The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Taking Stock: Monetary Policy Transmission to Equity Markets
Open accessAbstract
This paper analyses the effects of US monetary policy on stock markets.We find that, on average, a tightening of 50 basis points reduces returns by about 3%.Moreover, returns react more strongly when no change had been expected, when there is a directional change in the monetary policy stance and during periods of high market uncertainty.We show that individual stocks react in a highly heterogeneous fashion and relate this heterogeneity to financial constraints and Tobin's q.First, we show that there are strong industry-specific effects of US monetary policy.Second, we find that for the individual stocks comprising the S&P500 those with low cashflows, small size, poor credit ratings, low debt to capital ratios, high price-earnings ratios or high Tobin's q are affected significantly more.The use of propensity score matching allows us to distinguish between firmand industry-specific effects, and confirms that both play an important role.
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Cites
The central role of the propensity score in observational studies for causal effects
ROSENBAUM, P. R., & RUBIN, D. B. (1983) · Biometrika · doi:10.1093/biomet/70.1.41 · Cited by 31,241
Do Investment-Cash Flow Sensitivities Provide Useful Measures of Financing Constraints?
Kaplan, S. N., & Zingales, L. (1997) · The Quarterly Journal of Economics · doi:10.1162/003355397555163 · Cited by 6,770
A General Equilibrium Approach To Monetary Theory
Tobin, J. (1969) · Journal of Money, Credit and Banking · doi:10.2307/1991374 · Cited by 5,294
Propensity Score-Matching Methods for Nonexperimental Causal Studies
Dehejia, R. H., & Wahba, S. (2002) · Review of Economics and Statistics · doi:10.1162/003465302317331982 · Cited by 4,846
Agency Costs, Net Worth, And Business Fluctuations
Bernanke, B., Gertler, M., Bernanke, B., & Gertler, M. (1988) · Unknown · doi:10.22004/ag.econ.292693 · Cited by 4,386
Inside the black box: the credit channel of monetary policy transmission
Bernanke, B. S., & Gertler, M. (1995) · Journal of Economic Perspectives · doi:10.1257/jep.9.4.27 · Cited by 4,211
Matching As An Econometric Evaluation Estimator
Heckman, J. J., Ichimura, H., & Todd, P. (1998) · Review of Economic Studies · doi:10.1111/1467-937x.00044 · Cited by 3,807
Size and Book‐to‐Market Factors in Earnings and Returns
FAMA, E. F., & FRENCH, K. R. (1995) · The Journal of Finance · doi:10.1111/j.1540-6261.1995.tb05169.x · Cited by 3,430
The Central Role of the Propensity Score in Observational Studies for Causal Effects
Rosenbaum, P. R., & Rubin, D. B. (1983) · Biometrika · doi:10.2307/2335942 · Cited by 3,261
The federal funds rate and the channels of monetary transmissionPreprint
Bernanke, B., & Blinder, A. S. (1989) · RePEc: Research Papers in Economics · Cited by 2,833
Cited by
Identifying the interdependence between US monetary policy and the stock market
Bjørnland, H. C., & Leitemo, K. (2009) · Journal of Monetary Economics · doi:10.1016/j.jmoneco.2008.12.001 · Cited by 440
Are Sticky Prices Costly? Evidence from the Stock Market
Gorodnichenko, Y., & Weber, M. (2016) · American Economic Review · doi:10.1257/aer.20131513 · Cited by 369
Stocks, bonds, money markets and exchange rates: measuring international financial transmission
Ehrmann, M., Fratzscher, M., & Rigobon, R. (2011) · Journal of Applied Econometrics · doi:10.1002/jae.1173 · Cited by 369
Self-citationHanousek, J., Kočenda, E., & Kutan, A. M. (2009) · Journal of Financial Stability · doi:10.1016/j.jfs.2008.01.003 · Cited by 133
Metadata
- Authors
- Ehrmann, M., & Fratzscher, M.
- Venue
- Journal of Money, Credit, and Banking
- Publisher
- Project MUSE
- Published
- 2004
- Volume
- 36
- Issue
- 4
- Pages
- 719-737
- ISSN
- 0022-2879 (ISSN-L)
- 1538-4616
- OpenAlex
- W2096527115
- Cited by
- 465
- References
- 47
- FWCI
- 17.41
- Type
- journal article
- Language
- en
- Open access
- bronze
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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.