Improved Wealth Measures in the Health and Retirement Study

Asset Reconciliation and Cross-Wave Imputation

by Michael D. Hurd, Erik Meijer, Michael Moldoff, Susann Rohwedder

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In this report, we present improved wealth measures for the Health and Retirement Study (HRS), which aim to reduce the effect of observation error on wealth levels and changes in wealth. The new wealth measures take account of the asset verification section in the HRS and use cross-wave information, most notably the value of the same asset in adjacent waves, in the imputation models, so imputed values better preserve serial correlation in the asset values. We document how we dealt with several methodological challenges in the implementation of these improvements. The corrections from the asset verification data reduce the standard deviations of wave-to-wave changes by substantial amounts (up to 57 percent for total wealth). The most important effect of the cross-wave imputations is a considerable reduction of the number of spikes and trenches (large changes in value followed by large changes back).

Table of Contents

  • Chapter One

    Introduction and overview of the HRS asset elicitation

  • Chapter Two

    Overview of section U

  • Chapter Three

    Issues with implementing section U corrections

  • Chapter Four

    Section U corrections of the previous wave

  • Chapter Five

    Descriptive statistics of section U correction results

  • Chapter Six

    Cross-wave imputation methodology

  • Chapter Seven

    Descriptive statistics of cross-wave imputations

  • Chapter Eight

    The experiment with confirmation checks in sections H and Q in 2012

  • Chapter Nine

    Conclusions and discussion

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