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Benkwitz, Alexander; Lütkepohl, Helmut; Neumann, Michael H. - 1997

Bootstrap confidence intervals for impulse responses computed from autoregressive processes are considered. A detailed analysis of the methods in current use shows that they are not very reliable in some cases. In particular, there are theoretical reasons for them to have actual coverage...

Persistent link: https://www.econbiz.de/10009660382

Bootstrap approximations in a partially linear regression model

Härdle, Wolfgang; Liang, Hua; Sommerfeld, Volker - 1997

Persistent link: https://www.econbiz.de/10009661015

Dynamic nonparametric state price density estimation using constrained least squares and the bootstrap

Härdle, Wolfgang; Yatchew, Adonis John - 2001

The economic theory of option pricing imposes constraints on the structure of call functions and state price densities (SPDs). Except in a few polar cases, it does not prescribe functional forms. This paper proposes a nonparametric estimator of option pricing models which incorporates various...

Persistent link: https://www.econbiz.de/10009620779

Empirical likelihood-based inference in linear errors-in-covariables models with validation data

Wang, Qihua; Rao, J. N. K. - 2001

. -- Bootstrap empirical likelihood ; Confidence region ; Measurement error ; Surrogate variables …

Persistent link: https://www.econbiz.de/10009615434

Comparison of bootstrap confidence intervals for impulse responses of German monetary systems

Benkwitz, Alexander; Lütkepohl, Helmut; Wolters, Jürgen - 1999

It is argued that standard impulse response analysis based on vector autoregressive models has a number of shortcomings. Although the impulse responses are estimated quantities, measures for sampling variability such as confidence intervals are often not provided. If confidence intervals are...

Persistent link: https://www.econbiz.de/10009580485

Semiparametric bootstrap approach to hypothesis tests and confidence intervals for the hurst coefficient

Hall, Peter; Härdle, Wolfgang; Kleinow, Torsten; … - 1999

A major application of rescaled adjusted range analysis (RS analysis) is the study of price fluctuations in financial markets. There, the value of the Hurst constant, H, in a time series may be interpreted as an indicator of the irregularity of the price of a commodity, currency or similar...

Persistent link: https://www.econbiz.de/10009581110

Bootstrapping impulse responses in VAR analyses

Lütkepohl, Helmut - 2000

Because the parameters of vector autoregressive processes are often difficult to interpret directly, econometricians use quantities derived from the parameters to disentangle the relationships between the variables. Bootstrap methods are often used for inference on the derived quantities....

Persistent link: https://www.econbiz.de/10009583428

Asymptotic properties of robust three-stage procedure based on bootstrap for m-estimator

Hlávka, Zdeněk - 2000

The paper concerns the fixed-width confidence intervals for location based on M- estimators in the location model. A robust three-stage procedure is proposed and its asymptotic properties are studied. The performance of the procedure depends on some tuning parameters. Their effect on the...

Persistent link: https://www.econbiz.de/10009612029

Construction of automatic confidence intervals in nonparametric heteroscedastic regression by a moment-oriented bootstrap

Sommerfeld, Volker - 1997

We construct pointwise confidence intervals for regression functions. The method uses nonparametric kernel estimates and the "moment-oriented" bootstrap method of Bunke which is a wild bootstrap based on smoothed local estimators of higher order error moments. We show that our bootstrap...

Persistent link: https://www.econbiz.de/10009632602

Measurement error, biases, and the validation of complex models

Carroll, Raymond J.; Galindo, Christian D. - 1997

There are three major points to this article: 1. Measurement error causes biases in regression fits. The line one would … exposure with error. 2. The effects of measurement error vary from study-to-study. It is dangerous to take measurement error … corrections derived from one study and apply them to data from entirely different studies or populations. 3. Measurement error can …

Persistent link: https://www.econbiz.de/10009631751

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