This paper uses stochastic simulations on calibrated models to assess the steady state impact of different pension arrangements in an environment where financial markets are less than perfect. Surprisingly little is known about the optimal split between funded and unfunded systems when there are...

A Monte Carlo study is undertaken to analyze the small sample properties of two time domain and two frequency domain estimators for low order autoregressive fractionally integrated moving average Gaussian models, ARFIMA (p,d,q). More specifically (1,0,0), (0,0,1), (0,d,0), various (2,0,0),...

Many papers (including most of the papers in this issue of Computational Statistics) deal with Markov Chain Monte Carlo (MCMC) methods. This paper will give an introduction to the augmented Gibbs sampler (a special case of MCMC), illustrated using the random intercept model. A 'nonstandard'...

We consider the problem of instrumental variable estimation of semipara-metric dynamic panel data models. We propose several new semiparametric instrumental variable estimators for estimating a dynamic panel data model. Monte Carlo experiments show that the new estimators perform much better...

Recent work by Said and Dickey (1984 ,1985) , Phillips (1987), and Phillips and Perron(1988) examines tests for unit roots in the autoregressive part of mixed autoregressive-integrated-moving average (ARIHA) models (tests for stationarity). Monte Carlo experiments show that these unit root tests...

Small sample properties of parameter estimates and test statistics in the vector autoregressive dividend ratio model (Campbell and Shiller [1988 a,b]) are derived by stochastic simulation. The data generating processes are co integrated vector autoregressive models, estimated subject to...

We examine the finite sample properties of the variance ratio test of the random walk hypothesis via Monte Carlo simulations under two null and three alternative hypotheses. These results are compared to the performance of the Dickey-Fuller t and the Box-Pierce Q statistics. Under the null...