This paper considers observation driven models with conditional mean and variance dynamics for non-negative valued time series. The motivation is to relax the restriction imposed on the higher order moment dynamics in standard multiplicative error models driven only by the conditional mean...

This paper considers observation driven models with conditional mean and variance dynamics for non-negative valued time series. The motivation is to relax the restriction imposed on the higher order moment dynamics in standard multiplicative error models driven only by the conditional mean...

Purpose: This study aims to examine the relation between population composition and financial market variables in post-war Japan. Design/methodology/approach: Cointegration and Granger causality tests are applied to annual data for the period 1948-2015. Findings: Accounting for nonstationarity,...

We propose an EM algorithm to estimate ordered probit models with endogenous regressors. The proposed algorithm has a number of computational advantages in comparison to direct numerical maximization of the (limited information) log-likelihood function. First, the sequence of conditional...