The limiting distributions of two unit-root test statistics are derived and discussed for data that have both cross-sectional and time-series dimensions.

Building on recent advances in the theory of the optimal timing of investment under uncertainty, this paper proposes a stylized theoretical model to study an individual's optimal migration strategy. It shows that, as a result of following the optimal strategy, the individual may choose to delay...

Using Canadian data, the consumption-based asset pricing model is studied, defined in terms of nondurable and durable goods consumption. A two-stage estimation procedure is used, which takes account of the presence of common stochastic trends in the forcing processes. This method yields more...

This paper tests the prediction of the Permanent Income Hypothesis (PIH) that news about future income induce a revision in consumption equal to the revision in permanent income. We use time-series data from 48 contiguous US states to perform the test. The empirical results provide some support...

We examine the theoretical, empirical, and public policy implications of the proportion of females in the establishment. Arrow's model of heterogeneous employer discrimination provides predictions that are tested. Empirical results indicate support for the theory using establishment data, but a...

Recently Wang and Wirjanto (1997) proposed a simple dynamic model to study the optimal timing strategy for an individual's migration decision, using the theory of the optimal timing of investment under uncertainty, reviewed in Dixit (1992), Dixit and Pindyck (1994), and Pindyck (1991). It is...

There is substantial empirical literature which examines the relationship between private and public consumption. The conclusions from this literature, however, are generally mixed. In this paper, we attempt to provide some additional evidence on this relationship. We consider a two-good...

Volatility clustering is a well-known stylized feature of financial asset returns. In this paper, we investigate the asymmetric pattern of volatility clustering on both the stock and foreign exchange rate markets. To this end, we employ copula-based semi-parametric univariate time-series models...

In this paper we introduce resampling techniques to a multi-layer feed-forward neural network model for noisy financial time series in order to obtain more reliable interval forecasts of the time series along with a large amount of statistical information associated with the observed data. In...