References
[1] Atkinson, A. C., Koopman, S. J., and Shephard, N. (1997). Detecting
shocks: outliers and breaks in time series. Journal of Econometrics 80,
387-422.
[2] Balke, N. S., and Fomby, T. B. (1994). Large shocks, small shocks, and
economic fluctuations: outliers in macroeconomic time series. Journal
of Applied Econometrics 9, 181-200.
[3] Berrendero, J. R, and Zamar, R. H. (2001). Maximum bias curves for
robust regression with non-elliptical regressors. The Annals of Statistics
29(1), 224-251.
[4] Bianco, A., Ben, M. G., Martnez, E., and Yohai, V. J. (2001). Regression
models with ARIMA errors. Journal of Forecasting 20, 565-579.
[5] Bilodeau , M., and Duchesne, P. (2000). Robust estimation of the SUR
model. Canadian Journal of Statistics 28, 277-288.
[6] Chen, C., and Liu, L.-M. (1993). Joint estimation of model parameters
and outlier effects in time series. Journal of the American Statistical
Association 88, 284-297.
[7] Chernozhukov, V., and Hansen, C. (2006). Instrumental quantile re-
gression inference for structural and treatment effect models. Journal of
Econometrics, in press.
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