Harnessingnaturally occurring data to measure the response of spending to income

Michael Gelman, Shachar Kariv, Matthew D. Shapiro, Daniel Silverman, Steven Tadelis

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

This paper presents a new data infrastructure for measuring economic activity. The infrastructure records transactions and account balances, yielding measurements with scope and accuracy that have little precedent in economics. The data are drawn from a diverse population that overrepresents males and younger adults but contains large numbers of underrepresented groups. The data infrastructure permits evaluation of a benchmark theory in economics that predicts that individuals should use a combination of cash management, saving, and borrowing to make the timing of income irrelevant for the timing of spending. As in previous studies and in contrast to the predictions of the theory, there is a response of spending to the arrival of anticipated income. The data also show, however, that this apparent excess sensitivity of spending results largely from the coincident timing of regular income and regular spending. The remaining excess sensitivity is concentrated among individuals with less liquidity.

Original languageEnglish (US)
Pages (from-to)212-215
Number of pages4
JournalScience
Volume345
Issue number6193
DOIs
StatePublished - 2014

ASJC Scopus subject areas

  • General

Fingerprint Dive into the research topics of 'Harnessingnaturally occurring data to measure the response of spending to income'. Together they form a unique fingerprint.

Cite this