In this paper we propose a new test procedure with more general steady state information to test the convergence hypothesis for a specific economy. We consider a model where demeaned per capita output of an economy is a function of time trend and then set the convergence hypothesis as negative...

In this paper we present a test statistic, which will be used to test for significant differences between generating processes of two time series that may be logically connected. The test statistic is based on the differences between estimated parameters of the autoregressive models which are...

It is well known that the usual techniques for estimating random and fixed effects panel data models are inconsistent in the dynamic setting. As a consequence, numerous consistent estimators have been proposed in the literature. However, all such estimators rely on certain well defined...

In this paper two new estimators are offred (one each for the fixed random effects specifications), and small sample performance compared with that of all the existing estimators.

Theoretical results on the properties of forecasts obtained using singular spectrum analysis are presented in this paper. The mean squared forecast error is derived under broad regularity conditions, and it is shown that the forecasts obtained in practice will converge to their population...

A general parametric framework is developed for pricing S&P500 options. Skewness and leptokurtosis in stock returns as well as time-varying volatility are priced. The parametric pricing model nests the Black-Scholes model and can explain volatility smiles and skews in stock options. The data...

In this paper we apply Bayesian methods to estimate a stochastic volatility model using both the prices of the asset and the prices of options written on the asset. Implicit posterior densities for the parameters of the volatility model, for the latent volatilities and for the market price of...

Two methods of identifying cointegrating vectors are commonly used: linear restrictions and the nonlinear method of Johansenos maximum likelihood procedure. That linear method can produce invalid estimates while the Johansen approach always produces valid estimates has been recognised in several...

When the unobservable Markov chain in a hidden Markov model is stationary the marginal distribution of the observations is a finite mixture with the number of terms equal to the number of the states of the Markov chain. This suggests estimating the number of states of the unobservable Markov...

The local linear trend and global linear trend models embody extreme assumptions about trends. According to the local linear trend formulation the level and growth rate are allowed to rapidly adapt to changes in the data path. On the other hand, the Glaobal linear trend model makes no allowance...