appropriate dynamic models in this study compared to the mainly cross-sectional approaches of previous research. The researchers find that individuals with higher healthcare utilization are less likely to have supplementary private health insurance. This finding holds true even after controlling for various factors, including health status, income, and other demographic characteristics. The study notes that this result is consistent with the theoretical framework developed earlier in the paper. This contrasts with much of the existing literature, which often concludes differently due to the use of static models which neglect dynamic effects and unobserved fixed effects. The researchers emphasize that the use of dynamic models is crucial in accurately assessing the presence and magnitude of advantageous selection, and hence the importance of the methodological choices made in the study.

A key driver of advantageous selection is education. The analysis reveals a substantial and independent positive effect of education on the likelihood of purchasing supplementary private health insurance. Higher levels of education are associated with a significantly lower probability of needing substantial healthcare. For each additional year of education, the probability of having supplementary private health insurance increases by more than 0.06. This effect is independent of income, health status, and health behaviors, indicating a significant role of education beyond simply reflecting higher income or better health. The researchers hypothesize that education may influence health preferences, risk attitudes, time discount rates, and cognitive ability. Higher cognitive ability, as argued by Fang et al. (2008), might improve an individual's ability to evaluate the costs and benefits of insurance, leading to a more informed decision to purchase coverage. The strong and independent relationship between education and the likelihood of purchasing supplemental health insurance is a novel finding compared to the existing literature.

While education is a significant factor, income and health behaviors also influence the decision to purchase supplementary private health insurance. Higher income is associated with better health and a higher probability of insurance uptake. A similar pattern is observed for health behaviors: non-smokers are more likely to have insurance and exhibit better health outcomes. Individuals in poor health are significantly less likely to have supplementary private health insurance, particularly those with mental health issues. The study highlights that these health conditions are strongly linked to higher healthcare utilization. This further strengthens the evidence for advantageous selection, suggesting that individuals who anticipate higher health care costs are less likely to purchase supplemental insurance. This aligns with the concept of advantageous selection as healthier and wealthier individuals, less likely to require extensive healthcare services, are more inclined to obtain supplemental health insurance.

Ireland's healthcare system includes a national insurance program, but it's characterized by substantial copayments. This means individuals bear a portion of healthcare costs. Supplementary private health insurance serves to offset these copayments and potentially improve access to and quality of care. The existence of copayments creates a financial incentive for individuals to consider supplementary private insurance, especially those concerned about high out-of-pocket expenses. The study highlights the key difference in the coverage provided by private insurance compared to the Medical Card, which mainly addresses co-payments rather than offering additional treatment or shorter wait times. The study also highlights the key role of the Medical Card in the Irish system, providing free or heavily subsidized care to those below a certain income threshold. Around 30% of the Irish population benefited from Medical Card coverage in 2005, highlighting its impact on access to care for low-income households. The system's structure is crucial to understanding the demand for supplementary private health insurance.

Supplementary private health insurance in Ireland helps cover copayments and offers advantages like reduced waiting times, more choice in medical specialists, and increased privacy (e.g., private hospital rooms). The cost of this supplemental insurance was around €50 per month in 2006 for an adult. This relatively moderate cost, combined with the potential benefits, explains the growing demand observed in the study. The supplementary private insurance market in Ireland is dominated by VHI, a formerly state-supported, non-profit organization. The entrance of BUPA Ireland in 1997, following EU regulations, introduced competition but VHI remains the market leader. Both providers are required to accept all applicants regardless of health status or other factors, and premiums are based on community rating. This regulatory environment limits the insurers' ability to select only low-risk clients. However, some employers offer to subsidize the premiums for their employees, which influences insurance take-up.

Public attitudes towards supplementary private health insurance are explored, citing data from the Economic and Social Research Institute's (ESRI) 1999 consumer survey. The primary drivers for purchasing private insurance are the fear of high medical or hospital bills (88.5% of respondents rated this as 'very important') and the desire to avoid lengthy waiting lists in the public system (86.4% considered this 'very important'). Other significant motivations included the desire for good treatment, consultant care, and flexible scheduling of hospital treatment. The less important reasons were having a private room or access to a private hospital. This highlights the practical needs motivating insurance purchasing decisions, rather than purely luxury concerns. The survey indicates that avoidance of waiting lists is the most important factor driving the decision to purchase supplementary private health insurance, regardless of insurance status. The study notes that even Medical Card holders, whose copayments are reduced, may purchase supplementary insurance to mitigate waiting times.

The core dataset for this study is the Irish Longitudinal Study on Ageing (ILSA), a longitudinal study initiated in 1994. The study utilizes data from the first wave in 1994, and also data from the subsequent waves of the study through 2000. The initial sample comprised 4048 households, representing 57% of the originally targeted sample size. The researchers acknowledge a substantial annual attrition rate ranging from 12% to 18%, primarily due to factors such as household relocation, refusal to participate, and difficulty contacting participants. Despite the attrition, approximately 95% of the responding households were successfully interviewed. By 2000, 48% of the original 1994 participants were still involved, leading to the inclusion of 1554 new households to augment the sample. This addition of new households helps to mitigate some of the potential biases introduced by the attrition rate and subsequent sampling.

To gain further insights into the potential biases resulting from attrition, the researchers cross-referenced the data from households still participating in 2000 with Irish census data. This comparison revealed that certain demographic groups, particularly young single adults aged 20-40, were underrepresented in the ILSA sample compared to the general population, while individuals aged 50-60 were overrepresented. Additionally, the ILSA sample showed a lower proportion of individuals in full-time education and fewer residents in major urban centers, as well as a slightly larger average household size. This supports the finding by Nolan et al (2002) that the attrition primarily affected younger single adults. Due to a lack of income data in the census, a further analysis comparing income distributions from the 1994 sample (still participating in 2000) with the newly added 2000 sample revealed that the original sample participants had somewhat lower average earnings.

The study uses a wide array of variables. Key variables include household income, education levels, age, gender, employment status, and the possession of a Medical Card. The study also includes individual-level variables concerning health care utilization. These detailed individual-level measures of healthcare utilization include the number of visits to a General Practitioner (GP), the number of visits to medical specialists, and the number of nights spent in hospital during the previous 12 months. Additionally, the individual’s health status (mental health, chronic illness) is considered, along with information on whether they received health insurance subsidies from their employer. Around 36% of households in the dataset held a Medical Card, with 8% of Medical Card holders also having supplementary private health insurance. Among households without a Medical Card, the private health insurance uptake was considerably higher—more than 67%. The uptake is higher for women, older individuals, higher educated individuals, and individuals residing in larger urban areas. This thorough analysis of variables and descriptive statistics provides a foundation for the econometric analyses that follow.