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Household surveys, one of the main innovations in social science research of the last century, are threatened by declining accuracy due to reduced cooperation of respondents. While many indicators of survey quality have steadily declined in recent decades, the literature has largely emphasized rising nonresponse rates rather than other potentially more important dimensions to the problem. We divide the problem into rising rates of nonresponse, imputation, and measurement error, documenting the rise in each of these threats to survey quality over the past three decades. A fundamental problem in assessing biases due to these problems in surveys is the lack of a benchmark or measure of truth, leading us to focus on the accuracy of the reporting of government transfers. We provide evidence from aggregate measures of transfer reporting as well as linked microdata. We discuss the relative importance of misreporting of program receipt and conditional amounts of benefits received, as well as some of the conjectured reasons for declining cooperation and survey errors. We end by discussing ways to reduce the impact of the problem including the increased use of administrative data and the possibilities for combining administrative and survey data.

We evaluate consumption and income measures of the material well-being of the poor. We begin with conceptual and pragmatic reasons that favor income or consumption. Then, we empirically examine the quality of standard data by studying measurement error and under-reporting, and by comparing micro-data from standard surveys to administrative micro-data and aggregates. We also compare low reports of income and consumption to other measures of hardship and well-being. The closer link between consumption and well-being and its better measurement favors the use of consumption when setting benefits and evaluating transfer programs. However, income retains its convenience for determining program eligibility.

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