Arbeitspapier
Using extraneous information and GMM to estimate threshold parameters in TAR models
A prominent class of nonlinear time series models are threshold autoregressive models. Recently work by Kapetanios (2000) has shown in a Monte Carlo setting that the superconsistency property of the threshold parameter estimates does not translate to superior performance in small samples. Another issue concerning inference for the threshold parameters relates to estimation of their standard errors. As the asymptotic distribution of the threshold parameters is neither normal nor nuisance parameter free, an outstanding issue is how to obtain standard errors and confidence intervals for them. This paper aims to address these issues. In particular, we suggest that using extraneous information on the location of the threshold parameters may lead to better estimates. The extraneous information comes in the form of moment conditions that relate residuals of standard threshold models to shocks driving other variables. Additionally the paper considers the problem of estimating standard errors and confidence intervals for threshold parameter estimates. We suggest use of the bootstrap for this problem.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 494
- Klassifikation
-
Wirtschaft
Estimation: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- Thema
-
Threshold Models, GMM, Bootstrap
Zeitreihenanalyse
Momentenmethode
Nichtlineares Verfahren
Autokorrelation
Bootstrap-Verfahren
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Kapetanios, George
- Ereignis
-
Veröffentlichung
- (wer)
-
Queen Mary University of London, Department of Economics
- (wo)
-
London
- (wann)
-
2003
- Handle
- Letzte Aktualisierung
- 10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Kapetanios, George
- Queen Mary University of London, Department of Economics
Entstanden
- 2003
Ähnliche Objekte (12)
Testing for exogeneity in nonlinear threshold models
Factor-GMM estimation with large sets of possibly weak instruments
Estimating deterministically time-varying variances in regression models
A note on joint estimation of common cycles and common trends in nonstationary multivariate systems
A note on an iterative least squares estimation method for ARMA and VARMA models
Testing for strict stationarity
Variable selection using non-standard optimisation of information criteria
A bootstrap procedure for panel datasets with many cross-sectional units
Unit root testing against the alternative hypothesis of up to m structural breaks
Determining the stationarity properties of individual series in panel datasets
Nonlinear autoregressive models and long memory
A new method for determining the number of factors in factor models with large datasets
Testing for exogeneity in nonlinear threshold models
Factor-GMM estimation with large sets of possibly weak instruments
Estimating deterministically time-varying variances in regression models
A note on joint estimation of common cycles and common trends in nonstationary multivariate systems
A note on an iterative least squares estimation method for ARMA and VARMA models
Testing for strict stationarity
Variable selection using non-standard optimisation of information criteria
A bootstrap procedure for panel datasets with many cross-sectional units
Unit root testing against the alternative hypothesis of up to m structural breaks
Determining the stationarity properties of individual series in panel datasets
Nonlinear autoregressive models and long memory
A new method for determining the number of factors in factor models with large datasets
Testing for exogeneity in nonlinear threshold models
Factor-GMM estimation with large sets of possibly weak instruments
Estimating deterministically time-varying variances in regression models
A note on joint estimation of common cycles and common trends in nonstationary multivariate systems
A note on an iterative least squares estimation method for ARMA and VARMA models
Testing for strict stationarity
Variable selection using non-standard optimisation of information criteria
A bootstrap procedure for panel datasets with many cross-sectional units
Unit root testing against the alternative hypothesis of up to m structural breaks
Determining the stationarity properties of individual series in panel datasets
Nonlinear autoregressive models and long memory