This paper is concerned with the estimation of an employment relationship and employment efficiency under production risk using a panel of Zimbabwe's manufacturing industries. A flexible labour demand functions are used and consist of two parts: the traditional labour demand function and labour...

In this paper we propose a general method for testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form. These tests are based on a Taylor expansion of the nonlinear model around a given point in a sample space. We study the performance of our tests by...

In this paper, new noncausality tests relying on a general nonlinear framework are proposed and their performance studied by a Monte Carlo experiment and a variety of nonlinear artificial series. Two of the tests are based on a Taylor expansion of the nonlinear model around a given point in the...

In this paper we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new Double Smooth Transition Conditional Correlation GARCH model extends the Smooth Transition Conditional Correlation GARCH model of Silvennoinen and Teräsvirta (2005) by including...

This paper deals with a dynamic adjustment process in which adjustment of a key variable input (labor) towards its desired level is modeled in a panel data context. The partial adjustment type model is extended to incorporate firm- and time-specific adjustment parameter. A flexible (translog)...

This paper is concerned with empirical measurement of patterns of productivity growth by means of competing panel data models of technical change. We argue that short term analysis must rely on models of technical change which are more flexible than the standard time trend model, because...

In this paper we propose a Lagrange multiplier test for volatility interactions among markets or assets. The null hypothesis is the Constant Conditional Correlation GARCH model in which volatility of an asset is described only through lagged squared innovations and volatility of its own. The...

The detection of structural change and determination of lag lengths are long-standing issues in time series analysis. This paper demonstrates how these can be successfully married in a Bayesian analysis. By taking account of the inherent uncertainty about the lag length when deciding on the...

In this paper we introduce the STAR-STGARCH model that can characterize nonlinear behaviour both in the conditional mean and the conditional variance. A modelling cycle for this family of models, consisting of specification, estimation, and evaluation stages is constructed. Misspecification...

This paper considers maximum likelihood estimation and inference in the two-way random effects model with serial correlation. We derive a straightforward maximum likelihood estimator when the time-specific component follow an AR(1) or MA(1) process. The estimator is easily generalized to...