Pfeffer Fabian T, Griffin Jamie
University of Michigan.
Methoden Daten Anal. 2017;11(1):87-108. doi: 10.12758/mda.2016.015.
Measuring fluctuation in families' economic conditions is the of household panel studies. Accordingly, a particularly challenging critique is that fluctuation in measured economic characteristics might indicate compounding measurement error rather than actual changes in families' economic wellbeing. In this article, we address this claim by moving beyond the assumption that particularly large fluctuation in economic conditions might be too large to be realistic. Instead, we examine predictors of large fluctuation, capturing sources related to actual socio-economic changes as well as potential sources of measurement error. Using the Panel Study of Income Dynamics, we study between-wave changes in a dimension of economic wellbeing that is especially hard to measure, namely, net worth as an indicator of total family wealth. Our results demonstrate that even very large between-wave changes in net worth can be attributed to actual socio-economic and demographic processes. We do, however, also identify a potential source of measurement error that contributes to large wealth fluctuation, namely, the treatment of incomplete information, presenting a pervasive challenge for any longitudinal survey that includes questions on economic assets. Our results point to ways for improving wealth variables both in the data collection process (e.g., by measuring active savings) and in data processing (e.g., by improving imputation algorithms).
衡量家庭经济状况的波动是家庭面板研究的重点。因此，一个特别具有挑战性的批评观点认为，所测量的经济特征中的波动可能表明存在复合测量误差，而非家庭经济福祉的实际变化。在本文中，我们通过超越经济状况的特别大的波动可能大到不现实这一假设来回应这一观点。相反，我们研究大幅波动的预测因素，找出与实际社会经济变化相关的来源以及潜在的测量误差来源。利用收入动态面板研究，我们研究了经济福祉一个特别难以衡量的维度，即作为家庭总财富指标的净值的波间变化。我们的结果表明，即使净值的波间变化非常大，也可归因于实际的社会经济和人口过程。然而，我们也确实发现了一个导致财富大幅波动的潜在测量误差来源，即对不完整信息的处理，这对任何包含经济资产问题的纵向调查来说都是一个普遍存在的挑战。我们的结果指出了在数据收集过程中（例如，通过测量主动储蓄）和数据处理过程中（例如，通过改进插补算法）改善财富变量的方法。
