Introducing the approach by Masanao Aoki (1981) to time series econometrics, we show that the dynamics of symmetric linear possibly cointegrated two-country VAR models can be separated into two autonomous subsystems: the country averages and country differences, where the latter includes the...

Traditional vector autoregressions derive impulse responses using iterative techniques that may compound specification errors. Local projection techniques are robust to this problem, and Monte Carlo evidence suggests they provide reliable estimates of the true impulse responses. We use local...

This paper analyses Czech and Hungarian index options that are traded on the Austrian Futures and Options Exchange. We find that the Poisson jump-diffusion and not the GARCH (1,1) process lends statistical support for the data description. We estimate that approximately four-fifth of 4 percent...

Factor models can cope with many variables without running into scarce degrees of freedom problems often faced in a regression-based analysis. In this article we review recent work on dynamic factor models that have become popular in macroeconomic policy analysis and forecasting. By means of an...

The wavelet transform is used to identify a biannual and an annual seasonality in the Phelix Day Peak and to separate the long-term trend from its short-term motion. The short-term/long-term model for commodity prices of Schwartz & Smith (2000) is applied but generalised to account for weekly...

This paper investigates the relationship between human capital and economic growth in Pakistan with time series data. Estimated with the Johansen (1991) approach, the aggregate production function rejects one version of the endogenous growth formulation. But the fitted model indicates that the...

The linear Gaussian state space model for which the common variance istreated as a stochastic time-varying variable is considered for themodelling of economic time series. The focus of this paper is on thesimultaneous estimation of parameters related to the stochasticprocesses of the mean part...

We examine the asymptotic efficiency of OLS and IV estimators in a simple dynamic structural model with a constant and two explanatory variables: the lagged dependent variable and an explanatory variable, which is also autoregressive and may include lagged or instantaneous feedbacks from the...

In this paper we replace the Gaussian errors in the standard Gaussian, linear state space model with stochastic volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are ineffective, but that this problem can be removed by...

We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...