ECONOMETRIC ASSESSMENT OF MENTAL HEALTH INDICATORS

此首个奖项提案需要4年的资金，以便在计量经济学上 评估自我报告和基于临床的测量方法的可靠性 心理健康，因为它们通常被用于市场的经验模型 行为。“可靠性”一词包括广泛使用的两个方面 心理健康的衡量标准；与之相关的程度 实际健康状况以及它们包含系统报告的程度 偏见。该项目将开发收入计量模型， 服务的利用率和供应商的选择明确说明 心理健康指标的测量误差。 这项研究的长期目标有两个：第一，提供 对精神障碍对收入和收入的影响的一致估计 精神卫生保健服务的使用。这样的估计对于 对影响提供服务的政策进行适当评估 精神卫生保健部门。第二个主要目标是确定 心理健康变量的测量误差在多大程度上偏向 非健康变量对收入和使用模式的影响。这些 变量包括性别、种族、收入和教育程度。所扮演的角色 受这些因素的影响，政策制定者也对这些问题感兴趣 与医疗费用增长相关的，占增长来源的， 消费者信息在选择提供商、访问 对弱势群体的医疗照顾，以及种族和性别的程度 劳动力市场上的歧视。 这个项目的主要数据来源将来自第一波 由国家心理研究所进行的一项纵向调查 卫生组织在美国五个地点的流行病集水区计划。 20世纪80年代初。模拟(多指标多原因)模型 为分析提供基础网络。

This First Award proposal requests 4 years of funding to econometrically assess the reliability of both self-reported and clinically-based measures of mental health as they are typically used in empirical models of market behavior. The term 'reliability' encompasses two aspects of widely-used measures of mental health; the degree to which they are correlated with actual health and the extent to which they contain systematic reporting biases. The project will develop econometric models of earnings, utilization of services, and choice of provider which explicitly account for measurement error in mental health indicators. The long-term objectives of the research are twofold: first, to provide consistent estimates of the impact of mental disorders on earnings and on the use of mental health care services. Such estimates are essential for the proper evaluation of policies which affect the provision of services in the mental health care sector. The second major objective is to determine the extent to which measurement errors in mental health variables bias the effects of nonhealth variables on earnings and utilization patterns. These variables include, gender, race, income, and education. The roles played by these factors are also of interest to policymakers bearing on issues related to, accounting for the sources of growth in medical expenditures, the role of consumer information in the choice of provider, access to medical care for the disadvantaged, and the extent of race and gender discrimination in the labor market. The primary source of data for this project will come from the first wave of a longitudinal survey conducted by the National Institute of Mental Health's Epidemiological Catchment Area Program at five sites in the U.S. during the early 1980s. MIMIC (Multiple Indicator Multiple Cause) models provide the basic network for the analysis.