The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
Modeling the demand for narrow money in the United Kingdom and the United States
Abstract
Despite the importance of well-specified empirical money-demand functions for inference, forecasting, and policy, problems in modeling have arisen concerning the economic theories of money demand, the data, institutional frameworks, financial innovation, and econometric implementation. By developing constant, data-coherent M1 demand equations for the UK and the US, we investigate these issues and explain such puzzles as "missing money", the great velocity decline, and the recent explosion in M1. The endogeneity of money, the Lucas critique, and the non-invertibility of our M1 models are also discussed.
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Cites
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Cited by
Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data
Banerjee, A., Dolado, J. J., Galbraith, J. W., & Hendry, D. (1993) · doi:10.1093/0198288107.001.0001 · Cited by 1,752
Self-citationTHE POWER OF COINTEGRATION TESTS
Kremers, J. J. M., Ericsson, N. R., & Dolado, J. J. (1992) · Oxford Bulletin of Economics and Statistics · doi:10.1111/j.1468-0084.1992.tb00005.x · Cited by 1,302
Self-citationBanerjee, A., Dolado, J. J., Galbraith, J. W., & Hendry, D. F. (1993) · Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data · doi:10.1093/0198288107.003.0004 · Cited by 872
Self-citationTesting for an unstable root in conditional and structural error correction models
Peter Boswijk, H. (1994) · Journal of Econometrics · doi:10.1016/0304-4076(93)01560-9 · Cited by 592
The Properties of Automatic Gets Modelling
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Metadata
- Authors
- Hendry, D. F., & Ericsson, N. R.
- Venue
- European Economic Review
- Publisher
- Elsevier BV
- Published
- 1991-05
- Volume
- 35
- Issue
- 4
- Pages
- 833-881
- ISSN
- 0014-2921 (ISSN-L)
- OpenAlex
- W2067351926
- Cited by
- 377
- References
- 59
- FWCI
- 63.24
- 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.