ECONOMETRIC ASSESSMENT OF MENTAL HEALTH INDICATORS

第一个奖项的提案要求4年的资金，以计量经济学 评估自我报告和临床测量的可靠性 因为它们通常用于市场的经验模型， 行为 “可靠性”一词包括两个方面， 心理健康的衡量标准;它们与 实际健康状况及其包含系统报告的程度 偏见 该项目将开发收益的经济计量模型， 服务的利用，以及选择明确考虑 心理健康指标的测量误差。 研究的长期目标有两个：第一，提供 对精神障碍对收入和对健康的影响的一致估计 使用精神卫生保健服务。 这些估计数对于以下方面至关重要： 适当评估影响提供服务的政策， 精神卫生保健部门。 第二个主要目标是确定 心理健康变量中的测量误差在多大程度上使 非健康变量对收入和利用模式的影响。 这些 变量包括性别、种族、收入和教育。 发挥的作用 这些因素也是决策者感兴趣的问题 有关，占医疗费用增长的来源， 消费者信息在选择供应商、获得 弱势群体的医疗保健，以及种族和性别 劳动力市场的歧视。 这个项目的主要数据来源将来自第一波 美国国家心理研究所进行的一项纵向调查显示， 卫生部在美国五个地点的流行病学集水区计划。 在20世纪80年代早期。 MIMIC（多指标多原因）模型 为分析提供基本的网络。

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.