Shifrah Aron-Dine
Stanford University
366 Galvez St.
Stanford, CA
E-Mail: 
Institutional Affiliation: Stanford University
NBER Working Papers and Publications
| September 2019 | From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending
with Aditya Aladangady, Wendy Dunn, Laura Feiveson, Paul Lengermann, Claudia Sahm: w26253
Access to timely information on consumer spending is important to economic policymakers. The Census Bureau’s monthly retail trade survey is a primary source for monitoring consumer spending nationally, but it is not well suited to study localized or short-lived economic shocks. Moreover, lags in the publication of the Census estimates and subsequent, sometimes large, revisions diminish its usefulness for real-time analysis. Expanding the Census survey to include higher frequencies and subnational detail would be costly and would add substantially to respondent burden. We take an alternative approach to fill these information gaps. Using anonymized transactions data from a large electronic payments technology company, we create daily estimates of retail spending at detailed geographies. Our... |
| July 2019 | From Transactions Data to Economic Statistics: Constructing Real-Time, High-Frequency, Geographic Measures of Consumer Spending
with Aditya Aladangady, Wendy Dunn, Laura Feiveson, Paul Lengermann, Claudia Sahm
in Big Data for 21st Century Economic Statistics, Katharine G. Abraham, Ron S. Jarmin, Brian Moyer, and Matthew D. Shapiro
Access to timely information on consumer spending is important to economic policymakers. The Census Bureau’s monthly retail trade survey is a primary source for monitoring consumer spending nationally, but it is not well suited to study localized or short-lived economic shocks. Moreover, lags in the publication of the Census estimates and subsequent, sometimes large, revisions diminish its usefulness for real-time analysis. Expanding the Census survey to include higher frequencies and subnational detail would be costly and would add substantially to respondent burden. We take an alternative approach to fill these information gaps. Using anonymized transactions data from a large electronic payments technology company, we create daily estimates of retail spending at detailed geographies. Our... |
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