Basic structure of the asymptotic theory in dynamic nonlinear econometric models
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Publication:3989294
DOI10.1080/07474939108800209zbMath0761.62170OpenAlexW1968745116MaRDI QIDQ3989294
Benedikt M. Pötscher, Ingmar R. Prucha
Publication date: 28 June 1992
Published in: Econometric Reviews (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/07474939108800209
surveyasymptotic normalitycentral limit theoremsTaylor series expansionscore vectormixing processesnonlinear economic modelsdynamic nonlinear econometric modelsleast mean distance estimatorsasymptotic distributions of \(M\)-estimatorsvariance covariance matrix estimators
Applications of statistics to economics (62P20) Asymptotic distribution theory in statistics (62E20)
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Aggregated heterogeneous dependent data and the logit model: ⋮ WEAK DEPENDENCE: MODELS AND APPLICATIONS TO ECONOMETRICS ⋮ Distribution of test statistics under parameter uncertainty for time series data: an application to testing skewness, kurtosis and normality ⋮ Nonparametric panel stationarity testing with an application to crude oil production ⋮ Nonparametric pseudo-Lagrange multiplier stationarity testing ⋮ Stationarity and mixing properties of the dynamic Tobit model ⋮ PARAMETER ESTIMATION IN NONLINEAR AR–GARCH MODELS ⋮ Kernel autocorrelogram for time-deformed processes ⋮ Generic uniform convergence and equicontinuity concepts for random functions. An exploration of the basic structure
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