Sample covariances of random-coefficient AR(1) panel model

10/26/2018
by   Remigijus Leipus, et al.
0

The present paper obtains a complete description of the limit distributions of sample covariances in N × n panel data when N and n jointly increase, possibly at different rate. The panel is formed by N independent samples of length n from random-coefficient AR(1) process with the tail distribution function of the random coefficient regularly varying at the unit root with exponent β >0. We show that for β∈ (0, 2) the sample covariances may display a variety of stable and non-stable limit behaviors with stability parameter depending on β and the mutual increase rate of N and n .

READ FULL TEXT

page 1

page 2

page 3

page 4

research
01/16/2019

Joint temporal and contemporaneous aggregation of random-coefficient AR(1) processes with infinite variance

We discuss joint temporal and contemporaneous aggregation of N independe...
research
10/26/2017

Testing for long memory in panel random-coefficient AR(1) data

It is well-known that random-coefficient AR(1) process can have long mem...
research
02/28/2018

Limit theory for an AR(1) model with intercept and a possible infinite variance

In this paper, we derive the limit distribution of the least squares est...
research
02/18/2021

Explicit Bivariate Rate Functions for Large Deviations in AR(1) and MA(1) Processes with Gaussian Innovations

We investigate large deviations properties for centered stationary AR(1)...
research
02/14/2023

A rate of convergence when generating stable invariant Hermitian random matrix ensembles

Recently, we have classified Hermitian random matrix ensembles that are ...
research
12/27/2018

Asymptotic Distribution of Centralized r When Sampling from Cauchy

Assume that X and Y are independent random variables, each having a Cauc...
research
08/12/2021

A coefficient related to splay-to-root traversal, correct to thousands of decimal places

This paper takes another look at the cost of traversing a binary tree us...

Please sign up or login with your details

Forgot password? Click here to reset