The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
The Savers–Spenders Theory of Fiscal Policy
Abstract
The macroeconomic analysis of fiscal policy is usually based on one of two canonical models--the Barro-Ramsey model of infinitely-lived families or the Diamond-Samuelson model of overlapping generations. This paper argues that neither model is satisfactory and suggests an alternative. In the proposed model, some consumers plan ahead for themselves and their descendants, while others live paycheck to paycheck. This model is easier to reconcile with the essential facts about consumer behavior and wealth accumulation, and it yields some new and surprising conclusions about fiscal policy.
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Cites
Availability: A heuristic for judging frequency and probability
Tversky, A., & Kahneman, D. (1973) · Cognitive Psychology · doi:10.1016/0010-0285(73)90033-9 · Cited by 9,984
Recent Trends in the Size Distribution of Household Wealth
Wolff, E. N. (1998) · Journal of Economic Perspectives · doi:10.1257/jep.12.3.131 · Cited by 430
Cited by
Understanding the Effects of Government Spending on Consumption
Galí, J., López-Salido, J. D., & Vallés, J. (2007) · Journal of the European Economic Association · doi:10.1162/jeea.2007.5.1.227 · Cited by 1,922
The Response of Household Consumption to Income Tax Refunds
Souleles, N. S. (1999) · American Economic Review · doi:10.1257/aer.89.4.947 · Cited by 698
Recent Trends in the Size Distribution of Household Wealth
Wolff, E. N. (1998) · Journal of Economic Perspectives · doi:10.1257/jep.12.3.131 · Cited by 430
Metadata
- Authors
- Mankiw, N. G.
- Venue
- American Economic Review
- Publisher
- American Economic Association
- Published
- 2000-05-01
- Volume
- 90
- Issue
- 2
- Pages
- 120-125
- ISSN
- 0002-8282 (ISSN-L)
- OpenAlex
- W3124658309
- Cited by
- 512
- References
- 2
- FWCI
- 18.67
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
