The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
The econometric analysis of models with risk terms
Abstract
In this paper we have attempted to provide an integrated approach to the estimation of models with risk terms. It was argued that there exist orthogonality conditions between variables in the information set and higher‐order moments of the unanticipated variable density. These could be exploited to provide consistent estimators of the parameters associated with the risk term. Specifically, it was recommended that an IV estimator should be applied, with instruments constructed from the information set. Four existing methods commonly used to estimate models with risk terms are examined, and applications of the techniques are made to the estimation of the risk term in the $US/$C exchange market, and the effects of price uncertainty upon production.
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Cites
Co-integration and error correction: representation, estimation and testing
Engle, R. F., & Granger, C. W. J. (1987) · Econometrica · doi:10.2307/1913236 · Cited by 32,007
A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity
White, H. (1980) · Econometrica · doi:10.2307/1912934 · Cited by 25,861
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Large Sample Properties of Generalized Method of Moments Estimators
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A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix
Newey, W., & West, K. (1986) · National Bureau of Economic Research · doi:10.3386/t0055 · Cited by 12,278
Expected stock returns and volatility
French, K. R., Schwert, G. W., & Stambaugh, R. F. (1987) · Journal of Financial Economics · doi:10.1016/0304-405x(87)90026-2 · Cited by 4,107
Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?
Shiller, R. (1980) · National Bureau of Economic Research · doi:10.3386/w0456 · Cited by 3,986
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Cited by
Why Does Stock Market Volatility Change Over Time?
SCHWERT, G. W. (1989) · The Journal of Finance · doi:10.1111/j.1540-6261.1989.tb02647.x · Cited by 3,427
Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts
Andersen, T. G., & Bollerslev, T. (1998) · International Economic Review · doi:10.2307/2527343 · Cited by 3,375
Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances
Bollerslev, T., & Wooldridge, J. M. (1992) · Econometric Reviews · doi:10.1080/07474939208800229 · Cited by 3,217
Stock Volatility and the Crash of ’87
Schwert, G. W. (1990) · Review of Financial Studies · doi:10.1093/rfs/3.1.77 · Cited by 1,044
The econometrics of financial markets
Pagan, A. (1996) · Journal of Empirical Finance · doi:10.1016/0927-5398(95)00020-8 · Cited by 873
Self-citation
Metadata
- Authors
- Pagan, A., & Ullah, A.
- Venue
- Journal of Applied Econometrics
- Publisher
- Wiley
- Published
- 1988-04
- Volume
- 3
- Issue
- 2
- Pages
- 87-105
- ISSN
- 0883-7252 (ISSN-L)
- 1099-1255
- OpenAlex
- W2107775083
- Cited by
- 342
- References
- 36
- FWCI
- 40.05
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.