منابع مشابه
Uniform Inference in Panel Autoregression∗
This paper considers estimation and inference concerning the autoregressive coefficient (ρ) in a panel autoregression for which the degree of persistence in the time dimension is unknown. The main objective is to construct confidence intervals for ρ that are asymptotically valid, having asymptotic coverage probability at least that of the nominal level uniformly over the parameter space. It is ...
متن کاملInference in Autoregression under Heteroskedasticity∗
A scalar p-th order autoregression (AR(p)) is considered with heteroskedasticity of unknown form delivered by a smooth transition function of time. A limit theory is developed and three heteroskedasticity-robust tests statistics are proposed for inference, one of which is based on the nonparametric estimation of the variance function. The performance of the resulting testing procedures in finit...
متن کاملUnit Root Quantile Autoregression Inference
We study statistical inference in quantile autoregression models when the largest autoregressive coefficient may be unity. The limiting distribution of a quantile autoregression estimator and its t-statistic is derived. The asymptotic distribution is not the conventional Dickey-Fuller distribution, but a linear combination of the Dickey-Fuller distribution and the standard normal, with the weig...
متن کاملRegression-type Inference in Nonparametric Autoregression
1 1 1. Introduction Autoregressive models form an important class of processes in time series analysis. A nonparametric version of these models was introduced by Jones (1978). To allow for heteroscedastic modelling of the innovations, people often consider the model where the " t are assumed to be i.i.d. with mean 0 and variance 1. Several authors dealt with the interesting statistical problem ...
متن کاملIndirect inference for spatio-temporal autoregression models
In this note we introduce a new inferential method for STAR (spatio-temporal autoregression) models. Due to the complexity of such models the maximum likelihood estimation is difficult to undertake when several nearest neighbours are included in the model, see Ali (1979). Moreover, only approximate likelihoods are available in practice because of the observations lying on the edges of the spati...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2017
ISSN: 1556-5068
DOI: 10.2139/ssrn.2901048